Early Outcomes of the 

GEAR UP Program

Final Report 

Prepared for 

U.S. Department of Education 

Office of Planning, Evaluation and Policy Development 

Policy and Program Studies Service 

By 

Kim Standing 

David Judkins 

Brad Keller 

Amy Shimshak 

Westat 

Rockville, Md. 

2008 
This report was prepared for the U.S. Department of Education under Contract No. ED-99-CO-1039 by Westat. Dan 

Goldenberg served as the contracting officer's representative. The views expressed herein do not necessarily 

represent the positions or policies of the Department of Education. No official endorsement by the U.S. Department 

of Education of any product, commodity, service or enterprise mentioned in this publication is intended or should be 

inferred. 

U.S. Department of Education 

Margaret Spellings 

Secretary 

Office of Planning, Evaluation and Policy Development 

Bill Evers 

Assistant Secretary 

Policy and Program Studies Service 

Alan L. Ginsburg 

Director 

Program and Analytic Studies Division 

David Goodwin 

Director 

August 2008 

This report is in the public domain. Authorization to reproduce it in whole or in part is granted. While permission to 

reprint this publication is not necessary, the citation should be: U.S. Department of Education, Office of Planning, 

Evaluation and Policy Development, Policy and Program Studies Service, Early Outcomes of the GEAR UP 

Program―Final Report. Washington, D.C., 2008. 

Copies of this report may be ordered in the following ways: 

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 iii 

CONTENTS 

Chapter Page 

LIST OF FIGURES........................................................................................................... vii 

LIST OF TABLES ............................................................................................................ ix 

ACKNOWLEDGMENTS................................................................................................. xv 

EXECUTIVE SUMMARY............................................................................................... xvii 

1 INTRODUCTION............................................................................................................. 1

1.1 Context and Purpose of the Gaining Early Awareness and Readiness for 

Undergraduate Programs (GEAR UP) Program ................................................... 1

1.2 Goals of This Evaluation ...................................................................................... 4

1.3 Methodology......................................................................................................... 6

1.4 Scope of Report..................................................................................................... 8

1.5 Limitations ............................................................................................................ 9

1.6 Organization of This Report ................................................................................. 12

2 MIDDLE SCHOOL STUDENTS AND THEIR PARENTS............................................ 13

2.1 Student Characteristics.......................................................................................... 14

2.2 Services Provided to Middle School Students ...................................................... 17

2.3 Services Provided to Middle School Students’ Parents ........................................ 24

2.4 Intensity of Services Provided in GEAR UP Schools........................................... 26

3 STUDENT AND PARENT OUTCOMES........................................................................ 31

3.1 Academic Preparation and Progress ..................................................................... 36

3.2 Expectations, Student Attitudes and Behaviors .................................................... 46

3.3 Postsecondary Education Knowledge and Parental Involvement......................... 55

3.4 Orientation Toward College.................................................................................. 60

3.5 Pulling It All Together .......................................................................................... 65

4 GEAR UP MIDDLE SCHOOLS ...................................................................................... 69

4.1 Academic Curriculum........................................................................................... 69

4.2 Professional Development Opportunities ............................................................. 72

4.3 Teacher Attitudes.................................................................................................. 75
 iv 

Contents (continued) 

Chapter Page 

5 PARTNERSHIP PROJECTS ............................................................................................ 79

5.1 Composition of Partnerships................................................................................. 79

5.2 Projects’ Goals for Meeting Program Objectives ................................................. 81

5.3 Organization and Management of Partnerships .................................................... 83

5.4 Involvement of Partners........................................................................................ 84

5.5 Relationship With Other Projects and Programs .................................................. 86

5.6 Evaluation Plans.................................................................................................... 87

6 LOOKING FORWARD.................................................................................................... 89

6.1 Transition to High School..................................................................................... 89

6.2 Efforts at Sustainability......................................................................................... 93

REFERENCES .............................................................................................................................. R-1

Appendix Page 

A Methodology for the National Evaluation of GEAR UP................................................... A-1

B Student Sample Design, Imputations, Weights and Error Estimation............................... B-1

C Index Construction ............................................................................................................ C-1

D Index Validation Using the National Longitudinal Study (NELS:88) .............................. D-1

E Removal of Baseline Differences...................................................................................... E-1

F Hierarchical Linear Modeling (HLM) Simulation Study.................................................. F-1

G Methodology for Analyzing Transcript Data .................................................................... G-1

H Analysis of Standardized Test Scores ............................................................................... H-1

I Methodology for Analyzing Program Activity Records ................................................... I-1

J Glossary............................................................................................................................. J-1
 v 

Contents (continued) 

Appendix Page 

K Data Collection Instruments.............................................................................................. K-1

Seventh-Grade Student Survey ................................................................................... K-3 

Eighth-Grade Student Survey ..................................................................................... K-35 

Seventh-Grade Parent Interview ................................................................................. K-65 

Eighth-Grade Parent Interview ................................................................................... K-77 

Student Information Matrix (Administrative Records Data) ...................................... K-89 

Activity Records Forms .............................................................................................. K-91 



 vii 

Contents (continued) 

Figures 

Figure Page 

1-1 Conceptual framework of the impact of GEAR UP....................................................... 2

2-1 Percentage of activities in six GEAR UP projects for students and parents, by 

duration of activity ......................................................................................................... 28

A-1 Conceptual framework of the impact of GEAR UP....................................................... A-2

B-1 Number of cases with different combinations of each of three seventh-grade data 

sources............................................................................................................................ B-5

B-2 Number of cases with different combinations of each of the three eighth-grade 

data sources .................................................................................................................... B-12

C-1 Conceptual framework of the impact of GEAR UP....................................................... C-2

H-1 Histogram of Test A probit reading scores .................................................................... H-2

H-2 Histogram of Test A probit mathematics scores ............................................................ H-3

H-3 Histogram of Box-Cox transformed Test A probit reading scores with 

lambda=1.17931............................................................................................................. H-3

H-4 Histogram of Box-Cox transformed Test A probit mathematics scores with 

lambda=0.924138........................................................................................................... H-4

H-5 Grouped actual versus predicted Test A reading scores................................................. H-6

H-6 Grouped actual versus predicted Test A mathematics scores ........................................ H-7

H-7 Actual Test A reading scores by predicted Test A reading scores, by treatment 

school status ................................................................................................................... H-8

H-8 Actual Test A mathematics scores by predicted Test A mathematics scores, by 

treatment school status ................................................................................................... H-9

H-9 Standardized residual analysis of Test B reading scores................................................ H-12

H-10 Standardized residual analysis of Test B mathematics scores........................................ H-12

H-11 Actual Test B reading scores by predicted Test A reading score, by treatment 

school status ................................................................................................................... H-13
 viii 

Contents (continued) 

Figures (continued) 

Figure Page 

H-12 Actual Test B reading scores by predicted Test A mathematics score, by 

treatment school status .................................................................................................. H-14

I-1 Scatter plot of predicted and observed TotalDose in six schools with adequate 

participation data............................................................................................................ I-4
 ix 

Contents (continued) 

Tables 

Table Page 

1-1 History of program funding and awards......................................................................... 4 

1-2 Student sample selection at schools in the national evaluation...................................... 7 

2-1 Comparison of characteristics of GEAR UP and non-GEAR UP students in the 

national evaluation ......................................................................................................... 15

2-2 Percent of students self-reporting participation in various activities ............................. 18 

3-1a Association for GEAR UP with percentage of students taking more challenging 

core academic courses.................................................................................................... 37 

3-1b Association for GEAR UP with level of mathematics courses taken ............................ 39 

3-1c Association for GEAR UP with level of science courses taken..................................... 40 

3-1d Association for GEAR UP with level of English courses taken .................................... 41 

3-1e Association for GEAR UP with level of foreign language courses taken...................... 42 

3-1f Association for GEAR UP with academic rigor of courses taken.................................. 43 

3-1g Association for GEAR UP with level of academic performance ................................... 44 

3-1h Association for GEAR UP with percentage of students with high levels of 

academic performance.................................................................................................... 45 

3-1i Association for GEAR UP with student discipline ........................................................ 47 

3-2a Association for GEAR UP with students’ expectations about postsecondary 

education ........................................................................................................................ 49 

3-2b Association for GEAR UP with students’ responses to selected questions about 

postsecondary education ................................................................................................ 50 

3-2c Association for GEAR UP with parents’ expectations for their children....................... 51 

3-2d Association for GEAR UP with selected facets of the Parental Expectations 

Index............................................................................................................................... 52 

3-2e Association for GEAR UP with students’ attitudes about and behaviors in school....... 53 
 x 

Contents (continued) 

Tables (continued) 

Table Page 

3-3a Association for GEAR UP with students’ knowledge about postsecondary 

education ........................................................................................................................ 57 

3-3b Association for GEAR UP with Parent Knowledge and Involvement Index................. 59 

3-3c Association for GEAR UP with information on college planning components of 

Parent Knowledge and Involvement Index .................................................................... 59 

3-3d Association for GEAR UP with parent attendance at parent-teacher conferences 

and school events ........................................................................................................... 60

3-4a Average values on selected student questions in GEAR UP College Orientation 

Index............................................................................................................................... 64 

3-4b Average values on parent question in GEAR UP College Orientation Index................ 65 

3-4c Association for GEAR UP with the College Orientation Index..................................... 66 

3-5 GEAR UP outcomes for all students and subgroups of interest..................................... 67 

4-1 Comparison of gateway curricula at GEAR UP and non-GEAR UP middle 

schools in the national evaluation sample ...................................................................... 71 

4-2 Number of schools in the national evaluation sample using each source for 

determining class assignments ....................................................................................... 72 

A-1 Distribution of 20 sampled projects across strata........................................................... A-5 

A-2 Difference measures for each variable ........................................................................... A-7 

A-3 School-level response rates among participating schools .............................................. A-13 

A-4 Number and percentage of parents giving consent by school year and type of 

data, for students remaining in original school .............................................................. A-13 

A-5 Number and percentage of students who left original school for whom parent 

consent was obtained, by type of data............................................................................ A-14 

A-6 Student-level response rates for GEAR UP and non-GEAR UP schools ...................... A-15 

A-7 Participation data response rates, project level .............................................................. A-16 
 xi 

Contents (continued) 

Tables (continued) 

Table Page 

B-1 Analysis of students who left their original sampled school before the end of 

eighth grade.................................................................................................................... B-3 

B-2 Variables, parameter estimates and standard errors used to create predicted 

College Orientation Index values................................................................................... B-6 

B-3 Parent variables that were copied in the Nearest Neighbor procedure........................... B-6 

B-4 Model for whether student was in an honors or gifted and talented program 

during seventh grade (HONORS_7) .............................................................................. B-7 

B-5 Model for total number of absences for student (excused or unexcused) during 

seventh grade (TOTABSNC_7) ..................................................................................... B-7 

B-6 Model for number of unexcused absences for student during seventh grade 

(UNEXABSN_7) ........................................................................................................... B-8 

B-7 Model for total number of disciplinary actions taken against student during 

seventh grade (TOTDISP_7).......................................................................................... B-8 

B-8 Model for whether student received any honors or awards during seventh grade 

(AWARDS_7)................................................................................................................ B-8 

B-9 Average predicted values for selected student administrative records variables, 

by school type and student records data status............................................................... B-9 

B-10 Size and predicted seventh-grade student records values for each of the five 

natural clusters used for seventh-grade student records imputation............................... B-9 

B-11 Beta coefficients used to determine a student’s propensity for response....................... B-10 

B-12 Variables and beta coefficients used in the model to predict College Orientation 

Index values for the imputation of student data to cases in Section 8P ......................... B-13 

B-13 Variables and beta coefficients used in the model to predict College Orientation 

Index values for the imputation of student data to cases in section 8SP........................ B-15 

B-14 Variables and beta coefficients used in the model to predict College Orientation 

Index values for the imputation of parent data to cases in sections 8T and 8ST............ B-16 

B-15 Model for HONORS_8 .................................................................................................. B-17 
 xii 

Contents (continued) 

Tables (continued) 

Table Page 

B-16 Model for TOTABSNC_8.............................................................................................. B-18 

B-17 Model for UNEXABSN_8 ............................................................................................. B-18 

B-18 Model for TOTDISP_8 .................................................................................................. B-19

B-19 Model for AWARDS_8 ................................................................................................. B-19 

B-20 Size and predicted eighth-grade student records values for each of the five 

natural clusters used for eighth-grade student records imputation................................. B-19 

B-21 Beta coefficients used to determine a student’s propensity for nonresponse................. B-20 

B-22 Variables and beta coefficients used to predict a student’s probability of 

transcript nonresponse.................................................................................................... B-21

E-1 Analysis methods ........................................................................................................... E-2 

E-2 Application of analysis methods .................................................................................... E-3 

E-3 Illustration of contaminated variable and analysis options (among eighth-grade 

respondents) ................................................................................................................... E-4 

E-4 Contaminated baseline student questionnaire variables by GEAR UP status 

(tabulated on eighth-grade completes with nonresponse-adjusted weights) .................. E-6 

E-5 Means of contaminated baseline indexes by GEAR UP status (tabulated on 

eighth-grade completes with nonresponse-adjusted weights) ........................................ E-6 

E-6 Variables and interactions that define membership in a GEAR UP school ................... E-8 

E-7 Makeup of propensity groups, by school attendance ..................................................... E-9 

E-8 Comparisons between GEAR UP and non-GEAR UP schools with ordinary 

weights and with CFP weights....................................................................................... E-10 

E-9 Predictor specifications for effect variables in tables E-10 through E-24...................... E-13 

E-10 Beta coefficients for HLM for the variable Academic................................................... E-15 

E-11 Beta coefficients for HLM for the variable CollegeMoreMoney................................... E-16 
 xiii 

Contents (continued) 

Tables (continued) 

Table Page 

E-12 Beta coefficients for HLM for the variable CollegeBoundRev...................................... E-17 

E-13 Beta coefficients for HLM for the variable ECBusy...................................................... E-18 

E-14 Beta coefficients for HLM for the variable ExpectSERev............................................. E-19 

E-15 Beta coefficients for HLM for the variable HeardOfSchools (contaminated) ............... E-20 

E-16 Beta coefficients for HLM for the variable HomeWorkHours ...................................... E-21 

E-17 Beta coefficients for HLM for the variable NegJunkHours ........................................... E-22 

E-18 Beta coefficients for HLM for the variable Performance............................................... E-23 

E-19 Beta coefficients for HLM for the variable ParInvolve.................................................. E-24 

E-20 Beta coefficients for HLM for the variable PExpect (contaminated)............................. E-25 

E-21 Beta coefficients for HLM for the variable PPartCB ..................................................... E-26 

E-22 Beta coefficients for HLM for the variable SDiligent.................................................... E-27 

E-23 Beta coefficients for HLM for the variable SPartCB ..................................................... E-28 

E-24 Beta coefficients for HLM for the variable TalkCoursePlanning .................................. E-29 

F-1 Model for student-level treatment propensity ................................................................ F-3 

F-2 True and fitted models for followup outcome................................................................ F-5 

G-1 Middle school CSSC developed for National Evaluation of GEAR UP........................ G-2 

G-2 Course codes for each academic pipeline....................................................................... G-39 

G-3 Adjustments to class codes with honors identifiers........................................................ G-40 

G-4 Adjustments to class codes with remedial or resource identifiers.................................. G-40 

H-1 Seventh-grade variables used to predict Test A reading scores ..................................... H-5 

H-2 Seventh-grade variables used to predict Test A mathematics scores ............................. H-6 
 xiv 

Contents (continued) 

Tables (continued) 

Table Page 

H-3 Goodness of fit tests for normal distribution of residuals from the Test A reading 

model.............................................................................................................................. H-7 

H-4 Seventh-grade variables used to predict Test B reading scores ..................................... H-10 

H-5 Seventh-grade variables used to predict Test B mathematics scores ............................. H-11 

I-1 Participation hours by service category and correlation with TotalDose and with 

first two factors .............................................................................................................. I-2 

I-2 Distribution of total participation hours across six responding schools......................... I-3 

I-3 Model for total participation hours (TotalDose) ............................................................ I-4 

I-4 Statistics about the imputation strata in the six GEAR UP schools with adequate 

participation data............................................................................................................ I-5 

I-5 Model for change in College Orientation Index in terms of baseline variables 

other than baseline versions of primary outcome indexes*............................................ I-6 

I-6 Effects of intense participation in GEAR UP services on unexplained growth in 

the College Orientation Index ........................................................................................ I-7 

J-1 Definitions of variables used in the analyses report....................................................... J-4 
 xv 

Acknowledgments 

We would like to thank the many individuals whose efforts contributed to the preparation of this report. 

First, we would like to acknowledge Dan Goldenberg, who has been involved with the evaluation from 

the very beginning and the project officer for the past three years. His thoughtful guidance, insight and 

dedication have proven invaluable over the course of the project. David Goodwin, Policy and Program 

Studies Service, has also been involved with the project since the beginning and has provided 

indispensable guidance at key junctures. Maggie Cahalan and James Maxwell, Policy and Program 

Studies Service, saw the report through the final stages and form. 

We also would like to express our gratitude to members of the Technical Working Group for their 

participation in meetings throughout the evaluation and their review of this report. They provided 

insightful comments and constructive recommendations for improvements to the analyses and the 

resulting report. The members of the Technical Working Group include Ann Coles, The Education 

Resources Institute (TERI); David Cordray, Institute for Public Policy Studies, Vanderbilt University; 

Mary Beth Curtis, Center for Special Education, Lesley College; Hector Garza, National Council for 

Community and Education Partnerships (NCCEP); Amaury Nora, University of Houston; and Linda 

Shiller, Vermont Student Assistance Corporation (VSAC). 

Similarly, we are appreciative of the staffs of our subcontractors, Branch Associates and Decision 

Information Resources, and the staff of Westat who conducted the site visits. They prepared the site visit 

reports and encouraged the schools and GEAR UP projects to provide the study data. 

Special thanks go to the students and parents who participated in the evaluation and the GEAR UP 

projects, their staffs and the schools. By helping with our many requests for data and hosting the site visit 

teams, the schools made this project and report possible. 

Finally, we would like to thank Lynn Mahaffie, director of the GEAR UP Program Office; Andrea Baird, 

GEAR UP Program Office; and Phillip Juengst, Budget Service, for their participation in meetings and 

comments on drafts of this report. 

 Linda A. LeBlanc 

 Project Director 

 Kimberly A. Standing 

 Deputy Project Director 

 Alexander C. Ratnofsky 

 Senior Vice President and 

Director of the Human Services Group 
 xvi 
xvii 

Executive Summary 

In 1998, Congress authorized the Gaining Early Awareness and Readiness for Undergraduate Programs 

(GEAR UP) program. The purpose of the program is to foster increased knowledge, expectations, and 

preparation for postsecondary education among low-income students and their families. GEAR UP 

projects may provide services to students, parents and teachers at high-poverty schools with at least 50 

percent of students eligible for free or reduced price lunch. Services may include: tutoring, mentoring, 

college field trips, career awareness, colleges-readiness counseling, classes, meetings, parent education 

about access to higher education, curriculum reform, and teacher training. GEAR UP is based on a model 

of providing services to an entire grade cohort, and grantees are required to offer services to all students 

in the target grade or grades according to their needs, but individual participation is voluntary. GEAR UP 

services must begin no later than the seventh grade. The GEAR UP model also stresses partnerships of 

schools, districts, community organizations and postsecondary institutions. The first grants were awarded 

in August of 1999. Most of the first GEAR UP grantees began by serving sixth- or seventh-graders in fall 

of 1999, with the intention of providing continuing services to this cohort of students as they progressed 

through high school. 

Evaluation Design 

The five-year contract supporting the evaluation started at about the same time as the first grants were 

awarded. Because the GEAR UP program was new, the evaluation was given the task of describing the 

projects as they existed as well as evaluating key student and parent interim outcomes. As a random 

assignment study was not possible, a quasi-experimental evaluation design was used. 

There were two major goals of the evaluation. The first was to provide descriptive information on the 

early implementation of the program and the second was to observe the association between GEAR UP 

participation, and student and parent outcomes. To provide the descriptive information the study 

conducted site visits to a sample of 20 of the initial partnership projects. From these partnerships, a 

sample of 18 middle schools and 18 matched comparisons schools was selected and up to 140 seventhgrade students were randomly selected from each school. Student and parent surveys were administered 

about midway through the seventh grade and near the end of the eighth grade. Student school records and 

GEAR UP participation records were also obtained. 

The design focused on GEAR UP’s intended middle school outcomes, with plans for subsequent studies 

to examine the longer term outcome of entry into postsecondary education since it was more than five 

years before the first program participants would be college-age. This report primarily discusses interim 

GEAR UP outcomes for middle school students and their parents. In addition, using qualitative data from 

the site visits, the report examines the secondary outcomes for GEAR UP on middle schools and the 

sustainability of the program’s activities after federal funds are no longer available. The interim outcomes 

examined are those identified in the conceptual framework of the GEAR UP program: improved 

knowledge, behavior and expectations. The outcomes for GEAR UP associated with high school 
 xviii 

achievement and preparation for and enrollment in college will be examined in subsequent data 

collections and reports.1

Data Sources and Limitations 

The information for the evaluation comes from site visits, surveys of students and parents, student 

transcripts and school administrative records for a sample of GEAR UP middle school students and from 

a matched comparison group of non-GEAR UP middle school students. A number of factors in the 

evaluation design lead to some important limitations on the strength of conclusions that are drawn in the 

report. First of all, it was not a randomized experiment. The set of cooperating grantees and schools is a 

small purposive sample, leading both to concerns about generalizability and power to detect small 

effects―particularly schoolwide effects such as curriculum changes and the resulting shift in coursetaking patterns. The comparison schools could not be matched on historical college attendance rates, as 

would have ideally been desired, and because service provision started prior to baseline data collection in 

the seventh grade, it was not possible to remove all seventh-grade differences between the two sets of 

students without simultaneously removing some of the effects of early information services. 

Two important parts of the evaluation were to describe the actual interventions and to assess the prospects 

for the sustainability of the program’s activities after federal funds are no longer available to these 

grantees. These goals required intensive onsite activities that could only be done at a small number of 

schools due to the associated costs. Thus, the school sample size is small. Eighteen schools from GEAR 

UP projects and 18 non-GEAR UP comparison schools participated in the evaluation. The analytic 

procedures used in the report fully adjusted significance levels for the small number of study schools. 

There is, however, the possibility that effects were missed because the process for adjusting significance 

levels sharply reduced the statistical power. The reduction in statistical power was particularly acute for 

school-level outcomes because the sample size (36 schools) is so small. 

As a result of these factors―project selection procedure and sample size―the procedure for selecting 

matching comparison schools and the difficulties in obtaining baseline measurements, the findings in this 

report are more suggestive than definitive. 

Key Findings 

 Attending a GEAR UP school as measured near the end of eighth grade was positively 

associated2 with parents’ knowledge of opportunities and benefits of postsecondary 

education for their children (table 3-3c). 

 Attending a GEAR UP school as measured near the end of eighth grade was positively 

associated with students’ knowledge concerning postsecondary education 

opportunities available to them (table 3-3a). 

 

1

 In September 2004, the U.S. Department of Education issued a contract to determine high school outcomes, such as academic 

preparation for postsecondary education and postsecondary enrollment. 

2

 Throughout the report, an "association" is discussed only if the supporting hypothesis test was significant at the 5 percent level, 

meaning there would have been only a 5 percent chance of finding the difference by chance. Some associations are discussed 

when the significance level of the test was at the 10 percent level. These are qualified by the phrase "modest evidence." If no

evidence was found even at the 10 percent level, the phrase "no evidence" is used. 
xix 

 Attending a GEAR UP school as measured near the end of eighth grade was positively 

associated with parents’ involvement in the school and their children’s education 

(tables 3-3b and 3-3d). 

 Attending a GEAR UP school as measured near the end of eighth grade was positively 

associated with parents’ having higher academic expectations for their children (tables 

3-2c and 3-2d). However, there was no evidence of an association between attending a 

GEAR UP school and the strength of student intentions to attend college, expectations 

for postsecondary education or overall orientation toward college (tables 3-2a, 3-2b 

and 3-4c). 

 There was no evidence of an association between attending a GEAR UP school and 

grades or school behavior, such as attendance or disciplinary problems (table 3-1i). 

 Attending a GEAR UP school as measured near the end of eighth grade was positively 

associated with taking above-grade-level science courses in middle school (table 3-

1a). 

While these general statements are true, there were differences in the magnitude and statistical 

significance of the associations by various classifications of students. In no case, however, was the 

direction of the association (i.e., positive versus negative) different across the classifications. Students 

were categorized by their race or ethnicity, whether any members of their family had gone to college (so 

called first-generation students) and the degree to which their seventh-grade orientation to going to 

college was not at the extremes of their cohort (i.e., had orientations toward definitely going to college or 

definitely not going to college). Because the vast majority of students in the study were from low-income 

families, no categorization of students by income was possible. 

For the most part, the results reported above for all students were true across the various classifications of 

students. A notable exception is presented below. 

 For African-American students attendance at a GEAR UP school as measured near the 

end of eighth grade was positively associated with the number of rigorous (or abovegrade-level)3

 courses taken during middle school. African-American students from 

GEAR UP schools averaged 1.0 rigorous course as compared to 0.5 of a course 

among African-American students from non-GEAR UP schools (table 3-1f). 

The site visits to the sampled GEAR UP middle schools revealed the following: 

 GEAR UP middle school staff, participating in the study focus groups, reported that 

GEAR UP middle schools were more likely than non-GEAR UP middle schools to 

offer honors and above-grade-level classes. They perceived that some of these 

changes took place with the implementation of the GEAR UP projects in 1999 

(section 4.1). 

 Most of the teachers who participated in focus groups expressed positive opinions 

about GEAR UP-sponsored professional development, although there was some 

 

3

 Academic rigor is determined by the number of core academic courses taken that are considered to be above grade level for an 

average eighth-grade student. 
 xx 

variation in how useful or relevant teachers felt individual sessions were for them or 

to GEAR UP’s purpose (section 4.2). 

Finally, the study examined GEAR UP on two important issues: transitioning the program to high school 

and sustainability beyond the federal grant. 

 Projects reported some difficulty transitioning into high schools; such as inadequate 

staffing and administrative barriers, which were similar to those reported two years 

earlier when the grants were just starting out in middle schools. Projects reporting the 

smoothest transitions tended to provide services to high school students that were 

similar to those provided to middle school students (section 6.1). 

 Early evidence suggests that some aspects of GEAR UP will be sustained in middle 

schools beyond the period of federal funding. About half of the projects studied were 

optimistic about continuing, and one-third had made specific plans to do so as they 

neared the third year of their grants (section 6.2). 
 1 

1. Introduction 

1.1 Context and Purpose of the Gaining Early Awareness and Readiness 

for Undergraduate Programs (GEAR UP) Program 

The economic success of individuals and the larger economy has become increasingly 

dependent on individuals continuing their education beyond high school, whether through 

college or some other form of postsecondary vocational training. For this reason, 

policymakers and educators have focused greater attention over the past decade on 

improving access to postsecondary education for all students. The federal government 

began the practice of initiating and supporting programs to facilitate equal opportunity for 

higher education among historically underrepresented groups such as ethnic minorities 

and low-income families with the enactment of the Higher Education Act of 1965. In 

addition, over the past decade, school reform efforts have focused on standards and 

accountability and have been geared toward the whole school and all of its students. A 

consensus has emerged that it is necessary to intervene early in order to influence student 

behavior and outcomes in high school and beyond. According to the Carnegie Council on 

Adolescent Development (1995), adolescence is the last chance for social institutions to 

influence youth behavior and attitudes. 

The GEAR UP program was authorized under the 1998 amendments to the Higher 

Education Act to further address the continuing imbalance in postsecondary attendance 

rates by specifically promoting equal access to higher education for low-income students. 

Initiatives such as the I Have A Dream project placed an emphasis on the role of peers. 

Research in this area led to GEAR UP’s cohort approach, which is unique compared to 

other federal programs that seek to promote college for low-income youths. Grants were 

awarded to either states or partnerships between a college or university and a school 

district. 

The use of partnerships is a unique feature of GEAR UP. The GEAR UP program 

requires a variety of entities to work together to provide services to a cohort (or whole 

grade) of students, starting no later than the seventh grade and following them through 

high school. The long-term outcomes sought by the GEAR UP program are increased 

postsecondary education enrollment and success for those targeted by the program. 

The conceptual framework that guides GEAR UP is depicted in figure 1-1. The 

framework shows that within a context of targeted students, families, schools and 

communities, GEAR UP projects provide various types of services. It is anticipated that 

these services are derived from research-based best practices. 

Early intervention is 

believed to influence 

a student’s behaviors 

and outcomes and 

facilitate equal 

opportunity for 

postsecondary 

education.

GEAR UP promotes 

equal access to 

postsecondary 

education for lowincome students.
 2 

Figure 1-1. Conceptual framework of the impact of GEAR UP 

1. CONTEXT 2. SERVICES 3. INTERIM 4. LONG-TERM 

 OUTCOMES OUTCOMES 

Source: Westat analysis of HEA 1988 Amendments, 2007. 

1a. Local 

Characteristics 

 Students 

 Families 

 Schools 

 Communities 

1b. Policy Inputs 

 Local 

 State 

 Federal 

2. Projects 

 Academic assistance 

 Mentoring 

 Information on 

postsecondary education 

options 

 Information on student aid 

 Counseling 

 Programs for families 

 Curriculum development 

 Professional development 

 Financial aid incentives 

3a. Families 

 Expectations 

 Knowledge 

 Involvement 

3b. Students 

 Expectations 

 Knowledge 

 Challenging 

courses 

 Attendance, 

grades, on-time 

promotions 

3c. Schools 

 Challenging 

curricula 

 Teacher and staff 

expectations, 

knowledge and 

involvement 

3d. Partners 

 Collaboration 

 Communication 

 Comprehensive 

services 

4. Students 

 Increased 

postsecondary 

education 

enrollment 

 Increased 

postsecondary 

education 

success
 3 

Furthermore, these services are intended to result in interim (or early) outcomes that are 

logically associated with the desired longer term outcomes of the program. 

Federal Grants 

The GEAR UP legislation stipulates that projects be awarded five-year grants. During the 

108th Congress, appropriation language was introduced and passed that included a 

provision to fund a sixth year for all GEAR UP projects so that projects starting with a 

cohort of seventh-graders could continue serving these students through 12th grade. The 

legislation is nonprescriptive about how grantees should operate or the services that 

should be provided, but consistent with the conceptual framework, it does mandate that 

grantees increase postsecondary access and completion through the promotion of the 

following: 

 Information to students and parents (e.g., appropriate information on 

college preparatory courses, cost of college attendance, financial 

assistance and different programs of study), 

 Individualized academic and social support to students, 

 Parent involvement in education, 

 Educational excellence, 

 School reform, and 

 Student participation in rigorous courses. 

The first GEAR UP grants were awarded in August 1999 to two types of recipients: (1) 

partnerships of school districts, colleges and other organizations and (2) state agencies. 

Partnership grantees are charged with establishing strong and lasting partnerships among 

school districts, colleges and other entities to operate the projects. State GEAR UP 

grantees do not have this requirement. In its first round of awards, the U.S. Department of 

Education awarded $75 million in federal resources to 164 partnership grantees and $42 

million to 21 state grantees. Table 1-1 shows the history of the program funding and 

awards. The legislation stipulates that two-thirds of the federal funds are to be awarded to 

partnership grantees and the remaining one-third to state grantees. 

Partnership grants require recipients to begin providing services to students no later than 

seventh grade and to continue services to these students in participating high schools until 

graduation. This requirement means that, in nearly all school districts in the program, 

middle schools have been the first schools to participate in GEAR UP. (A small number 

of grantees chose to begin providing services at the elementary school level when the 

elementary school included a seventh grade. A handful of grantees chose to provide 

services to students living in housing authorities, which are exempt from the age 

requirements.) In all participating middle schools, at least 50 percent of the students must 

The GEAR UP 

legislation gives 

projects latitude in 

determining services 

needed by schools, 

students and parents.

By FY 2005, there 

were 641 GEAR UP 

projects.

GEAR UP 

partnerships must 

begin providing 

services to a cohort 

of students no later 

than the seventh 

grade.
 4 

Table 1-1. History of program funding and awards 

Fiscal year 

Funding 

(dollars in millions) Number of new awards 

1999 $120 185 (164 partnerships, 21 states) 

2000 $200 80 (73 partnerships, 7 states) 

2001 $295 8 (6 partnerships, 2 states) 

2002 $285 51 (45 partnerships, 6 states) 

2003 $294 0 

2004 $298 0 

2005 $306 125 (98 partnerships, 27 states) 

 

Total $1,798 641 

Note: A total of 245 grants were active in 2005–06, of which 125 were new awards and 120 were continuations from 

prior years. 

be low-income (i.e., eligible for free or reduced-price lunches).4

 GEAR UP partnership 

grantees must provide assistance to all students in designated grade levels (called 

cohorts) in participating schools, unlike other federal programs designed to increase 

college access for students who meet specified criteria. 

The cohort approach recognizes that in schools with high rates of family poverty, all 

students are at greater risk of poor academic performance and low rates of college 

attendance (Howley and Bickel 2000; Howley, Strange, and Bickel 2000; and Guskey 

1997). The GEAR UP approach of serving all students also allows services to be 

integrated into the school day and regular educational offerings, providing greater 

opportunities for academic assistance and education reform. 

1.2 Goals of This Evaluation 

Given the timeframe of this evaluation, the goal was to focus on student and parent 

outcomes near the end of eighth grade that were considered to be associated with an 

increased likelihood of attending postsecondary education after high school. The 

conceptual framework, figure 1-1, for the GEAR UP program guided the study design for 

the national evaluation. Within the context of the conceptual framework, the National 

Evaluation of GEAR UP had the dual purpose of describing the projects as they existed 

and evaluating their outcomes. Because the GEAR UP legislation is nonprescriptive 

about how to meet the stated goals, services provided by partnerships varied 

considerably. Brief lists of the general types of services that may be offered are shown in 

box 2 in figure 1-1. As shown in box 3 (a-d), interim outcomes are intended at the family, 

student, school and partner levels. Data were collected at each of these levels. 

 

4

 Children from families with incomes at or below 130 percent of the poverty level are eligible for free meals 

(breakfasts, lunches and snacks) under the National School Lunch Program. Those with incomes between 

130 percent and 185 percent of the poverty level are eligible for reduced-price meals. For the period July 1, 

2000, through June 30, 2001, 130 percent of the poverty level was $22,165 for a family of four; 185 

percent was $31,543 (Federal Register, vol. 65, no. 65 (April 4, 2000): 17620). 

This study looks at 

key interim outcomes.
 5 

At the base of the outcomes study were 18 GEAR UP partnership projects. One GEAR 

UP middle school was selected and agreed to participate from each of these 18 

partnerships. In addition, 18 non-GEAR UP comparison schools were selected and 

agreed to participate. An additional two projects agreed to participate in the case studies 

but not the outcomes study. 

The long-term outcomes for GEAR UP, which are shown in box 4 of the conceptual 

framework (figure 1-1), are increased rates of participation and success in postsecondary 

education. These long-term outcomes are the focus of the followup evaluation. 

This report: 

 Describes how GEAR UP projects are using their federal dollars 

(chapter 2), 

 Looks at student and parent outcomes near the end of eighth grade 

(chapter 3), 

 Looks at school-level process outcomes at the GEAR UP projects and 

partner schools (chapter 4), 

 Describes the organizational structures and experiences of GEAR UP 

projects (chapter 5), and 

 Discusses the future prospects for GEAR UP beyond the study period 

(chapter 6). 

The core of this report focuses on the outcomes for the GEAR UP program for student 

preparation for college. As discussed in more detail later, the evaluation was unable to 

address the question about effective strategies because of incomplete information on 

services provided to individuals. We attempted to look at the outcomes of different 

services on students where complete data were provided. Because the analysis is limited 

to a small group of projects, this analysis appears in appendix I. 

To capture a middle school perspective about postsecondary education, data were 

collected from and about a sample of students and their parents in late fall 2000. This 

represented the baseline measure for examining the outcomes of the GEAR UP projects. 

We followed up with these same students and their parents in spring 2002 when most 

were completing the eighth grade. 

Two primary features of the GEAR UP program made it infeasible to use an experimental 

or random assignment design in this study (as would clearly be preferred given the 

research questions). First, GEAR UP projects are required by law to serve an entire grade 

level of students, so random assignment to treatment and control was not possible at the 

student level. Second, random assignment of schools within projects was not possible 

since many districts participating in the partnerships only had one middle school within 

their district. In addition, districts consciously selected the schools with the most need to 

participate in GEAR UP. 

The outcome study 

comprises students 

from 18 GEAR UP 

schools and 18 nonGEAR UP schools.

This report focuses 

on student 

preparation for 

college.

Data were collected 

at the beginning of 

seventh grade and 

end of eighth grade.
 6 

Accordingly, the study used matched comparison schools to evaluate GEAR UP’s 

outcomes. For each GEAR UP middle school in the sample, a middle school that was not 

receiving GEAR UP funds was selected for comparative purposes. The two schools were 

matched on the demographics of the students served and the communities in which they 

were located using the Common Core of Data (CCD). When possible, non-GEAR UP 

schools were located in the same school district as the GEAR UP schools. As in the 

GEAR UP schools, a sample of seventh-grade students was selected in the non-GEAR 

UP schools. The full complement of student-level data collected on GEAR UP school 

students was also collected on the non-GEAR UP school students. Analyses primarily 

examined outcome measures between the GEAR UP students and students from the nonGEAR UP group at the end of eighth grade. 

The remainder of this report focuses on the GEAR UP partnership grantees and the 

outcomes for the students they served between fall 2000 and spring 2002. State GEAR 

UP grantees did not participate in the outcomes study because they can serve students at 

any age and are not required to continue providing services to the same students each 

year. 

1.3 Methodology 

The National Evaluation of GEAR UP began in fall 1999 just as the GEAR UP projects 

themselves were getting underway. A sample of 20 partnerships was selected and 

recruited. Projects were first categorized according to three strata: whether the project 

was located in a state with a state GEAR UP grant; whether the primary grant holder was 

a school district or postsecondary institution; and whether the project intended to provide 

the bulk of its services directly to students. Projects that were not planning to serve a new 

cohort of seventh-graders in fall 2000 were ineligible. Approximately one-third of the 

164 first year partnership grantees did not have a seventh-grade cohort in fall 2000. 

Because the study was not about the program’s implementation, projects that were not yet 

operational because they lacked a project director or had not yet started working with 

schools were excluded from the sample. During the selection process, every effort was 

made through stratification to include projects with different programmatic approaches 

and a mix of primary grant holders (i.e., school districts, colleges and universities).5

The second stage in the sampling process was the selection of middle schools within each 

of the 18 participating projects.6

 Given GEAR UP program requirements, assigning 

schools randomly to GEAR UP projects was not feasible. Thus, the National Evaluation 

of GEAR UP used a comparison-group approach. Because more than one middle school 

could participate in each GEAR UP project, a GEAR UP middle school was 

simultaneously selected with a middle school in the same or nearby school district with 

 

5

 Based on the programmatic approaches in their grant applications, grantees were categorized as interacting 

primarily with students directly, interacting primarily at the school level or interacting equally with schools 

and students. 

6

 Two partnerships declined participation in the outcome study but did agree to participate in the case 

studies. 

A total of 20 

partnership grantees 

were selected to 

reflect a variety of 

programmatic 

approaches.

One middle school 

from each of the 18 

GEAR UP projects 

was simultaneously 

selected with a 

comparison school.

The study used a 

matched comparison 

group design.
 7 

similar students but without GEAR UP.7

 A simple random sample of up to 140 students 

for whom parental consent to participate in the study was obtained was then selected for 

each sampled GEAR UP and comparison school. Table 1-2 summarizes the sampling rate 

for students in the national evaluation. 

Table 1-2. Student sample selection at schools in the national evaluation 

 Number 

Seventh-grade enrollment fall 2000 9,121 

Parent consent to participate obtained 6,941 

Sampled 4,692 

Chapter 2 compares the characteristics of sampled GEAR UP and non-GEAR UP 

students. GEAR UP and non-GEAR UP students are closely matched on the percentage 

of female, minority and low-income students; percentage of students with special needs; 

and percentage of students with English language deficiencies. These students and their 

parents were the basis for the longitudinal outcomes study. Because all types of GEAR 

UP projects are not represented in the study, the results of the outcome analysis are not 

generalizable to the full GEAR UP program. They are, however, representative of those 

projects similar to the ones that participated in the evaluation. 

Information for this report comes from several different sources and includes the 

following: 

 Descriptive information from site visits. During each of the first 

three years of GEAR UP, researchers conducted site visits to the 20 

partnerships to explore the nature and status of the program. During 

those visits, site visitors asked project, district and school personnel 

as well as partners about the design and approach of the GEAR UP 

project; the partnerships, program administration and activities that 

had been undertaken or were planned; the project staffing; and the 

role of the project in education reform at the school. Site visitors 

asked project directors what activities were underway to enable 

comparable efforts to continue after the end of the grant. Site visitors 

also conducted group interviews with students, parents and teachers. 

 Outcome information about participating students and their 

parents. Data were collected on students at 18 GEAR UP and 18 

non-GEAR UP comparison schools through student records and 

student and parent surveys, as well as records of students’ and 

parents’ participation in GEAR UP-sponsored activities. GEAR UP 

 

7

 Data from NCES’ Common Core of Data (CCD) were used to select the “best” school matches based on 

student demographics, percentage of students eligible for free or reduced-price lunches and the grade span 

of the school. Geographic proximity was also taken into consideration in those instances when a 

comparison school was not available within the same school district. Later analyses showed that students 

were closely matched. Appendix A, contained in this volume, discusses the comparison selection process, 

and appendix E, discusses the removal of baseline differences. 

Three rounds of site 

visits were conducted 

to provide 

information on 

program operations.

Data were collected 

from students, 

parents, student 

records and 

transcripts and 

project activity 

records.

Up to 140 students 

with parental consent 

were randomly 

sampled from each 

middle school.
 8 

schools in the evaluation were connected to 18 of the 20 sites visited. 

Surveys were conducted early in seventh grade with both students and 

parents and then again near the end of eighth grade. Data on 

participation in GEAR UP activities were collected continuously 

between September 2000 and June 2002 on sampled GEAR UP 

students and their parents. Not all projects provided these data. 

 Information from the 2002 GEAR UP Annual Performance 

Reports (APRs). The APR provided aggregate data on all GEAR UP 

projects. Data on the number and demographic composition of 

students served were used to determine the comparability of the 

evaluation’s sample of projects to the GEAR UP program overall. All 

GEAR UP grantees funded before April 2002 submitted APRs for the 

period May 2001 to April 2002. 

Schools that draw from communities with high rates of poverty often have high mobility 

rates as well. While some of the schools in the evaluation reported relatively stable 

student populations, especially those schools located in rural areas, other schools reported 

annual student turnover rates of 50 percent or greater. For this reason, in the national 

evaluation, many students who started the seventh grade in a GEAR UP school did not 

finish seventh grade—or start the eighth grade—in the same school. By spring 2002, 16 

percent of the students in the study left the school they attended in fall 2000. (See 

appendix A for more information on the handling of students leaving sampled schools.) 

The mobility figures are similar for students in both the GEAR UP and non-GEAR UP 

schools. Students who were initially sampled in the fall of their seventh grade but who 

were not enrolled in the same school in the spring of the eighth grade were not included 

in the analyses reported herein. 

An analysis of students who left their original sampled school before the end of eighth 

grade showed that these students differed on specific characteristics from those who 

remained. (See appendix B for a full analysis of students who left their sampled schools.) 

By controlling for resulting baseline differences between those students who remained 

and those who left their sampled schools, the validity of the findings in this report is not 

affected. 

1.4 Scope of Report 

The legislation establishing GEAR UP mandated an evaluation of the program. This 

report is the final product of the National Evaluation of GEAR UP, which began in fall 

1999. The report describes the program, as implemented, and examines the outcomes of 

GEAR UP in middle school on early indicators of future postsecondary enrollment. This 

report does not include an analysis of the outcomes of specific early intervention services 

on interim outcomes since complete service records were not obtained from all projects. 

Appendix I does provide an analysis of services on a limited number of projects and 

students where complete service information was obtained. 

Annual Performance 

Reports provided 

information about all 

GEAR UP 

partnership grantees.

Because of high 

mobility rates, this 

report focuses on 

students who 

remained in the same 

school throughout the 

study period.
 9 

1.5 Limitations 

A number of factors in the evaluation design lead to some important limitations on the 

strength of conclusions that are drawn in the report: It was not a randomized experiment; 

the set of cooperating grantees and schools is a small purposive sample, leading both to 

concerns about generalizability and power to detect small effects―particularly 

schoolwide effects such as curriculum changes and the resulting shift in course-taking 

patterns; the comparison schools could not be matched on historical college attendance 

rates, as would have ideally been desired; and because service provision started prior to 

baseline data collection in the seventh grade, it was not possible to remove all seventhgrade differences between the two sets of students without simultaneously removing 

some of the effects of early information services. More detail on these limitations is 

provided below. 

This study can report only on “interim outcomes” of students and their parents: increased 

knowledge, improved behavior and increased expectations. The GEAR UP students had 

not yet completed high school so the longer term outcomes of increased postsecondary 

enrollment and completion could not be obtained. The program had not been in effect 

long enough to serve students from the seventh through the 12th grade and into college. 

The information for the evaluation comes from site visits, surveys of students and parents 

and school administrative records, including student transcripts for a sample of GEAR 

UP middle school students and from a matched comparison group of non-GEAR UP 

middle school students. Because GEAR UP projects were newly funded in 1999, the 

selection of sites for this evaluation was limited to those projects that were up-andrunning within the first six months after receiving their awards. Matching was done at the 

school level and involved a limited set of demographic type variables. It was not possible 

to match on historical postsecondary education pursuit rates because this information is 

not available at the middle school level. Only a small number of schools (18 GEAR UP 

and 18 comparison) were involved in the study in order to allow in-depth reporting on the 

implementation process. The significance levels of the statistical tests between the two 

groups are fully adjusted for the small number of schools in the study. 

The main substance of the report involves statistical analyses of differences between the 

GEAR UP and non-GEAR UP school students and their parents. As noted above, these 

comparisons adjust for some, but not all, of the baseline differences between the two 

groups. Because the GEAR UP programs were already active in fall of 2000 before the 

baseline measurements were collected, some discretion was required in deciding which 

baseline differences should be controlled (removed) through adjustment techniques. Both 

students and parents were surveyed in the late fall and early winter of seventh grade 

(2000–01 school year) after the start of the GEAR UP program. The seventh-grade data 

showed that the GEAR UP projects had been very active in the early fall, holding GEAR 

UP kickoff convocations with students and parents, taking students on field trips to local 

colleges and providing other services. 

 

On the other hand, grant applications and site visit evidence showed that school districts 

generally began their GEAR UP projects in schools with the greatest proportion of at-risk 

students. In fact, survey, transcript and administrative records data showed that GEAR 
 10 

UP schools were less committed to the educational process and had somewhat higher 

signs of socioeconomic distress. Thus a paradoxical pattern was encountered in which 

students in GEAR UP schools at the time of the seventh-grade surveys had less positive 

attitudes about school in general and worse study habits, but had been exposed to 

substantially more information about postsecondary education options than their nonGEAR UP counterparts. Judgments had to be made about which data elements reflected 

GEAR UP early intervention activities (therefore not appropriate for use as baseline 

covariates) and which could still serve as baseline covariates. These judgments were 

made before looking at eighth-grade data. Variables were identified that were very 

unlikely to be affected by GEAR UP in this short period of time, and other variables were 

identified that could be affected. 

The following are likely to be the result of early GEAR UP services and using these as 

covariates would covary out the GEAR UP program effect we want to measure: 

 GEAR UP students reported more frequent meetings with adult 

mentors such as a Big Brother or Big Sister, 

 More GEAR UP students reported having a one-on-one counseling or 

advising session about getting ready for college, 

 More GEAR UP students reported attending a class or meeting about 

getting ready for college, 

 More GEAR UP parents reported attending meetings about college 

preparatory curricula, 

 More GEAR UP parents reported finding out about child participation 

in the kinds of activities sponsored by GEAR UP through letters or 

written notices, 

 More comparison parents reported having no information about 

college entrance requirements, 

 More GEAR UP students had at least heard of two-year and 

community colleges, 

 More GEAR UP parents reported that their seventh-graders had 

visited a college campus, 

 More GEAR UP parents reported attending meetings about the types 

of classes their children should be taking to get ready for college, and 

 More GEAR UP parents reported receiving written materials of 

college preparatory curricula. 

On the other hand, the following are not likely to be the result of GEAR UP, at least not 

in the first few months of the program, and are used as covariates: 
 11 

 Fewer GEAR UP parents perform volunteer services in the schools, 

 Class skipping by minority students is more common in GEAR UP 

schools, 

 GEAR UP students spend more time watching TV and playing video 

games, 

 Comparison students more strongly affirm the importance of hard 

work in school, 

 White mobility is higher in GEAR UP schools, 

 Adult educational attainment among mobile families is lower in 

GEAR UP schools, and 

 Student-parent conversations among white families about community, 

national and world events were less common in GEAR UP schools. 

Another important part of the evaluation was to describe the actual interventions and to 

assess the prospects for the sustainability of the program’s activities after federal funds 

are no longer available to these grantees. These goals required intensive onsite activities 

that could only be done at a small number of schools due to the associated costs. Thus, 

the school sample size is small. Eighteen schools from GEAR UP projects and 18 nonGEAR UP comparison schools participated in the evaluation. The analytic procedures 

used in the report fully adjusted significance levels for the small number of study schools. 

There is, however, the possibility that effects were missed because the process for 

adjusting significance levels sharply reduced the statistical power. The reduction in 

statistical power was particularly acute for school-level outcomes because the sample size 

(36 schools) is so small. Throughout the report, an “association” is discussed only if the 

supporting hypothesis test was significant at the 5 percent level, meaning there would 

have been only a 5 percent chance of finding the difference by chance. There are some 

associations discussed when the significance level of the test was at the 10 percent level. 

These are qualified by the phrase “modest evidence.” If no evidence was found even at 

the 10 percent level, the phrase “no evidence” is used. 

The statistical power is reasonably good for self-reported student and parent data but poor 

for school-level data because of the small number of schools. Power is also poor for 

school reported student-level data. Although course taking is analyzed at the student 

level, it is strongly influenced by school-level decisions about course offerings, thereby 

resulting in low power 

Due to the limitations in the selection of study schools, the small number of schools in 

the sample, the procedure for selecting matching comparison schools and the timing of 

baseline measurements, the findings in this report are portrayed as merely suggesting 

effects rather than as proving them. The language of the report generally refers to 

associations, although these associations are adjusted in ways that should give them 

better inferences about causal relationships than would be the case with simple raw 

associations. 
 12 

1.6 Organization of This Report 

An Executive Summary is provided at the beginning of this volume. The remainder of 

this volume is organized into five chapters. Chapter 2 provides descriptive information 

about GEAR UP students in the national evaluation, their parents and the services they 

received while in middle school. Chapter 2 also provides descriptive information about 

non-GEAR UP students and the services offered at their middle schools. Outcomes for 

GEAR UP middle school students and their parents are the focus of chapter 3. Schoollevel outcomes for GEAR UP are covered in chapter 4 and look at changes that took 

place in GEAR UP schools since the implementation of the project. Particular focus is 

given to changes in academic curriculum, professional development opportunities and 

teachers’ attitudes. Chapter 5 provides background information on the GEAR UP 

partnerships by describing the organization and management of the projects participating 

in the national evaluation. The chapter looks at the relationship between partners, 

including their efforts to communicate and collaborate. The last chapter of the report, 

chapter 6, looks at the projects’ transitions as the students moved from middle school into 

high school and evidence that the projects will continue beyond the end of their federal 

GEAR UP grant. Appendix A details the measurement methodology for the National 

Evaluation of GEAR UP. Appendix B describes how the student sample was drawn, how 

missing data were handled and how variances were estimated. 

A detailed description of the development of outcome indices, including the College 

Orientation Index, is presented in appendix C. A validation of the College Orientation 

Index using the National Education Longitudinal Study8

 appears in appendix D. Because 

a simple comparison of change across two sets of matched schools was not possible, 

appendix E details the process undertaken to remove any differences between the two 

groups of students that existed at baseline. A simulation study using hierarchical linear 

modeling (HLM) is presented in appendix F. Appendix G describes the method used for 

analyzing the student transcript data. An analysis of standardized test scores is presented 

in appendix H, and appendix I describes the method for analyzing program activity 

records. The glossary of variables is contained in appendix J. Appendix K contains the 

data collection instruments used for the study. 

 

8

 The National Education Longitudinal Study (NELS) is a study of the educational experiences and 

transitions of students conducted by the National Center for Education Statistics. NELS began with a 

sample of eighth-graders in 1988 and conducted followups with these students in 1990, 1992, 1994 and 

2000. 

Additional 

information can be 

found in the 

appendices.
13 

2. Middle School Students and Their Parents 

At the time the GEAR UP legislation was written, there was growing concern that 

students were not being adequately prepared for the job market, which increasingly 

required education beyond high school. The literature pointed to several important factors 

in addressing the problem of students not being prepared to succeed in the information 

economy. Studies showed that to change student behavior one needed to intervene early 

in their education careers. Other studies found that student success was linked to 

enrollment in gateway courses such as algebra (Atanda 1999; Oakes 1990). Also 

important were the positive results achieved by the I Have A Dream Foundation, which 

adopts a cohort of students at an early age and promises funds for college if the youths 

stay in school and prepare academically for college. School reform was also a central 

issue at the time GEAR UP was designed. This led to the curriculum reform and 

professional development features of GEAR UP that set it apart from other early 

intervention programs funded by the U.S. Department of Education. 

The overarching goal of the GEAR UP program is to increase postsecondary attendance 

and success among low-income students. The GEAR UP legislation also stipulates that 

funded partnership projects must begin providing services to students no later than the 

seventh grade and follow those students through high school. At the time the first grants 

were awarded in fall 1999, projects could receive federal funding for a maximum of five 

years. Funding was later extended to include a sixth year. Because the vast majority of 

projects were designed to begin with an initial cohort of incoming seventh-graders, the 

sixth year of funding meant that projects could provide services to these students through 

all of their high school years before the federal funding ran out. For later cohorts, projects 

would need to secure funding from other sources to serve those students through the 12th 

grade. 

Because the initial years of the GEAR UP program were focused on middle school 

students, this chapter lays the foundation for determining the outcomes for GEAR UP on 

these students by addressing the following questions. 

 What are the characteristics of middle school students who are being 

served by GEAR UP partnerships? How well do the GEAR UP 

students who participated in the national evaluation represent middle 

school students overall? How similar are GEAR UP students to 

students in non-GEAR UP schools in the national evaluation? 

 What services are the national evaluation of GEAR UP students 

receiving? Do students in the non-GEAR UP schools in the national 

evaluation receive services similar to those provided in GEAR UP 

schools? 

GEAR UP’s goal is 

to increase 

postsecondary 

attendance and 

success among lowincome students.

Projects serve 

cohorts of students 

beginning no later 

than seventh grade.

The evaluation 

focuses on outcomes 

during middle school.
 14 

 What services do parents of national evaluation of GEAR UP students 

receive? 

 How frequently do GEAR UP students and their parents participate in 

GEAR UP-sponsored activities? 

With the target low-income population in mind, the GEAR UP program was designed 

with enough flexibility to permit a project to develop models of service that fit the needs 

of individual schools and their students within the cohort structure. The GEAR UP 

program and those projects in the national evaluation served a higher percentage of 

minority students than the average middle school in the United States. 

The varying intensities of services and differences in the services provided an opportunity 

to understand how projects serve a cohort of students. Most GEAR UP projects planned 

their offerings so that some services, such as remedial services, were not provided to all 

students. In addition, participation in many widely reported GEAR UP services was 

limited, voluntary or both. Most of the schools in the study did not spend resources solely 

on services that could be provided equally to all students. Rather, their programs were 

designed to provide services to those students and parents who were targeted or who 

volunteered to participate. These projects typically assessed the students to determine 

their individual needs and how best to serve them. 

In addition, only the projects having a widespread effect on instruction, through reform of 

core curricula or extensive in-service training to improve instruction, were likely to 

provide a service that affected an entire cohort at a relatively intense level. One of the 

projects in the national evaluation was offering a new curriculum in a core academic 

subject that affected instruction for all students. A few additional projects were embarked 

on reforms that could have affected curricula for all or could have affected all students 

through policy changes in the future, such as persuading a district to mandate eighthgrade algebra for all students or by encouraging students to explore career choices and 

use instructional software programs. 

2.1 Student Characteristics 

In its third year of operation, GEAR UP was reaching roughly 3 percent of the middle 

school population across the United States. Nationally, there were more than 10.8 million 

students enrolled in sixth through eighth grades in fall of 2000 (U.S. Department of 

Education 2003a). For the school year 2001–02, about 220,000 middle school students 

were being served by 243 GEAR UP partnerships.9

 

 

9

 Because some students had already moved on to high school, an additional 80,000 GEAR UP students who 

were in high school were also participating in GEAR UP-sponsored activities. 

Projects were 

designed to meet the 

needs of the 

population they were 

serving.

Projects assessed 

student needs and 

targeted services 

accordingly.

Professional 

development and 

curriculum reform 

efforts were 

undertaken by some 

projects.

In 2001, GEAR UP 

served about 3 

percent of middle 

school students.
15 

Table 2-1 compares the demographics of GEAR UP and non-GEAR UP middle school 

students participating in the national evaluation and lays the foundation for discussing 

GEAR UP’s outcomes for students and parents in the next chapter.10 The table also 

compares the characteristics of students in GEAR UP nationally and in all public middle 

schools with those GEAR UP and non-GEAR UP students in the national evaluation. 

Because the sites selected for the evaluation are a subset of the GEAR UP projects, this 

section establishes how similar the students in the national evaluation were to GEAR UP 

students program-wide. This section also looks at how students being served by GEAR 

UP compare to middle school students nationally. 

Table 2-1. Comparison of characteristics of GEAR UP and non-GEAR UP 

students in the national evaluation

National Evaluation of GEAR 

UPa

Characteristics 

All public 

middle schools

(%) 

GEAR UP 

program 

nationally 

(%) 

GEAR UP 

middle schools

(%) 

Non-GEAR 

UP middle 

schools 

(%) 

Gender 

 Male 

 Female 

51 

49 

50 

50 

50 

50 

50 

50 

Race/ethnicity 

 African-American 

 Asian 

 Hispanic 

 Native American 

 White 

17 

4 

16 

1 

62 

30 

3 

36 

5 

26 

25 

3 

31 

7 

35 

19 

6 

25 

2 

48 

Special programs 

 IEPb

 LEPc

 NSLPd

13 

8 

37 

11 

12 

N/Ae

12 

12 

65 

10 

8 

62 

a Comparison between GEAR UP and non-GEAR UP students who remained in the evaluation through the end of eighth 

grade. 

b

 Individualized Education Program 

c

 Limited English Proficient 

d

 National School Lunch Program 

e Not available, however, to be eligible, at least 50 percent of the students in the school must be eligible for free or 

reduced-price meals. 

SOURCE: 2001 Common Core of Data, 2001–02 GEAR UP Annual Performance Reports, and 2001–02 National 

Evaluation of GEAR UP student record data. 

 

10 Methods used to control for baseline differences, such as those discussed here, are presented in 

Appendix E, Removal of Baseline Differences. 
 16 

Although non-GEAR UP schools in the national evaluation were selected based on their 

similarity to GEAR UP schools, by the end of eighth grade, differences in attrition 

(mobility) resulted in the differences shown in table 2-1. (Because a perfect match during 

sample selection was not feasible, appendix E describes the methods used to control for 

baseline differences between the two groups.) While there was virtually no difference in 

the percentages of boys and girls, GEAR UP partnerships served a higher percentage of 

minority students than the national average for middle school students. (See table 2-1.) 

Nearly two-thirds (65 percent) of GEAR UP students in the national evaluation were 

members of minority groups compared to roughly three-quarters (74 percent) of the 

middle school students participating in GEAR UP during 2001–02. By comparison, 

minority students made up only 38 percent of the middle school population nationally 

(U.S. Department of Education 2003b). More than one-half (52 percent) of the nonGEAR UP students in the national evaluation were members of minority groups. 

The schools participating in GEAR UP served a needier student population than the 

typical public school in the United States during 2001–02. This is primarily because the 

GEAR UP legislation requires that 50 percent or more of the students at participating 

schools qualify for free or reduced-price lunches under the National School Lunch 

Program (NSLP). Nationally, nearly 17.4 million students (37 percent) were reported as 

eligible for free or reduced-price meals during 2001–02 (U.S. Census Bureau 2000). 

Many of the schools in GEAR UP, however, had NSLP eligibility rates well in excess of 

50 percent of their student populations, with GEAR UP partnership projects reporting 

that 65 percent of their students, on average, were eligible for NSLP that year. In the two 

sets of schools, similar percentages of students were eligible for the NSLP (65 percent 

GEAR UP versus 62 percent non-GEAR UP). 

Students who have been identified as having special educational needs are required to 

have individualized education programs (IEPs) to monitor their education progress. The 

percentage of students with IEPs being served by GEAR UP was similar to the 

percentage of students nationally with IEPs. Approximately 13 percent of all students 

nationally had IEPs compared with 11 percent of the GEAR UP middle school students 

nationally (U.S. Department of Education May 2003a). Approximately 10 percent of the 

students attending non-GEAR UP schools in the national evaluation were identified as 

having special educational needs. Comparatively, 12 percent of the GEAR UP students in 

the national evaluation had IEPs. 

During 2000–01, the most recent year for which data are available, more than 870,000 

middle school students nationally (8 percent) were identified as limited English proficient 

(LEP) (U.S. Department of Education October 2002). During 2001–02, 12 percent of 

GEAR UP students program-wide needed additional English language instruction. In the 

national evaluation, 12 percent of GEAR UP students and 8 percent of non-GEAR UP 

students were identified as having limited English skills. 

In 2002, 74 percent 

of GEAR UP students 

nationally were 

minorities.

The GEAR UP 

students in the 

national evaluation 

were fairly 

representative of the 

GEAR UP program.

GEAR UP serves a 

needier population 

than the typical 

middle school.
17 

2.2 Services Provided to Middle School Students 

GEAR UP and non-GEAR UP students participating in the national evaluation were 

asked about the types of activities they participated in during the eighth grade. Table 2-2 

shows the percentage of students self-reporting participation in each type of activity. 

Compared to non-GEAR UP students, GEAR UP students reported receiving more 

mentoring and one-on-one counseling about high school and college. GEAR UP students 

were also more likely to attend classes or meetings about getting ready for college and 

were more likely to visit a college campus by the end of eighth grade than non-GEAR UP 

students. GEAR UP students, however, reported receiving less tutoring in mathematics 

and homework help than their non-GEAR UP counterparts. 

Information on the full range of activities and services undertaken by GEAR UP projects 

participating in the national evaluation was obtained through detailed activity records as 

well as from the three rounds of site visits to the projects conducted in spring 2000, 2001 

and 2002. Each of the projects participating in the national evaluation was asked to 

maintain records on all of the services they provided to students and parents between 

September 2000 and June 2002, which covers school years 2000–01 and 2001–02. Those 

projects that provided services to students during the intervening summer were also asked 

to collect information on all services they provided during that time period. (Sample 

copies of three types of activity forms used can be found in Appendix K, Data Collection 

Instruments.) Projects were asked to provide a general description of each activity that 

included: 

 Type of activity (e.g., tutoring, field trip, workshop), 

 Subject matter covered (e.g., English, college financial aid), 

 Timing of the activity (e.g., after school, weekend), 

 Number of students or parents attending each activity, 

 Leader of the activity (e.g., classroom teacher, project staff), and 

 Duration of the activity (e.g., days, hours, minutes). 

The projects were asked to provide the above information about each student activity 

they sponsored and which students attended the activity. The same information was 

requested for all project-sponsored parent activities. 

Although the projects were asked to report information on all activities sponsored by 

their GEAR UP grant, the level of recordkeeping varied considerably across projects. Site 

visit information and detailed discussions with projects revealed that many sites provided 

incomplete data on the extent of their activities. (See Appendix I, Methodology for 

Analyzing Program Activity Records, for a full discussion of the completeness of the 

participation data obtained from sites and limitations in analyzing these data.) 

GEAR UP students 

were more likely to 

visit college 

campuses and receive 

information about 

getting ready for 

college.

Few projects 

provided detailed 

records of the 

services provided to 

students although all 

were asked.

Because the level of 

recordkeeping varied 

considerably, only 

limited analysis of 

services is possible.
 18 

Table 2-2. Percent of students self-reporting participation in various activities 

Activities 

GEAR UP 

students 

Non-GEAR 

UP students Difference 

Received homework help 43 47 -4* 

Received tutoring in math 28 32 -4* 

Received tutoring in English or language arts 19 16 3 

Received tutoring in science 15 15 0 

Met with an adult mentor such as Big Brother or 

Big Sister 

29 23 6* 

Attended one-on-one counseling or advising 

session about getting ready for high school 

46 40 6* 

Attended one-on-one counseling or advising 

session about getting ready for college 

34 22 12* 

Attended a class or meeting about getting ready for 

college 

50 29 21* 

Attended a class or meeting about how to study 

better 

23 20 3 

Attended a class or meeting about possible careers 

after school completion 

56 55 1 

Visited a college campus 59 34 25* 

Visited a job site or talked with someone about 

their job 

48 48 0 

*

Statistically significant at the 0.05 level. 

SOURCE: National Evaluation of GEAR UP Eighth-grade Student Survey, 2002.

Across all projects in the national evaluation (including those projects providing 

incomplete information), the vast majority of GEAR UP students participated in at least 

one activity during the study period. More than 80 percent of the approximately 1,800 

GEAR UP students in the national evaluation were reported to have participated in more 

than 2,700 GEAR UP events between September 2000 and June 2002. (The actual 

number of events per student is probably higher because not all data were reported by all 

projects.) These activities were primarily led by classroom teachers or GEAR UP staff 

but were sometimes conducted by paraprofessionals, school counselors, other school 

professionals, college faculty, college students or a community, business or parent 

volunteer. In general, most student activities took place during school or directly after 

school. A few were held before school, in the evenings or on the weekends. A few 

projects provided services to students during the summer break primarily between the 

first and second years of the program. 

Although the services provided by grantees varied considerably, the basic services 

offered to students and parents fell into the following basic categories: 

 Academic Support. These services were supplemental services to 

help students improve their academic performance in their classes or 

prepare for standardized tests. 

 Guiding Students to College. These services consisted of two types: 

More than 2,700 

GEAR UP events 

took place across 19 

GEAR UP sites 

between September 

2000 and June 2002. 

Most events occurred 

during the school 

day. 
19 

- Career Oriented. These services focused on raising students’ 

awareness of career opportunities and determining what their 

interests and skills were. 

- College Information. These services focused on providing 

students and parents with information about college entrance 

requirements and the availability of college financial 

assistance. 

 Other Activities. These services tended to be more enrichment types 

of activities such as field trips to museums or theatrical performances. 

Projects saw these activities as helping broaden student and parent 

life experiences. 

GEAR UP activities frequently covered two or more of these categories at any one event. 

For example, projects combined career information with information about college 

preparation and college financial assistance. Other combinations included linking 

academic support and counseling about college majors. Although such linkages were 

frequently made at the project level, the discussion that follows focuses on the individual 

activities. 

Because it was expected that non-GEAR UP schools might offer similar types of services 

to students, visits were made to non-GEAR UP schools each spring at the same time 

visits were made to GEAR UP projects and schools. The purpose of the visits to nonGEAR UP schools was to obtain information about the schools, the students attending the 

schools and the services available to students and their parents. Particular interest was 

paid to those services that may have been similar to the services provided at the GEAR 

UP schools. Although information on the types of services available to students and 

parents was obtained during the site visits, the actual utilization of those services by nonGEAR UP students was not collected (except through self-reporting in the student 

survey). 

Based on information obtained during the site visits, all of the non-GEAR UP schools 

provided at least some supplemental services to students outside of the school’s regular 

curriculum. Much like the services at GEAR UP schools, the services available at the 

non-GEAR UP schools were diverse and varied widely from school to school. The types 

of services fell into the same general categories as those offered by the GEAR UP 

projects. 

Academic Support 

Activities that provided academic support to students were the most prevalent type of 

activity across the GEAR UP projects that submitted detailed participation records. This 

was consistent with information obtained during site visits to all projects in the national 

evaluation. Academic support activities at GEAR UP schools took the form of: 

 Tutoring. This was the most prevalent type of academic support. It 

was provided mostly as small-group assistance, but it was also 

provided in one-on-one sessions. Computer-assisted instructional 

GEAR UP activities 

frequently covered 

multiple topics.

Academic support 

services, such as 

tutoring, were the 

most common.

Many non-GEAR UP 

schools offer similar 

services as GEAR UP 

schools; however, 

data on utilization of 

services are not 

available.
 20 

laboratories were also used as tutorials by providing students an 

opportunity to practice specific skills as well as helping students 

prepare for standardized tests. Tutoring was primarily offered during 

or immediately after school. In a few cases, projects offered tutoring 

in the morning before the school day began. 

 After-school or Saturday academies. A small number of the 

sampled projects operated either an after-school or a Saturday 

component to their GEAR UP project that combined tutoring or other 

academic assistance with career exploration, interest clubs or 

recreational activities. These programs were most commonly called 

clubs, after-school academies or Saturday academies. After-school 

programs were typically held several times a week, and Saturday 

programs were held from once a month to every Saturday. Most were 

led by GEAR UP staff, paid teachers or social service professionals. 

Some of the programs were extensions of offerings available before 

GEAR UP (under 21st-Century Schools, Title I or other auspices). 

These programs typically were voluntary, and sites reported that 

participation levels were generally lower than expected. 

 Summer programs. Academic assistance and college awareness 

were merged in many of the GEAR UP summer programs. In their 

first year, the GEAR UP partnership projects had plans for ambitious 

summer offerings. Projects that had only begun to offer student 

services in the second half of that year held summer programs that 

were considerably more intensive than the school-year services. Some 

schools offered primarily remedial education, others provided 

enrichment programs that combined instruction in core subjects with 

trips, hands-on activities, cultural events and recreation. Services 

were offered at colleges, middle schools and community agencies. 

They were planned for three or more weeks. Projects reported that 

most of the summer programs attracted only a limited number of 

students. Transportation was a major problem in some projects. 

Projects did not attract as many students as anticipated, even when 

students could participate at a neighborhood school or community 

center.

When services were provided outside of regular school hours, many projects indicated 

during the site visits that they sometimes had difficulty attracting students to tutoring 

sessions and to some other activities. In focus groups, students indicated that 

transportation was a problem for after-school activities. Parents’ work schedules often did 

not permit them to pick up their child after school. Transportation issues were particularly 

prevalent in the rural communities. 

Competition from other school-sponsored activities and other nonschool activities also 

drew students away from GEAR UP and reduced participation levels. A few students also 

said that they were often just too tired at the end of the school day to engage in additional 

academic-related activities. Despite these difficulties, some projects in the evaluation 

tutored large numbers of students. The tutoring in these projects was generally required 

A few projects 

operated after-school 

or Saturday 

academies that 

combined tutoring 

with other assistance 

such as career 

exploration.

Transportation was a 

problem for afterschool activities.

Other activities 

sometimes drew 

students away.
21 

for students at risk of poor performance and frequently occurred several weeks before the 

administration of district- and state-required standardized tests. 

In their original designs, many of the projects planned to provide one-on-one tutoring to 

most or all of their students, with much of it to be provided by college students or other 

volunteers from partner organizations or the community. During the site visits in 2001, 

GEAR UP project staff expressed frustration at being unable to find adequate numbers of 

volunteer tutors. The project staff said they had difficulty attracting and retaining student 

volunteer tutors because of scheduling conflicts and transportation needs. School policies 

regarding volunteers in conjunction with the limited availability of qualified volunteers 

further hindered projects’ abilities to capitalize on their plans. The data from the activity 

reports support this claim, indicating that little tutoring was conducted by outside 

volunteers. 

Because of these problems, by spring 2002, many projects had turned to paid tutors for 

fulfilling their tutoring needs. Projects frequently hired regular teachers to work before or 

after school or on Saturdays. They also used GEAR UP project staff and student teachers 

as tutors or paid a limited number of college students who then worked part time (e.g., 

through the college work-study program). In one case, the project used high-performing 

high school students to tutor the middle school students during the school day. The high 

school tutors received a stipend from the GEAR UP project. 

Across the projects in this evaluation, the supplemental services of academic support, 

which include tutoring, were provided to students with academic problems or to those 

who had performed poorly on standardized tests. Most projects did not have the staff 

needed to provide such support to all participants with academic deficiencies. Teacher 

recommendations played a major role in deciding who received academic support, both 

during school hours and out of school. 

The site visits indicated that academic support during school hours was more likely than 

out-of-school academic support to focus on a specific course or on preparation for 

standardized tests. Teachers used a tutor in the classroom to work with individuals or 

with small groups of students who needed more assistance with a specific lesson. In some 

cases, students or whole classes needing additional help used a GEAR UP-supported 

computer laboratory to practice new skills. A few projects offered tutoring during lunch 

or study hall periods, when students could receive more individualized attention. Only a 

few projects indicated that students were taken out of classes for tutoring. When this 

occurred, the students were excused from physical education or elective classes, not core 

academic classes. 

More than any other type of GEAR UP activity, tutoring began and remained at the core 

of GEAR UP services for students. As the projects matured over the academic years 

studied, schools made program changes to better fit their specific needs. As grantees 

implemented their GEAR UP projects, they modified their initial designs to meet the 

specific needs of their students. Even with these modifications it was clear from the 

participation data reported and site visits that tutoring was the primary activity provided 

to students. 

Projects paid tutors 

to address shortage 

of volunteers.

Teachers frequently 

recommended 

tutoring for students 

with academic 

deficiencies.

Tutoring was 

provided in the 

classroom to 

individuals or small 

groups.

Tutoring remained at 

the core of GEAR UP 

services.
 22 

After experiencing lower than anticipated attendance during the first summer, 2000, the 

projects planned less remedial instruction and fewer weeks of service for the following 

summer. Several of the projects in the evaluation provided services to students during 

summer 2001, but these sessions were shorter than in the previous year. Services focused 

on academics, but they also included field trips and other cultural events. Even with these 

changes, attendance was considered by GEAR UP staff to be lighter than anticipated. 

Most programs, however, expected relatively small numbers of students—up to one-third 

of their students. A few projects established eligibility criteria as well and planned to 

enroll only those students who had demonstrated good behavior during the school year or 

whose parents actively enrolled them in the session. 

As with the GEAR UP schools, the most common service reported across the non-GEAR 

UP schools was academic support. Nearly all of the schools provided this type of service. 

These services included after-school tutoring and homework hotlines as well as the two 

TRIO programs, Talent Search and Upward Bound, which also serve middle and high 

school students.11 Several non-GEAR UP schools also reported offering special programs 

for academically talented students such as the gifted and talented programs. Two other 

non-GEAR UP schools reported offering either computer programming or journalism 

classes to academically talented students. Another school reported that it offered a special 

summer remediation program to students to help them catch up and prepare for the 

coming year. 

Guiding Students to College 

The projects in the national evaluation provided a variety of activities aimed at 

encouraging students to plan for college. Depending on the project, these services 

focused either on career opportunities or information about college. 

GEAR UP projects sponsored career-oriented activities such as career fairs that focused 

on opportunities like career academies, interest inventories and individual development 

plans. Information about colleges was typically provided through college fairs. Both 

career and college fairs, which took place in almost all projects, were generally 

schoolwide events. These fairs involved posters and information tables; visits and 

presentations from college officials, college students and business representatives (some 

of whom were project partners); special games; and other college-related activities. Some 

fairs occurred on a single day, while others involved activities spread over a week or a 

month. Sometimes, GEAR UP projects operated these fairs independently, but more often 

these fairs were jointly sponsored by GEAR UP and another program in the school. This 

co-sponsoring of activities helped GEAR UP projects stretch their resources so that other 

activities could be provided. 

 

11 TRIO refers to several federal programs known officially as Federal TRIO Programs. The three original 

federal programs from which the “trio” programs derived their name were Upward Bound (1964), Talent 

Search (1965) and Student Support Services (1968). With the passage of the 1998 Higher Education 

Amendments, the number of programs authorized under this legislation increased to eight. Although the 

term TRIO (in all caps) is not an acronym or initialism, it has been retained to avoid confusion. 

Tutoring was also the 

most common service 

at non-GEAR UP 

schools.

A variety of activities 

were designed to 

encourage college 

planning.

Projects shortened 

and targeted their 

summer programs.
23 

All of the projects in the study held at least one college visit, and many organized 

multiple visits over the length of the study. In fact, as their programs matured, more 

schools organized visits to college campuses in 2001–02 than in the earlier year of the 

evaluation. Students who participated in the focus groups reported they greatly “enjoyed”

the college visits and were considering college more seriously as a result of the visits. 

Several project staff indicated that GEAR UP was responsible for starting college visits 

for seventh-grade students. Before GEAR UP, such visits were not held or were only for 

eighth-graders. In the first year of GEAR UP, when implementation was just beginning, it 

was typical for all students in a grade to go on a single college visit, usually to a partner 

college for a half or a full school day. Over the next two years, there was more diversity 

in visits. In some projects, all students went on one visit, but selected, smaller groups of 

students went on additional college visits. These students typically were selected based 

on a first-come, first-served basis, but sometimes participation was based on 

recommendations from teachers or others. 

More than one-half of the non-GEAR UP schools visited provided information about 

college to students and parents. A few of the schools reported that general information 

about colleges was typically provided to parents through college nights. A few other 

schools provided more intensive, specific information through college counseling 

sessions. One school offered a college planning workshop for students and parents. A few 

of the middle schools took students on visits to college campuses, and one other middle 

school invited college recruiters to the school to talk about their college and campus life. 

Information about future career opportunities or options was also discussed with students 

at non-GEAR UP schools. About one-half of the non-GEAR UP schools provided career 

exploration opportunities to their students. These opportunities came in a variety of 

forms, including career education classes, career days or guest speakers. A few schools 

provided one-on-one career counseling to students or conducted career assessments. Only 

one school provided students with the chance to visit job sites and learn firsthand about 

specific occupations. 

Other Activities 

In addition to college trips and career fairs, many of the GEAR UP projects held a variety 

of special events that were seen as opportunities to expand the horizons of program 

participants. Project staff and teachers spoke about the limited experiences most of the 

students had, stating that many students and their parents had never traveled outside their 

neighborhoods or communities. Special events included trips to theatrical performances 

on college campuses, museum exhibits and places of employment. Some other common 

types of special events were GEAR UP program orientation sessions, awards assemblies 

and engagement in community service. 

Special events were generally voluntary; therefore, only relatively small numbers of 

students participated in any single event. A few projects took small numbers of students 

on major trips to distant cities, such as Washington, D.C. These exceptional trips were 

usually a reward for special activity or behavior (e.g., participating in an essay contest). 

In one project, two eighth-grade students were selected to travel to Japan during the 

All GEAR UP 

projects held at least 

one college visit.

Prior to GEAR UP, 

college visits were 

restricted to eighthgraders.

Each year, the 

projects visited a 

wider variety of 

postsecondary 

institutions.

Special events were 

planned to expand 

experiences of 

students and parents.

The level of college 

information varied 

widely across nonGEAR UP schools.

Special events were 

voluntary and 

generally limited to a 

few individuals.

About half of the nonGEAR UP schools 

provided information 

about careers.
 24 

summer as part of a cultural exchange program. Projects varied considerably on the 

number of special events they provided. 

Most of the GEAR UP projects in the evaluation planned to provide volunteer one-onone mentoring to all participants, and, as with tutoring, the inability to find volunteers 

made projects reconsider that plan. By the third year of the grant, only a small number of 

students had participated in mentoring, according to reported participation records. This 

is consistent with site visit reports. 

Where mentoring did take place, GEAR UP project staff were the largest source of 

mentors. An increasing number of projects gave up on providing one-on-one mentoring 

to students, or they provided mentors to only a small percentage of students who 

requested them or were referred by teachers or others. Other projects used college 

students or adult volunteers to serve as mentors with a small group of middle school 

students. Some project directors felt that tutoring had results similar to those of 

mentoring. 

As with the GEAR UP schools, nearly all of the non-GEAR UP schools offered a wide 

range of other support services to students. These fell primarily into two categories: 

enrichment and intervention. The enrichment activities included academic clubs and 

recognition for academic achievement. The intervention services were in the form of 

dropout prevention programs and self-esteem trainings. Two of the non-GEAR UP 

schools offered mentoring to students. The mentors were local college students who met 

periodically with a small number of students recommended for the program. The college 

mentors typically provided tutoring help as part of their mentoring. 

While similar types of activities were found in both GEAR UP and non-GEAR UP 

schools, the number of those services across schools appears dramatically different 

between the two types of schools. Based on information gathered from school staff, 

individual GEAR UP schools tended to offer a wide variety of services to students, while 

the non-GEAR UP schools offered far fewer services. 

2.3 Services Provided to Middle School Students’ Parents 

GEAR UP funds can also be used for activities designed to increase parental 

involvement. GEAR UP’s parent activities and services were analyzed through site visits 

and activity records. The largest difference between GEAR UP student and parent 

services across sites is the extent of services. More students than parents actively 

participated in GEAR UP, and students participated in many more activities than their 

parents. This confirmed what projects reported, i.e., that they provided more student 

activities in part because they had difficulty getting parents to attend. (Similar 

information about services provided to parents at non-GEAR UP schools was not 

collected.) 

Site visits found that parent services were a smaller part of GEAR UP activities than 

student activities for several reasons. First, they were designed to be smaller, serving 

fewer people and offering fewer services. In addition, with some notable exceptions, the 

Volunteer mentors 

were difficult to find.

GEAR UP staff were 

the largest source of 

mentors.

Non-GEAR UP 

schools also provided 

enrichment activities.

GEAR UP schools 

offered more and a 

wider variety of 

services to students 

than non-GEAR UP 

schools.

Parents did not 

participate in as 

many activities as 

students.

Although a smaller 

part of GEAR UP, 

projects continued to 

try to engage parents.
25 

projects experienced difficulty engaging parents in activities. However, despite parents’ 

low participation rates, the projects continued to offer activities to parents, and many 

projects expanded the range of parent activities. Activities fell into three categories. 

 Parent Institutes. During the site visits, about one-third of the 

projects believed that they were successfully reaching parents. In 

these projects, two different approaches seemed to work. In the first 

approach, which was used by several of the projects, parents were 

enrolled in parent institutes. In some of these projects, the institutes 

were operated by a contractor under a state GEAR UP grant. Another 

institute was operated as part of a citywide effort to empower parents. 

The institutes typically were 9- or 10-week workshops that provided 

parents with information and assistance to help their children prepare 

for college. Institutes operated by the contractor relied on the 

contractor to recruit parents. Instruction was offered in English and 

Spanish, and child care was provided. Parents “graduated” if they 

attended a certain number of sessions. All such projects with institutes 

reported large enrollments and planned to hold more workshops in the 

future. 

 Individual Parent and Child Counseling Sessions. The second 

approach was used by four projects. The projects held individual 

parent and child counseling sessions for all or most of the cohort. In 

one case, the individual meetings with parents and their children were 

“facilitated” by specially trained teachers. Ninety percent of the 

parents participated in these meetings. Two other projects made 

frequent home visits during the school year. In the other projects, the 

parent counseling sessions were operated by GEAR UP staff 

(including specialized community liaisons). Although clearly not 

mandatory for parents, all of the projects made strong efforts to 

impress upon parents how important these sessions were for their 

children’s future. 

 Other. Other types of activities were more informal and were 

becoming more prevalent as the GEAR UP projects matured. For 

example, two schools began a monthly talk between the school’s 

principal and any interested parents. Donuts and coffee were served, 

to reinforce the casual nature of these meetings. Other schools 

instituted a family game night or family reading night, in which 

parents participated in activities with their children. Finally, several 

projects simply made it a point to invite parents to GEAR UP 

activities and to keep them abreast of upcoming events through 

occasional GEAR UP newsletters sent home with the students. 

Staff members in more than one-half of the projects in the national evaluation indicated 

that attracting parents to meetings and events was quite difficult. With mixed success, 

schools sent out newsletters and bulletins to attract parents to workshops on college 

awareness, parent components of Saturday programs, parent meetings or “nights,” GED 

classes and parent auxiliary groups. 

GEAR UP projects 

had mixed success 

attracting parents to 

meetings.
 26 

Some project staff members said they became frustrated with the lack of parent 

responsiveness, a viewpoint echoed by teachers in the same project schools. Many 

teachers attributed poor attendance at school events to parents’ lack of concern with their 

children’s education. Discussions with parents in focus groups, however, indicated that 

parents saw themselves as involved in, and concerned about, their children’s education. 

(While teachers at GEAR UP schools may not have been satisfied with the level of parent 

involvement, an analysis of this issue in Chapter 3 shows that attendance at GEAR UP 

middle schools was positively associated with parent involvement.) 

Several differences existed in the types and timing of parent and student activities. First, 

and most obvious, is that parent activities were more likely to be held in the evenings. 

Student events, conversely, were more likely to be held during the school day or 

immediately after school. Another difference is that on average, parent activities attracted 

more participants per event than did student events. Parents tended to participate in 

events that focused on life skills and information about college while students 

participated in events focusing on academics and college awareness. Finally, parents 

largely participated in events led by GEAR UP staff and college students, while student 

events were mostly led by classroom teachers and GEAR UP staff. 

2.4 Intensity of Services Provided in GEAR UP Schools 

The previous discussion describes the types of GEAR UP activities offered. This section 

focuses on participation levels or intensity for these activities, including how many 

students and parents participated, how many separate GEAR UP events were held, and 

the relative size of the events. 

There are limitations to the analysis of the intensity of services. Only six of the 18 

projects completed activity records for all of their activities over the entire study. (Recall 

that only 18 of the 20 sampled GEAR UP projects provided student data for the outcomes 

study.) Because the data are incomplete from 12 of the projects, the intensity discussion 

will be based on information from the six schools that had completed activity records.12 

Much of the GEAR UP intervention is supplemental. Therefore, measuring the amount of 

service or contact the typical participants are likely to receive is important. Even without 

considering which students use which services, GEAR UP resources are limited. For 

 

12 A comparison of the six schools with complete records to the 12 schools with incomplete activity records 

indicates that both groups are largely similar, with some exceptions. First, schools with complete activity 

records had a larger percentage of events (and participants at those events) in the first year of the study 

(2000–01) than those projects with incomplete records. Second, schools with complete activity records 

held a larger percentage of their events after school and in the evenings and a smaller percentage during the 

school day. Finally, projects with complete activity records had a lower percentage of events (and 

participation at those events) led by classroom teachers and project staff and a slightly higher percentage 

led by college students and community volunteers. Unfortunately, it is impossible to determine with 

available data whether these differences arise from inherent differences between the two groups of projects 

or from the fact that not all activities were reported from 12 of the schools. Because of this uncertainty, the 

analysis in this section will be based solely on the activity records from those six schools with complete 

records. 

Parent activities were 

held in the evening 

and focused on life 

skills and college 

information.

Intensity of services 

discussion is limited 

to six GEAR UP 

projects.

The typical GEAR 

UP project spends 

about $650 (federal 

portion) per student 

per year.
27 

those GEAR UP projects in the national evaluation, the typical grant expended, on 

average, about $650 of its federal resources per student per year during the study 

period.13 This figure includes only the federal portion of the grant and does not take into 

account matching contributions, either financial or in-kind, that grantees are required to 

secure from their partners. 

In the six schools with complete activity records, about two-thirds of the 839 students 

sampled in these schools participated in at least one GEAR UP activity. The typical event 

attracted, on average, about 2 percent of the sampled students in these schools.14 Several 

hundred parents of sampled students in those six schools participated in more than 100 

events. In these same six schools, about 1 percent of parents, on average, participated in 

an event. The average level of participation was low because of several confounding 

factors, including cost; the limited types of “all participant” services, such as fairs and 

some college visits; the targeting of tutoring, which was the most common and frequent 

service; and the voluntary nature of other more intensive services such as the summer 

programs. 

The most common student services focused on academic activities or special events. In 

the six schools with complete activity records, those types of activities accounted for 

about three-fourths of all student activities. The most common parent services, in the six 

schools with complete activity records, focused on several topics, most often academics 

and college awareness. Such events made up over three-fourths of all parent activities. 

The service sessions provided to students tended to be shorter than those in which parents 

participated. More than one-half of the student activity sessions in the six schools lasted 

an hour or less. (See figure 2-1.) Parent activities in these six schools varied more in 

length. Fifty-three percent of these projects’ parent activity sessions lasted more than two 

hours, and about one-third lasted more than five hours. 

Activities varied in frequency as well as in length. The difference in frequency of 

services was the result of individual projects’ designs. Site visits indicated that the most 

universal (or projectwide) services offered to all students were relatively infrequent ones, 

such as week-long career fairs or college visits lasting one or more days. Most projects 

offered one career fair a year and one or two college visits for all participants. Tutoring, 

while far more frequent, was used by a subset of students with academic need. In the six 

projects with complete participation records, about one-quarter of students received 

tutoring. Available information indicates that the number of students participating in 

individual tutoring sessions varied considerably from one-quarter to three-quarters of the 

students within a given project. 

 

13 This figure is for all services, including those for students, parents and teachers as well as costs associated 

with curriculum reform efforts and general program operations. 

14 Because the national evaluation sampled up to 140 students in each school, the total number of students 

attending an individual event could very well be higher. Five of the six GEAR UP schools providing 

complete participation information had grade cohorts with more than 140 students. 

Academic activities 

were the most 

common services 

provided to students.

A typical session for 

students lasted an 

hour or less.

Frequency and length 

of activity were 

related to the type of 

activity.
 28 

Figure 2-1. Percentage of activities in six GEAR UP projects for students and 

parents, by duration of activity 

0

10

20

30

40

50

30 minutes or

less

31–60 minutes 61–90 minutes 91–120 minutes 121–180

minutes

181–300

minutes

300 minutes or

more

Duration of activity

Percent of activities

Student events

Parent events

SOURCE: National Evaluation of GEAR UP participation records, Sept. 2000 through June 2002. 

One-third of the projects provided one-on-one guidance services to students with 

academic need. However, guidance counselors reported that contact hours per participant 

were relatively low, ranging from less than one hour to about four or five hours a year. 

Activity records for the six projects indicated that most sessions between students and 

guidance counselors lasted between 30 minutes and one hour. Information collected 

during site visits indicated that the guidance hours received under GEAR UP were not 

duplicative of counseling services already provided by schools because counselors 

reported that before GEAR UP, they had insufficient time to meet with each seventhgrade student. 

In programs in which GEAR UP offered a class in addition to the school’s regular 

curriculum, the hours per enrollee were high, but the number of students enrolled in the 

course was often lower than for some other activities. Projects reported that only onequarter of a cohort or less enrolled in these classes (such as a MESA or AVID class).15

The same holds true for the summer programs. The summer programs could be intensive, 

including full-day and even residential projects. These activities typically lasted from one 

 

15 MESA stands for the Mathematics, Engineering and Science Achievement Program. This is a “hands-on” 

program that has been developed by several university engineering departments. AVID stands for 

Advancement Via Individual Determination. This program is designed to help underachieving students 

with high academic potential prepare for entrance into a four-year college. 

GEAR UP increased 

the amount of 

guidance counseling 

students received.

Summer programs 

served fewer 

students, but 

accounted for many 

hours.
29 

to four weeks. Generally, up to one-quarter of the students were enrolled in the summer 

programs. Some projects designed these summertime activities for larger numbers of 

students, while in other sites, these activities were specifically designed for smaller 

segments of the cohorts. 

31 

3. Student and Parent Outcomes 

The conceptual framework in chapter 1 (figure 1-1), identified several interim outcomes 

or steps to achieving the goals of GEAR UP of increased attendance and success in 

postsecondary institutions. This chapter examines those interim outcomes for GEAR UP 

since at the time of the National Evaluation it was still several years before the long-term 

outcomes could be known, given the ages of the participants in the study. 

For students, the current questions to be addressed are the following: 

 Does GEAR UP increase knowledge of postsecondary education 

requirements and availability of financial assistance? 

 Does GEAR UP cause positive behavioral changes, such as 

increased enrollment in more challenging classes, improved 

attendance in school, improved academic performance and increased 

on-time promotion? 

 Does GEAR UP raise expectations of what will occur in life after 

high school? 

The following questions focus on parental outcomes for GEAR UP: 

 Does GEAR UP increase parent’s knowledge of postsecondary 

education requirements and the availability of financial assistance? 

 Does GEAR UP increase parent’s involvement in their child’s 

education through such things as attendance at school events and 

activities? 

 Does GEAR UP raise parent’s expectations about their student’s 

schoolwork and future endeavors? 

The hypothesis is that these interim outcomes will happen sequentially, first increased 

knowledge, then more positive behavior, and then an increase in expectations. Prior 

research studies have found that students typically have high expectations in middle 

school and that these expectations wane as they get closer to high school graduation (U.S. 

Department of Education 1996). With this in mind, an increase in expectations for GEAR 

UP may actually appear as less or no decline in expectations as graduation nears. 

Research has shown 

that middle school 

students have high 

expectations about 

their futures.
 32 

Analytic Method 

A variety of methodological issues were confronted in the analysis phase of the study. 

Outcome data needed to be condensed and summarized. The quality of the initial 

matching needed to be reviewed. Additional adjustments based on student-level data 

rather than just school-level data needed to be considered. Standards of evidence and 

rules for analyzing subgroups needed to be established. Each of these issues is briefly 

discussed here. Greater detail can be found on all these issues in the appendices. 

Index Formation and Usage. For the majority of this chapter, indices were developed 

and tested to summarize the interim outcomes for the GEAR UP program, which are 

identified in the conceptual framework. The indices measure complex constructs and are 

composites of responses to student and parent questionnaire items. The primary purpose 

of index formation is to sharpen hypotheses before examining the data. This analytic 

approach is typically done to avoid statistical problems associated with running multiple 

tests on the same concepts. A secondary purpose of indices is to increase the statistical 

power and the ability to discern broad but subtle associations with a collection of 

outcomes. A disadvantage to using indices of this nature is that the index values 

themselves have no intrinsic meaning because they combine multiple questions. This can 

make it difficult to judge the programmatic value of statistically significant findings. 

Thus, where statistically significant findings for an index were found, the original 

questions used to create the index were also tested to determine the association of 

individual components with GEAR UP participation. Appendix C, Index Construction, 

describes how the indices were constructed for the national evaluation and details the 

elements that make up each index. Among these indices, one especially broad index was 

created called the College Orientation Index.16

The tables presented in this chapter show adjusted differences between students attending 

GEAR UP schools (GEAR UP students) and students attending schools not participating 

in GEAR UP projects (non-GEAR UP students) on each of the interim outcome 

indicators identified above. Two different analytic techniques were used for the 

adjustments. It is important to note that professional judgment was applied in the 

selection of covariates for the adjustments. It was felt that inferences should not be based 

solely on the school-level matching. Instead, it was decided to control on some but not all 

“baseline” variables collected in the fall and early winter of seventh grade. 

Matching and Covariate Selection Rules. As described earlier, a matching set of 20 

GEAR UP schools and 20 comparison schools was initially selected. Of these, 36 (18 and 

18, respectively) participated in the seventh-grade data collection. Because not all of the 

dropout schools were originally paired with each other, conditioning on the original 

 

16 The College Orientation Index is a summative index based on student and parent survey data that has been 

confirmed to be strongly linked to a student’s likelihood of attending college through analysis of NELS 

data. The index comprises the following six constructs: academic performance from the student’s 

perspective, parents’ views of student’s academic performance, student’s postsecondary aspirations, 

parents’ postsecondary aspirations for their child, student’s report of parent-child discussions and time 

spent by the student reading for pleasure. The NELS analysis may be found in appendix D. 

Indices were used to 

determine GEAR 

UP’s relationship 

with interim 

outcomes.

Associations were 

estimated using 

either hierarchical 

linear models or 

counterfactual 

projection weights.
33 

pairing would have reduced the school sample size to just 34 (17 and 17). Rather than 

accept this loss in power and representativeness, it was decided to ignore the original 

matching in the analysis, thereby gaining an additional pair. 

Data from the seventh grade were used to examine the quality of the matching between 

the 18 GEAR UP and 18 comparison schools. As these data were examined, a pattern of 

imbalances emerged. On the one hand, there were a number of indications that students in 

the comparison schools had better attitudes about school, their parents were better 

educated and more connected to the schools, their families were more deeply rooted in 

their communities and the home environment had a richer intellectual tone.17 On the other 

hand, both students and parents in the GEAR UP schools reported a much richer set of 

college-related services and more knowledge about college.18 

 GEAR UP students reported more frequent meetings with adult 

mentors such as a Big Brother or Big Sister than comparison 

students reported (44 percent versus 37 percent). 

 More GEAR UP than comparison students reported having a oneon-one counseling or advising session about getting ready for 

college (31 percent versus 26 percent). 

 More GEAR UP than comparison students reported attending a 

class or meeting about getting ready for college (40 percent versus 

22 percent). 

 More GEAR UP than comparison students had at least heard of 

two-year and community colleges (62 percent versus 52 percent). 

 More GEAR UP than comparison parents reported attending 

meetings about college preparatory curricula (17 percent versus 9 

percent). 

 More GEAR UP than comparison parents reported finding out 

about child participation in the kinds of activities sponsored by 

GEAR UP through letters or written notices (39 percent versus 27 

percent). 

 More comparison than GEAR UP parents reported having no 

information about college entrance requirements (54 percent 

versus 46 percent). 

 More GEAR UP than comparison parents reported that their 

seventh-graders had visited a college campus (21 percent versus 8 

percent). 

 

17 See table E-6. 

18 See table E-4. 

A pattern of 

imbalance between 

GEAR UP and 

comparison students 

at baseline emerged.
 34 

 More GEAR UP than comparison parents reported attending 

meetings about the types of classes their children should be taking 

to get ready for college (13 percent versus 6 percent). 

 More GEAR UP than comparison parents reported receiving 

written materials of college preparatory curricula (21 percent 

versus 12 percent). 

We believe that these remarkable differences in postsecondary education awareness were 

caused by early GEAR UP activities. This is substantiated by four facts. First, the 

seventh-grade interviews did not take place until late fall or early winter of the school 

year, so there was ample time for the GEAR UP projects to have provided services that 

would have produced these differences in awareness resulting in the observed 

imbalances. Second, the theoretical model of GEAR UP indicated that the first effects of 

GEAR UP should be on postsecondary education awareness. Third, site visitors reported 

that the GEAR UP projects were providing services of the types that would be expected 

to produce these awareness imbalances. Fourth, if these awareness differences had no 

causal connection to GEAR UP services, then we should have seen a surrounding 

constellation of pro-postsecondary education attitudes and habits. We found nothing of 

the sort. As noted above, GEAR UP students had worse school work ethics. Most 

importantly, when we looked at current intentions for postsecondary education, GEAR 

UP students were significantly less likely to be definitely intent on attending college (53 

percent versus 59 percent). 

Given this substantiated belief about the causes of the observed imbalances, it was 

decided to control on some but not all seventh-grade variables. The analyses in this 

chapter were controlled on only those we believed to be uncontaminated by early GEAR 

UP activities. Controlling on the full set of seventh-grade variables would have resulted 

in finding fewer significant positive associations for GEAR UP with targeted outcomes. 

It is also likely that fewer such associations would have been found if none of the 

seventh-grade variables had been controlled. (See appendix E for more details about the 

removal of these baseline differences.) 

Adjustment Techniques. The adjusted differences were estimated by comparing GEAR 

UP and non-GEAR UP students using either a hierarchical linear modeling (HLM) 

approach or counterfactual projection (CFP) weights to handle several complicating 

factors described in Appendix E, Removal of Baseline Differences. The HLM approach 

was used for those outcomes that were approximately normally distributed, while the 

CFP weighting approach was used for outcomes that were not normally distributed. Both 

methods controlled for baseline differences between the GEAR UP and non-GEAR UP 

students on a common set of baseline variables that were initially out of balance between 

the two groups, as discussed in section 2.1. However, beyond controlling on this common 

set of variables, the HLM approach provided somewhat stronger control on baseline 

differences in three respects. First, if the baseline version of the variable being analyzed 

was judged not to be contaminated by early program activities, then the HLM approach 

controlled on it. Second, the HLM approach controlled on several school-level baseline 

summaries. Third, the HLM approach controlled some interactions among the variables. 

The notes following each table indicate whether CFP weights or HLM methods were 

used to prepare the analyses in the table. If HLM was used, the note also indicates 
35 

whether the baseline value of the outcome was included as a covariate in the model. The 

full HLM models are shown in appendix E. 

As evidence for the success of the CFP weighting approach, we note that the initial 

difference in seventh-grade report of strong intentions for college attendance was reduced 

by the adjustment and no longer presented a significant imbalance. Prior to adjustment, 

the gap between GEAR UP students and the comparison students was 6 percentage points 

(53 percent versus 59 percent). After the adjustment, the gap was 4 percentage points (54 

percent versus 58 percent) and no longer statistically significant. More strikingly, the 

College Orientation Index dropped from -0.086 standard deviations to just -0.004 

standard deviations. So using the CFP weights resulted in the two groups of students (and 

their parents) being very well-matched in terms of their initial orientation toward college. 

Although separate scores are presented in the tables in this chapter for the two groups of 

students, the difference and confidence interval columns are the important columns to 

examine. To assess whether an adjusted difference is statistically significant, a two-tailed 

statistical test was used. Whether the adjusted difference was estimated with CFP weights 

or by HLM, the test fully reflects the extra uncertainty caused by the small number of 

schools in the study. 

Significance Levels. The probability of rejecting the hypothesis of no effect was set at 

the 5-percent level. Specifically, confidence intervals that do not include zero are 

statistically significant at the 5-percent level and are identified by an asterisk (*) in the 

difference column. Adjusted differences that are statistically significant at the 10-percent 

level are identified with a dagger (†), although confidence intervals are not presented. 

Using a 10-percent level means that 10 times out of 100, the hypothesis of no effect may 

be rejected by chance alone. Whether the estimated adjusted difference is a positive or 

negative number shows the direction of the association; a positive number indicates a 

positive association with respect to the theoretical model of how GEAR UP should work, 

and a negative number indicates a negative association (again with respect to the 

theoretical model) for GEAR UP students when the measure is determined to be 

statistically significant. 

Subgroups. In addition to investigating the outcomes of GEAR UP for all students, 

several subgroups were identified as of interest. These groups were African-Americans, 

Hispanics, potential first-generation college students and those students scoring in the 

middle third on the College Orientation Index.19 African-Americans and Hispanics are of 

interest because they are underrepresented in postsecondary institutions. Similarly, 

potential first-generation college students—students who would be the first in their 

immediate families to attend college—have been shown to be less likely than their peers 

to complete the steps necessary to enroll in a four-year college (Education Resources 

Institute 1997). Those who do enroll are less likely to do so directly following high 

school. There was very little variation on income among the students studied because of 

 

19 The middle third of the College Orientation Index was chosen because it was hypothesized that the greatest 

difference between the GEAR UP and non-GEAR UP students would be found for this group. The College 

Orientation Index estimates a student’s likelihood of attending college. It is a scaled score that was created 

based on student responses to specific questions and responses to questions asked of their parents. 

Positive associations 

were identified for 

subgroups of 

students: 

• African-Americans 

• Hispanics 

• First-generation 

college students 

• Middle third on 

College 

Orientation Index 
 36 

the GEAR UP program’s emphasis on low-income students, so this group was not 

isolated for analytic purposes. 

3.1 Academic Preparation and Progress 

Research has shown that students who take a full load of college preparatory courses are 

more likely than other students to attend college (Tierney, Colyar, and Corwin 2003). The 

middle school years are critical to a student’s ability to take difficult courses in high 

school. The overall difficulty of a student’s course work (or academic rigor) has been 

shown in studies focusing on high school students to be strongly associated with 

postsecondary entry and the student’s postsecondary grade point average (GPA), the 

amount of remedial course work needed in college and their rates of persistence and 

attainment in college (Warburton, Burgarin, and Nunez 2001). Thus, in addition to 

course-taking behavior, students’ secondary school academic performance contributes 

heavily to their ability to succeed in postsecondary institutions, particularly four-year 

colleges and universities. 

In addition, students with positive attendance patterns are more engaged and therefore 

more likely to perform better in school (Schwarz and Lui 2000; Slem 1983; Steward, 

Steward, and Blair 2002,). Thus, the associations of GEAR UP affiliation with (1) 

course-taking behavior, (2) academic achievements and (3) attendance are discussed in 

the next three subsections. 

Course-taking Behavior 

Although each student’s entire eighth-grade transcript was coded and processed, this 

analysis focuses on the core academic subjects (mathematics, science, English and 

foreign language) that are considered to be the best indicators of a student’s preparation 

for high school and college. 

This section investigates the relationship of GEAR UP affiliation to students’ academic 

preparation for postsecondary education by first looking at course-taking behaviors in 

eighth-grade to see if GEAR UP students were enrolling in more challenging (rigorous) 

classes at higher rates than students not attending GEAR UP schools. More challenging is 

defined in terms of the percentage of students taking advanced or above-grade-level 

classes in each of the four core subjects. (The confidence intervals in this section are 

wider because course-taking behavior varied considerably across the schools. The high 

intraclass correlations compared with other outcome measures are attributable to the 

small number of schools in the study, the consistency of responses within schools and the 

sharp variation across schools.) 

Table 3-1a shows that GEAR UP affiliation had a positive association with rigorous 

science course-taking behavior. GEAR UP students, as a whole, Hispanic students, 

potential first-generation college students and those students scoring in the middle third 

on the College Orientation Index all enrolled in above-grade-level science classes at 

higher rates than the non-GEAR UP students. 

Research shows that 

preparation for 

college should begin 

in middle school.

Attendance patterns 

are important 

indicators for future 

academic success.

More GEAR UP 

students took 

advanced science 

courses.
37 

Table 3-1a. Association for GEAR UP with percentage of students taking more 

challenging core academic courses 

Measure and subgroup 

GEAR 

UP 

(%) 

NonGEAR 

UP 

(%) 

Difference

(%) 

95% 

Confidence 

interval 

(%) 

Percentage of students enrolled in 

algebra 

 

All 33.6 22.9 10.6 (-2.3,23.6) 

Middle 1/3 on College Orientation 

Index 30.9 21.0 9.8 (-5.7,25.3) 

African-American 18.5 9.6 9.0 (-5.9,23.8) 

Hispanic 49.0 39.8 9.2 (-16.2,34.5) 

First-generation student 32.3 21.9 10.4† (-2.0,22.8) 

 

Percentage of students enrolled at abovegrade level in science  

All 14.7 4.8 9.8* (2.2,17.5) 

Middle 1/3 on College Orientation 

Index 14.3 4.8 9.5* (1.7,17.3) 

African-American 9.4 2.0 7.4 (-1.7,16.4) 

Hispanic 24.6 7.9 16.7* (0.3,33.1) 

First-generation student 13.0 4.6 8.3* (1.2,15.4) 

 

Percentage of students enrolled at abovegrade level in English  

All 24.8 12.2 12.6 (-6.5,31.7) 

Middle 1/3 on College Orientation 

Index 18.9 10.5 8.4 (-3.8,20.6) 

African-American 15.6 4.2 11.4† (-0.8,23.6) 

Hispanic 32.2 25.3 6.9 (-11.2,25.1) 

First-generation student 25.3 11.9 13.4 (-8.6,35.4) 

 

Percentage of students enrolled at abovegrade level in foreign language  

All 2.7 3.0 -0.2 (-5.1,4.7) 

Middle 1/3 on College Orientation 

Index 1.9 2.7 -0.9 (-5.6,3.9) 

African-American 0.5 1.4 -1.0 (-3.7,1.8) 

Hispanic 9.1 3.4 5.7 (-4.0,15.3) 

First-generation student 1.3 3.1 -1.9 (-6.4,2.7) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

 Detail may not sum to totals because of rounding. 
 38 

There is modest evidence (measured at the 90 percent confidence level) that GEAR UP 

affiliation was also positively associated with enrollment in algebra for potential firstgeneration college students and for above-grade-level English for African-American 

students. Similar apparent increases in the likelihood of taking algebra and above-gradelevel English in the eighth grade were found for GEAR UP students overall and for other 

subgroups, but these differences could not be statistically confirmed, just failing to meet 

the 0.10 level needed for statistical significance. Taking algebra in the eighth-grade is 

important because research has shown that this is associated with completing advancedlevel mathematics classes in high school, which has been shown to have a direct bearing 

on whether a student continues his or her education after high school (Oakes 1990, U.S. 

Department of Education 2000). 

Table 3-1b shows the differences in enrollments by types of mathematics classes taken. 

In addition to the increased enrollments in algebra for potential first-generation college 

students, there is modest evidence that GEAR UP students were less likely to take prealgebra in the eighth grade than non-GEAR UP students. One plausible explanation is 

that some projects may have substituted algebra classes for pre-algebra classes and 

moved the less skilled students down to “nonacademic mathematics.”20

Table 3-1c shows that, in general, GEAR UP students were taking higher level science 

classes in eighth grade than non-GEAR UP students. Overall and for three of the four 

subgroups, GEAR UP students were enrolled in above-grade-level life or physical 

science classes at a higher rate than non-GEAR UP students. There was evidence of this 

association overall and for potential first-generation college students and students scoring 

in the middle third on the College Orientation Index. 

There was modest positive evidence that Hispanic GEAR UP students were enrolling in 

above-grade life or physical science classes at higher rates during the eighth grade than 

their non-GEAR UP counterparts. 

There was a statistically significant difference at the 0.05 level between GEAR UP and 

non-GEAR UP students for African-American students in above-grade-level English (see 

table 3-1d). Differences regarding English were also observed between GEAR UP and 

non-GEAR UP students overall and those who were potentially first-generation college 

students; however, these differences could not be statistically confirmed. (For the 

purposes of this analysis, English as a second language classes were classified in the “No 

English” category because they fall outside the normal course progression.) 

As shown in table 3-1e, there are some statistically significant differences in the 

enrollments in foreign language between GEAR UP and non-GEAR UP students for 

some subgroups of interest. These differences are primarily driven by the fact that few of 

the GEAR UP schools, as compared with non-GEAR UP schools, offered foreign 

language classes to their students. 

 

20 This term is used by NCES to describe general and basic skills mathematics classes. 

More GEAR UP 

students who could 

be the first in their 

families to attend 

college took algebra 

in eighth grade.

GEAR UP students 

were less likely to 

take pre-algebra.

African-American 

GEAR UP students 

were more likely to 

take advanced 

English.
39 

Table 3-1b. Association for GEAR UP with level of mathematics courses taken 

Measure and subgroup 

GEAR 

UP 

(%) 

NonGEAR 

UP 

(%) Difference 

95% 

Confidence 

interval 

Percentage of all students 

 Remedial or no mathematics 2.7 3.4 -0.7 (-3.9,2.5) 

 Nonacademic mathematicsa

 44.5 35.1 9.3 (-17.5,36.2) 

 Pre-algebra 19.3 38.5 -19.3* (-42.3,3.8) 

 Algebra 33.6 22.9 10.6 (-2.3,23.6) 

 

Percentage of students in middle 1/3 on 

College Orientation Index 

 

 Remedial or no mathematics 1.8 1.6 0.2 (-1.8,2.1) 

 Nonacademic mathematics 46.8 38.6 8.1 (-17.7,33.9) 

 Pre-algebra 20.6 38.7 -18.1 (-41.1,4.9) 

 Algebra 30.9 21.0 9.8 (-5.7,25.3) 

 

Percentage of African-American students 

 Remedial or no mathematics 1.8 6.2 -4.4 (-12.4,3.7) 

 Nonacademic mathematics 59.3 57.0 2.3 (-22.9,27.6) 

 Pre-algebra 20.3 27.2 -6.9 (-26.6,12.7) 

 Algebra 18.5 9.6 9.0 (-5.9,23.8) 

 

Percentage of Hispanic students 

 Remedial or no mathematics 5.3 3.1 2.2 (-1.6,6.0) 

 Nonacademic mathematics 36.7 32.9 3.8 (-22.3,29.8) 

 Pre-algebra 9.0 24.2 -15.1 (-38.5,8.2) 

 Algebra 49.0 39.8 9.2 (-16.2,34.5) 

 

Percentage of first-generation students 

 Remedial or no mathematics 2.3 2.9 -0.6 (-4.3,3.2) 

 Nonacademic mathematics 44.1 36.3 7.8 (-21.0,36.6) 

 Pre-algebra 21.3 39.0 -17.7 (-42.5,7.2) 

 Algebra 32.3 21.9 10.4† (-2.0,22.8) 

* Statistically significant differences at the 5-percent level. 

a This term is used by NCES to describe general and basic skills mathematics classes.

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

 Detail may not sum to totals because of rounding. 
 40 

Table 3-1c. Association for GEAR UP with level of science courses taken 

Measure and subgroup 

GEAR UP 

(%) 

NonGEAR UP 

(%) Difference 

95% 

Confidence 

interval 

Percentage of all students 

Remedial or no science 1.1 6.8 -5.6 (-15.6,4.3) 

On-grade or below-grade life 

or physical sciences 74.4 76.0 -1.7 (-30.3,27.0) 

Above-grade life or physical 

sciences 12.4 3.9 8.5* (1.4,15.7) 

Chemistry or physics 12.1 13.3 -1.2 (-25.6,23.2) 

Percentage of students in middle 

1/3 on College Orientation Index 

 

Remedial or no science 0.4 6.7 -6.3 (-17.1,4.6) 

On-grade or below-grade life 

or physical sciences 72.0 78.7 -6.7 (-35.1,21.8) 

Above-grade life or physical 

sciences 12.8 4.2 8.6* (0.7,16.4) 

Chemistry or physics 14.8 10.4 4.4 (-20.4,29.2) 

Percentage of African-American 

students 

 

Remedial or no science 1.0 12.8 -11.7 (-28.5,5.1) 

On-grade or below-grade life 

or physical sciences 56.0 80.2 -24.1 (-81.7,33.4) 

Above-grade life or physical 

sciences 6.4 1.0 5.4 (-1.8,12.6) 

Chemistry or physics 36.5 6.1 30.4 (-23.0,83.9) 

Percentage of Hispanic students 

Remedial or no science 1.7 6.9 -5.2 (-14.3,3.8) 

On-grade or below-grade life 

or physical sciences 65.1 84.4 -19.3 (-47.3,8.6) 

Above-grade life or physical 

sciences 21.9 6.6 15.3† (-1.3,31.9) 

Chemistry or physics 11.4 2.1 9.2 (-14.0,32.5) 

Percentage of first-generation 

students 

 

Remedial or no science 1.0 7.2 -6.2 (-17.8,5.5) 

On-grade or below-grade life 

or physical sciences 75.4 74.4 1.0 (-30.4,32.5) 

Above-grade life or physical 

sciences 10.5 3.7 6.8* (0.8,12.7) 

Chemistry or physics 13.0 14.6 -1.6 (-28.9,25.7) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

 Detail may not sum to totals because of rounding. 
41 

Table 3-1d. Association for GEAR UP with level of English courses taken 

Measure and subgroup 

GEAR UP 

(%) 

NonGEAR UP 

(%) Difference 

95% 

Confidence 

interval 

Percentage of all students 

 No English 3.0 4.5 -1.5 (-4.4,1.4) 

 Remedial English 1.1 3.9 -2.8 (-10.5,5.0) 

 Below-grade English 1.4 3.2 -1.9 (-6.1,2.4) 

 On-grade English 69.7 76.2 -6.5 (-28.3,15.3) 

 Above-grade English 24.8 12.2 12.6 (-6.5,31.7) 

 

Percentage of students in middle 

1/3 on College Orientation Index 

 

 No English 3.8 4.4 -0.6 (-4.0,2.8) 

 Remedial English 0.6 4.8 -4.2 (-14.1,5.7) 

 Below-grade English 1.9 2.3 -0.3 (-3.3,2.6) 

 On-grade English 74.8 78.0 -3.2 (-20.6,14.1) 

 Above-grade English 18.9 10.5 8.4 (-3.8,20.6) 

 

Percentage of African-American 

students 

 

 No English 2.1 3.8 -1.6 (-7.5,4.2) 

 Remedial English 0.7 14.3 -13.6 (-41.8,14.6) 

 Below-grade English 1.6 1.7 -0.1 (-4.7,4.6) 

 On-grade English 79.9 76.0 3.9 (-36.0,43.8) 

 Above-grade English 15.6 4.2 11.4* (-0.8,23.6) 

 

Percentage of Hispanic students 

 No English 7.5 7.4 0.2 (-4.0,4.3) 

 Remedial English 2.3 1.5 0.8 (-4.4,6.1) 

 Below-grade English 2.8 4.2 -1.4 (-5.1,2.3) 

 On-grade English 55.1 61.7 -6.5 (-24.6,11.5) 

 Above-grade English 32.2 25.3 6.9 (-11.2,25.1) 

 

Percentage of first-generation 

students 

 

 No English 1.9 3.2 -1.4 (-4.4,1.6) 

 Remedial English 0.9 4.2 -3.3 (-11.7,5.1) 

 Below-grade English 0.9 2.8 -1.9 (-6.6,2.7) 

 On-grade English 71.1 77.9 -6.8 (-31.8,18.2) 

 Above-grade English 25.3 11.9 13.4 (-8.6,35.4) 

* Statistically significant differences at the 5-percent level. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

 Detail may not sum to totals because of rounding. 
 42 

Table 3-1e. Association for GEAR UP with level of foreign language courses 

taken 

Measure and subgroup 

GEAR UP 

(%) 

NonGEAR UP 

(%) Difference 

95% 

Confidence 

interval 

Percentage of all students 

 No foreign language 84.5 66.6 17.9 (-4.4,40.1) 

 On-grade or below-grade foreign 

language 12.8 30.4 -17.6 (-39.3,4.0) 

 Above-grade foreign language 2.7 3.0 -0.2 (-5.1,4.7) 

 

Percentage of students in middle 1/3 on 

College Orientation Index 

 

 No foreign language 84.9 66.0 18.9† (-2.5,40.3) 

 On-grade or below-grade foreign 

language 13.2 31.3 -18.0† (-38.9,2.8) 

 Above-grade foreign language 1.9 2.7 -0.9 (-5.6,3.9) 

 

Percentage of African-American students 

 No foreign language 74.4 48.5 25.9 (-8.3,60.1) 

 On-grade or below-grade foreign 

language 25.1 50.1 -25.0 (-59.6,9.6) 

 Above-grade foreign language 0.5 1.4 -1.0 (-3.7,1.8) 

 

Percentage of Hispanic students 

 No foreign language 73.0 77.6 -4.6 (-23.0,13.8) 

 On-grade or below-grade foreign 

language 17.9 19.0 -1.1 (-12.2,10.0) 

 Above-grade foreign language 9.1 3.4 5.7 (-4.0,15.3) 

 

Percentage of first-generation students 

 No foreign language 87.5 63.2 24.3* (0.7,47.9) 

 On-grade or below-grade foreign 

language 11.2 33.7 -22.5† (-46.3,1.4) 

 Above-grade foreign language 1.3 3.1 -1.9 (-6.4,2.7) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

 Detail may not sum to totals because of rounding. 

To determine the academic difficulty (or rigor) of the student’s course work, the highest 

level class in each subject was first identified. The overall rigor of each student’s course 

load was determined by counting the number of classes the student took that were 

considered to be advanced or above-grade-level work. Thus, a student could score from 

“0” to “4” on the rigor scale. For example, if a student was taking an advanced English 

class and algebra, the student was counted as having two classes above-grade level and 

was placed at level two on the rigor scale. Four core subject areas were used in creating 

the academic rigor scale. 
43 

Table 3-1f shows the estimated association of GEAR UP affiliation with the level of 

difficulty of the core academic courses taken by students. There was a positive 

association of GEAR UP affiliation with the level of difficulty of the course load for 

African-American students. Thus, African-American GEAR UP students were taking 

more higher level classes than their non-GEAR UP counterparts. 

Table 3-1f. Association for GEAR UP with academic rigor of courses taken 

Measure and subgroup GEAR UP 

NonGEAR UP Difference 

Mean number of academically rigorous 

core courses taken 

 

All 1.1 1.0 0.1 

Middle 1/3 on College Orientation 

Index 1.0 0.9 0.1 

African-American 1.0 0.5 0.5* 

Hispanic 1.3 1.0 0.3 

First-generation 1.1 1.0 0.1 

* Statistically significant differences at the 5-percent level. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

Academic rigor is determined by the number of core academic classes taken that are considered to be abovegrade level for an average eighth-grade student. 

Detail may not sum to totals because of rounding. 

Academic Performance 

This section looks at how students were performing in the classes they were taking 

according to school records.21 If the GEAR UP program is having a positive effect on 

students in GEAR UP schools, then these students would have improved academic 

performance exhibited through better grades and higher grade point averages (GPAs). 

This section considers two measures of academic achievement: academic GPA and high 

performance in above-grade-level classes. Because of considerable variability in grading 

standards across schools, the confidence intervals for academic achievement are 

unusually wide. 

As Tables 3-1g and 3-1h show, both measures were unable to detect a statistically 

significant difference in performance between GEAR UP and non-GEAR UP students by 

the end of the eighth grade. Table 3-1g shows that there was no discernable difference 

between GEAR UP and non-GEAR UP students at the end of the eighth grade in the 

grades these students received in each of the four subject areas. 

 

21 Students and parents also assessed the student’s academic performance. These are, respectively, the 

Academic and Performance subindices in appendix C. They are referred to as subindices because both 

were averaged into the overall College Orientation Index. They are also discussed separately later in this 

chapter under the heading, “student attitudes and behaviors.” For this section of the report, we analyzed the 

school transcript data on performance. 

GEAR UP was 

positively associated 

with the number of 

high-level classes 

African-American 

students took.
 44 

Table 3-1g. Association for GEAR UP with level of academic performance 

Measure and subgroup GEAR UP 

Non-GEAR 

UP Difference 

95% 

Confidence 

interval 

Mean GPA for mathematics 

All 2.5 2.4 0.1 (-0.2,0.4) 

Middle 1/3 on College 

Orientation Index 2.5 2.3 0.1 (-0.2,0.4) 

African-American 2.3 2.2 0.1 (-0.2,0.5) 

Hispanic 2.5 2.2 0.4 (-0.3,1.0) 

First-generation 2.5 2.5 0.0 (-0.2,0.3) 

 

Mean GPA for science 

All 2.6 2.6 -0.1 (-0.4,0.2) 

Middle 1/3 on College 

Orientation Index 2.5 2.6 -0.1 (-0.4,0.2) 

African-American 2.2 2.3 -0.1 (-0.4,0.2) 

Hispanic 2.7 2.5 0.2 (-0.1,0.6) 

First-generation 2.6 2.7 -0.1 (-0.4,0.2) 

 

Mean GPA for English 

All 2.7 2.7 -0.1 (-0.3,0.2) 

Middle 1/3 on College 

Orientation Index 2.6 2.7 -0.0 (-0.3,0.3) 

African-American 2.3 2.4 -0.1 (-0.4,0.2) 

Hispanic 2.7 2.7 0.0 (-0.3,0.4) 

First-generation 2.7 2.7 -0.1 (-0.4,0.2) 

 

Mean GPA for foreign language 

All 2.5 2.7 -0.2 (-0.6,0.2) 

Middle 1/3 on College 

Orientation Index 2.4 2.8 -0.4 (-0.9,0.1) 

African-American 2.1 2.5 -0.4 (-1.2,0.4) 

Hispanic 2.7 2.9 -0.2 (-0.7,0.4) 

First-generation 2.4 2.7 -0.3 (-0.8,0.2) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

The number -0.0 indicates that the true value of this number is less than zero but more than -0.1. 

 Detail may not sum to totals because of rounding. 
45 

Table 3-1h. Association for GEAR UP with percentage of students with high levels of 

academic performance 

Measure and subgroup 

GEAR UP 

(%) 

Non-GEAR 

UP 

(%) Difference 

95% 

Confidence 

interval 

Percentage of all students with 

grade of B or better in above-grade 

level 

 

 Mathematics 21.4 11.6 9.8 (-0.3,19.8) 

 Science 10.5 3.7 6.8 (-0.8,14.4) 

 English 17.9 10.5 7.4 (-6.6,21.4) 

 Foreign language 0.9 2.4 -1.4 (-4.3, 1.4) 

Percentage of students in middle 

1/3 on College Orientation Index 

with grade of B or better in abovegrade level 

 

 Mathematics 15.7 8.2 7.6 (-1.4,16.6) 

 Science 9.8 3.7 6.1 (-2.6,14.8) 

 English 13.5 8.7 4.8 (-4.3,14.0) 

 Foreign language 0.6 2.4 -1.8 (-5.0,1.4) 

Percentage of African-American 

students with grade of B or better in 

above-grade level 

 

 Mathematics 8.0 5.5 2.5 (-5.5,10.5) 

 Science 4.6 2.0 2.5 (-2.4,7.5) 

 English 9.3 4.2 5.1 (-3.4,13.6) 

 Foreign languagea

 – – – – 

Percentage of Hispanic students 

with grade of B or better in abovegrade level 

 

 Mathematics 30.3 16.0 14.3 (-6.4,35.1) 

 Science 20.3 5.3 15.1 (-1.4,31.5) 

 English 24.3 20.7 3.5 (-14.5,21.6) 

 Foreign language 2.8 3.0 -0.2 (-2.6,2.3) 

Percentage of first-generation 

students with grade of B or better in 

above-grade level 

 

 Mathematics 20.9 11.9 9.0 (-0.7,18.6) 

 Science 9.0 3.7 5.3 (-1.7,12.3) 

 English 17.7 10.4 7.4 (-8.7,23.4) 

 Foreign language 0.3 2.5 -2.2 (-5.2,0.8) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

a

 Inadequate sample size to produce estimates. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

The number -0.0 indicates that the true value of this number is less than zero but more than -0.1. 

 Detail may not sum to totals because of rounding. 
 46 

A student’s academic performance is an indicator of his or her understanding of the 

subject matter. Colleges and other postsecondary institutions typically use students’ 

grades to determine their ability to handle more challenging course work. Table 3-1h 

looks at those students who received above-average grades (a B or better) in their abovegrade-level classes. Again, by eighth grade there was no discernable difference in 

academic performance between the two groups of students. (The GEAR UP students 

were taking a more rigorous curriculum, but their grades were not lower.) Alternative 

measures of academic achievement reported by students as well as their parents are 

discussed in section 3.2. Although confidence intervals are narrower on these selfreported measures, few significant differences were identified. 

Attendance 

A student’s attitude toward school is often apparent through his or her attendance patterns 

and adherence to school rules. A student’s presence at school and in the classroom is 

generally considered to be an indicator of whether the student takes school and academics 

seriously. Table 3-1i shows that by the end of the eighth grade, there was no significant 

association for GEAR UP with the rate of absences or class skipping. The suspension 

rates for failing to follow school policies were also uncorrelated with GEAR UP 

affiliation. (Absences and suspensions were reported by schools, while class-cutting was 

reported by students.) 

3.2 Expectations, Student Attitudes and Behaviors 

Student expectations about college are one of the important factors in a student’s decision 

about whether to attend college. Students in middle and high school often have high 

expectations about their future but lack the knowledge of how to get there (Venezia, 

Kirst, and Antonio 2003). In addition, students’ attitudes about and behaviors in school 

play a major role in their ability to continue their education after high school. As 

discussed in earlier chapters, GEAR UP provides a broad array of services to students, 

their parents and the schools these students attend. A core objective of the services 

provided by GEAR UP is to raise student expectations about postsecondary education. 

GEAR UP also seeks to improve student attitudes about school and behaviors relative to 

school. 

Given that parent activities are an important part of project services (as described in 

chapter 2), an important set of evaluation hypotheses concerns effects on parents. One 

area in which these effects were anticipated was parents’ expectations for their children’s 

postsecondary education. In addition to changes in students’ expectations, this section 

also looks at associations for GEAR UP affiliation with parents’ expectations for their 

children. 

All measurements in this section pertain to the end of eighth grade. 

There was no 

difference in 

academic 

performance between 

the best performing 

students in each 

group.

Attendance patterns 

and suspension rates 

were unaffected.
47 

Table 3-1i. Association for GEAR UP with student discipline 

Measure and subgroups GEAR UP 

NonGEAR UP Difference 

Median total days absent 

All 5.0 5.1 -0.2 

Middle 1/3 on College Orientation Index 5.1 5.4 -0.4 

African-American 6.7 5.1 1.6 

Hispanic 3.2 3.4 -0.2 

First-generation 5.1 5.6 -0.4 

 

Percentage of students cutting classes at least 

once in last month 

 

All 12.9% 11.9% 1.0 

Middle 1/3 on College Orientation Index 14.4% 11.4% 3.0 

African-American 15.4% 13.5% 1.9 

Hispanic 17.0% 12.7% 4.3 

First-generation 12.5% 11.5% 1.0 

 

Mean total suspensions 

All 1.5 1.2 0.3 

Middle 1/3 on College Orientation Index 1.4 1.1 0.2 

African-American 2.7 2.3 0.4 

Hispanic 1.3 1.0 0.3 

First-generation 1.5 1.1 0.4 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

The number -0.0 indicates that the true value of this number is less than zero but more than -0.1. 

 Detail may not sum to totals because of rounding. 

Students’ Expectations 

Students’ early expectations about their postsecondary future are strongly linked to their 

likelihood of attending college. Using restricted data from the National Education 

Longitudinal Study (NELS) covering six years beginning with eighth grade and subsetted 

to high-poverty public middle schools, the probability of entering a postsecondary 

education institution on a traditional schedule (i.e., the fall immediately following high 

school graduation) is 45 percent for those who stated in the spring of eighth grade “[I’m] 

very sure I’ll go,” when asked about the likelihood of continuing their education past 

high school. For those less sure (or sure of the opposite), the comparable percent was just 

22 percent. If GEAR UP could raise expectations in the eighth grade, that would be a 

hopeful sign for achieving ultimate program goals. 

In this evaluation of GEAR UP, a broad index of student expectations was studied. 

Additional analyses were run on two of the component variables thought to be most 

important. The index was constructed using four responses from the student survey 

related to the student’s own expectations about how much education he or she believes is 

necessary after high school as well as three questions concerning knowledge about 
 48 

postsecondary education options that were found to be highly correlated with intentions. 

The index consists of responses to questions about the following: 22

 How likely the student is to attend college, 

 How important the student believes it is to go to college, 

 How far in school the student thinks he or she will go, 

 How much education the student believes he or she needs for 

anticipated job at age 30, 

 Whether student has heard of four-year institutions, 

 How many people student has talked to about postsecondary 

education, and 

 Whether student believes a person with a college education earns 

more money. 

By the end of the eighth grade, GEAR UP had not affected students’ expectations about 

pursuing postsecondary education as measured by the index (see upper panel in table 

3-2a). GEAR UP and non-GEAR UP students showed no statistically significant 

difference in their expectations about how much education they felt they needed after 

high school for their anticipated career as measured by the index.23 This is true for all 

students as well as for the four subgroups. 

Next, particular attention was paid to the question about intentions of going to college. A 

binary split was studied that identifies those students who agreed with the statement, “I 

will definitely go to college.” Results are shown in the second panel of the table. Again, 

there was no discernable difference between GEAR UP and non-GEAR UP students. In 

both groups, a slim majority said they will “definitely” go to college. 

Concerned that this binary split may have masked some shifting among lesser degrees of 

certainty about intentions toward going to college, table 3-2b (upper panel) compares 

student responses on the full range of answers to the intentions question. No evidence 

was found for any shifting in the distribution. Digging further, the lower panel of table 

3-2b shows similar detail on the question about expected ultimate educational attainment. 

Here, there is evidence of a shift toward expected associate’s degrees but without a 

significant offsetting decline in some other category. 

 

22 For more information, see the “ExpectPSErev” section of appendix C. We also experimented with a 

version of the index using only responses to the first four questions. The Cronbach alpha for this index was 

0.68. The knowledge questions were added because of their high correlation with the other four questions. 

These knowledge questions are also part of the KnowPSE index that is analyzed in table 3-3a. 

23 This comparison is fully controlled for the seventh-grade scores for the students on the same index. 

Students’ 

expectations about 

attending college 

were not affected.
49 

Table 3-2a. Association for GEAR UP with students’ expectations about 

postsecondary education 

Measure and subgroups GEAR UP 

NonGEAR UP Difference 

95% 

Confidence 

interval 

Index of students’ expectations about 

postsecondary education 

 

All -0.2 -0.4 0.3 (-0.2,0.7) 

Middle 1/3 on College Orientation 

Index 0.0 -0.2 0.2 

(-0.3,0.8) 

African-American -0.5 -0.7 0.2 (-0.4,0.8) 

Hispanic -0.0 -0.3 0.3 (-0.6,1.2) 

First-generation -0.1 -0.2 0.1 (-0.3,0.6) 

Percentage of students who say they will 

“definitely” go to college 

 

All 50.3% 51.7% -1.4 (-5.1,2.4) 

Middle 1/3 on College Orientation 

Index 45.6% 49.3% -3.7 

(-10.9,3.5) 

African-American 50.7% 52.8% -2.1 (-9.2,5.1) 

Hispanic 47.1% 44.8% 2.3 (-10.8,15.3) 

First-generation 51.7% 54.4% -2.7 (-6.7,1.2) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates for the index in this table were prepared with hierarchical linear modeling (HLM) with control 

on baseline value of outcome. 

 Estimates for the percentages in this table were prepared with replicated counterfactual projection (CFP) 

weights. 

The number -0.0 indicates that the true value of this number is less than zero but more than -0.1. 

 Detail may not sum to totals because of rounding. 
 50 

Table 3-2b. Association for GEAR UP with students’ responses to selected 

questions about postsecondary education 

Question and responses 

GEAR UP 

(%) 

NonGEAR UP 

(%) Difference 

95% 

Confidence 

interval 

How likely are you to go to college? 

I will definitely go to college 50.3 51.7 -1.4 (-5.1,2.4) 

I will probably go to college 30.5 27.5 3.0 (-0.4,6.3) 

I may go to college 11.7 10.8 0.9 (-0.9,2.6) 

I will probably not go to college 2.9 3.9 -1.0 (-2.4,0.5) 

I will definitely not go to college 1.1 1.2 -0.1 (-1.1,0.9) 

I have not decided yet 3.5 4.9 -1.4 (-3.2,0.4) 

How far in school do you think you will get 

after high school? 

 

A certificate from a vocational, trade, 

or business school (less than twoyear program) 7.1 7.7 -0.6 (-2.9,1.7) 

A two-year degree from a community 

college; an associate’s (A.A.) 

degree 12.3 9.5 2.8* (0.2,5.4) 

A four- to five-year degree from a 

college or university or bachelor’s 

(BA) degree 29.9 27.8 2.1 (-1.8,6.0) 

A graduate or professional degree such 

as a master’s (M.A.), doctorate 

(Ph.D.), law (J.D.), or medical 

(M.D.) degree 27.0 27.5 -0.4 (-6.2,5.4) 

I’m not going to school after high 

school 1.9 1.4 0.5 (-0.5,1.5) 

Don’t know 21.8 26.2 -4.4 (-3.2,0.4) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates for this table were prepared with replicated counterfactual projection (CFP) weights. 

NOTES: Detail may not sum to totals because of rounding. 

Parent Expectations 

Parent expectations are considered an important aspect of a student’s success in school. 

Research has shown that parents who have high expectations for their children, in turn, 

have children who achieve at higher levels than other children (Hofferth 1988, Sukhdeep 
51 

and Reynolds 1996). The index measuring differences in parent expectations consists of 

responses to questions from the parent survey about the parents’:24

 Conversations with their child about future college attendance, 

 Expectations about the ultimate certificate or degree that their child 

might earn, 

 Expectations about whether their child is likely to attend college away 

from home, and 

 Expectations about their ability to afford tuition at a four-year state 

college or university for their child. 

Table 3-2c shows the association for GEAR UP affiliation with parent expectations.25

Overall, there was evidence that GEAR UP parents had higher expectations for their 

students at the end of eighth grade than non-GEAR UP parents. Significant results were 

observed at the 95-percent confidence level for parents of African-American students and 

the parents of students scoring in the middle third on the College Orientation Index. 

Table 3-2c. Association for GEAR UP with parents’ expectations for their 

children 

 Parental Expectations Index 

Population GEAR UP 

Non-GEAR 

UP Difference 

All 0.0 -0.3 0.3* 

Middle 1/3 on College Orientation Index 0.3 -0.1 0.4* 

African-American -0.1 -0.5 0.5* 

Hispanic 0.2 -0.2 0.4 

First-generation 0.1 -0.2 0.3 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates for the index in this table were prepared with hierarchical linear modeling (HLM). without 

control on baseline value of outcome. 

 Confidence intervals are not presented for mean scores because they have no inherent meaning. 

 Detail may not sum to totals because of rounding. 

 

24 This index has a Cronbach’s alpha of 0.58. For more information, see the “Pexpect” index section of 

appendix C. 

25 This analysis does not control for scores of parents when their children were in seventh grade. As shown in 

table E-5, this subindex was well balanced at baseline, but one of its components (parent-child 

conversations about future college attendance) was thought to possibly be contaminated by early program 

activities, and so the decision was made not to control on baseline scores. When the HLM runs are 

performed with baseline control on parent expectations, the association on the total population slips over 

into statistical insignificance. The same is true for students in the middle third of the College Orientation 

Index and for African-American students. 

GEAR UP increased 

parents’ expectations 

about college for 

their child.
 52 

Looking at two of the questions that make up the parental expectations index, table 3-2d 

shows significant differences were found between the two groups for discussions 

between parents and their children about college attendance and for parent expectations 

of the likelihood the child will attend college or other postsecondary school. There is 

evidence that more parents of GEAR UP students were talking to their children about 

attending college than parents of non-GEAR UP students. There was some modest 

evidence that GEAR UP parents were more likely to anticipate that their child will attend 

college. No significant difference between GEAR UP and non-GEAR UP parents’ 

responses were found for questions on whether parents consider a four-year college to be 

affordable or what they expect their child’s ultimate degree to be. 

Table 3-2d. Association for GEAR UP with selected facets of the Parental 

Expectations Index 

Activity or cognition 

GEAR UP 

(%) 

NonGEAR UP 

(%) Difference 

95% 

Confidence 

interval 

Percentage who 

Talked with child about college 91.8 88.7 3.1* (0.8,5.4) 

Anticipated college or other 

postsecondary school attendance♦

 80.8 78.6 2.2† (-0.4,4.8) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

♦

 Parents who thought that the youth would continue education after high school (either immediately or eventually) and 

had an opinion about whether the school would be local or distant. 

NOTES: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

 Detail may not sum to totals because of rounding. 

Student Attitudes and Behaviors 

To determine the relationship of GEAR UP affiliation with students’ attitudes and 

behaviors regarding school, six different measures were investigated. The first two 

measures looked at student seriousness about school from the student’s and parent’s 

perspectives. The other four measures looked at student participation in extra-curricular 

activities, time spent on homework, time spent not watching TV or playing video games 

and parental assessments of homework efforts. Table 3-2e shows the association for 

GEAR UP affiliation with each of these six scales. 

More GEAR UP 

parents talked to 

their children about 

attending college.
53 

Table 3-2e. Association for GEAR UP with students’ attitudes about and 

behaviors in school 

Measure and subgroup GEAR UP 

NonGEAR UP Difference 

Students’ self-assessment of academic 

seriousness 

 

All -0.3 -0.1 -0.2 

Middle 1/3 on College Orientation Index -0.3 -0.2 -0.1 

African-American -0.1 -0.1 -0.0 

Hispanic -0.5 -0.4 -0.1 

First-generation -0.3 -0.1 -0.2 

Parents’ report of students’ academic seriousness 

All -0.1 -0.2 0.1 

Middle 1/3 on College Orientation Index 0.0 -0.3 0.3† 

African-American -0.5 -0.5 0.0 

Hispanic 0.2 0.1 0.1 

First-generation -0.2 -0.2 0.1 

Participation in extracurricular activities 

All -0.4 -0.1 -0.3† 

Middle 1/3 on College Orientation Index -0.5 -0.2 -0.3 

African-American -0.7 -0.2 -0.5 

Hispanic -0.6 -0.2 -0.3 

First-generation -0.2 0.1 -0.3† 

Time spent on homework 

All -0.0 -0.0 0.0 

Middle 1/3 on College Orientation Index -0.0 -0.1 0.1 

African-American -0.1 -0.1 -0.0 

Hispanic -0.1 -0.1 0.1 

First-generation 0.0 0.0 0.0 

Time spent not watching TV or playing video 

games 

All -0.0 -0.0 -0.0 

Middle 1/3 on College Orientation Index -0.0 -0.0 -0.0 

African-American -0.3 -0.2 -0.1 

Hispanic 0.0 -0.1 0.1 

First-generation -0.1 -0.0 -0.0 

Parent report of student homework diligence 

All -0.1 -0.0 -0.0 

Middle 1/3 on College Orientation Index 0.1 0.1 0.0 

African-American -0.2 -0.2 0.0 

Hispanic 0.0 0.3 -0.3* 

First-generation -0.1 -0.0 -0.1 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates for the index in this table were prepared with hierarchical linear modeling (HLM) with control 

on baseline value of outcome. 

The number -0.0 indicates that the true value of this number is less than zero but more than -0.1. 

 Detail may not sum to totals because of rounding. 
 54 

For the first measure, an index of the student’s seriousness about school was constructed 

that comprised five questions from the student survey that focused on the following:26

 How hard the student thinks he or she works in school, 

 How important the student thinks it is to work hard, 

 How good a student the student thinks he or she is, 

 What kind of grades the student reports he or she receives, and 

 How often the student is absent or skips classes. 

Next, the parent’s perception of the student’s seriousness about school was examined as 

an index of items from the parent survey on the following:27

 Whether the parent feels the student understands his or her 

homework, 

 What type of grades the parent reports the student as receiving, and 

 How important the parent thinks the student sees schoolwork. 

The next four panels of table 3-2e show other aspects of middle school life that were 

identified as interesting while developing the theoretical model for GEAR UP and 

whichwere positively correlated with the College Orientation Index.28 The first of these 

consisted of questions from the student survey that asked how involved the student was in 

extracurricular activities and whether the parent attended school events. The next 

measure, based on questions from the student survey, focused on how much time the 

student spent on homework each week. The next measure was an index that comprised 

questions from the student survey, focusing on how much time a student spent watching 

television or playing video games. The last measure reflected how hard the student 

worked on homework from the parent’s perspective. 

 

26 This index has a Cronbach’s alpha of 0.57. For more information about it, see the “Academic” section of 

appendix C 

27 This index has a Cronbach’s alpha of 0.71. For more information about the “Performance” index see 

appendix C. 

28 For more information about these indices, see appendix C. The scale on extracurricular activities 

(“ECBusy”) has a Cronbach’s alpha of 0.70. The scale on homework hours (“HomeworkHours”) has a 

Cronbach’s alpha of 0.80. The index on TV watching and video-game playing (“NegJunkHours”) has a 

Cronbach’s alpha of 0.53. The scale on parental assessment of student diligence (“Sdiligent”) has a 

Cronbach’s alpha of 0.64. Although all of these scales were related to the College Orientation Index, the 

relationships were not deemed strong enough to warrant including them in the index itself. 
55 

Table 3-2e illustrates that, with few exceptions, by the end of eighth grade, GEAR UP 

had shown little effect on student attitudes and behaviors in school. One exception was 

parents’ perception of their children’s seriousness about school, in which a modest 

relationship at the 90-percent confidence level was observed for those students scoring in 

the middle third of the College Orientation Index. A modest association for GEAR UP 

affiliation was also observed with regard to participation in extracurricular activities, in 

which GEAR UP students overall and those students identified as potential firstgeneration college students participated in more extracurricular activities at the end of 

eighth grade than non-GEAR UP students. The third exception was in the area of how 

hard the parent felt his or her child works on homework. There appears to be a negative 

relationship with how hard the parents of Hispanic students participating in GEAR UP 

felt their children were working on homework compared with Hispanic parents in the 

non-GEAR UP schools. One possible explanation of this result is that GEAR UP may 

have raised Hispanic parents’ expectations for how hard they thought their children 

should have worked on homework, without a corresponding increase in the actual effort 

they saw their children putting into homework. 

3.3 Postsecondary Education Knowledge and Parental Involvement 

In addition to raising student and parent expectations about the future, a second objective 

of GEAR UP is to increase their knowledge of academic entrance requirements, actual 

cost of attendance and availability of financial assistance to attend college. This section 

looks separately at the outcomes for GEAR UP on student knowledge about 

postsecondary issues and parent knowledge of the same issues. It also looks at parents’ 

involvement in their children’s education. 

Student Knowledge of Postsecondary Education 

Knowledge about course requirements for postsecondary enrollment, the application 

process, types of postsecondary institutions, actual cost of attendance and availability of 

financial assistance are important pieces of information students need to know to 

successfully apply to college. Although the accuracy of students’ knowledge was not 

tested, factors to measure the students’ activities to acquire knowledge about the 

necessary steps to prepare for postsecondary education were examined. 

A single scale was created to try to summarize all these aspects of knowledge. It was 

constructed with eight questions from the eighth-grade student survey that focused on the 

following:29

 Whether the student had talked with a high school counselor about the 

classes required to graduate high school, 

 Whether the student had talked with a high school counselor about the 

classes required to enter college, 

 

29 This index has a Cronbach’s alpha of 0.59. For more information about it, see the “KnowPSE” section of 

appendix C. 

Student attitudes and 

behaviors were 

generally not 

affected.

Hispanic parents felt 

their children were 

not working hard 

enough in school.
 56 

 Whether the student had talked with an adult at home about the 

classes required to enter college, 

 Whether the student had heard of two-year or community colleges, 

 Whether the student had heard of four-year colleges or universities, 

 Whether the student had heard of vocational, trade or business 

schools, 

 The number of different types of people that the student had used to 

find about postsecondary education such as parents, siblings, 

guidance counselors, and so on, and 

 The strength of the student’s belief about the differential income that 

can be earned by finishing college. 

This scale was also divided into more narrow constructs. One was based on just the first 

three components of the index. It focuses on discussions about college and course 

planning.30 The second averaged together the next three. It deals with the student’s 

familiarity with different types of postsecondary institutions.31 Finally, the lone question 

about differential income was analyzed separately. (One item in the overall index was not 

analyzed in a separate smaller index or individually.) 

Table 3-3a shows evidence that GEAR UP affiliation was positively associated with 

students’ knowledge acquisition about postsecondary education by the end of eighth 

grade.32 GEAR UP students reported having more discussions about college with parents 

and other adults and about planning the courses they needed to take than did non-GEAR 

UP students. The difference between GEAR UP and non-GEAR UP students was present 

in all the subgroups. 

In addition, GEAR UP students were more familiar than non-GEAR UP students with 

different types of postsecondary institutions. This difference was evident overall and for 

first-generation students. No significant differences were detected, however, between the 

percentages of GEAR UP and non-GEAR UP students who thought college graduates 

earned higher salaries than other individuals. 

 

30 This index is called TalkCoursePlanning in appendix J and has a Cronbach’s alpha of 0.66. 

31 This index is called HeardOfSchools in appendix J and also has a Cronbach’s alpha of 0.66. 

32 None of the analyses in this table are baseline controlled. 

More GEAR UP 

students talked about 

and made plans for 

college.

More GEAR UP 

students knew about 

different types of 

postsecondary 

institutions.
57 

Table 3-3a. Association for GEAR UP with students’ knowledge about 

postsecondary education 

Measure and subgroup 

GEAR 

UP 

NonGEAR 

UP Difference 

95% 

Confidence 

interval 

Index of knowledge acquisition about 

postsecondary education 

 

All 0.2 -0.8 1.0* N/A 

Middle 1/3 on College Orientation 

Index 0.3 -0.7 0.9* 

N/A

African-American 0.3 -0.8 1.1* N/A

Hispanic -0.1 -0.8 0.8† N/A

First-generation 0.4 -0.5 0.9* N/A

 N/A

Index of discussions about college and 

course planning 

 N/A

All 0.2 -0.4 0.6* N/A

Middle 1/3 on College Orientation 

Index 0.2 -0.3 0.5* 

N/A

African-American 0.5 -0.3 0.8* N/A

Hispanic 0.2 -0.3 0.4* N/A

First-generation 0.2 -0.4 0.6* N/A

 N/A

Index of students familiar with different 

types of postsecondary institutions 

 N/A

All 0.1 -0.2 0.3* N/A

Middle 1/3 on College Orientation 

Index 0.1 -0.2 0.3 

N/A

African-American 0.1 -0.3 0.4 N/A

Hispanic -0.3 -0.6 0.3 N/A

First-generation 0.2 0.1 0.3* N/A

 

Percentage of students who think college 

graduates earn higher salaries than others 

 

All 59.3 59.2 0.0 (-7.1,7.2) 

Middle 1/3 on College Orientation 

Index 58.5 57.5 1.0 

(-5.7,7.7) 

African-American 51.9 53.9 -2.0 (-15.6,11.8) 

Hispanic 64.4 62.4 2.0 (-4.6,8.7) 

First-generation 58.4 59.2 -0.8 (-8.2,6.7) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

N/A – Not applicable because confidence intervals for indices have no inherent meaning.

NOTES: Estimates for the indices (first three panels) in this table were prepared with hierarchical linear modeling 

(HLM) without control on baseline value of outcome. Estimates for the percentages in this table (last 

panel) were prepared with replicated counterfactual projection (CFP) weights. 

 The number -0.0 indicates that the true value of this number is less than zero but more than -0.1. 

 Detail may not sum to totals because of rounding. 
 58 

Parent Knowledge and Involvement 

Parent knowledge about and involvement in school activities are considered important 

aspects of student success in school. Previous research has supported this hypothesis 

(Carey and Farris 1996, U.S. Department of Education 1994). The index built to test the 

association for GEAR UP affiliation with parent knowledge and involvement in school 

activities included questions on the following:33

 Frequency of parent-teacher conferences, 

 Attendance at various types of school events such as PTA meetings, 

 Receipt of written information about planning a college preparatory 

curriculum, 

 Attendance at meetings about planning a college preparatory 

curriculum, 

 Perceived adequacy of personal information about college entrance 

requirements, and 

 Attendance at parent workshops about financial assistance for college. 

Table 3-3b shows that the estimated association for GEAR UP affiliation with parent 

knowledge and involvement was significant and positive. This was true overall and for 

three of the four subgroups examined.34

The estimated associations for GEAR UP with each of the questions on the parent survey 

that were used to create the parent knowledge and involvement index are shown in 

tables 3-3c and 3-3d. 

All four of the questions about the process of parent information gathering showed a 

positive association with GEAR UP affiliation (see table 3-3c). While only about half of 

the GEAR UP parents received written materials on college preparatory curricula, this is 

12 percentage points more than for parents of similar non-GEAR UP students. Similarly, 

only about a third of GEAR UP parents attended meetings on this same topic, but this is 

nearly 15 percentage points more than for parents of non-GEAR UP students. Attendance 

at workshops on student financial aid was still uncommon among parents in both GEAR 

UP and non-GEAR UP middle schools, but again, a considerably higher percentage of 

GEAR UP parents reported this experience. The majority of parents in both types of 

schools claimed having at least some information about college entrance requirements, 

 

33 This index has a Cronbach’s alpha of 0.59. For more information on it, see the “ParInvolve” section of 

appendix C. 

34 Several of the variables in this index were judged to be contaminated by early GEAR UP effects in the 

months leading up to the baseline interviews This analysis did not control on baseline differences in the 

value of the index itself. Thus, the estimated effects include some baseline differences that are assumed to 

be attributable to pre-baseline effects of GEAR UP but could also be because of other factors. 

Parent knowledge 

and involvement were 

increased.

GEAR UP parents 

had more information 

about planning for 

college.
59 

Table 3-3b. Association for GEAR UP with Parent Knowledge and Involvement 

Index 

 Parent Knowledge and Involvement Index 

Population GEAR UP 

NonGEAR UP Difference 

All students 0.4 -0.8 1.1* 

Middle 1/3 on College Orientation 

Index 0.3 -0.8 1.1* 

African-American 0.0 -0.8 0.7† 

Hispanic 0.5 -1.3 1.7* 

First-generation 0.5 -0.6 1.1* 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates for the index in this table were prepared with hierarchical linear modeling (HLM) without 

control on baseline value of outcome. 

The number -0.0 indicates that the true value of this number is less than zero but more than -0.1. 

 Detail may not sum to totals because of rounding.

Table 3-3c. Association for GEAR UP with information on college planning 

components of Parent Knowledge and Involvement Index 

Information on college planning 

GEAR UP 

(%) 

Non-GEAR 

UP 

(%) Difference♣

95% 

Confidence 

interval 

Percentage who 

Received written materials on preparatory 

curricula 48.9 36.5 12.4* (6.1,18.7) 

Attended meetings on preparatory 

curricula 34.8 20.1 14.7* (7.2,22.3) 

Attended workshops on financial aid 16.2 9.0 7.3* (3.7,10.8) 

Received some or enough information on 

entrance requirements 72.1 62.3 10.2* (4.3,16.1) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTE: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 
 60 

Table 3-3d. Association for GEAR UP with parent attendance at parent-teacher 

conferences and school events 

Activity 

GEAR UP 

(%) 

NonGEAR UP 

(%) Difference 

95% 

Confidence 

interval 

Percentage of parents attended 

Back-to-school night 49.5 43.6 5.9* (0.4,11.4) 

PTA meetings 73.5 68.5 5.0* (0.5,9.5) 

School plays, sport events, etc. 17.2 17.1 0.1 (-3.4,3.7) 

Field trips, such as museum or zoo 33.1 39.0 -5.9 (-13.1,1.3) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTE: Estimates in this table were prepared with replicated counterfactual projection (CFP) weights. 

but the GEAR UP parents scored 10 points higher than their counterparts. Clearly, the 

evidence is strong that GEAR UP is succeeding in its goal of exposing more parents to 

information about college. 

Attendance at back-to-school nights and PTA meetings showed significant positive 

associations with GEAR UP affiliation (see table 3-3d). However, attendance at school 

plays or sports events or attendance on field trips showed no difference between GEAR 

UP and non-GEAR UP parents. 

Other factors such as the frequency of parent-teacher conferences were tested but were 

not found to be significant. Attendance at parent-teacher conferences (by reason for 

conference) as well as parent volunteerism, which were not included in the overall index, 

were not found to be significant. 

3.4 Orientation Toward College 

The national evaluation cannot measure actual college attendance because students in the 

study will not graduate from high school and go to college until 2006 at the earliest. The 

evaluation attempted to measure the likelihood of college attendance as of the end of 

eighth grade. To do this, the College Orientation Index was constructed a priori based on 

the theoretical model for GEAR UP presented in chapter 1, empirical covariance patterns 

at baseline and new basic research using the National Education Longitudinal Study 

(NELS) on early, eighth-grade, indicators of entry into postsecondary education. 

The College 

Orientation Index 

attempts to measure 

whether a student 

appears oriented 

toward going to 

college.

GEAR UP parents 

attended more backto-school nights and 

PTA meetings.
61 

The College Orientation Index is a single measure based on information from student and 

parent questionnaires.35 A student’s College Orientation Index score is an attempt to 

summarize all of the elements from those questionnaires that are considered predictive of 

going on to college. The index is intended to indicate the degree to which a student 

appears to be oriented toward attending college. 

Before discussing the findings regarding the College Orientation Index, this section 

briefly describes the construction and validation of the index. A more lengthy discussion 

can be found in the appendices, Appendix C, Index Construction, and Appendix D, Index 

Validation. 

Index Construction 

The eighth-grade College Orientation Index summarizes information from the student 

and parent surveys that were completed at the end of eighth grade. As discussed in detail 

in appendix C, the College Orientation Index is the compilation of six separate concepts 

(constructs) that are believed to show a student’s likelihood of attending college. 

The first concept measures the student’s view of his or her own current performance in 

school and comprises responses to questions on the following: 

 How hard the student thinks he or she works in school, 

 How good a student he or she thinks he or she is, 

 

35 The College Orientation index was constructed, validated and subjected to external review by the 

Technical Review Group for the evaluation prior to inspection of eighth-grade data. Using the index 

sharply reduced the expected rate of false positive findings resulting from the multiple comparison 

problems. Using a single index can result in a lack of sensitivity to program effects in a narrow portion of 

the range of effects expected. It is also difficult to translate effects of the index into utility estimates. Thus, 

a mixed approach was used in analyzing the major subindices of the index, a few individual variables that 

were judged to be of critical importance (such as self-assessed likelihood of attending college and the 

individual variables within subindices where significant effects were observed). The first two steps were 

undertaken to improve sensitivity to localized efforts. The last step was undertaken to contextualize the 

effects in a way that might be more easily understood. 

 Transcript and administrative information (attendance, disciplinary actions, course taking, actual grades 

and standardized test scores) were excluded from the index. Standardized test scores could not be used 

because there were no tests in common across the entire sample. The other data were not used because the 

authors wanted to define the index in such a way that it was possible to construct both pretest and posttest 

versions of the index. This procedure had two benefits. First, it made it possible to control on the baseline 

value of the index in the multi-level modeling. This reduced variances and probably reduced selection 

biases. Administrative data were first collected in late seventh grade, and transcript data were not collected 

until after the end of eighth grade. Thus, baseline information was not available from these sources. If these 

sources had been built into the index, it would not have been possible to control on the baseline value of 

the index in the analysis. In addition it was later determined that the transcript data were subject to very 

high intraclass correlation, which would have made the index far noisier and harder to interpret. 

 The College Orientation Index consists of items that met two criteria. First, the items had to measure areas 

of student or parent thoughts or behavior that the conceptual framework suggested could be influenced by 

GEAR UP and would improve the student’s chances of attending college. Next, the items had to be either 

useful in building a predictive model for college enrollment or highly correlated with other variables which 

did meet this criterion. 
 62 

 How important the student thinks it is to work hard in school, 

 What kind of grades the student says he or she gets in school, 

 How often the student reports being absent from school, and 

 How often the student reports skipping class. 

The next concept measures the student’s postsecondary aspirations. It includes responses 

to questions on the following: 

 How likely the student thinks it is that he or she will go to college, 

 How important the student thinks it is to go to college, 

 How far the student thinks he or she will go in his or her education, 

 What sort of education the student thinks is required for the job he or 

she wants to have at age 30, 

 Whether the student has heard of four-year colleges, 

 Number of people the student reports talking to about postsecondary 

education, and 

 Whether the student thinks people who attend college have higher 

salaries than those who do not. 

The third concept measures the student’s report of discussions with his or her parents. It 

contains responses to questions about school activities and events; new knowledge from 

class; grades; community, national and world events; and things that were bothering the 

student. 

The next concept in the College Orientation Index consists of a single question that 

measures how much time the student spent reading for pleasure. 

The last two concepts come from the parent surveys. One concept measures the parent’s 

view of the student’s performance and is made up of responses to questions on the 

student’s understanding of homework, grades received and the student’s view of the 

importance of hard work. The final concept measures the parent’s postsecondary 

aspirations for the child. It is based on the following: 

 Discussions with the child regarding college, 

 Ultimate degree expectations for the child, 

 Whether the parent envisioned the child attending a college away 

from home, and 
63 

 Parent’s perception of the affordability of college. 

Index Validation 

The College Orientation Index was validated using the National Education Longitudinal 

Study (NELS:88), a widely used longitudinal study of students, starting in their eighthgrade year. For this validation test, questionnaire items from the NELS:88 eighth-grade 

survey that matched the questions that made up GEAR UP’s College Orientation Index 

were identified. Out of the 22 questions that make up the College Orientation Index, 12 

similar questions were identified in NELS:88. These 12 NELS:88 questions were used to 

create a NELS:88 College Orientation Index. 

Next, the NELS:88 follow-up surveys were used to determine which students actually 

attended college after high school. Using multiple regression, the relationship between 

the NELS:88 College Orientation Index score and the student’s actual college attendance 

was measured. (See appendix D for a more complete explanation of the creation and use 

of the NELS:88 validation process.) 

Parent education and race characteristics were used as control measures. In an effort to 

replicate the target GEAR UP population, the analysis was limited to those NELS:88 

students with a low family income. 

The NELS:88 validation test showed that, for the students studied, as the NELS:88 

College Orientation Index rose, so did the likelihood of the student attending college. In 

addition, the NELS:88 College Orientation Index correctly predicted students’ college 

attendance 75 percent of the time. 

The NELS:88 College Orientation Index was based on only 12 of the 22 GEAR UP 

College Orientation Index items. Adding the remaining 10 items, if possible, to the 

NELS:88 College Orientation Index would have increased the predictive ability of the 

index because the GEAR UP College Orientation Index items were so closely related to 

others within the same cluster. Given this relationship and because the NELS:88 Index 

had such a high predictability based on only 12 of 22 items, the GEAR UP College 

Orientation Index is believed to be a good predictor of a student’s likelihood of attending 

college. 

Tables 3-4a and 3-4b show that the average values for the College Orientation Index 

varied widely by students’ perceptions of their academic standing, by their beliefs about 

the value of college, their current intention for college enrollment, their ultimate 

education goals and by their parents’ expectations for them. Students with positive scores 

on the index report mostly grades of As and Bs in their classes, are convinced that those 

who attend college make more money, aspire to college themselves, expect a bachelor’s 

degree or higher and have parents who expect them to earn a bachelor’s degree or higher. 

NELS was used to 

validate the College 

Orientation Index’s 

predictability.
 64 

Table 3-4a. Average values on selected student questions in GEAR UP College 

Orientation Index 

Score on 

College Orientation Index 

Question and responses Average Standard error 

Thinking about the last school year, how would you describe 

your grades? 

 

Mostly As 9.4 0.70 

As and Bs 4.0 0.48 

Mostly Bs -1.0 0.66 

Bs and Cs -3.6 0.45 

Mostly Cs -8.6 0.71 

Cs and Ds -10.2 0.71 

Mostly Ds or below -16.1 1.31 

 

In general, do you think a person who finishes college makes 

more money in a year than a person who does not finish college? 

 

Definitely 2.5 0.57 

Probably -2.3 0.42 

I doubt it -10.4 0.92 

Definitely not -12.1 1.72 

Don’t know -9.1 0.73 

 

How likely are you to go to college? 

I will definitely go to college 5.1 0.53 

Probably -2.5 0.43 

May -8.3 0.55 

Probably not -13.3 1.03 

Definitely not -19.2 1.91 

Don’t know -14.0 0.82 

 

How far in school do you think you will get after high school? 

A certificate from a vocational, trade or business school 

(less than a two-year program) 

-8.2 0.96 

A two-year degree from a community college or an 

Associate’s degree 

-5.5 0.59 

A four- to five-year degree from a college or university or a 

Bachelor’s degree 

1.6 0.37 

A graduate or professional degree such as an M.A., Ph.D., 

J.D. or M.D. 

7.8 0.60 

I’m not going to school after high school -18.7 1.38 

I don’t know -5.7 0.56 
65 

Table 3-4b. Average values on parent question in GEAR UP College Orientation 

Index 

Score on 

College Orientation Index 

Question and responses Average Standard error 

How far in school do you think [child] will get? 

Child will not continue past high school -11.5 0.49 

A certificate from a vocational, trade or business school -7.5 0.57 

Associate’s degree -2.7 0.60 

Bachelor’s degree 2.8 0.57 

Graduate or professional degree 5.1 0.66 

College Orientation Index Results 

As shown in table 3-4c, there was no detection of significant associations with GEAR UP 

affiliation and the likelihood of attending college as predicted by the College Orientation 

Index. This was true overall and for each of the four subgroups analyzed. Average scores 

for both GEAR UP and non-GEAR UP students were negative. Differences between the 

two groups were generally much smaller than those shown in table 3-4a. Confidence 

intervals were also generally narrow relative to gaps in table 3-4a. For example, the 

difference in the College Orientation Index between those definitely intending to enroll 

and those who think they will probably enroll is 2.6 points. In contrast, the half width of 

most of the confidence intervals in the top panel of table 3-4a is on the order of 1.5 

points. 

A significant relationship, however, was found on the parent subindex for those scoring 

in the middle third on the overall College Orientation Index. As discussed in section 3.2, 

this is most likely a result of increased discussions with the youth about college. 

3.5 Pulling It All Together 

Positive associations with GEAR UP affiliation were detected for several of the outcome 

measures even though the period of time over which middle school students and their 

parents in the national evaluation received GEAR UP services was less than 24 months. 

Table 3-5 provides a summary of GEAR UP’s relationships with the outcome measures 

identified in the evaluation’s conceptual framework, organized by the theorized 

progression for change. 

The best evidence for effect by the GEAR UP program was observed in the area of 

knowledge, with increases in parent knowledge about postsecondary education 

requirements and availability of financial aid showing the strongest associations with 

GEAR UP affiliation. There was evidence of increases in knowledge of the same issues 

for GEAR UP students. Because parents and students were not tested on the accuracy of 

their knowledge about college-related information, this measure could be considered 
 66 

Table 3-4c. Association for GEAR UP with the College Orientation Index 

Measure GEAR UP 

NonGEAR UP Difference 

95% 

Confidence 

interval 

College Orientation Index at end 

of eighth grade 

 

All -0.6 -0.6 -0.0 (-1.2,1.2) 

Middle 1/3 on College 

Orientation Index early in 

seventh-grade -0.2 -0.5 0.4 (-1.0,1.8) 

African-American -1.5 -1.6 0.1 (-1.3,1.4) 

Hispanic -0.2 -0.4 0.2 (-1.9,2.3) 

First-generation -0.5 -0.3 -0.2 (-1.4,0.9) 

 

Subindex of student-reported 

items 

 

All -0.6 -0.4 -0.1 (-1.0,0.8) 

Middle 1/3 on College 

Orientation Index early in 

seventh-grade -0.5 -0.5 -0.0 (-1.0,0.9) 

African-American -0.9 -0.9 -0.0 (-1.1,1.1) 

Hispanic -0.7 -0.5 -0.2 (-1.7,1.3) 

First-generation -0.4 -0.2 -0.2 (-1.1,0.6) 

 

Subindex of parent-reported 

items 

 

All -0.1 -0.3 0.2 (-0.3,0.7) 

Middle 1/3 on College 

Orientation Index early in 

seventh-grade 0.3 -0.3 0.6* (0.0,1.2) 

African-American -0.5 -0.8 0.3 (-0.4,0.9) 

Hispanic 0.5 -0.0 0.5 (-0.2,1.2) 

First-generation -0.1 -0.2 0.1 (-0.3,0.6) 

* Statistically significant differences at the 5-percent level. 

† Statistically significant differences at the 10-percent level. 

NOTES: Estimates for the index in this table were prepared with hierarchical linear modeling (HLM) with control 

on baseline value of outcome. 

 The number -0.0 indicates that the true value of this number is less than zero, but more than -0.1. 

 Detail may not sum to totals because of rounding. 
67 

Table 3-5. GEAR UP outcomes for all students and subgroups of interest 

Measure All 

Middle 1/3 

on College 

Orientation 

Index 

AfricanAmerican Hispanic First 

generation 

Knowledge 

Parent 

Student 

* 

* 

* 

* 

† 

* 

* 

† 

* 

* 

 

Behavior 

Parent involvement 

Science course-taking 

Academic achievement 

Academic rigor 

Attendance 

Academic seriousness 

Homework diligence 

* 

* 

Ø 

Ø 

Ø 

Ø 

Ø

* 

* 

Ø 

Ø 

Ø 

Ø 

Ø

† 

Ø 

Ø 

* 

Ø 

Ø 

Ø 

* 

* 

Ø 

Ø 

Ø 

Ø 

Ø

* 

* 

Ø 

Ø 

Ø 

Ø 

Ø

 

Expectations 

Parent 

Student 

* 

Ø 

* 

Ø 

* 

Ø 

Ø 

Ø

Ø 

Ø

 

College attendance N/A N/A N/A N/A N/A 

 

College success N/A N/A N/A N/A N/A 

* Evidence (95% or greater confidence). 

† Modest evidence (90 to 95% confidence). 

Ø Test for association has p-value larger than 0.10. 

more indicative of GEAR UP’s implementation process as opposed to the achievement of 

program goals. These process variables help build the case that any improvements in the 

likelihood of students’ attending college would be reasonably attributable to GEAR UP 

because GEAR UP distributed the information. Clearly, however, the receipt of 

information by itself does not demonstrate changes in behavior. 

The second stage in the process of attaining GEAR UP’s overarching goal is to change 

student and parent behaviors related to the student’s current education. Because of the 

close relationship between parent knowledge and parent involvement, as discussed 

previously, evidence of a positive outcome for GEAR UP is also detected in the area of 

parent involvement in his or her child’s education. Among students, the evidence for 

effects on behavior is weaker. There was a positive association of GEAR UP status with 

above-grade-level science course-taking, and there was an association among AfricanAmerican students with the number of academically rigorous courses being taken. 

Beyond that, there was very little evidence of any effects on seriousness about school, 

study habits or any other student behavioral variables. 
 68 

The third stage is to change long-term expectations and intentions. The analysis indicates 

that there was evidence that parents’ expectations for their children increased although 

there was no change in the measure of the students’ expectations about attending college. 

The College Orientation Index summarizes into a single number for each child: selfassessed seriousness about school, parent-assessed seriousness about school, self-reported 

expectations and intentions, parent-reported expectations and aspirations and the 

intellectual richness of the home atmosphere in terms of parent-child discussions and 

reading for pleasure. The resulting analysis of the College Orientation Index shows no 

difference at that time in the prospective likelihood of college attendance between the 

two groups. 

In summary, the national evaluation observed that GEAR UP succeeded in exposing 

more parents to information about college than would have happened in the program’s 

absence. This accomplishment does appear to have led to increased parent expectations 

for some groups, particularly in the area of increased parent-child discussions about the 

possibility of college attendance. As with parents, the program has also been successful 

in exposing students to information about college. It remains to be seen whether these 

changes will translate into stronger intentions and striving on the part of students. The 

evidence thus far is negative, but it may have been too early to make that measurement 

because the students had been affiliated with GEAR UP for less than two years. 
69 

4. GEAR UP Middle Schools 

In addition to having a direct effect on students and their parents, GEAR UP aims to 

effect change in the partner schools these students attend. As depicted in the conceptual 

framework (see figure 1-1), the intended outcomes for schools include a more 

challenging curriculum and higher teacher and staff expectations for students. Through 

GEAR UP-sponsored professional development opportunities, GEAR UP expects to 

increase teachers’ knowledge of how best to prepare low-income, disadvantaged students 

for postsecondary education. In addition, by raising teachers’ expectations of students, 

GEAR UP aims to effect a positive change in the school environment that will continue 

even after the GEAR UP project has moved out of the school. 

To understand the changes that may be taking place in middle schools as a result of 

GEAR UP, this chapter uses data from focus groups and class catalogs to address the 

following questions. 

 Are there differences in academic curricula offered at GEAR UP and 

non-GEAR UP schools? Is there evidence of change at GEAR UP 

schools resulting from GEAR UP? [Source: school class catalogs and 

class listings.] 

 Does GEAR UP provide professional development opportunities for 

teachers? [Source: project staff interviews and teacher focus groups.] 

 Are changes in teachers’ attitudes evidenced by their educational 

expectations for students and perceptions of change in students 

attributable to GEAR UP? [Source: teacher focus groups.] 

4.1 Academic Curriculum 

The importance of a rigorous academic curriculum has been shown in several research 

studies to be a strong predictor of postsecondary attendance (Mathtech 1998; U.S. 

Department of Education 1997). The academic classes students take in middle school are 

an important aspect of the process of preparing students for high school and 

postsecondary education. This relationship is particularly well documented in 

mathematics, where taking advanced mathematics courses in high school increases a 

student’s likelihood of attending college (Warburton, Bugarin, and Nuñez 2001). For 

students to take the appropriate mathematics classes at the high school level, it is 

recommended that algebra be completed by the end of eighth grade. Thus, algebra is 

frequently referred to as a “gateway” class. Other classes that improve students’ 

GEAR UP also seeks 

to affect schools.
 70 

likelihood of continuing their education beyond high school are advanced English, 

advanced science and foreign language.36

Of first concern is whether any of the gateway classes in the four core academic subject 

areas (mathematics, science, English, foreign language) were even available to students. 

All 18 of the GEAR UP schools and 17 non-GEAR UP schools in the national evaluation 

provided information about their curricula during the study period. They provided 

information for seventh- and eighth-grade students through school class catalogs, master 

schedules and interviews with guidance counselors. Table 4-1 provides summary 

information about the gateway classes and the number of rigorous classes the schools in 

the national evaluation offered across the four subject areas. 

GEAR UP and non-GEAR UP schools had both similarities and differences. Algebra was 

the most prevalent gateway class available to both GEAR UP and non-GEAR UP 

students. All but four GEAR UP and four non-GEAR UP schools offered algebra as part 

of their middle school curriculum. The greatest difference between GEAR UP and nonGEAR UP schools was in honors or above-grade-level science class offerings. Twice as 

many GEAR UP schools offered above-grade-level science classes compared with nonGEAR UP schools. Conversely, non-GEAR UP schools were more likely to offer foreign 

language classes than the GEAR UP schools, with nearly two-thirds of the non-GEAR 

UP schools offering foreign language classes to students compared with one-half of the 

GEAR UP schools. 

In the sampled schools in the national evaluation, the number of gateway classes offered 

to middle school students ranged from none to four in the core academic subjects. Nine 

GEAR UP schools offered advanced classes in at least three subject areas, with six 

schools offering more rigorous classes in all four core subject areas. By comparison, six 

of the non-GEAR UP schools offered three or more rigorous classes with only one school 

offering rigorous classes in all four subject areas. 

Many of the schools offered the gateway classes. However, the student generally did not 

decide which classes he or she would take; that decision was usually made by the 

school’s guidance counselor. This was true for both GEAR UP and non-GEAR UP 

schools. Middle school students were generally assigned to their core academic classes 

by the guidance counselor without any input from students or parents. Guidance 

counselors reported that students either had no choices or they had limited selection 

opportunity. In all but a few cases, class selections were limited to electives such as band, 

chorus and art. Eighth-grade students in only three of the GEAR UP and two non-GEAR 

UP schools were permitted to choose classes other than their electives. Fewer schools 

offered students the opportunity to select classes at the seventh-grade level; two GEAR 

UP schools and one non-GEAR UP school allowed students input into class selection 

other than electives. 

 

36 Advanced classes may also be referred to as honors or above-grade-level classes by different schools. 

Overall, more GEAR 

UP schools offered 

advanced classes.

Typically, guidance 

counselors assigned 

students to classes.
71 

Table 4-1. Comparison of gateway curricula at GEAR UP and non-GEAR UP 

middle schools in the national evaluation sample 

Number of schools 

Curriculum GEAR UP Non-GEAR UP 

Number of schools providing information 18 17 

Number of schools offering 

Algebra 

Honors or above-grade-level English 

Honors or above-grade-level science 

Foreign language 

14 

7 

9 

9 

13 

6 

4 

11 

Number of rigorous classes offered 

None 

One 

Two 

Three 

Four 

2 

4 

3 

3 

6 

2 

2 

7 

5 

1 

Changes between SY 1998–99 and SY 1999–00 

Mathematics 

Science 

Arts and humanities 

Other 

6 

1 

1 

2 

2 

0 

-- 

-- 

-- 

-- 

Changes between SY 1999–2000 and SY 2000–01* 

Mathematics 

Science 

Arts and humanities 

Other 

6 

4 

1 

0 

2 

8 

4 

1 

3 

2 

* Some schools made changes in more than one area. 

NOTE: Classes identified as honors or above grade level were classified as rigorous. 

SOURCES: Course catalogs, master schedules and guidance counselor interviews; spring 2001 and 2002. 

Both the GEAR UP and non-GEAR UP schools provided information about curriculum 

changes between school years 1998–99 and 2000–01. Between school years 1998–99 and 

1999–2000, six GEAR UP schools indicated they made changes to their curriculum for 

academic courses (see table 4-1). Only one of these schools made a change in its 

mathematics curriculum, which resulted in all seventh-graders taking some form of prealgebra. Two schools made changes in their arts and humanities curriculum; two made 

changes to their science curriculum; and one raised its overall academic standards. None 

of the non-GEAR UP schools made any changes to their curriculum during this period. 

The following year, school year 2000–01, six GEAR UP schools and eight non-GEAR 

UP schools indicated they made changes to their academic curriculum. Four GEAR UP 

schools changed their mathematics curricula by either updating the curricula, making all 

eighth-grade mathematics classes some form of algebra, adding geometry to their course 

offerings or offering pre-algebra to seventh- and eighth-grade students with high 

mathematics test scores. Four non-GEAR UP schools also made changes to their 

mathematics curricula. Three non-GEAR UP schools either updated their mathematics 

curricula or began offering algebra and pre-algebra to advanced students. The remaining 

non-GEAR UP school dropped algebra from its curriculum because school administrators 

Few curriculum 

changes were made 

at GEAR UP schools 

between school years 

1998–99 and 

2000–01. 

A few schools added 

or increased 

enrollment in prealgebra and algebra. 
 72 

felt their students were not ready for the class. As with the prior year, other changes were 

primarily in the areas of arts and humanities and science. 

Most of the schools participating in the national evaluation had only one guidance 

counselor for each grade, and some schools had only one counselor for the entire middle 

school. The counselors indicated that this limited their ability to meet with students to 

discuss class selection. Guidance counselors reported that they used multiple sources to 

determine class assignments for each student. The most frequently cited sources by 

counselors in both GEAR UP and non-GEAR UP schools were results of standardized 

tests, recommendations from the students’ current teachers and current class grades 

within subject area (see table 4-2). If counselors only consulted one source for 

determining in which classes to enroll students, they tended to rely on teacher 

recommendations. This process varied little by subject and type of school. 

Table 4-2. Number of schools in the national evaluation sample using each 

source for determining class assignments 

Source GEAR UP Non-GEAR UP 

Number of schools providing information 18 17 

Standardized test scores 10 9 

Teacher recommendations 6 7 

Grades 9 6 

Education plan 1 3 

Administrator request 1 1 

SOURCE: Guidance counselor interviews, spring 2001 and 2002. 

4.2 Professional Development Opportunities 

To meet some of the core objectives of the GEAR UP program, most of the GEAR UP 

grantees provided teachers in GEAR UP schools with additional opportunities to 

undertake professional development beyond those already offered by the school districts. 

During site visits, GEAR UP project staff provided information about professional 

development opportunities for teachers. (This information was obtained only from GEAR 

UP schools.) GEAR UP-sponsored professional development was used to expose 

teachers to a variety of academic and college preparatory activities that they could then 

use to enhance their classroom teaching. Projects also used professional development as 

the means for discussing with teachers their attitudes toward their students and their 

perception of the potential for students in their schools to continue their education beyond 

high school. In addition, teachers became aware of, and learned about, the GEAR UP 

program and its objectives through professional development sponsored by the GEAR 

UP project. 

Consistent with other professional development provided by the school districts, GEAR 

UP-sponsored professional development was delivered by four different means: 

Guidance counselors 

frequently used 

standardized test 

scores or teacher 

recommendations to 

assign students to 

classes. 

GEAR UP provided 

additional 

professional 

development 

opportunities to 

teachers. 

Some professional 

development focused 

on teacher attitudes 

toward students’ 

potential for 

postsecondary 

education. 
73 

 Workshops and Seminars. More than one-half of the projects visited 

offered some kind of workshop or seminar focusing on numerous 

topics, such as vertical teaming, leadership, conflict resolution, school 

culture and specific content areas. 

 Training Sessions. Training sessions were held by more than onehalf of the projects on such topics as different types of software, 

teaching methods, interpreting test scores, learning style and career 

interest inventories and new programs the schools were 

implementing. 

 Conferences. Teachers at a few schools attended conferences through 

GEAR UP. Teachers attended state and national level conferences, 

including the National Science Teachers Conference and the GEAR 

UP national conference. 

 Other Activities. A few projects offered professional development 

opportunities in addition to workshops and seminars, trainings and 

conferences. These activities included a teacher college day, book 

discussion groups and discussion groups focusing on educational 

issues. 

About one-half of the projects provided services to teachers using only one of the four 

delivery modes above, while others used several modes to address their objectives. 

Professional development was most commonly provided in the form of workshops 

covering a variety of topics at various sessions. Some projects periodically offered a 

range of services, while other projects held professional development programs on a 

regular basis (once a week or month). 

In some instances, GEAR UP actively participated in delivering the professional 

development. For the most part, however, GEAR UP projects either arranged the 

professional development for the teachers through vendors or paid for teachers to attend 

professional development offered through other organizations not connected to GEAR 

UP. Project staff required that the professional development be consistent with the 

project’s objectives. 

In general, there appeared to be a connection between the amount of services offered to 

teachers and the inclusion of professional development in a project’s goals. For one 

project in particular, professional development was the one aspect around which the 

project seemed to center. The underlying reasons projects gave for including professional 

development in their goals focused on the belief that professional development was the 

primary means for the following: 

 Promoting systemic change in the school, 

 Sustaining the GEAR UP program once the grant ends, and 

 Designing and promoting rigorous academic course work. 

GEAR UP staff 

generally did not 

provide the 

professional 

development 

themselves. 

Professional 

development was 

linked to the projects’ 

goals. 
 74 

A substantial increase in professional development opportunities for teachers was 

observed at the 18 projects between the first and second years of the GEAR UP program. 

The availability of professional development had stabilized by the third year. The 

emphasis on professional development in relation to other activities, however, did change 

at a few sites. While about one-half of the projects offered the same services in the third 

year as in previous years, other projects provided the same types of services as before but 

addressed different topics. During school year 2001–02, one project arranged for teachers 

to enroll in graduate courses for credit at a local college; this opportunity had not been 

available during the previous years. Two projects that had not previously included 

professional development opportunities as a part of their grant added these services for 

teachers. Another project shifted its focus to preparing students for college through 

professional development in mathematics and language arts, and a fourth changed its 

approach from focusing on mathematics and language arts instruction to concentrating on 

a character education program. 

During focus group discussions, teachers talked about the various GEAR UP-sponsored 

professional development activities they participated in and gave their opinions about the 

value of the sessions. There was some variation in how useful or relevant teachers felt it 

was to GEAR UP’s purpose. Teachers who voiced positive feedback on professional 

development commented that 

 The sessions were informative and useful, 

 They were able to incorporate the material into their classroom 

instruction, and 

 The information helped them stay current in their field. 

Additional comments from teachers focused on the interaction with the GEAR UP 

projects. Teachers commented that they felt the GEAR UP coordinator seemed very 

concerned about what the teachers wanted. They were also very pleased with the ease by 

which they could obtain professional development training. 

The assessments on the value of the professional development, however, were not 

uniformly positive across sites. The most common complaints cited by teachers were as 

follows: 

 The purpose of the session was unclear, 

 The project’s expectations for teachers were unclear, 

 The quality of the material was poor, 

 The topics were unrelated to the project’s goals, and 

 The sessions offered did not address their needs. 

It is important to note that there were generally fewer complaints in the 2001–02 school 

year than in the previous year. 

Professional 

development 

opportunities 

increased over the 

course of the study. 

Teachers voiced 

different opinions on 

the value of the 

professional 

development they 

received. 
75 

4.3 Teacher Attitudes 

One of GEAR UP’s goals is to generate a more positive attitude among teachers that lowincome, disadvantaged students can succeed at postsecondary education. Teachers at the 

GEAR UP schools in the national evaluation were given the opportunity to talk about 

GEAR UP in their schools and their perceptions of its effect on students. Focus groups 

were held with seventh- and eighth-grade teachers in the GEAR UP schools in spring 

2001 and 2002, providing a way to garner any changes in teachers’ educational 

expectations for their students. (Focus groups were not held with teachers in non-GEAR 

UP schools.) Because many of the teachers were at the schools when GEAR UP was first 

implemented in fall 1999, they had experienced GEAR UP’s integration into their 

schools over the three years. Evidence of change in teacher attitudes was looked for in 

spring 2002 focus group discussions versus spring 2001. Teacher perceptions of GEAR 

UP and whether they attributed positive changes in their students to GEAR UP were 

other areas where potential change was examined. 

Higher Expectations for Students 

Teacher expectations of educational attainment for their students beyond high school 

varied across projects. While teachers in all focus groups did not extensively discuss their 

academic expectations for students, the discussions that did occur showed little change, in 

general, between the two years in teachers’ educational expectations for their students. 

There were, however, some notable exceptions. Between spring 2001 and spring 2002, 

teachers at a few schools reported that their own expectations of students in their schools 

had increased. This was supported at one school by teachers’ beliefs that the rate at which 

students pass algebra would increase as a result of the tutoring provided by the GEAR UP 

project. 

Such positive changes in expectations were not found at all the national evaluation 

schools. For example, teachers at one school felt that GEAR UP would not affect who 

goes to college; they felt that the students who would ultimately continue their education 

beyond high school would do so without GEAR UP. These teachers, who were strongly 

opposed to an incentive program established by GEAR UP to change student behaviors, 

felt that there was no real change in students’ attitudes toward postsecondary education as 

a result of GEAR UP. Teachers at a few schools felt that the majority of their students 

would not attend college and gave proportions of students they believed would. They felt 

that a variety of barriers would prevent the students at their schools from attending 

college, such as finances, low self-esteem and parents placing a low value on education. 

While some of the barriers cited are “targets” of GEAR UP, others mentioned by 

teachers, such as teen pregnancy and family situations, are not necessarily as central to 

GEAR UP. 

There were also some conflicts in expectations among teachers within two schools. 

Teachers at these schools had mixed views on GEAR UP’s association with students’ 

academic achievements and long-term educational expectations. For example, in one 

school, seventh-grade teachers reported seeing college as a possibility for students who 

they would not have previously thought would consider college. Eighth-grade teachers at 

Educational 

expectations for 

students beyond high 

school varied across 

projects. 

Teachers’ 

expectations 

increased at some 

schools. 
 76 

this school said they had not changed their expectations because they encourage all of 

their students to think about college. 

Perception of Change in Students 

An indicator that GEAR UP is achieving its goal of expanding teacher opinions about the 

academic futures of their students is evidence that teachers believe their students have 

changed, and, thus, their prospects are improved. Most of the teachers who participated in 

focus groups had positive perceptions of GEAR UP and attributed positive changes they 

observed in their students to the program. In all but two of the schools visited, teachers 

had very positive views of the GEAR UP program, particularly with respect to GEAR 

UP’s effect on short-term student achievements. 

Among the short-term changes in student behaviors teachers attributed to GEAR UP as a 

result of the tutoring provided by the project were the following: 

 Increased college awareness, 

 Increased numbers of students wanting to go to college, and 

 Improved grades. 

Through the activities provided by the GEAR UP projects, teachers believed students had 

benefited in several ways: 

 Knowledge. Teachers believed students had learned about a variety 

of topics related to higher education and had been introduced to 

careers that otherwise would have remained unknown to them. 

Teachers at many schools voiced the opinion that GEAR UP helped 

students see college as a reality, got students thinking more about 

college, and as a result, the teachers felt that students had become 

more confident that they could attend college. In addition, teachers 

felt GEAR UP had helped improve students’ outlooks about the 

future and increased their aspirations and career goals. 

 Awareness. Teachers felt that as a result of GEAR UP activities, 

students had become increasingly aware of options available to them. 

At one school, teachers felt that GEAR UP had helped Latino girls 

overcome the cultural belief that they have to stay at home. Teachers 

at another school specifically stated that they felt GEAR UP had 

affected gender roles in mathematics and science by increasing girls’ 

awareness of the importance of doing well in those subjects. GEAR 

UP was also credited with helping students have a better idea of the 

options available to them to pursue as they get older. 

 Behavior. Teachers perceived increases in student motivation, focus 

and self-esteem. Teachers saw students’ attitudes toward learning 

become more positive and felt that students were choosing more 

difficult classes because they knew they needed them for college, 

Most teachers viewed 

GEAR UP positively. 

Teachers attributed 

some positive 

behavior changes in 

students to GEAR 

UP. 
77 

whereas teachers believed that before GEAR UP, students were just 

taking the classes needed to graduate from high school. Teachers 

noted increases in the number of students enrolling in their honors 

programs, taking pre-advanced placement classes and joining the 

Junior National Honors Society. Students who had not actively 

participated in the classroom before GEAR UP were observed to be 

making a more concerted effort. Teachers believed that suspension 

rates also declined. 

 Academic Performance. Several teachers associated the presence of 

GEAR UP in their schools with increased student academic 

performance. Teachers were of the opinion that students were more 

concerned than they had been in the past about improving their grades 

because they wanted to go to college. Teachers were also of the 

opinion that GEAR UP contributed to students’ improving their 

grades and test scores. At several other schools, teachers believed 

GEAR UP had improved students’ academic achievements by 

increasing the number of students taking higher level classes. 

A positive change in the academic climate was noted by teachers in two schools, which 

they believed was brought about by the GEAR UP projects. Several teachers at one of the 

schools believed GEAR UP had made it “acceptable” to be smart, which was an attitude 

they said had not existed among students before GEAR UP. Teachers at the other school 

noted that GEAR UP created a new “reading culture.” GEAR UP was credited with 

helping cultivate what teachers termed a “college culture,” where teachers no longer 

heard students say they could not go to school because of money. 

Thus, by spring 2002, teachers at nearly all of the schools in the national evaluation felt 

that students had benefited from GEAR UP, although there was little evidence of change 

in teacher long-term expectations for students. Teachers attributed a variety of students’ 

short-term achievements to GEAR UP, such as increased college awareness and 

academic performance. In addition, at a few schools the teachers’ educational 

expectations for students appeared to increase. The long-term changes that teachers 

anticipated as a result of GEAR UP included increasing numbers of students passing 

algebra and more students attending college. 

As discussed in Chapter 3, by the end of eighth-grade, GEAR UP had not achieved all of 

its goals for students. The important factor here was that teachers’ perceptions of GEAR 

UP students had changed; teachers participating in focus groups believed that GEAR UP 

students were somehow different as a result of the GEAR UP program. 

GEAR UP created a 

positive academic 

climate. 

Teachers attributed 

students’ short-term 

achievements to 

GEAR UP. 

There was some 

change in teachers’ 

perceptions of 

students. 
 78 
79 

5. Partnership Projects 

The central focus of this report is to examine the outcomes for GEAR UP on students, 

their families and schools through the middle school years. It seems appropriate, 

however, to have an understanding of these GEAR UP programs and the context within 

which services were provided and outcomes were attempted. (For a more extensive 

description of the GEAR UP projects, see the evaluation’s earlier report titled National 

Evaluation of GEAR UP: A Summary of the First Two Years.) GEAR UP legislation 

prescribes a partnership structure for grantees and stipulates overarching objectives for 

the projects. The legislation suggests several areas in which projects might focus their 

goals but does not prescribe specific goals or services. In this chapter, the following 

questions are addressed: 

 What do GEAR UP partnerships look like? Have they used the 

partnership to their advantage? 

 How did projects select their goals, and do they plan to meet the 

program’s overall objectives? 

 How are GEAR UP projects organized and managed? 

 What role do partners play? 

 How does GEAR UP interact with other programs? 

 What plans do projects have to evaluate themselves? 

5.1 Composition of Partnerships 

One of the objectives of the GEAR UP program is to establish strong and lasting 

partnerships that would continue to provide support to schools beyond the grant period. 

The GEAR UP legislation stipulates the following: 

 Partnerships must, at a minimum, consist of a school district, an 

institution of higher education and two other partners that could be 

community-based organizations (CBOs), businesses, state agencies or 

other public or private organizations. 

 The members of the partnership must cover at least 50 percent of the 

operating costs of the program either through monetary or in-kind 

contributions. 
 80 

Most partnerships participating in the national evaluation comprised four or five partners, 

with one partner being the lead. The lead partner was the fiscal agent for the grant. 

Although most partnerships visited consisted of one or two school districts, one or two 

postsecondary institutions and two CBOs, a few projects consisted of as many as 10 or 11 

partners. Those projects with the greatest number of partners were more likely to have 

multiple higher education institutions involved in the partnership. 

There was little variation in the overall composition of the GEAR UP partnerships, at 

least among those sites visited. There were, however, differences in the numbers of each 

type of partner and which partner was the lead organization. For those projects in the 

national evaluation, the lead partner was: 

 a school district (eight projects), 

 a two-year postsecondary institution (six projects), or 

 a four-year postsecondary institution (six projects). 

CBOs associated with the 20 GEAR UP projects visited were a wide range of educational 

and noneducational organizations. 

Several projects included a local business as a partner in their grant. Businesses typically 

became involved with GEAR UP because the lead organization had a previous 

relationship with the business, or the business had previous involvement with the school 

being served or the school district. In at least one case, the business became involved 

with the GEAR UP project through a personal friendship with a school district official 

who was involved with GEAR UP. GEAR UP staff at a number of partnerships expressed 

interest in seeking more business representation in their projects. 

During the first two years, grantees experienced significant changes in the composition of 

their partnerships. Projects reported losing partners, including CBOs, due to a variety of 

factors. In several cases, the partner organization ceased to exist, or the business was 

beginning to fail and was unable to fulfill the services that it had agreed to provide. Other 

projects lost partners because of changes in leadership within the partner organizations 

themselves. Through interviews, it was also apparent that new staff within the partner 

organizations frequently did not have the same level of commitment to the GEAR UP 

project that the original member who signed the agreement did. 

By the third year of their grants, a few projects had only one of the original CBOs 

remaining. Projects typically replaced the CBOs that dropped out with several additional 

partners. For the most part, these new partners tended to be community organizations, 

parent-teacher organizations or educational programs, such as school-to-work and 

MESA.37 Other partners involved in GEAR UP projects included the following: 

 

37 MESA stands for the Mathematics, Engineering and Science Achievement Program. This is a “hands-on” 

program that has been developed by several university engineering departments. AVID stands for 

Advancement Via Individual Determination. This program is designed to help underachieving students 

with high academic potential prepare for entrance into a four-year college. 

Projects replaced 

partners as necessary 

during first two 

years. 
81 

 Local health departments, religious organizations and chambers of 

commerce, 

 League of United Latin American Citizens, 

 American Indian Resource Centers, and 

 The National Guard. 

When recruiting partners for their projects, the lead organizations reported that one of the 

most important considerations for selection was a previous working relationship. Many of 

the partners had a history of collaboration on other grants and initiatives such as Schoolto-Work or partners who had provided assistance in the past to the schools selected for 

participation in GEAR UP. The lead organizations also felt the partners brought critical 

resources and connections to the endeavor. One project noted that the GEAR UP 

partnership was built on a previously existing program, so it made sense to include that 

organization in the operation of the GEAR UP project. 

By the third year, the composition of the partnerships participating in the national 

evaluation had stabilized. About one-half of the projects reported no changes in partners 

during the third year. Of those that did experience changes, a few acquired new partners 

and in some cases, programs replaced lost ones. In most instances, these new partners 

were additional higher education institutions; in one case, the project added a local 

business as a partner. 

5.2 Projects’ Goals for Meeting Program Objectives 

While the legislation states the overall objectives of GEAR UP, each project defines its 

own goals as to how best to meet the program’s objectives given the specific needs of the 

student population it is serving. Most of the projects participating in the national 

evaluation focused on a few goals. Several projects, however, maintained a much broader 

focus and outlined as many as five or six specific goals. 

During meetings with site visitors, a couple of the projects discussed the underlying 

model or educational philosophy that guided them. One project described its method as a 

holistic approach to achieving the ultimate goal of increasing students’ awareness of and 

preparation for college as well as the number of students attending college. Another 

project’s philosophy was that every child should have an opportunity to learn and be 

provided an educational environment that strives for excellence. One project saw GEAR 

UP as a school reform opportunity that it hoped to expand to the entire school. 

The goals most frequently discussed by the partnerships fell into the following categories: 

academic achievement, college preparation, college awareness, professional development 

and curriculum reform. Other goals cited less frequently were parental involvement and 

career preparation. 

Partnership 

composition 

stabilized by the third 

year. 

Projects defined their 

own goals within 

broader objectives of 

the GEAR UP 

program. 
 82 

Virtually every project stated a goal related to academic achievement. Examples include 

those listed below: 

 Addressing academic deficiencies in specific subjects, 

 Having all GEAR UP participants take algebra by the eighth or ninth 

grade, 

 Providing tutoring or academic advisement and support, 

 Strengthening the academic rigor of the school, 

 Increasing the number of students graduating high school, 

 Helping each student read at grade level or higher, and 

 Improving students’ standardized test scores. 

Many projects had goals associated with college preparation and college awareness

such as those listed below: 

 Motivating more students to aspire to college, 

 Increasing students’ academic readiness for postsecondary education, 

 Increasing the number of opportunities for students to visit college 

campuses, 

 Increasing the number of students taking college entrance 

examinations, 

 Improving performance on college entrance examinations, and 

 Increasing the number of students applying to and attending a 

postsecondary institution. 

Professional development and curriculum reform were seen in some cases as the 

means to help meet the projects’ primary goals. The goals for professional development 

included developing more competent teaching staff with skills aligned with an 

academically rigorous curriculum. Goals for curriculum reform included instituting more 

college preparatory sequences and integrating curriculum change into the classrooms. 

A few projects had other goals not covered above. Two projects wanted to provide 

services for parents and to increase parental involvement. A few projects also 

mentioned as goals providing career-related activities and preparing students for 

careers. Other goals unique to specific projects are listed below: 

 Providing intervention services to prevent social barriers from 

affecting students, 
83 

 Improving technical access and skills for students, and 

 Focusing on community participation and awakening civic 

responsibility among residents about the need to improve education. 

For the most part, project goals remained the same during the three years projects 

participated in the national evaluation. Some projects adjusted the focus of their projects 

over the years, such as placing less emphasis on academic preparation and more on 

supporting students in college awareness. These modifications were deemed necessary 

for several reasons. Projects noted that in some cases an objective was met and, therefore, 

was no longer a problem. For example, one project had a goal to increase student 

attendance rates. Once the goal was met, it was no longer necessary to continue. 

Because GEAR UP schools served a predominantly low-income population, most 

projects did not discuss their goals in relation to a particular group of students. A few, 

however, did have goals to aid more disadvantaged populations and to focus more on 

students in traditionally underrepresented groups. 

5.3 Organization and Management of Partnerships 

Project organization followed two basic models, primarily driven by the size of the 

project. About one-half of the projects visited were small; they consisted of one middle 

school and one high school. In these smaller projects, the organizational structure was 

simple because there were often fewer staff than at the larger projects. The larger projects 

with multiple middle schools and high schools typically had several administrative layers. 

Projects were generally managed by a project director, or the equivalent, with oversight 

from other administrators at the lead organization (e.g., deans at the colleges, school 

district officials). A few projects established advisory boards or steering committees 

composed of GEAR UP staff and others from the major partners. The purpose of these 

boards or committees was to set programmatic goals, discuss the progress of the project, 

hire staff, plan for the sustainability of the project and to address other unanticipated 

issues as they arose. 

The project directors typically had similar responsibilities. They were involved in project 

planning, supervision of staff, interfacing with partners and school staff, hiring staff, 

budget and resource allocation and the daily operations of running the project. 

Frequently, at the smaller projects, the project director was in charge of the day-to-day 

operations of the project and the administration of the project at the schools. In fact, the 

project director was often housed at the middle school at least during the first two years. 

In a few cases, the project director moved on to the high school at the same time as the 

first cohort of students. 

The organizational structure at the small projects was fairly flat, with only a few staff 

reporting directly to the project director. Full-time and part-time staff and volunteers who 

reported to the project director included counselors, teachers, evaluators, tutors, 

coordinators, liaisons, case managers and mentors. These staff members were often 

Project goals 

remained fairly 

stable with 

adjustments made as 

necessary. 

About half of the 

projects served one 

middle school and 

one high school. 

A few projects 

established advisory 

boards or steering 

committees. 

Project directors had 

a wide range of 

responsibilities. 
 84 

located in the schools. In some instances, a few other staff reported to individuals under 

the project director. The project director typically was one of the only individuals, if not 

the sole individual, involved in the day-to-day oversight of the project. The other staff 

who reported to the project director primarily delivered services and had little 

administrative responsibility. 

Another characteristic of the smaller projects was that school staff had a greater role in 

actual project administration than school staff at larger projects. At a few small projects, 

the GEAR UP staff reported to school administrators. At one project, the project director 

was the principal. 

Larger projects, which included two or more middle school and high school pairs, were 

predominantly led by higher education institutions as opposed to school districts. They 

tended to be organized with more administrative layers and more staff than the smaller 

projects. At larger projects, the project director’s office was generally not located within 

one of the schools. These project directors were responsible for overall administration of 

the project and tended to be less hands-on than those at the smaller projects. GEAR UP 

coordinators, who were often located at the schools, reported to the project director and 

oversaw the operation of the GEAR UP project within the schools. 

The coordinators occasionally oversaw other GEAR UP staff responsible for delivering 

services. They coordinated and organized GEAR UP activities, assisted with planning 

and worked with school staff. At a few projects, GEAR UP staff were housed at some of 

the schools in the project. In at least one case, the project design called for the 

coordinator to be responsible for multiple schools. 

Nearly all of the projects had support staff, such as administrative assistants, secretaries 

and clerks, who assisted the project director and other GEAR UP administrators and staff. 

Some of the support staff worked on GEAR UP full time, while others only worked part 

time and spent the rest of their time on other similar projects. Their responsibilities, for 

the most part, did not include service delivery or coordination of activities, but primarily 

consisted of clerical tasks, such as data entry, financial and accounting duties, 

administrative paperwork and database management. 

5.4 Involvement of Partners 

In addition to the lead partner, partners at a few projects played a large role in GEAR UP 

through designing services and overseeing the projects. These partners assisted with 

content decisions, managed or hired GEAR UP staff or led different components of the 

project, such as curriculum development, professional development or evaluation. For the 

most part, the partners did not participate in the day-to-day administration of the project. 

A number of partners provided money, in-kind assistance, transportation, facilities or 

scholarships but were not involved in actual service delivery. Most of the higher 

education institutions provided access to their campuses and hosted visits. The business 

partners typically provided volunteers for activities and speakers. The more actively 

involved partners were key service providers, responsible for a variety of services, 

Larger projects were 

typically led by 

higher education 

institutions and had 

more administrative 

layers. 
85 

including professional development seminars, workshops, after-school programs, 

counseling and summer camps. 

School staff were involved in the administration of GEAR UP to varying degrees. At the 

majority of the projects, decisions about GEAR UP that affected the schools were often 

made by GEAR UP staff in conjunction with school staff. This occurred most often in the 

smaller projects, in which the project director and other GEAR UP staff had regular 

contact with school staff. In these projects, school staff tended to have a fair amount of 

input in how GEAR UP was implemented at their schools. The level of input also 

increased over the years. For example, at one project, the steering committee originally 

designed the services, but in later years the school staff came up with new ideas for 

services. Another project established site teams composed of teachers, school 

administrators and other faculty located at each middle school and high school pair. The 

teams were instrumental in running GEAR UP at their schools and in deciding how to 

spend resources. In fact, the project director of this project pulled back to allow the site 

teams to become more autonomous and involved in decision-making. The GEAR UP 

project staff saw this as a positive step toward the school’s taking ownership of the 

project. 

The role of school staff varied at other projects. At a number of projects, the teachers and 

administrators were also considered to be GEAR UP school-based staff and were 

responsible for delivering services or acting as liaisons between the schools and GEAR 

UP staff. At other schools, school staff were minimally involved in project decisions and 

provided only informal input or were not involved in GEAR UP at all. At another project, 

the school staff, including the teachers, had to approve the assignment of office space for 

GEAR UP staff at the schools. 

The staff at some projects communicated and met regularly. These projects held meetings 

quarterly or monthly to discuss GEAR UP activities and decisions. These meetings often 

included partner staff, school-based project staff and GEAR UP administrative staff. A 

few projects also held regular meetings between GEAR UP staff and school staff to 

discuss services at the schools. 

Several projects experienced staffing and organizational changes between the second and 

third years of their grants. A few projects hired new project directors or experienced 

turnover in other positions. At a few projects, the new project directors came from the 

ranks of the project. Some of the staffing changes occurred because projects moved into 

high schools during the third year of their grants. A few projects added staff to work with 

the GEAR UP students in the high schools. At least one project redefined the roles of the 

coordinators to better meet the needs of the project. 

With a few notable exceptions, changes in personnel did not appear to have a lasting 

impact on the projects as new staff were smoothly integrated into the project with 

minimal disruption to services. An example of an exception was one project that had a 

new project director, the third one in three years and a new principal at the middle school. 

These administrative changes created some communication problems between the high 

school administrators and GEAR UP staff, which caused delays in service delivery. This 

had a profound effect on the project because school staff and the former principal had 

GEAR UP staff 

frequently made 

decisions in 

conjunction with 

school staff. 

Organization and 

school staff roles 

varied across 

projects. 

New staff were 

integrated into 

projects generally 

without disruption. 
 86 

been very involved in the hiring and staffing of GEAR UP under the previous project 

director. 

Another management change that occurred at a few projects was greater control and 

decision-making responsibility at the school level as the project administration tried to 

provide schools with more ownership of the projects. One project’s organizational 

structure was altered somewhat the third year by adding an additional coordinator 

stationed in the school, who provided school staff with direct, easy access to the GEAR 

UP project. School staff used this opportunity to influence the project. This allowed the 

project director to be more involved in overall project oversight and management instead 

of working at the school level. 

5.5 Relationship With Other Projects and Programs 

Because GEAR UP was not the only program intended to improve academic success that 

was operating in the vast majority of these schools, projects may have had to coordinate 

with other programs operating within the same schools. The level of coordination 

between GEAR UP and these other programs, however, varied across projects. Many of 

the GEAR UP partnerships were located in states with state GEAR UP grants, which is 

an additional source for potential coordination. 

Coordination with Programs Other Than GEAR UP 

About one-half of the projects coordinated, at least to some degree, with other similar 

programs such as Upward Bound, Talent Search and School-to-Work programs offered at 

the schools. GEAR UP staff coordinated with other programs to make sure efforts to 

provide services to students were not duplicated and that services did not conflict. 

Frequently, GEAR UP staff shared office space with the staff for these other programs, 

which made coordination easier. A few GEAR UP projects delivered services 

collaboratively with other programs, or the programs provided services for GEAR UP, 

including summer programs, college visits, financial aid workshops and after-school 

activities. These arrangements were provided either through in-kind arrangements, or 

GEAR UP paid for the services. Several projects commented that GEAR UP was so 

integrated into the schools that there was little or no separation between GEAR UP 

services and the rest of the schools’ activities. 

There were also projects that either did not coordinate with other programs in the schools 

or were in schools that had no services with which GEAR UP could collaborate. 

Relationship with GEAR UP State Projects 

Thirteen of the 20 GEAR UP projects participating in the national evaluation were 

located in states that received GEAR UP state grants. These 13 projects were dispersed 

across six different states: three states each with one partnership, two states each with 

three partnerships and one state with four partnerships. The relationship between the 

partnerships and state grantees varied from state to state and from partnership to 

Staff coordinated 

with other programs 

in about half of the 

schools. 

Relationships 

between partnership 

and state projects 

varied. 
87 

partnership. Some partnerships did not interact at all with the state grantees, while other 

partnerships interacted frequently with the state grantees and received ongoing assistance. 

5.6 Evaluation Plans 

The GEAR UP legislation requires grantees to conduct a self-evaluation. All projects are 

also required to track individual students so projects can respond to their Annual 

Performance Reports (APRs), which the U.S. Department of Education uses to make 

funding decisions each year. 

All of the projects tracked GEAR UP students in some form or another as necessary to 

prepare their APRs. Most projects had access to the schools’ databases of student-level 

information, or projects developed their own databases of this information, including test 

scores, grades, grade point averages or GPAs, courses taken and attendance. In addition, 

the projects collected data on participation in GEAR UP services. Some projects 

conducted other data collection activities, such as surveys, pre- and posttests and focus 

groups. Projects used the data to monitor their progress, look for areas in need of 

improvement and assess their goals. 

About one-half of the 20 projects conducted large-scale evaluations. Most of these 

projects hired an external evaluator, often from a college, to collect the data and conduct 

the analyses. The evaluators created reports from the data to help reshape service 

delivery. In addition, projects used the evaluations to examine students’ progress and 

compare GEAR UP cohorts over time using various data, such as test scores, GPAs and 

survey results. 

The evaluations were used to assess program outcomes and to determine what needed to 

be improved. A few projects mentioned incorporating the recommendations developed 

through the evaluations. A number of projects encountered problems collecting data and 

conducting the evaluations. These challenges included those listed here: 

 Problems processing and analyzing surveys because of low response 

rates, 

 Difficulty obtaining access to student-level data from the schools, and 

 Inconsistent data entry. 

Several of the projects had not started conducting their own evaluation by spring 2002, 

but they did have plans to do so. The plans varied across these projects on how best to 

conduct their self-evaluation. A few projects planned to compare GEAR UP students 

with non-GEAR UP students using a matched longitudinal sample from the NELS or 

comparison school data. Other projects anticipated conducting impact studies of GEAR 

UP services using student satisfaction survey results and looking at grades and test scores 

in relation to the GEAR UP services they had received. 

In addition to 

tracking students, 

some projects 

collected surveys and 

held focus groups. 

Half of the projects 

conducted largescale evaluations. 

Those projects that 

had not started their 

evaluations had 

evaluation plans in 

place. 

89 

6. Looking Forward 

In previous chapters, the focus was on describing GEAR UP projects as they existed in 

the middle schools that participated in the national evaluation and the program’s 

outcomes for the students in the study schools. Drawing on information collected from 

interviews conducted with GEAR UP project staff during spring 2002, chapter 6 looks 

beyond the first phase of implementation at the middle schools and explores the next two 

phases for GEAR UP grantees: transition into high school and evidence of sustainability 

beyond the federal grant. Because the last round of site visits occurred during spring 

2002, those visits were the evaluation’s only opportunity to glimpse GEAR UP at the 

high school level. In addition, in spring 2002, grantees were nearing the end of the third 

year of their grant.38 Grantees expected at that point that they would be preparing for the 

termination of their federal support. 

The study used qualitative analytic methods to determine common themes across projects 

on issues of transitioning projects into the high schools and project efforts to 

institutionalize their programs so that they would sustain themselves beyond the federal 

grant period. 

6.1 Transition to High School 

The U.S. Department of Education awarded the first set of GEAR UP grants in fall 1999. 

The legislation authorizing the awards stipulated that these grants must begin providing 

services to students no later than the seventh grade. For this reason, the overwhelming 

majority of grantees chose to begin with a cohort of seventh-grade students. For projects 

serving students in 1999–2000, this initial cohort of students was enrolled in ninth grade 

(i.e., their first year of high school) in spring 2002. Thus, all of the GEAR UP projects 

participating in the national evaluation were operating in both the middle school(s) and 

high school(s) associated with their grants during 2001–02. This move into high school 

provided the opportunity to talk to project staff about their experiences implementing the 

GEAR UP project at the high school level even though the cohort of students being 

followed by the national evaluation was still in middle school. GEAR UP staff were also 

able to provide information about the services offered to high school students that year. 

Projects took three basic approaches in providing services to high school students. 

Projects provided the following: 

 

38 During FY 2004, the duration of the grant period for GEAR UP was reviewed, and the Bush administration 

determined that the six-year service requirement in the statute provided the authority for six years. 

Congress clarified that interpretation in the Conference Report accompanying the FY 2004 appropriation. 

By spring 2002, 

projects were 

operating in high 

schools as well as 

middle schools. 
 90 

 Similar or identical services at both the middle school(s) and high 

school(s), 

 Identical core services at both the middle and high schools and some 

different, specifically designed services at the high school, or 

 Very different services at the high school(s) from those provided at 

the middle school(s). 

The most common approach, adopted by one-half of the 20 projects, was to provide very 

similar or identical services at both the middle and the high schools. Usually, however, 

fewer services were provided, or those services that were provided at the high school 

were a slightly modified version of the middle school services. Less common were 

projects that carried some of the same services over from the middle school to the high 

school. These projects also introduced some different services that were specifically 

designed for high school students. A few of the projects that served multiple high schools 

offered different services at each high school. Only one project appeared to offer 

completely different services at the high school. 

Some services are more appropriate for high school students than for middle school 

students. For example, SAT preparation programs are appropriate for high school 

students but not middle school students. Other services, such as tutoring and mentoring, 

were appropriate for both middle school and high school students. These services 

required little or no modification when carried over from middle school to high school. 

Other services, such as field trips and career fairs, had the same basic components but 

needed to be modified to fit the specific needs of high school students. 

The service approach, in conjunction with other factors, affected the ease of 

implementation, which varied across projects. A few projects seemed to experience a 

relatively smooth transition, but most projects ran into at least some difficulties. While 

each partnership experienced a unique transition, grantees faced some common successes 

and challenges. Based on information gathered during site visits, projects were grouped 

into those that experienced relatively smooth transitions and those that experienced 

difficult transitions into their GEAR UP high schools. 

Relatively Smooth Transitions 

Projects that implemented GEAR UP at the high school level without noteworthy 

problems had several factors in common. These common factors may have contributed to 

their success. The three projects that experienced the smoothest transition and five others 

that had relatively smooth transitions expanded their GEAR UP project to include the 

high school in a way similar to that in the middle school. These projects tended to be ones 

in which the following factors existed: 

 Lead organization for the project was a higher education institution, 

 High school staff and the administration supported GEAR UP, 

 GEAR UP staff were located within the high school, 

There was some 

variation in services 

between middle 

schools and high 

schools, but about 

half the projects 

provided similar or 

identical services at 

both. 

Services provided at 

middle schools and 

high schools differed 

when appropriate to 

those being served. 

Half the projects 

experienced smooth 

transitions into the 

high schools. 
91 

 Very similar or identical services were implemented at the high 

school as had been provided at the middle school, 

 GEAR UP staff had previous working relationships with high school 

staff, 

 High school staff were involved in planning and delivering GEAR UP 

services, and 

 Additional staff were hired to serve at the high school. 

The size of the project may also have contributed to the smoothness of the transition. For 

many of these projects, GEAR UP served a very small district that consisted of one 

middle school and one high school. In addition, for at least three of the projects, ninthgraders were either located very close to the middle school, or the middle school and high 

school were located within the same building. The proximity of the schools to one 

another and the small size of the districts seemed to make the transition simpler than for 

those projects in larger districts and projects serving multiple schools that were not 

located in close proximity to one another. 

Another common trait among these projects was that they maintained the same 

administrative and organizational structures in spite of the transition to high school. 

Although nearly all of the projects visited added staff to support GEAR UP at the high 

school level, the projects experiencing the smoothest transition retained their original 

administrative and organizational reporting structure. 

The support of high school staff and administrators was key to the smoothness of the 

transition. For example, at one partnership, several high school teachers were actively 

involved in GEAR UP planning and implementation. They also took part in service 

delivery to ninth-graders. The high school principals and other school personnel with 

another partnership assisted GEAR UP staff with planning for the transition. In a third 

partnership, the high school principal fully supported GEAR UP and interacted with 

GEAR UP staff, although he was not directly involved with the administration of the 

GEAR UP project. GEAR UP project staff felt that the high school principal’s support 

helped to increase teacher awareness and support at the high school level. 

All of the projects experiencing smooth transitions into the high schools either provided 

the same level of services to these students as they had received the previous year as 

eighth-graders or, in some cases, provided the same types of services but at a reduced 

level. By retaining the same types of services at the high school level, it appears that 

these projects were better able to concentrate on other factors vital to a successful 

transition. 

Difficult Transitions 

Based on site visit interviews, it appeared that nearly one-half of the projects visited 

experienced considerable difficulty transitioning GEAR UP into the high school. While 

the nature and the number of barriers experienced by individual projects varied, most 

Smaller projects had 

smoother transitions. 

Maintaining project 

organization 

contributed to 

smoother transition. 

Engaging high school 

staff aided in 

transition. 
 92 

projects experienced one serious impediment. Projects encountered issues such as those 

listed here: 

 Lack of teacher “buy-in,” 

 Lack of coordination between middle school and high school staff, 

 Lack of adequate staff, and 

 Administrative barriers, such as scheduling restrictions for activities. 

Lack of support from school staff (teacher buy-in) hindered the transition into high 

school for several projects, although reasons varied for the lack of support. Most of the 

projects that experienced this problem cited issues with administrators or school staff as 

the primary barrier to successful implementation. See examples below: 

 School administrators simply did not feel the services provided by the 

GEAR UP project would help their students. 

 There was tension between the high school principal and project staff 

because the principal wanted more control over GEAR UP staff. 

 School staff felt the GEAR UP project added to the competing 

demands already placed on their time. 

Communication problems at various levels also contributed to the rocky transitions. 

These included lack of communication and support among GEAR UP staff and lack of 

coordination and communication between GEAR UP staff and high school staff. 

Staffing issues were another source of implementation difficulties at the high school. 

Implementing a GEAR UP project at the high school level often meant that at least one 

school within a project needed staffing. All of the projects were still providing services at 

the middle schools when transitioning services to the high schools. Some projects had 

staff split their time between the middle school and the high school instead of hiring 

additional staff for the high school. While this approach seemed to work well for one 

project, it created severe problems for another project when staff appeared to be spread 

too thin. Staff at a project that was designed to add a new cohort of students each year 

expressed concern about serving more grades in the high school while continuing to serve 

the middle grades because the project was not planning to hire additional staff to meet the 

increased volume. At two projects, GEAR UP staff turnover forced projects to hire new 

staff. This slowed the implementation of the project at the high school, which contributed 

to school staff concerns about the stability of the project and consequently their buy-in of 

the project. 

Other reasons for difficult transitions concerned scheduling GEAR UP services in the 

high schools. Some examples of problems encountered at a few schools are listed here: 

 School administrators resisted allowing students to be pulled out of 

certain classes for career and college awareness workshops. 

The extent of 

implementation was 

linked to the amount 

of administrative 

support. 

Insufficient staff 

contributed to 

difficult transitions. 
93 

 School administrators did not permit students to be taken out of 

classes for GEAR UP field trips because they felt the trips did not 

provide “any added educational value.” 

 GEAR UP counselors who were available to meet with students only 

after school experienced difficulty scheduling counseling sessions 

with the ninth-graders because the high school did not offer any afterschool programs. 

For two projects, GEAR UP’s implementation at the high school was very limited. For 

both projects, the transition presented a new bureaucracy that needed to be navigated. 

Because the school administrators had not been involved with GEAR UP previously, it 

was believed that the project was not considered their highest priority. To increase their 

contact with ninth-grade students, GEAR UP staff attempted to maintain contact with 

these students and provide services at locations away from the high schools. 

In summary, the transition to high school presented some level of challenge for many of 

the projects. 

6.2 Efforts at Sustainability 

GEAR UP grants are viewed by some as seed money. As a result, questions arise about 

what aspects of the projects will remain once federal funding ends. The legislation 

authorizing GEAR UP intended that the reforms begun with federal assistance would be 

continued by the partnerships. Those individuals involved with GEAR UP voiced their 

opinions about the likelihood of sustaining GEAR UP once federal support ends for the 

projects involved in the national evaluation. Evidence suggests that facets of GEAR UP 

will remain in some middle schools, but only time will tell. Individuals involved with the 

GEAR UP projects had some ideas about which components were likely to remain and 

why. 

Individuals at about nine projects were optimistic that at least some of the GEAR UP 

services would continue in the middle schools. At several of these projects, those 

involved in GEAR UP had different opinions on exactly which services would continue. 

School staff at one project, for example, were optimistic about sustaining GEAR UP, but 

their partners were skeptical. 

Three factors are considered here in making an early assessment of the sustainability of 

the GEAR UP projects participating in the national evaluation. These include the 

following: 

 Strength of partnerships, 

 Level of planning and preparation for the future, and 

 Level of institutionalization in schools. 

Half of the projects 

felt aspects of 

projects would 

continue. 
 94 

Strength of Partnerships 

The strength of the partnerships, as well as the level of commitment and communication 

among the partners, is likely to affect the partnerships’ ability to sustain GEAR UP 

without federal support. During site visits, site visitors observed that many of the 

partnerships were strong and fairly effective. At a number of projects, the partners were, 

for the most part, satisfied with the composition of the partnership and felt that they 

worked well. Interestingly, all of these partnerships predated the GEAR UP grant. A few 

had been initially formed under other grants, such as the School-to-Work Program, or as 

part of an early collaboration effort with similar objectives, such as connecting middle 

and high school students to postsecondary educational opportunities. Because these 

partnerships (or previously established connections) were formed before GEAR UP and 

had existed in some cases for years, there is a strong likelihood that the relationship 

among the partners will continue beyond the federal funding for GEAR UP. 

Common characteristics among those partnerships that appear most effective include 

involvement in the decision-making process and communication among partners. These 

seem to be related to the partnerships’ outcomes and strength. At several projects, 

partners other than the one or two key partners also played a role in decision-making and 

implementation, which strengthened their commitment to the project. At least one 

project’s decisions were made as a group, not unilaterally. Another project emphasized 

that collaboration and input should occur at all levels. These partners felt their partnership 

approach was essential for institutionalizing GEAR UP for future cohorts. In addition, 

partners in these strong partnerships tended to communicate well with one other. The 

partners at a number of these projects met regularly and maintained ongoing telephone 

and e-mail communication. 

Those partnerships that were not functioning as well were plagued by lack of 

coordination and communication among partners, little involvement from partners, high 

staff turnover within the partner organizations, frequent project administration changes 

and weak leadership from the lead agency. Decision-making was typically the sole 

responsibility of the lead agency. This occurred in some instances because the partners 

were minimally involved in, or committed to, GEAR UP. These issues clearly have 

implications for the sustainability of the projects. 

Level of Planning and Preparation for the Future 

The projects varied in terms of how much they had planned and prepared for the 

continuation of GEAR UP beyond the grant period. During spring 2002 site visits, GEAR 

UP staff were asked about their plans for continuing to operate their projects. For the 

most part, the more planning for the future that had taken place by that point, the more 

optimistic the individuals were regarding the sustainability of the project. Some projects 

had developed concrete plans for sustaining parts of GEAR UP, while a number of other 

projects were just beginning to formulate their plans. The most common strategy 

mentioned for sustaining GEAR UP was to find additional funding through other grants, 

new partners, existing partners or the schools. 

Partnerships were 

strengthened by 

involvement of 

partners in decisionmaking. 

Level of planning for 

the future varied. 
95 

At the time of the last visit, about one-third of the projects had not developed concrete 

plans for the future of GEAR UP. Individuals at these sites who were not optimistic about 

the sustainability of GEAR UP mentioned various reasons why they believed GEAR UP 

would not continue. They cited reasons such as schools not having taken ownership of 

GEAR UP, lack of staff to coordinate GEAR UP once funding ends, the disintegration of 

the partnerships and lack of available funding from other sources. 

One of the projects furthest along in the planning efforts was part of an informal alliance 

with other GEAR UP projects in the region. The alliance was formed to address the very 

issue of how to continue GEAR UP once funding ends. The alliance was planning to 

conduct a needs assessment to identify which GEAR UP services to preserve and how 

much money was needed. 

Level of Institutionalization in Schools 

Another tactic for maintaining GEAR UP cited by several projects was the 

institutionalization of GEAR UP in the schools and school districts. At these projects, 

staff felt GEAR UP had been integrated into the schools, or there were plans to more 

fully integrate GEAR UP to ensure its continuation. These projects noted that building a 

strong foundation of GEAR UP’s goals among school staff aided in the 

institutionalization. At a few schools, GEAR UP staff were allowing school staff to 

assume more responsibility in the administration of the project by having them plan and 

implement services. 

Another indication of institutionalization is apparent through the actions of school 

principals. The principals at schools in four different projects were committed to the 

goals of GEAR UP enough that they built GEAR UP into either the school’s budget or 

long-term plans. 

Although specific plans were not in place, one project believed that the spirit of GEAR 

UP would carry on through the ideologies that had been instilled in the schools even 

though GEAR UP’s services may not necessarily continue. 

A few projects had let sustainability guide their service delivery decisions. One project 

used funds to purchase only sustainable resources (i.e., resource materials that would 

transcend the GEAR UP grant). GEAR UP staff at another project decided to implement 

higher education centers in the schools as opposed to a mentoring component. The 

schools needed more counselors, and the centers met that need, even though GEAR UP 

staff knew mentoring positions would be eliminated once funding ended. 

Teachers’ buy-in or their commitment to GEAR UP objectives, as well as changes in 

teachers’ expectations because of GEAR UP, may increase a project’s chances of 

continuing because there is a greater likelihood that teachers will continue to include 

aspects of GEAR UP in their teaching. In addition, curriculum reforms initiated by 

GEAR UP and successfully implemented in the schools are likely to remain in the 

schools once funding ends. In particular, reforms initiated by GEAR UP in the GEAR UP 

schools that spread to other schools in the district are evidence of the sustainability of 

GEAR UP because they show the district’s commitment to the project. Staff at a number 

About one-third had 

established plans. 

Only a few projects 

were institutionalized 

into the middle 

schools. 
 96 

of projects believed that GEAR UP had been integrated into the curriculum, and the 

reforms started by GEAR UP would continue. At one project, GEAR UP is viewed as a 

vehicle for introducing curriculum reforms that are eventually implemented districtwide. 

Aspects of GEAR UP are likely to remain at some schools once federal funding ends. 

Those involved in GEAR UP at a number of schools are confident that aspects of GEAR 

UP will remain as a result of additional funding, the project’s decisions to offer 

sustainable services from the beginning and the institutionalization of GEAR UP in the 

schools. 
R-1 

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A-1 

Appendix A 

Methodology for the National Evaluation of GEAR UP 

The purpose of this five-year evaluation was to assess the outcomes for projects funded under the U.S. 

Department of Education’s (ED’s) Gaining Early Awareness and Readiness for Undergraduate Programs 

(GEAR UP) program. GEAR UP projects are aimed at increasing the enrollment rate of disadvantaged 

students in postsecondary education by supporting programs that provide early college awareness 

information, academic and individual support services and financial assistance. GEAR UP projects are 

authorized under the 1998 amendments to Title IV of the Higher Education Act. GEAR UP is intended to 

give more low-income students the skills, encouragement and preparation needed to pursue postsecondary 

education and to strengthen academic preparation programs and student services at participating schools. 

GEAR UP provides two major types of grants: (1) partnerships of school districts, colleges and other 

organizations and (2) state grants. This appendix focuses on the study methods used to evaluate the 

partnership grants. 

A.1 Study Design 

The core component of the National Evaluation of GEAR UP is the outcomes study that looks at the 

association between outcomes for participation in GEAR UP projects and key student and parent interim 

outcomes that are considered to be associated with an increased likelihood of attending postsecondary 

education. The conceptual framework, figure A-1, for the GEAR UP program guided the study design for 

the national evaluation. Within the context of the conceptual framework, the National Evaluation of 

GEAR UP had the dual purpose of describing the projects as they existed and evaluating their outcomes. 

Because GEAR UP legislation is nonprescriptive about how to meet the stated goals, services provided by 

partnerships vary considerably. Brief lists of the general types of services that may be offered are shown 

in Box 2. This includes services provided by state GEAR UP projects, which are discussed in a separate 

report. As shown in Box 3 (a-d), interim outcomes are intended at the family, student, school, and partner 

levels. Data were collected at each of these levels. 

Long-term outcomes for GEAR UP (Box 4) are increased rates of participation and success in 

postsecondary education. The period of data collection for this evaluation covered middle school seventh 

and eighth grades. Therefore, only interim outcomes were assessed. 

After selecting and recruiting 20 GEAR UP partnership projects to participate in the study, one middle 

school from each partnership was then selected to participate in the evaluation. To maximize the 

likelihood of a “clean” baseline, only projects providing services to a new cohort of seventh-grade 

students in fall 2000 were chosen. Within each school, a sample of seventh-grade students was chosen for 

the outcome study. Data were collected about these students in fall and winter 2000, which represented 

the baseline measures for examining the outcomes for the GEAR UP projects. To capture information on 

interim outcomes expected to be related to eventual postsecondary success, data were collected from and 

about these same students in spring 2002 when most were completing the eighth grade. 
 A-2 

Figure A-1. Conceptual framework of the impact of GEAR UP 

1. CONTEXT 2. SERVICES 3. INTERIM 4. LONG-TERM 

 OUTCOMES OUTCOMES 

Source: Westat analysis of HEA 1988 Amendments, 2007. 

1a. Local 

Characteristics 

 Students 

 Families 

 Schools 

 Communities 

1b. Policy Inputs 

 Local 

 State 

 Federal 

2. Projects 

 Academic assistance 

 Mentoring 

 Information on 

postsecondary education 

options 

 Information on student aid 

 Counseling 

 Programs for families 

 Curriculum development 

 Professional development 

 Financial aid incentives 

3a. Families 

 Expectations 

 Knowledge 

 Involvement 

3b. Students 

 Expectations 

 Knowledge 

 Challenging 

courses 

 Attendance, 

grades, on-time 

promotions 

3c. Schools 

 Challenging 

curricula 

 Teacher and staff 

expectations, 

knowledge and 

involvement 

3d. Partners 

 Collaboration 

 Communication 

 Comprehensive 

services 

4. Students 

 Increased 

postsecondary 

education 

enrollment 

 Increased 

postsecondary 

education 

success
A-3 

Through a subsequent study awarded in 2005, it will be possible to obtain additional information as 

students complete high school and move into their postsecondary years. This will enable ED to address 

the primary research questions on whether GEAR UP increases postsecondary school attendance and 

success. 

Because GEAR UP partnership projects are required by law to serve entire grade levels of students, it was 

not possible to use an experimental or random assignment design in this study, which would, of course, 

have been the preferred evaluation technique to draw strong inferences about program effectiveness. 

Accordingly, to assess the outcomes for GEAR UP, the study used matched comparison schools to 

evaluate GEAR UP’s outcomes. For each GEAR UP middle school in the sample, a middle school that 

was not receiving GEAR UP funds was selected for comparative purposes. The two schools were 

matched on the demographics of the students served and the communities in which they were located. 

Where possible, the non-GEAR UP schools were located in the same school district as the GEAR UP 

schools. As in the GEAR UP schools, a sample of seventh-grade students was selected in the non-GEAR 

UP schools. The full complement of student-level data collected on GEAR UP school students was also 

collected on the non-GEAR UP school students. Analyses primarily examine the change in outcome 

measures over time between the GEAR UP students and students from the non-GEAR UP group. 

The design also was intended to collect data about students who were seventh-graders in the GEAR UP 

schools the year before GEAR UP was implemented (in school year 1998–99). The purpose of selecting 

this sample was to compare academic information across two cohorts of students that completed seventh 

grade in the same school before and after the introduction of GEAR UP. In many cases, academic and 

administrative information was no longer available at the middle school level, and refusal rates were high 

among the high schools to which the information had been transferred. Thus, this analysis was not 

undertaken. 

A.2 Sample Design and Recruitment 

The sample design for the national evaluation used a three-tiered approach. The first tier was the selection 

of GEAR UP projects. The second tier was the simultaneous selection of GEAR UP and non-GEAR UP 

schools and the final tier was the student sample. The selection and recruitment process for each tier is 

discussed in detail below. 

 Selection and Recruitment of Partnerships 

Twenty GEAR UP partnership projects were selected for the in-depth study of program implementation 

and inclusion in the longitudinal outcomes study. The study sample was limited to partnerships located in 

the 50 states and those that began providing GEAR UP services to a new cohort of seventh-grade students 

during the 2000–01 school year. 

In August 1999, ED awarded 164 partnership grants through a competitive process. Of the 164 

partnership grants, 142 met the initial criteria for selection in the national evaluation. Of those excluded, 

six were located in U.S. territories, and 14 were not planning to serve a new cohort of seventh-graders 

during the 2000–01 school year. The remaining two projects were eliminated because of concerns of 

conflicts of interest because in each case a member of the GEAR UP Technical Working Group was 

involved in the administration of the GEAR UP project. 
 A-4 

Partnership Selection. In preparation for sample selection, the following taxonomy of service models 

was developed based on available literature on existing middle school interventions. The purpose of the 

taxonomy was to differentiate grantees to ensure that a representative group of projects be included in the 

evaluation. The following are the program models: 

 Curriculum development, 

 Schoolwide reform and systemic change, 

 Professional development, 

 College awareness, 

 Academic preparation, and 

 Multiservice. 

All partnership grant applications were reviewed and assigned a rank of 0 to 5 on each of the above 

program models, with 0 meaning not an element of the project and 5 representing a primary program 

focus of the project. Projects were then sorted into three service categories based on this ranking. 

 Direct Services (81 grants). These projects emphasized providing services directly to 

students and parents and included activities such as college awareness or academic 

preparation. 

 Indirect Services (42 grants). These projects did not focus on interacting directly 

with students and included activities such as curriculum development, schoolwide 

reform and systemic change and professional development. 

 Multiservices (19 grants). These projects placed equal emphasis on direct and 

indirect serves (i.e., indirect service models and direct service models were ranked 

equally). 

Within each service category, projects were sorted by the type of organization that had primary 

administrative and fiscal responsibility for the grant. The three types of organizations follow: 

 College or university (94 grants), 

 Elementary or secondary school district (45 grants), and 

 Other (three grants). 

Projects also were sorted based on whether they were located in a state that was awarded a state GEAR 

UP grant during the 1999 grant cycle. 

The sample selection of GEAR UP partnership projects for the national evaluation was undertaken in 

three stages. The first stage consisted of randomly selecting 40 projects across 12 strata cells—service 

category (3), fiscal agent (2) and state grant (2). The Other category for fiscal agent was eliminated before 
A-5 

stratification because there were so few grants of this type, and they appeared to be so different from 

other partnership projects. 

The second stage reduced the sample from 40 to 30 projects. Elimination was based on confirmation of 

the project’s program model ranking and whether the project was a new initiative or if project was 

initiated under some other funding source before GEAR UP. Projects indicating that explicit parental 

consent would be required to access student records and administer student surveys were eliminated from 

the sample. This decision was based on previous experience that obtaining a sufficiently high response 

rate from projects requiring explicit parental consent would prove impossible. Nine projects were 

determined to be ineligible. One additional project was randomly deselected. 

For the final stage in the selection process, more in-depth calls were conducted with the 30 projects. 

These calls focused on the project’s expected level of implementation by early 2000. An important 

requirement of the study design was that projects be able to describe and report the provision of planned 

services and be able and willing to participate fully in the longitudinal data collection. As a result of these 

telephone calls, nine projects were eliminated and one project was randomly deselected reducing the 

sample to 20 partnership projects. In addition to two projects that refused to participate in the study even 

after numerous attempts at obtaining cooperation, seven projects were eliminated for the following 

reasons: 

 Inadequate level of implementation anticipated (three projects), 

 Inability to gain access to student records (two projects), and 

 Inability to track students according to study design (two projects). 

Table A-1 shows the distribution of the final sample across the strata. 

Table A-1. Distribution of 20 sampled projects across strata 

In state with state GEAR UP grant? 

Yes No 

Service category 

College/ 

university 

School 

district 

College/ 

university 

School 

district Total 

Indirect 1 3 0 1 5 

Direct 4 1 2 1 8 

Multiple 1 0 4 2 7 

Total 6 4 6 4 20 

Partnership Recruitment. Project recruitment was ongoing at every stage of the sample selection 

process to ensure full cooperation in the study. Letters were mailed to project directors for the initial 

sample of 40 partnership projects. The letters described the national evaluation and informed the grantees 

that their projects were being considered for participation. The letters indicated that the project directors 

would be contacted by telephone to confirm the program model or models that appeared to be the primary 

focus of their grant based on a review of their grant application. 
 A-6 

Those projects that moved onto the second stage were contacted by telephone and asked additional 

screening questions. The 20 projects that remained in the final sample received a letter outlining the study 

and informed them that they would receive $500 each year to offset any expenses incurred as a result of 

their participation in the national evaluation. 

 Selection and Recruitment of Schools 

Once the GEAR UP projects agreed to participate in the national evaluation, the next phase was the 

selection and recruitment of schools. 

School Selection. Two middle schools were selected for each partnership: one GEAR UP school served 

by the partnership project (GEAR UP school) and one matched comparison school with no GEAR UP 

services (non-GEAR UP school). The steps to identify paired GEAR UP and non-GEAR UP schools are 

detailed below. Given the purpose of the program, similar is defined as students in the GEAR UP and 

non-GEAR UP schools having the same probability of attending and succeeding in postsecondary 

education in the absence of the GEAR UP program. 

 Step 1. The 1997–98 Common Core of Data (CCD) was used to determine (1) the 

percentage of students in the school receiving free or reduced-priced lunches (measure 

of poverty); (2) percentages of African-American, Asian and Hispanic students in the 

school; (3) the ratio of students to teachers; (4) the grade span; and (5) the location of 

the school relative to a populous area (i.e., urbanicity). 

 Step 2. Schools targeted by GEAR UP projects were identified. Schools not receiving 

GEAR UP services were defined as potential non-GEAR UP schools. 

 Step 3. For each measure (except location and grade span) and for each school, a 

normalized measure (a value that runs between 0 and 1) was calculated. This was 

done by first finding the minimum and maximum values for each of the measures, 

then by taking each school’s value of the measure, subtracting from that the minimum 

measure, and dividing this difference by the maximum minus the minimum value. For 

example, suppose that in the set of schools in the district, the ratio of students to 

teachers ranges from a minimum of 14 to a maximum of 28. If in a particular school 

the ratio of students to teachers is 21, then the normalized value for that school for this 

measure is [(21-14) divided by (28-14)] or 0.5. 

 Step 4. A difference measure for each variable for each potential pair of GEAR UP 

and non-GEAR UP schools was calculated. The difference measure is equal to the 

absolute value of the difference between a potential non-GEAR UP school’s value of 

the normalized measure and the value of the normalized measure for the GEAR UP 

school. For example, assume the normalized measure in step 3 is calculated to be 0.3 

for the GEAR UP school. Then the difference measure for the GEAR UP school is 

(|0.3-0.3|) or 0. For a potential non-GEAR UP school with a normalized measure of 

0.5, the difference measure is equal to (|0.5-0.3|) or 0.2. 

 Step 5. For location, only those schools with the same urbanicity codes were 

considered. 
A-7 

 Step 6. To determine the grade span of the school, schools with the same grade span 

were given a value of 0 and all others were given a value of 1. 

 Step 7. These difference measures were displayed for each variable for each GEAR 

UP school and each potential non-GEAR UP school. An example of such a display is 

shown in Table A-2. 

Table A-2. Difference measures for each variable 

Potential 

non-GEAR 

UP school 

Percent free 

or reducedpriced lunch

Percent 

AfricanAmerican

Percent 

Hispanic 

Percent 

Asian 

Student/

teacher 

ratio 

Grade 

span 

Weighted 

average 

1 .12 .50 .50 .90 .33 0 .39 

2 .35 .00 .10 .22 .21 0 .15 

3 .90 .22 .37 .76 .02 1 .55 

4 .27 .13 .25 .15 .55 1 .39 

 Step 8. The last column, weighted average, provides an aggregate distance score. The 

lower this number, the closer a non-GEAR UP school is to the GEAR UP school. 

Therefore, potential non-GEAR UP school #2 would be the first choice for the nonGEAR UP school. Each measure was weighted equally. 

 Step 9. The process was repeated for each GEAR UP school. School districts were 

contacted to ascertain high school feeder patterns among the paired GEAR UP and 

non-GEAR UP schools. The pair with the lowest weighted average when both schools 

did not feed into the same high school was selected, if possible. 

 Step 10. If a non-GEAR UP school was not available within the district, a non-GEAR 

UP school from outside the district was selected. To do this, Steps 3 through 9 were 

repeated for all schools within the state. In those sites where it was necessary to search 

outside the GEAR UP school district, geographic proximity of the schools to one 

another was taken into consideration when making the final selection. 

School Recruitment. Letters were first mailed to district superintendents for each of the sampled schools 

to request permission to contact the schools. At the same time, letters were mailed to the state education 

agencies (SEAs) to inform them of the study. District superintendents were contacted by telephone to 

discuss the study and gain their support. Applications to conduct research were initiated in those districts 

that required approval before school principals were contacted. Once approval was received at the district 

level, letters were mailed to school principals to inform them of their selection and request their 

participation. The letters outlined the requirements of the study. Principals were contacted by telephone to 

answer any questions about the study and to gain their cooperation. All schools were given monetary 

incentives the next year, and some schools were given additional funds over the course of the study to 

help offset costs incurred by participating in the study. 

 Selection and Recruitment of Student Sample 

The student sample was selected to correspond to the whole-grade, or cohort, approach required of 

partnerships. The student sample was drawn from students enrolled in seventh grade in GEAR UP and 
 A-8 

non-GEAR UP schools during the fall of 2000. Although 2000–01 was the second year of the grant, the 

sampled students did not receive any services during the prior school year. 

Unlike the previous stages, it was necessary to conduct recruitment efforts before sample selection. 

Recruitment of Students and Parents. At the beginning of the 2000–01 school year, each school mailed 

letters to all parents of seventh-graders. Schools were provided English and Spanish versions of all 

materials for parents. Schools operating under implied consent for student participation compiled a list of 

the students enrolled in seventh grade. Letters were mailed by the schools to all parents or guardians to 

explain the study and provide them with an opportunity to decline participation. These lists of students, 

excluding refusals, were used to select the participant sample in these schools. 

Schools that required explicit parent consent for students to participate mailed letters to all parents or 

guardians of seventh-grade students. These letters explained the study and requested that they sign the 

consent form and return it to the school. Schools with low initial response rates were asked to conduct a 

second mailing. Where response rates remained low, schools were asked to contact parents by telephone 

and prompt them to return the consent form agreeing or declining to participate. Lists of students with 

parent consent submitted by each school were used to select the student sample. 

Student Sample Selection. Many of the schools in the sampled partnerships had very large seventh-grade 

classes. Preliminary information indicated that seventh-grade classes in the middle schools served by 

GEAR UP varied from about 60 students to as large as 600 students. For cost-efficiency, students from 

the larger schools were sampled. Sampling was done by setting a maximum sample size for a school at 

140 students. For schools with a seventh-grade class of 140 or fewer students, all students were sampled. 

For schools with a seventh-grade class of more than 140 students, 140 students were randomly selected. 

This yielded a total sample size of 4,692 students. 

A.3 Description of Data Collection Procedures 

Two major data collection streams were conducted during the course of the study. One gathered 

descriptive data through a series of site visits during spring 2000, 2001 and 2002. The second stream was 

the outcomes study data, which included student surveys, parent interviews, student administrative 

records and report cards, and GEAR UP program participation data. (Copies of the data collection 

instruments are in Appendix K.) To maximize efficiency and reduce burden on the projects, the two sets 

of activities were coordinated. During the spring 2001 and spring 2002 visits, site visitors conducted 

interviews as well as collected some of the outcomes study data. 

 Site Visits 

In-depth site visits were conducted in spring 2000, 2001 and 2002 to collect descriptive information on 

GEAR UP project structure, operations and environment from the participating partnerships. The initial 

round of site visits conducted in spring 2000 introduced the partnerships to the study. Initial interviews 

with the GEAR UP project director were held as well as with other GEAR UP project staff. The spring 

2000 visits were designed to capture information about early implementation experiences and the 

program environment. Information was also obtained about grading systems, courses and credits at 

GEAR UP and non-GEAR UP schools. To secure school “buy in” to the national evaluation, site visitors 
A-9 

visited the sampled schools and, during spring 2000, reemphasized the important role that each school 

would play in helping the study assess the outcomes for GEAR UP. 

Interviews. Site visits in spring 2001 and spring 2002 included interviews, document and record reviews, 

focus groups, and observations. Interviews were conducted with the grant administrator and, as 

appropriate, other key program staff; with administrators and other involved staff at partnership schools, 

specifically the school sampled for the outcomes study at each site; with project administrators at the 

partnering institution(s) of higher education and school district(s); and with representatives of other 

community organizations that were part of the partnership. 

Focus Groups. Focus groups were held at each sampled GEAR UP school during the spring 2001 and 

spring 2002 site visits. The focus groups generally had 6 to 10 participants and lasted approximately one 

hour. Three separate focus group sessions were conducted: students, parents or guardians, and seventhand eighth-grade teachers. The purpose of the focus groups was to obtain different perspectives on student 

academic achievement and college plans, school climate and the GEAR UP program at the middle 

schools. For their participation, parents and teachers were given telephone calling cards worth $10. 

Observations. In addition to the interviews and focus groups, site visitors observed GEAR UP project 

activities. The purpose of the observations was to provide an opportunity to see how activities were 

operated, the setting in which the services were provided, the student-to-staff ratio, the type of activities 

taking place, resources available, attendance patterns, and general climate. During the site visits, 

documents were collected and reviewed that were helpful in evaluating the project’s implementation and 

interpreting student transcripts. These documents included grantee progress reports, program calendars, 

materials developed for distribution to students and parents, middle school course catalogs and course 

lists. Site visitors used all of this information to prepare site visit reports for each site. Site visit reports 

were reviewed and synthesized to compile information to write reports of the study’s finding for public 

distribution. 

 Student Survey 

Sampled students in both the GEAR UP and non-GEAR UP schools were asked to complete a 

questionnaire in fall or winter 2000 and then again in spring 2002. (Seventh- and eighth-grade student 

surveys appear in appendix K.) To facilitate the completion of these, each school identified a school 

coordinator who served as a liaison between the school and evaluation staff. Questionnaires were sent to 

the school coordinator who arranged for their confidential administration to sampled students. Parents 

were notified as required under federal law and local policies. 

The student survey, which was administered only in English, covered the following topics: 

 Characteristics of the student’s family and home life; 

 Participation in clubs, student government, organized athletics, social organizations, 

etc., both in and out of school; 

 Education and career expectations and aspirations; 

 Knowledge of postsecondary education costs and available financial aid; 
 A-10 

 Knowledge of college entrance requirements and application processes; 

 Participation in and assessment of programs designed to increase enrollment of 

disadvantaged and at-risk students in postsecondary education; and 

 Self-assessment of academic ability and ability to achieve expectations. 

The questionnaire also collected the names, telephone numbers and addresses of family members and 

neighbors of students to be used to locate students for future follow-ups. The tracking information was 

used in spring 2002 to locate sampled students who no longer attended the participating GEAR UP or 

non-GEAR UP schools. 

 Student Information Matrix 

Schools provided administrative and demographic information on individual students either in hard copy 

or electronically using the Student Information Matrix or SIM (see appendix I). Information not subject to 

change, such as gender and race, was requested only once and verified for each student. Information was 

abstracted from school records for the GEAR UP sampled students and non-GEAR UP students to 

provide a complete picture of the student’s academic experience. School attendance, disciplinary action, 

truancy information, mobility, and student demographics (e.g., gender, race and ethnicity), eligibility for 

free or reduced-priced lunch, English proficiency, participation in special education and/or gifted 

programs were obtained from administrative records in spring 2001 and 2002 during site visits. 

 Transcripts 

Transcripts were requested for all sampled students enrolled in both the GEAR UP and non-GEAR UP 

sampled schools at the end of the 2001–02 school year. Seventh- and eighth-grade transcript data were 

collected for each student with parent consent. Transcript data included student report cards and 

standardized test scores. The data collected provided information about classes taken and completed, 

grades received and retention in grade. 

 Parent Interview 

Paper-and-pencil telephone interviews were conducted in either English or Spanish with parents or 

guardians of all sampled students. (See appendix K for copies of the English version of parent 

interviews.) The parent interviews were conducted concurrently with the administration of the student 

surveys in fall 2000 and spring 2002. Parents were asked about their educational background; their 

experiences with GEAR UP; their educational expectations for their child; involvement in their child’s 

education; and knowledge about college costs, financing, admissions and family income. Parents received 

a telephone calling card valued at $10 in appreciation for their participation. 

 Middle School Summaries 

During the spring 2001 and 2002 site visits, the study team completed a Middle School Summary for 

GEAR UP and non-GEAR UP schools. The purpose of the Middle School Summary was to provide 
A-11 

school profile information and obtain information about the types of support services available to 

students. This enabled the national evaluation to look at similarities and differences among GEAR UP and 

non-GEAR UP schools, as well as track changes over time. 

 Guidance Counselor Summaries 

During the spring 2001 and 2002 site visits, the study team completed Guidance Counselor Summaries 

for GEAR UP and non-GEAR UP schools. The Guidance Counselor Summary provided information 

about guidance counselors’ decision-making processes and practices when advising students each 

counselor’s own experiences, approaches and mindset toward counseling middle school students and 

information about course offerings, grading and credits. This provided a means for determining 

similarities and differences between GEAR UP and non-GEAR UP schools. Information about courses 

offered, grading scales and course credits were necessary to standardize coding of student transcripts 

across schools. 

 GEAR UP Activity Records 

Each partnership project participating in the outcomes study was asked to maintain student- and parentlevel information on attendance at GEAR UP-sponsored activities. Data on program participation were 

collected for all sampled GEAR UP students and their parents on an ongoing basis beginning in fall 2000 

and continuing through the end of the 2001–02 school year. 

On a monthly basis, projects were asked to submit the following information about each GEAR UP 

activity they provided: 

 Subject matter covered (e.g., English, college financial aid), 

 Timing of the activity (e.g., after school, weekend), 

 Number of students or parents attending, 

 Leader of the activity (e.g., classroom teacher, project staff), and 

 Duration of activity (e.g., days, hours, minutes). 

GEAR UP-sponsored classes recorded on a student’s report card were not reported on activity forms. The 

information provided at the student level was comparable to the information GEAR UP projects reported 

in aggregate form on their Annual Performance Reports (APRs) to ED. 

 Annual Performance Reports 

APRs were provided to the national evaluation by the program office in summer 2001 and 2002. These 

reports provide information for all GEAR UP projects, including those participating in the national 

evaluation. The APRs contain information about student demographics, the numbers and types of 

activities projects offer, targeting and recruiting students, project management, and staffing. These reports 
 A-12 

were used to set the context and show how representative the GEAR UP sampled sites are of the broader 

GEAR UP program. 

A.4 Response Rates 

This section details response rates at each level of the study, as well as for the various data collection 

instruments. 

 Project Level 

As discussed earlier, 20 GEAR UP partnerships were selected for inclusion in the descriptive study of 

program implementation and the outcomes study. Two partnerships were dropped subsequently from the 

outcomes study because the GEAR UP school they served refused to participate in the national 

evaluation. 

 School Level 

A total of 40 schools were sampled to participate in the outcomes study. Twenty GEAR UP schools were 

selected as treatment schools along with 20 non-GEAR UP comparison schools. One GEAR UP school 

and its comparison, non-GEAR UP school were removed from the study because of lack of cooperation 

from the school district early in the study. Lack of cooperation at the school level resulted in another 

GEAR UP school being removed. One additional comparison school also was removed after many 

attempts were made to contact the school and no response was received even though the school had 

agreed initially to participate in the study. These occurrences in addition to the removal of the project 

mentioned previously resulted in 36 schools participating during the base year. 

Site visitors collected school-level data by completing the Guidance Counselor Summary, Middle School 

Summary, and Student Information Matrix during the 2000–01 and 2001–02 site visits. Each school sent 

report card and standardized test score data at the end of the 2001–02 school year. Table A-3 summarizes 

the school-level response rates for each of these data sources. 

 Student Level 

Parent Consent. Parent consent was obtained for all students who participated in the outcomes study. 

Each year parents or guardians were asked permission for their child to complete a student survey and to 

allow access to their child’s records and report cards. Between the base year and follow-up year of data 

collection, some schools changed their consent status to written consent for both the student survey and 

records and report cards, while other schools changed from implied to written consent for student records 

and report cards, (i.e., records-based data) but not the student survey. 

In an effort to reduce the effect of this change on response rates, the study team worked closely with 

schools asking them to encourage parents to allow their children to participate. In some cases, GEAR UP 

project staff and school staff went to great lengths to gain consent by re-mailing consent forms to parents, 

making phone calls, and even visiting homes. Additionally, trained telephone interviewers contacted 
A-13 

parents directly to gain consent. Consent forms were mailed to parents who gave verbal consent. 

Telephone calling cards were included as an incentive for them to sign and return the form. Extensive 

telephone nonresponse conversion was attempted for parents who did not return signed consent forms. 

Table A-3. School-level response rates among participating schools 

All Schools GEAR UP Non-GEAR UP 

Data source Number Percent Number Percent Number Percent 

Sample size 40 100 20 100 20 100 

Participating schools 36 90 18 90 18 90 

Guidance counselor summary 32 80 16 80 16 80 

Middle school summary 34 85 18 90 16 80 

Student survey 

 Grade 7 

 Grade 8 

36 

33 

90 

83 

18 

17 

90 

85 

18 

16 

90 

80 

Administrative records 

 Grade 7 

 Grade 8 

31 

32 

78 

80 

17 

17 

85 

85 

14 

15 

70 

75 

Report card 

 Grade 7 

 Grade 8 

33 

34 

83 

85 

16 

17 

80 

85 

17 

17 

85 

85 

Standardized test scores^ 

 Grade 7 

 Grade 8 

27 

31 

68 

78 

14 

15 

70 

75 

13 

16 

65 

80 

GEAR UP activity records* 18 90 18 90 NA NA 

^ Schools reporting they do not administer a standardized test at this grade are included as respondents. 

* Includes schools that did not provide information on all services provided. 

NA = not applicable. 

Table A-4 summarizes parent consent response rates for the student survey and records-based data. In 

2000–01 parent consent was obtained for 99 percent of students for the student survey and 97 percent for 

records-based data. In 2001–02, for students who remained in sampled schools parent consent was 

obtained for 85 percent of students for the student survey and 80 percent for records-based data. 

Table A-4. Number and percentage of parents giving consent by school year and type of data, 

for students remaining in original school 

Data source Number Percent 

Seventh-grade sample (SY 2000–01)^ 

 Student survey 

 Administrative records 

4,692 

4,445 

4,336 

100 

95 

92 

Eighth-grade followup (SY 2001–02)* 

 Student survey 

 Administrative records 

3,762 

3,188 

2,991 

100 

85 

80 

^ Includes students who subsequently left original school. 

* Excludes students who left original school before spring 2002. 
 A-14 

Students Leaving Sampled Schools. The original study design called for tracking and collecting eighthgrade data on students who left their original school. To do this, GEAR UP and non-GEAR UP schools 

were asked to provide the study with the name and address of a transfer student’s new school. Using 

information provided by schools and student and parent locating information obtained from student 

surveys and parent interviews, eighth-grade surveys were mailed to transfer students in spring 2002. In 

addition to this, students’ new schools were contacted and asked to provide eighth-grade school record 

data and seventh- and eighth-grade transcript data. Program participation data were collected only for 

students remaining in sampled GEAR UP schools so these data were not requested. The response rates for 

the students were extremely low despite the study’s effort to gain parent consent and trace students using 

Westat’s telephone research center. 

Table A-5 gives an overview of the number of sampled students who transferred between the base year 

and follow-up year data collection periods. A total of 724 students were no longer enrolled in the schools 

where they were originally sampled. Consent was obtained for 20 percent of the transfer students for 

student surveys and 18 percent for records-based data. The low response rate, high cost of tracing these 

students, and the lack of information about their new school influenced the decision that a student would 

be considered no longer in the sample for analytic purposes once he or she transferred out of a treatment 

or comparison school (i.e., did not receive the full “dosage” of middle school GEAR UP). Information 

was retained on the transfer students should ED want to attempt to follow up with them at some future 

date. 

Table A-5. Number and percentage of students who left original school for whom parent 

consent was obtained, by type of data 

Data source Number Percent 

Base-year sample 4,692 100 

 

Transferred to another school 930 20 

 Parent consent given 

 Student survey 

 Administrative records 

143 

132 

15 

14 

Student Survey. Student surveys were administered to sampled students in fall and winter of 2000 when 

they had just entered seventh grade. Students were followed up in spring 2002 when most had been 

promoted to the eighth grade. Students who were retained in seventh grade remained in the sample and 

were administered the eighth grade version of the survey. Table A-6 provides response rate information 

for the student surveys for the 2000–01 and 2001–02 school years. 

The primary reason for the decline in response rates was the decreased rate of parent consent described 

earlier. 

Parent Interview. Telephone interviews with the parents or guardians of sampled students coincided 

with the administration of the student surveys. Table A-6 also provides response rate information for the 

parent interviews for the 2000–01 and 2001–02 school years. 

Student Administrative Records. Demographic and administrative data were collected for each sampled 

student at both the GEAR UP and non-GEAR UP schools using the SIM. Table A-6 provides response 

rate information for administrative data for the 2000–01 and 2001–02 school years. The drop in response 
A-15 

rate was because several schools changed from informed parental consent to requiring written, explicit 

consent. 

Table A-6. Student-level response rates for GEAR UP and non-GEAR UP schools 

Students in original 

school GEAR UP Non-GEAR UP Data source 

Number Percent Number Percent Number Percent 

Base-year sample 

Seventh-grade (SY 2000–01)^ 

Student survey 

Parent interview 

Administrative records 

4,692 

4,093 

3,774 

3,870 

100 

87 

80 

82 

2,408 

2,159 

1,944 

2,151 

100 

90 

81 

89 

2,284 

1,934 

1,830 

1,719 

100 

85 

80 

75 

Eighth-grade (SY 2001–02)* 

Student survey 

Parent interview 

Administrative records 

Report cards 

Standardized test scores 

2,578 

2,718 

2,687 

2,271 

2,430 

55 

58 

57 

48 

52 

1,358 

1,400 

1,494 

1,204 

1,283 

56 

58 

62 

50 

53 

1,220 

1,318 

1,193 

1,067 

1,147 

53 

58 

53 

47 

50 

^ Includes students who subsequently left original school. 

* Excludes students who left original school before spring 2002. 

Report Cards and Standardized Test Scores. Seventh- and eighth-grade report cards and standardized 

test scores were requested for all sampled students at the end of the 2001–02 school year. Response rates 

are given in table A-5. Changes in requirements for parental consent also contributed to a drop in 

response rates for these data. 

GEAR UP Program Activity Records. Each partnership was asked to collect information about the 

types of GEAR UP activities students participated in, how the activities were delivered, where they 

occurred and the frequency and duration of these services. Table A-7 gives an overview of participation 

data response rates. Of the participating projects, 83 percent submitted student group activity and student 

one-on-one activity data, while 78 percent of the projects submitted parent group activity data for the 

2001–02 school. Projects were less likely to provide data in the summer, with only 78 percent providing 

student group activity data and 67 percent submitting student one-on-one and parent group data. Projects 

submitting data often provided incomplete information. See appendix I for further discussion. 

A.5 Management and Quality Control 

 Identification (ID) Number Structure and Data Linkage 

The ID structure was designed to link sampled students, schools and projects and keep track of GEAR UP 

and non-GEAR UP status. Students were assigned a unique ID when the sample was drawn; this number 

stayed with the student across subsequent years of data collection. Parents were assigned the same ID as 

their child, thereby linking parents to the corresponding sampled student via the ID number. 
 A-16 

Table A-7. Participation data response rates, project level 

GEAR UP schools 

Type of activity and school year 

Number Percent 

Total schools 

Student group activity 

 2000–01 school year 

 Summer 2001 

 2001–02 school year 

Student one on one 

 2000–01 school year 

 Summer 2001 

 2001–02 school year 

Parent group activity 

 2000–01 school year 

 Summer 2001 

 2001–02 school year 

18 

14 

14 

15 

14 

12 

15 

13 

12 

14 

100 

78 

78 

83 

78 

67 

83 

72 

67 

78 

In fall 2001, schools were asked to report each sampled student who transferred out of the participating 

GEAR UP or non-GEAR UP school. These students maintained the same randomly assigned student ID 

and grantee linkage but were flagged in the database as a transfer student (i.e., no longer enrolled in 

sampled school). 

 Data Entry and Data Cleaning 

Survey and Student Information Matrix Data. To ensure that the student and parent survey data were 

complete and of high quality, trained clerical staff conducted a series of coding, data entry and editing 

procedures. Coding manuals, key entry and online editing programs, batch editing programs and 

frequency generation programs were created for each of the survey instruments. The Westat 

Codebook/Edit System (COED) was used for preparation of electronic files for the study data. 

Clerical staff performed manual edits directly on student surveys, parent interviews and SIM forms to 

check each document for completeness, extraneous marks and proper adherence to skip instructions. Staff 

also performed manual and electronic range checks, primarily to identify where respondents may have 

misinterpreted questions. Staff coded SIM forms to indicate missing data. 

Data entry staff keyed survey, participation and SIM data using software that provided for 100 percent 

key verification of all entries. Edits were performed after key entry. This included checking all fields for 

allowable use of numeric, alphabetic or special character entries; checking that each field contained only 

allowable codes; checking ranges to verify that coded values fell within permissible high and low values 

for each numeric field; and checking that skip instructions had been followed. In addition to these edits, 

data consistency and other logic checks were performed in batch editing. When the source of error was 

found to be in coding or keying, the error was corrected. When the problem could not be resolved, the 
A-17 

item was coded as “not ascertained.” Project staff reviewed the frequencies of responses to all data items 

(both individually and in conjunction with related data items) to ensure that appropriate skip patterns were 

followed. Members of the data management team checked each item to make sure the correct number of 

responses was represented for all items. The team ran frequencies and checked them at the batch edit 

stage. After the batch files were considered clean on the basis of machine edits and the review of marginal 

frequencies, the data management team declared the data ready for analysis file generation. 

Student Transcript Data. Students’ seventh- and eighth-grade report cards and test scores as well as 

student information, such as promotion and honors, were entered in the Middle School Transcript System 

(MSTS), which was specifically adapted for this task from a high school transcript study data system. A 

list of classes offered by each school was entered into the MSTS. These classes were then matched 

against a list of courses in the Classification of Secondary School Course (CSSC) system, which served as 

a framework for coding classes. Information about classes taken by each student, such as course name, 

grade level, grade received, whether taught in language other than English and whether course was 

considered honors, special education or on grade level, was entered into the system. Any standardized test 

scores that may have been listed were also entered. Report card courses were verified using double-blind 

entry, where errors occurred the necessary corrections were made. Staff performed quality control checks 

to verify that data were correctly entered into the MSTS. 

Annual Performance Report Data. Project staff entered data from APRs using a Web-based data entry 

system. Data were checked after key entry. This included checking all fields for allowable use of numeric, 

alphabetic or special characters; checking that each field contained only allowable codes; and checking 

ranges to verify that coded values fell within permissible high and low values for each numeric field. 

Frequencies of responses were run to ensure the correct number of responses was represented for all 

items. 

Program Activity Records. Projects were asked to submit their program participation data to the 

evaluation team on a monthly basis. Projects submitted these data in a standardized format either as hard 

copy or electronically. Clerical staff performed manual edits directly on forms to check each document 

for completeness. Manual data checks were made to ensure that the listed services occurred within the 

data collection timeline. When problems interpreting data arose sites were contacted and asked to clarify 

any data conflicts. Data were then keyed into a database and frequencies were reviewed. After the files 

were considered clean on the basis of manual edits and the review of frequencies, the data management 

team declared the data ready for analysis file generation. See appendix I for a more detailed discussion of 

the methodology used to analyze program activity records. 

B-1 

Appendix B 

Student Sample Design, Imputations, Weights and 

Error Estimation 

This appendix describes how the student sample was drawn, how missing data were handled and how 

variances were estimated. 

B.1 Sample Design 

In August 1999, the U.S. Department of Education awarded 164 Gaining Early Awareness and Readiness 

for Undergraduate Programs (GEAR UP) partnership grants. From those awards, 20 projects were 

recruited to participate in the National Evaluation of GEAR UP. One school within each of the 20 

partnership projects was then selected simultaneously with 20 non-GEAR UP (comparison) schools. 

Selection was based on several factors from the 1997 Common Core of Data (CCD). A more detailed 

description of how those selections were made is provided in appendix A. 

In the 18 GEAR UP and 18 non-GEAR UP schools that agreed to participate in the longitudinal outcomes 

study component of the national evaluation, a total of 9,121 students enrolled in the seventh grade during 

fall 2000. (Although 2000–01 was the second year of the grant, the sampled students did not receive any 

GEAR UP services during the previous school year.) For those students enrolled in fall 2000, parent 

consent to participate in the evaluation was obtained for 6,941 students. From those with parent consent, a 

sample of 4,692 students was drawn. 

The ideal situation would have been to include the entire seventh-grade class in the student sample to 

correspond to the whole-grade, or cohort, approach required of the GEAR UP partnerships. Many of the 

schools in the sampled partnerships, however, had very large seventh-grade classes. Preliminary 

information indicated that seventh-grade classes in the middle schools targeted by GEAR UP varied from 

about 60 students to as large as 600 students. For cost efficiency, students were sampled from the larger 

schools. 

Sampling was done by setting a maximum sample size for a school at 140 students. For schools with a 

seventh-grade class of 140 or fewer students, all students were included in the sample. For schools with a 

seventh-grade class of more than 140 students, a simple random sample of 140 students was selected from 

the group. (The sample was slightly larger in a small number of schools because it would have been 

difficult to exclude a handful of students.) The sample size of 140 students per school was intended to 

yield data for 110 students on average per sampled school. 

Students who were originally included in the sample were later excluded from the study. Specifically, 983 

students who transferred out of the GEAR UP and non-GEAR UP schools before to the end of eighth 

grade were excluded from the longitudinal outcomes study as explained in appendix A and below. 
 B-2 

B.2 Analysis of Students Leaving Sampled Schools 

The original study design for the outcomes study called for following all sampled students for the 

duration of the study. However, during the data collection period, about 18 percent of the students in the 

sample left the schools they were attending in fall 2000. Because follow-up information was obtained 

only from about 20 percent of these students using contact information from students and from 

information parents provided during the fall 2000 data collection, the decision was made in collaboration 

with the Technical Working Group to define participation in GEAR UP as the length of the study period 

because of response rates and differential participation. 

Table B-1 shows the percentages of students who attended GEAR UP or non-GEAR UP schools, whether 

they left their original sampled school (“Mobile” or “Stationary”), the student’s College Orientation Index 

score, the student’s race and ethnicity and whether the student would be the first in his or her family to 

attend college (“First Generation”). (See Appendix C, Index Construction, for a description of the College 

Orientation Index.) Overall the table shows that those students who left their schools (mobile students) 

before the end of eighth grade were different from those who remained (stationary students) on specific 

characteristics. In the GEAR UP schools, a greater percentage of the mobile students scored in the lowest 

third on the College Orientation index than the stationary students. A smaller percentage had the highest 

College Orientation Index scores. For students in non-GEAR UP schools, similar statistically significant 

differences were found for College Orientation Index scores. 

Mobile students in both sets of schools were disproportionately African-American. In addition, mobile 

students in GEAR UP schools were disproportionately non-Hispanic while those in non-GEAR UP 

schools were disproportionately nonwhite. 

It is important to note that the analysis controlled for baseline differences among the stationary students, 

so the disproportionality of the sample by mobility status does not affect the validity of the causal 

findings in this report. One interesting finding from this brief analysis of those who left the sampled 

school is that they are a group with a stronger than average need for intervention who are not able to fully 

benefit from GEAR UP because the program is tied to specific schools. 

B.3 Imputation and Weights 

The National Evaluation of GEAR UP obtained information about students participating in the study 

through eight different sources: 

 Seventh-grade student surveys, 

 Seventh-grade parent interviews, 

 Seventh-grade student administrative records data,39 

 

39 Student administrative records data included information such as number of absences, enrollment in special programs (e.g., 

free or reduced-priced lunch, special education, gifted and talented) and demographic information. 
B-3 

Table B-1. Analysis of students who left their original sampled school before the end of eighth grade  Students in GEAR UP schools Students in Non-GEAR UP schools  % Mobile 

% Stationary Difference % Mobile % Station- ary Difference 

Measure Est. Est. Diff. 95% Conf. Est. Est. Diff. 95% CoCollege Orientation Index 

Lowest 1/3 Middle 1/3 Highest 1/3 

59.8 23.7 16.4 

44.0 28.4 27.7 

15.9* 

-4.6 

-11.2* 

(10.1,21.7) 

(-9.6,0.3) 

(-18.1,-4.4) 

62.8 18.9 18.3 

40.1 25.7 34.3 

22.8* 

-6.8 

-16.0* 

(14.9,30

(-13.5,0

(-22.0,-10

Race/ethnicity 

White African-American Hispanic Asian 

39.1 35.6 20.0 

5.3 

41.0 21.0 32.9 

5.3 

-1.8 

14.7* 

-12.9* 

0.0 

(-15.1,11.4) 

(0.2,29.2) 

(-22.2,-3.6) 

(-2.7,2.8) 

28.8 51.7 16.9 

2.7 

50.5 21.2 24.7 

3.7 

-21.7* 

30.5* 

-7.8 -1.0 

(-38.6,-4

(12.2,48

(-20.0,4

(-3.1,1

First Generation 

Yes No 

89.9 10.1 

84.2 15.8 

5.6 

-5.6 

(-0.3,11.6) (-11.6,0.3) 

91.4 

8.7 

86.9 13.1 

4.4 

-4.4 

(-0.5,9(-9.4,0

* Statistically significant at α = 0.05. 
 B-4 

 Eighth-grade student surveys, 

 Eighth-grade parent interviews, 

 Eighth-grade student administrative records data, 

 Participation in program activity data, and 

 Transcript data (report cards and standardized test score(s). 

Copies of these instruments are included in appendix K. 

Preferably, all of the students in the study would have had complete information from all eight sources; 

unfortunately, this was not the case. To address the fact that most students only had partial data, several 

different approaches were used. 

The following discussion explains how imputation and weighting were used to account for missing and 

partial seventh-grade student data, seventh-grade parent data and seventh-grade student records data. The 

next section provides an explanation of the imputation and weighting used on eighth-grade student data, 

eighth-grade parent data and eighth-grade student administrative records data. Finally, the last section 

concerns nonresponse adjustment performed on transcript data. Because complete participation data were 

available for so few schools, no imputation or weighting was performed to offset gaps in the participation 

data (see appendix I for a discussion on analyzing the participation data). 

 Seventh-Grade Imputation and Weighting 

Among the 3,709 sampled non-transfer students with parental consent, complete information from all 

three seventh-grade sources was available for 2,596. (These students are located in section 7STP of figure 

B-1.) Of the remaining 1,113 students, 91 students in section 7P had only a parent interview. Given the 

lack of data, no adjustments were made for these 142 students. This left 971 with useful partial 

information in addition to the 2,596 with complete information. (These students are in sections 7T, 7TP, 

7STP, 7ST, 7SP and 7S of figure B-1.) To compensate for the partial data for these students, three 

different techniques were used, depending on the type of data that were missing. The patterns of partial 

data are shown in figure B-1. 

Nearest Neighbor Imputation for Cases with Missing Seventh-grade Parent Interview Data. The 

first adjustments performed were for those 491 cases without parent data but with student data. (These 

cases are in sections 7T and 7ST of figure B-1.) The procedure involved what is called a Nearest 

Neighbor imputation. In the Nearest Neighbor imputation, seventh-grade student survey data were used to 

predict a total College Orientation Index value for all cases in the sample.40 Table B-2 contains a list of 

the variables, parameter estimates, and standard errors that were contained in the model that produced the 

predicted College Orientation Index value. Note that the model fit was very good with an R2

 of 0.88, 

indicating that a good measurement of the student’s baseline College Orientation Index can be made even 

 

40 The College Orientation Index is based on both parent and student survey data, but in this case, the predicted College 

Orientation Index value was based only on the student variables in the index. See appendix C for a discussion of how this 

index was constructed. 
B-5 

Figure B-1. Number of cases with different combinations of each of three seventh-grade data 

sources 

Where 

7T = seventh-grade student survey data 

7P = seventh-grade parent interview data 

7S = seventh-grade student records data 

NOTE: Fifty-one students with no forms of data are not included in this figure. 

without parent data. The next step was to match each student with missing seventh-grade parent interview 

data to a student with seventh-grade parent interview data that had the closest predicted College 

Orientation Index value. 

Once each case with missing seventh-grade parent interview data was matched to its nearest neighbor 

with those data, the values for all parent variables used in analyses were copied from the donor case (the 

case with seventh-grade parent interview data) to the recipient (the case without seventh-grade parent 

interview data). Copying these values en masse preserves the correlation structure among parental 

variables, while the choice of a donor matched on the student part of the College Orientation Index 

minimizes the attenuation in the correlation structure between parent and student variables that frequently 

arises from imputation. Table B-3 provides a list of those parent variables that were copied. 

Seventh-grade student surveys

3,389 

Seventh-grade records data 

3,139 

Seventh-grade parent 

interviews 

3,113 

2,596

 (7STP) 

126 

(7T) 

302 

(7TP) 

365 

(7ST) 

54 

(7S) 

124 

(7SP) 

91 

(7P) 
 B-6 

Table B-2. Variables, parameter estimates and standard errors used to create predicted College 

Orientation Index values 

Variable 

Parameter 

estimate Standard error F value Pr > F 

Intercept 0.81 0.17 23.6 <.0001 

ImpWork_7 -0.33 0.09 13.1 0.0003 

SkipClasses_7 -0.28 0.09 9.2 0.0024 

Grades_7 1.27 0.11 141.5 <.0001 

StdParTalk_7 1.18 0.08 197.2 <.0001 

OtherSchoolHelp_7 -0.54 0.14 14.0 0.0002 

ReadingHours_7 1.02 0.07 184.9 <.0001 

NegJunkHours_7 0.32 0.08 17.7 <.0001 

VolunteerFreq_7 -0.27 0.10 6.9 0.0087 

Academic_7 1.17 0.04 822.3 <.0001 

ExpectPSERev_7 1.24 0.02 3759.9 <.0001 

Table B-3. Parent variables that were copied in the Nearest Neighbor procedure 

CollegeAffordable_7 EventPlaySport_7 Performance_7 

CollegeClose_7 EventPTA_7 Pexpect_7 

Confer_events_7 Hmwkundr_7 Pimphardwork_7 

ConferBehave_7 NumConfType_7 PrepMeet_7 

ConferFreq_7 NumEventType_7 Sdiligent_7 

ConferHomework_7 ParGrades_7 Simphardwork_7 

ConferOther_7 ParInvolve_7 TalkCollege_7 

ConferProgress_7 ParPrep_7 Ultdegree_7 

EnufInfo_7 ParRptHmwkFreq_7 Workshop_7 

EventBacktoSchool_7 ParRptHmwkHelp_7 WritInfo_7 

EventFieldTrip_7 ParRptHmwkHour_7 

Cluster Analysis Imputation for Cases with Missing Seventh-grade Student Administrative Records 

Data. Because student administrative record data were not used in constructing the College Orientation 

Index, it made little sense to use the Nearest Neighbor technique, which is based on a predicted College 

Orientation Index score, to impute missing student records data. Instead, five student record variables 

were modeled using survey data. The five variables that were modeled are listed below: 

 Whether the students were in an honors or gifted and talented program (HONORS), 

 Total number of excused and unexcused absences for student (TOTABSNC), 

 Number of unexcused absences for student (UNEXABSN), 

 Total number of disciplinary actions taken against a student (TOTDISP), and 

 Whether the student received any honors or awards (AWARDS). 
B-7 

These variables were chosen because of their theoretical importance to the program.41 Although these 

variables were not analyzed in the body of the report, they were used in the removal of baseline 

differences (appendix E) and in the compensation for missing followup data. The models used seventhgrade student and parent interview responses to predict values for each of the five student records 

variables. (Tables B-4 through B-8 provide the variables and coefficients that made up each of the five 

models.) The models for HONORS and AWARDS were logistic regressions. The models for the other 

three variables were linear models of Box-Cox transforms of the variables. 

Table B-4. Model for whether student was in an honors or gifted and talented program during 

seventh grade (HONORS_7) 

Predictor variable Beta coefficients Standard error Wald chi-square Pr > ChiSq 

Intercept -2.13 0.15 193.64 <.0001 

ParRptHmwkHelp_7 -0.20 0.07 8.83 0.00 

ConferProgress_7 0.57 0.14 16.81 <.0001 

EventBacktoSchool_7 -0.32 0.14 5.70 0.02 

ParGrades_7 0.43 0.10 17.73 <.0001 

ImpGoCollege_7 -0.32 0.10 10.74 0.00 

ImpWork_7 -0.31 0.07 16.85 <.0001 

Grades_7 0.72 0.12 38.76 <.0001 

OtherSchoolHelp_7 -0.46 0.13 12.04 0.00 

MathClub_7 0.39 0.13 8.30 0.00 

CollegeBoundRev_7 0.08 0.01 41.59 <.0001 

NOTE: The R2 for this model was 0.24. 

Table B-5. Model for total number of absences for student (excused or unexcused) during 

seventh grade (TOTABSNC_7) 

Predictor variable Beta coefficients Standard error t value Pr > |t| 

Intercept 1.44 0.01 161.18 <.0001 

ConferBehave_7 0.03 0.01 2.32 0.02 

Grades_7 -0.04 0.01 -6.90 <.0001 

AbsentDays_7 -0.12 0.00 -26.07 <.0001 

FriendHelp_7 -0.01 0.01 -1.27 0.21 

TakingClasses_7 0.03 0.01 3.09 0.00 

ParInvolve_7 -0.01 0.00 -4.72 <.0001 

ExpectPSERev_7 0.00 0.00 2.51 0.01 

NOTES: AbsentDays_7 is reverse coded. The R2 for this model was 0.31. 

 

41 See appendix J for the glossary of definitions for these variables. 
 B-8 

Table B-6. Model for number of unexcused absences for student during seventh grade 

(UNEXABSN_7) 

Predictor variable Beta coefficients Standard error t value Pr > |t| 

Intercept -0.56 0.01 -76.12 <.0001 

EventPlaySport_7 0.03 0.01 2.89 0.00 

Grades_7 -0.03 0.00 -6.80 <.0001 

AbsentDays_7 -0.10 0.00 -20.72 <.0001 

SDiligent_7 -0.01 0.00 -3.12 0.00 

NOTES: AbsentDays_7 is reverse coded. The R2 for this model was 0.25. 

Table B-7. Model for total number of disciplinary actions taken against student during seventh 

grade (TOTDISP_7) 

Predictor variable Beta coefficients Standard error F value Pr > F 

Intercept -0.83 0.02 2556.46 <.0001 

ConferBehave_7 0.25 0.03 82.02 <.0001 

ParRptHmwkHour_7 -0.05 0.01 21.48 <.0001 

BabysittingHours_7 0.02 0.01 10.60 0.00 

CollegeBoundRev_7 -0.01 0.00 51.62 <.0001 

NOTE: The R2 for this model was 0.12. 

Table B-8. Model for whether student received any honors or awards during seventh grade 

(AWARDS_7) 

Predictor variable Beta coefficients Standard error Wald chi-square Pr > ChiSq 

Intercept -0.65 0.14 21.41 <.0001 

EventBacktoSchool_7 -0.29 0.13 5.11 0.02 

EventPlaySport_7 0.97 0.14 51.42 <.0001 

ParGrades_7 0.51 0.08 44.05 <.0001 

PrepMeet_7 0.24 0.06 17.30 <.0001 

Grades_7 0.46 0.08 34.60 <.0001 

BabysittingHours_7 -0.12 0.04 8.12 0.00 

NOTE: The R2 for this model was 0.2. 

To demonstrate the bias that would have existed without student administrative records imputations, 

predicted values for HONORS and AWARDS were created, using the models described above. (Because 

this procedure was only used to demonstrate the need for student records imputations, only two of the five 

student records variables were tested.) The cases were then divided into four groups: 

 Students with complete student records data in GEAR UP schools, 

 Students with incomplete student records data in GEAR UP schools, 

 Students with student records data in non-GEAR UP schools, and 
B-9 

 Students with incomplete student records data in non-GEAR UP schools. 

Within each of these four groups, the predicted student records values were averaged for each variable. 

The group averages for these predicted student records variables are listed in table B-9. There were 

significant differences between students with complete student administrative records data and those with 

missing student records data, which reinforced the need to impute missing student administrative records 

data. The differences were particularly striking in the non-GEAR UP schools, where the students without 

student administrative records were predicted to be much less likely to be enrolled in honors programs 

and much less likely to have received awards. 

Table B-9. Average predicted values for selected student administrative records variables, by 

school type and student records data status 

Predicted student records variables, school type, and student 

records data status Frequency Mean (%) 

Standard 

error (%) 

HONORS variable 

 GEAR UP students with missing student records data 126 18.0 1.7 

 GEAR UP students with complete student records data 1,683 18.5 0.5 

 Non-GEAR UP students with missing student records 

 data 354 17.6 1.0 

 Non-GEAR UP students with complete student records 

 data 1,260 22.4 0.6 

AWARDS variable 

 GEAR UP students with missing student records data 126 36.2 2.0 

 GEAR UP students with complete student records data 1,683 38.8 0.6 

 Non-GEAR UP students with missing student records 

 data 354 36.7 1.1 

 Non-GEAR UP students with complete student records 

 data 1,260 40.6 0.7 

In the next step in the imputation process, a clustering algorithm was used to group each of the 3,389 

students into one of five natural clusters. The groups were formed so that students were similar 

(homogeneous) with respect to the five variables listed above. In addition, each cluster was different 

(heterogeneous) with respect to those same variables. Table B-10 describes each of these five clusters. 

Table B-10. Size and predicted seventh-grade student records values for each of the five natural 

clusters used for seventh-grade student records imputation 

Predicted values for selected seventh-grade student records variables 

Cluster 

Number of 

students 

Percent 

of total HONORS TOTABSNC UNEXABSN TOTDISP AWARDS 

1 835 24.6 1.11 -0.81 -0.78 -0.89 1.04 

2 322 9.5 -1.52 1.63 1.52 1.67 -1.29 

3 707 20.9 -0.80 -0.07 -0.07 0.34 -0.99 

4 1,132 33.4 0.12 -0.32 -0.36 0.02 0.21 

5 393 11.6 -0.02 1.42 1.58 -0.14 0.03 

A general description could be crafted for each of these five clusters. Cluster No. 1 contained serious 

students who did well academically, attended classes regularly and were least likely to be disciplined. The 

students in Cluster No. 2 tended to do poorly academically and skip school a great deal. Cluster No. 3 
 B-10 

contained students who did not do very well academically but who attended school regularly and were 

disciplined at close to average frequency. The students in Cluster No. 4 seemed to be average in most 

respects, with slightly better than average attendance. Finally, those students in Cluster No. 5 seemed to 

have average academic scores and average discipline issues but had attendance problems. 

Within each of these clusters, whole seventh-grade student records were copied from randomly chosen 

students with complete seventh-grade student records data and assigned to randomly chosen students 

within the same cluster who had missing seventh-grade student records data. Copying complete records of 

seventh-grade student records ensured that the data were internally consistent. Copying data from a fellow 

student within the same cluster minimized the attenuation in the correlation structure among student 

records variables on the one hand and parent and student questionnaire variables on the other hand that 

frequently arose from imputation. 

Nonresponse Adjustment for Cases with Missing Seventh-grade Student Survey Data. The most 

crucial seventh-grade data source was the seventh-grade student survey. Because of this fact, missing 

seventh-grade student survey data were not imputed; those cases that did not have seventh-grade student 

survey data were dropped from the analysis. 

However, the data on these students that had been obtained from student records were used to minimize 

any bias from these students’ nonresponse.42 These data were used to perform a nonresponse adjustment 

(NRA). The NRA process created weights that, when applied to the remaining cases, reduced the impact 

of weighing the nonrespondents as zero. To create the NRA weights, all 3,389 students were partitioned 

into one of five groups based on their probability of nonresponse. This predicted response propensity was 

estimated using a logistic regression that estimated the likelihood of a student completing the student 

survey based on data available from the student record. The results were then used to create five groups 

that contained students with similar propensities for nonresponse. Table B-11 provides the beta 

coefficients for the logistic regression model used to predict each case’s probability of nonresponse. Note 

that student nonresponse was most common among African-American students, students with poor 

attendance (the questionnaire was given in school), students with individualized education plans and 

students with limited English proficiency who were eligible for free or reduced-priced lunches. 

Table B-11. Beta coefficients used to determine a student’s propensity for response 

Parameter Estimate Standard error Wald chi-square Pr > ChiSq 

Intercept 6.19 0.73 72.74 <.0001 

Black -3.24 0.72 20.04 <.0001 

TOTABSNC -0.02 0.01 8.15 0.00 

GENDER -0.32 0.16 3.84 0.05 

TRUANCY -0.41 0.09 20.34 <.0001 

IEP -0.91 0.18 25.16 <.0001 

AWARDS 1.76 0.59 8.83 0.00 

LEP*LUNCH -1.31 0.33 16.13 <.0001 

NOTE: LEP*LUNCH refers to those in LEP programs but who were not eligible for free or reduced-priced lunches. 

 

42 As shown in figure B-1, 178 students had SIM data but no student questionnaire. (These students are represented in sections 

7SP and 7S of figure B-1.) In addition, 91 students had only parent data (section 7P), and 51 students had no data at all. NRA 

can only minimize the bias associated with leaving the 178 out of the analysis. 
B-11 

Within each of the five groups, the weights of the nonrespondents were proportionally allocated to the 

respondents. When completed, the sum of the adjusted weights for the respondents was equal to the sum 

of the pre-adjusted weights for the nonrespondents and the respondents. After this transfer of weights, the 

nonrespondents were given a weight of zero. Responding students in groups with poor response rates had 

their weights increased. The following equation provides the equation that determined the transfer of 

weights. 

,

, ,

, , , ,

,

 if 1

0 if 0

c j

j c

ci ci

NR c i cj cj

j c

c i

W

W

W W

δ

δ

δ

∈

∈

⎧

⎪

⎪ = = ⎨

⎪

⎪ = ⎩

∑

∑

where 

WNR c i , , = the new nonresponse-adjusted weight 

Wc, j = the initial weight of student j in the c

th cell 

Wc,i = the initial weight of student i in the c

th cell 

δ c, j = 1 if the j

th member of the cth cell is a respondent, 0 otherwise 

c i, δ = 1 if the student i in cell c is a respondent, 0 otherwise 

 Eighth-grade Imputation and Weighting 

The imputation and weighting procedures used to account for partial or missing eighth-grade data were a 

more complex version of the procedures used to manage partial or missing seventh-grade data. Figure B-2 

summarizes the number of cases with different combinations of the three eighth-grade data sources to be 

discussed in this section. 

The total number of eighth-grade student surveys, parent interviews and student records data forms is 

lower than for the seventh grade, primarily because during the eighth-grade survey procedure, permission 

issues arose in several of the schools. Because of these difficulties, many students were not allowed to 

complete the eighth-grade student survey at school, as planned. Subsequently, during the course of parent 

telephone interviews, parent interviews were obtained for many of these students, but student response 

rates were still much lower. Given the large number of nonresponding students with responding parents 

and given the high correlation that had previously been discovered between parent and student variables, 

it was decided to classify a student as a respondent at the eighth-grade level if either he or she responded 

or his or her parent responded. This meant that imputation was used for missing student questionnaires 

and for missing parent questionnaires and missing student records. Nonresponse weighting was used only 

for those students for whom neither a student nor a parent questionnaire was obtained. 

Nearest Neighbor Imputation for Cases With Missing Eighth-grade Student or Parent Data. Several 

sections of figure B-2 had missing eighth-grade student or parent interview data and, therefore, required 

data imputation using the Nearest Neighbor technique. 

Imputing Eighth-grade Student Data for Those with Only Eighth-Grade Parent Data. The 240 cases in 

section SP of figure B-2 contained no eighth-grade data other than eighth-grade parent interview data. To 
 B-12 

impute eighth-grade student data for these cases, complete seventh-grade records43 and eighth-grade 

parent records were used to predict an eighth-grade College Orientation Index value for all 3,389 cases 

with positive seventh-grade weights.44 Table B-12 contains a list of variables and beta coefficients that 

were used in the model to produce these predicted College Orientation Index values. Note that 

interpretation of this table is complicated by the use of indices as predictors. A number of the predictors 

have substantial correlations with each other and, therefore, this table is presented for documentation 

purposes only. Apart from that complicating issue, the model does well at predicting College Orientation 

Index, with an R2

 of 0.77. 

Figure B-2. Number of cases with different combinations of each of the three eighth-grade data 

sources 

Where 

8T = eighth-grade student survey 

8P = eighth-grade parent interview 

8S = eighth-grade student records data 

NOTES: This figure does not include 200 cases with seventh-grade student survey data but no data from any of the three eighth-grade data 

sources. A nonresponse adjustment was performed to account for these students. That procedure is explained later in this appendix. 

 

43 For the Nearest Neighbor imputations, the phrase complete seventh-grade records refers to all of the seventh-grade student and 

parent questionnaire data as well as seventh-grade administrative record data, regardless of whether or not they were imputed 

at the seventh-grade level. 

44 The eighth-grade College Orientation Index is based on seventh- and eighth-grade parent and student survey data. In the 

Nearest Neighbor imputations, however, the predicted College Orientation Index values were based on seventh-grade parent 

and student survey data and either eighth-grade parent or eighth-grade student survey data, whichever are noted as used in that

particular imputation. 

Eighth-grade student surveys 

2,578 

Eighth-grade records data 

2,687 

Eighth-grade parent interviews 

2,718 

2,005

 (8STP) 

77 

(8T) 

185 

(8TP) 

311 

(8ST) 

83 

(8S) 

288 

(8SP) 

240 

(8P) 
B-13 

Table B-12. Variables and beta coefficients used in the model to predict College Orientation 

Index values for the imputation of student data to cases in Section 8P 

Model Term Estimate Standard error tValue Probt 

Intercept -38.20 17.70 -2.16 0.03 

ArtsTutother_7 6.04 2.74 2.20 0.03 

ClubHours_7 7.39 3.72 1.99 0.05 

ConferBehave_8 -7.97 2.84 -2.81 0.01 

EXABSNC7 -43.26 16.44 -2.63 0.01 

EventBacktoSchool_7 -5.89 2.13 -2.76 0.01 

FriendOpImport_7 10.89 4.82 2.26 0.02 

MathTutother_7 -6.42 2.59 -2.48 0.01 

ParentAttends_7 9.17 2.87 3.20 0.00 

PostSecPlan_7 1 -0.54 4.91 -0.11 0.91 

PostSecPlan_7 2 2.46 5.21 0.47 0.64 

PostSecPlan_7 3 -6.86 2.53 -2.71 0.01 

PostSecPlan_7 4 0.00 . . . 

ProfAspiration_7 5.57 2.16 2.57 0.01 

SiblingEd_8 12.78 4.73 2.70 0.01 

Volunteerism_8 6.06 2.38 2.54 0.01 

simphardwork_7 -13.82 6.69 -2.07 0.04 

ultdegree_8 27.67 4.30 6.43 <.01 

ChurchFreq_7 12.98 3.12 4.16 <.01 

CollegeBoundRev_7 184.24 26.16 7.04 <.01 

FriendFreq_7 -12.24 3.31 -3.70 0.00 

GENDER -28.99 7.75 -3.74 0.00 

HHIncome_8 11.75 3.32 3.54 0.00 

Heard4Year_7 -9.99 2.62 -3.82 0.00 

ParGrades_8 -74.25 23.14 -3.21 0.00 

performance_7 -44.22 11.58 -3.82 0.00 

performance_8 161.33 17.80 9.06 <.01 

pexpect_7 -48.46 6.91 -7.01 <.01 

CollegeBoundRev_7*ParGrades_8 165.59 31.86 5.20 <.01 

GENDER*pexpect_8 27.14 10.51 2.58 0.01 

Performance_8*pexpect_8 139.46 11.49 12.14 <.01 

Each case in section 8P was then matched to the case with a parent and student survey (section 8TP) or 

the case with data from all three sources (section 8STP) with the closest predicted College Orientation 

Index value and that was in the same GEAR UP group.45 Once each case from section 8P was matched to 

its nearest neighbor, eighth-grade student data were copied from the donor (the case in either section 8TP 

or section 8STP) to the recipient (the case in section 8P). 

 

45 In other words, cases from GEAR UP schools were only matched with other cases from GEAR UP schools and cases from 

non-GEAR UP schools were only matched with others from non-GEAR UP schools. This additional stipulation was used in all 

of the eighth-grade imputations but was not required for seventh-grade imputations. 
 B-14 

Imputing Eighth-grade Student Data for Those with Eighth-Grade Parent and Eighth-Grade Student 

Records Data. There were 288 cases with eighth-grade student records data and eighth-grade parent data 

but no eighth-grade student data. (These cases are in section 8SP of figure B-2.) To impute eighth-grade 

student data for these cases, complete seventh-grade data, eighth-grade student records, and eighth-grade 

parent data were used to predict an eighth-grade College Orientation Index value for all 3,389 cases. 

Table B-13 provides the variables, and their beta coefficients, used to produce these predicted College 

Orientation Index values. The R2

 for this model is 0.77, indicating that it is a strong predictor of the 

College Orientation Index values. 

Each of the 288 cases in section 8SP was then matched to a case with student survey, parent interview and 

student records data (section 8STP) with the closest predicted College Orientation Index value and that 

was in the same GEAR UP group. Then, student data were copied from each donor to its recipient. 

Imputing Eighth-grade Parent Data for Those with Eighth-grade Student Data. Sections 8T and 8ST 

contained a total of 338 cases, all of which had eighth-grade student data but no eighth-grade parent data. 

Imputation of eighth-grade parent data were performed for these cases by predicting an eighth-grade 

College Orientation Index value for all 3,389 cases, based on their seventh-grade records and eighth-grade 

student questionnaires.46 Table B-14 contains a list of variables and beta coefficients that were used in the 

model to produce these predicted College Orientation Index values. This model’s R2

 is 0.92, revealing 

that it is an extremely strong predictor of College Orientation Index values. 

Each case in sections 8T and 8ST was then matched with the case with a parent and student survey 

(section 8TP) or a case with data from all three sources (section STP) that had the closest predicted 

College Orientation Index value and that was in the same GEAR UP group. Then, eighth-grade parent 

data were copied from the donor to the recipient. 

Cluster Analysis Imputation for Cases with Missing Eighth-grade Student Records Data. The 503 

students in sections 8T, 8TP and 8P in figure B-2 had missing eighth-grade student records data that 

needed to be imputed. As with the seventh-grade student records data, five student records variables were 

predicted. These predictions were made from the seventh-grade records and responses from both the 

eighth-grade student and parent questionnaires. The data used to create these models were taken only 

from those students with complete eighth-grade records (i.e., those in section STP in figure B-2). The five 

eighth-grade student records variables to be predicted were the same as were used for the seventh-grade 

model: HONORS, TOTABSNC, UNEXABSN, TOTDISP, and AWARDS. Tables B-15 through B-19 

provide the variables and coefficients that made up each of the five models. 

After the models were formed, predicted values for each of the five eighth-grade student records variables 

discussed above were predicted for each of the 2,507 students in sections 8STP, 8T, 8TP and 8P of figure 

B-2. A clustering algorithm was then used to group each student into one of five natural clusters. Within 

each cluster, students were homogeneous with respect to the five eighth-grade student records variables, 

but heterogeneous across the other four groups, with respect to those five variables. Table B-20 provides 

information on each of the five clusters. 

 

46 Student records data were ignored as probably contributing little to predicting parent variables beyond the students’ own 

reports. 
B-15 

Table B-13. Variables and beta coefficients used in the model to predict College Orientation 

Index values for the imputation of student data to cases in section 8SP 

Model Term Estimate Standard error tValue Probt 

Intercept -90.38 6.60 -13.7 <.001 

AWARDS8 2.92 1.33 2.2 0.028 

ChurchFreq_7 8.11 1.92 4.2 <.001 

CollegeBound_7 155.75 10.73 14.5 <.001 

EventBacktoSchool_7 -4.15 1.33 -3.1 0.002 

ExpectPSERev_7 19.65 6.46 3.0 0.002 

FriendFreq_7 -5.81 2.05 -2.8 0.005 

FriendOpImport_7 7.60 2.99 2.5 0.011 

HHIncome_8 7.07 2.03 3.5 0.001 

ProfAspiration_7 3.18 1.35 2.4 0.019 

SiblingEd_8 7.56 2.95 2.6 0.010 

Volunteerism_8 4.26 1.48 2.9 0.004 

Performance_8 141.52 7.27 19.5 <.001 

pexpect_8 72.39 4.62 15.7 <.001 

GENDER -5.04 1.32 -3.8 0.000 

ParentAttends_7 6.66 1.76 3.8 0.000 

TOTABS8 -26.91 7.40 -3.6 0.000 

Performance_7 -29.88 5.73 -5.2 <.001 

pexpect_7 -31.62 4.42 -7.2 <.001 

ParGrades_8*ultdegree_8 27.77 3.28 8.5 <.001 

As with the seventh-grade cluster analysis, these five clusters seem to describe familiar groups of 

students. Students with missing eighth-grade student records data were then randomly matched to 

students with complete eighth-grade student records data in the same cluster. Whole eighth-grade student 

records were then copied from donors to recipients. 

Nonresponse Adjustment for Eighth-grade Data. For the seventh-grade imputation, a student 

questionnaire was necessary for the analysis; if a student had not completed a seventh-grade student 

questionnaire, he or she was considered a nonrespondent. Because of the permission issues discussed 

earlier, there were a number of completed eighth-grade parent interviews or eighth-grade student records 

data forms without a corresponding eighth-grade student questionnaire. (Figure B-2 provides exact counts 

of the number of cases with different combinations of data.) As noted earlier, because of this situation, the 

rule determining a nonrespondent was changed for eighth-grade data. A student was considered a 

respondent for the eighth-grade portion of the analysis if he or she had a completed seventh-grade student 

questionnaire and had either a completed eighth-grade student questionnaire or a completed eighth-grade 

parent interview. 

Students without a completed seventh-grade student questionnaire had already been weighted as 

nonrespondents during the seventh-grade procedure. By definition, only those students with seventhgrade student questionnaires were allowed into the eighth-grade analysis. Among those in the eighthgrade analysis, students with neither a completed eighth-grade student questionnaire nor a completed 

eighth-grade parent interview were given a weight of zero and counted as nonrespondents. These 83 

 
 B-16 

Table B-14. Variables and beta coefficients used in the model to predict College Orientation 

Index values for the imputation of parent data to cases in sections 8T and 8ST 

Model Term Estimate Standard error tValue Probt 

Intercept -73.21 3.01 -24.3 <.001 

Academic_8 87.06 2.25 38.7 <.001 

AdultHangFreq_8 -2.00 0.64 -3.2 0.002 

Adultmentor_7 -1.06 0.43 -2.5 0.013 

DontNeedHelp_8 -1.30 0.55 -2.4 0.018 

ExpectPSERev_8 101.44 3.53 28.7 <.001 

ExpectPSE_8 9.21 2.75 3.4 0.001 

Grades_8 6.46 1.24 5.2 <.001 

HONORS7 1.61 0.54 3.0 0.003 

ImpWork_8 -5.17 1.56 -3.3 0.001 

LeagueSports_8 -0.85 0.43 -2.0 0.046 

ParentEd_7 3.31 0.97 3.4 0.001 

ReadingHours_8 16.21 0.85 19.1 <.001 

RevParDKCount_7 6.59 2.34 2.8 0.005 

StdParTalk_7 2.32 0.89 2.6 0.010 

StdParTalk_8 15.67 0.91 17.2 <.001 

TeacherHelp_7 1.59 0.52 3.1 0.002 

pexpect_7 12.66 1.20 10.6 <.001 

raceeth_7 1 2.07 0.85 2.4 0.015 

raceeth_7 2 2.44 0.93 2.6 0.009 

raceeth_7 3 3.21 0.93 3.5 0.001 

raceeth_7 4 1.08 1.72 0.6 0.530 

raceeth_7 5 0.00 . . . 

FirstLanguage_8 -1.16 0.60 -1.9 0.053 

HowHard_7 -2.85 1.07 -2.7 0.008 

ImpGoCollege_7 2.86 1.14 2.5 0.012 

SciTutother_8 -2.50 0.56 -4.4 <.001 

hmwkundr_7 -5.86 1.71 -3.4 0.001 

Performance_7 23.90 2.12 11.3 <.001 

students, whose only eighth-grade source of information was student records data, are in the section 8S of 

figure B-2. 

In addition to those from section 8S of figure B-2, the NRA had to adjust for 200 cases with seventhgrade student survey data and no data from any of the three eighth-grade data sources. There were 

indications that these students had not left the sample by transferring to another school. Nevertheless, 

there were no eighth-grade data about them. 

Eliminating these two groups of students from the sample reduced the sample size from 3,389 to 3,106. 

As with the seventh-grade data, an NRA needed to be performed to minimize the effect of weighting 283 

cases as nonrespondents. The NRA process would reweight the remaining 3,106 cases so that their 

combined weight would match the weight of the original 3,389. 
B-17 

Table B-15. Model for HONORS_8 

Model Term Estimate Standard error ChiSq ProbChiSq 

Intercept -5.23 0.67 61.7 <.0001 

AttendClforColl_7 0.35 0.15 5.7 0.017 

CollegeBound_7 3.53 0.90 15.5 <.0001 

CollegeMoreMoney_8 1.14 0.38 9.0 0.0027 

GrParentGoCollege_7 -0.44 0.16 7.4 0.0065 

HONORS7 2.19 0.15 205.1 <.0001 

HeardVocEd_7 0.37 0.14 7.0 0.0084 

INSCSUSP7 -3.12 1.44 4.7 0.0306 

ImpWork_7 -1.82 0.51 12.9 0.0003 

MathTutother_7 -0.37 0.18 4.5 0.0345 

OtherHelp_7 -0.42 0.16 7.3 0.0069 

ParGrades_7 1.41 0.43 10.6 0.0011 

ParRptHmwkHelp_7 -0.63 0.26 5.7 0.0169 

ParentAttends_8 -0.52 0.20 6.7 0.0099 

SiblingHelp_8 0.30 0.14 4.8 0.0289 

SkipClasses_8 -1.03 0.38 7.3 0.007 

SoloSport_7 -0.40 0.18 4.7 0.0305 

VisitCollCamp_7 0.51 0.15 11.5 0.0007 

Yearbook_8 0.43 0.20 4.5 0.0336 

conferFreq_7 0.78 0.26 9.2 0.0025 

knowcollcampus_7 0.53 0.17 9.4 0.0022 

ultdegree_8 0.62 0.25 6.3 0.012 

AttendPlays_8 -0.75 0.18 18.0 <.0001 

Grades_7 1.54 0.43 12.8 0.0003 

To create the NRA weights, a logistic regression predicted the probability of nonresponse for each case in 

the original group of 3,389. Then, each of the 3,389 cases was placed into one of five groups of cases with 

similar predicted probabilities for nonresponse. Table B-21 provides the beta coefficients for the logistic 

regression model used to predict each case’s probability of nonresponse. Note that only seventh-grade 

variables were allowed into the model but that all three sources of seventh-grade data were used. 

Within each of the five groups, nonrespondents’ weights were proportionally allocated to the respondents. 

After this weight transfer, nonrespondents were given a weight of zero. The equation to determine the 

transfer of weights is the same as was used for the seventh-grade nonresponse adjustment and is located 

on page B-11. The weights for GEAR UP and non-GEAR UP students were separately adjusted. 
 B-18 

Table B-16. Model for TOTABSNC_8 

Model Term Estimate Standard error tValue Probt 

Intercept 1.592 0.069 22.9 <.0001 

AttendPlays_7 0.086 0.024 3.6 0.0004 

EXABSNC7 0.775 0.224 3.5 0.0005 

Firstlanguage_7 0.067 0.030 2.2 0.025 

FriendOpImport_7 -0.139 0.046 -3.0 0.0024 

HeardVocEd_7 0.050 0.020 2.5 0.0131 

Mobility_7 0.098 0.028 3.4 0.0006 

NumAdult_7 -0.114 0.024 -4.7 <.0001 

ParRptHmwkHour_7 -0.103 0.045 -2.3 0.0219 

Truancy_7 0.205 0.035 5.8 <.0001 

raceeth_7 1 0.032 0.040 0.8 0.4297 

raceeth_7 2 -0.152 0.044 -3.5 0.0005 

raceeth_7 3 -0.141 0.043 -3.2 0.0012 

raceeth_7 4 -0.116 0.082 -1.4 0.1596 

raceeth_7 5 0.000 . . . 

ChurchFreq_7 -0.118 0.029 -4.0 <.0001 

INSCSUSP7 0.544 0.154 3.5 0.0004 

OUTSSUSP7 0.497 0.136 3.7 0.0003 

TOTABSNC7 3.393 0.189 18.0 <.0001 

GENDER*TOTABSNC7 -0.661 0.171 -3.9 0.0001 

Table B-17. Model for UNEXABSN_8 

Model Term Estimate Standard error tValue Probt 

Intercept -0.856 0.039 -21.89 <.0001 

AttendPlays_7 0.047 0.014 3.4 0.0007 

Band_7 -0.025 0.012 -2.12 0.0344 

Firstlanguage_7 0.032 0.017 1.91 0.0569 

ProfAspiration_7 -0.028 0.012 -2.36 0.0184 

TOTABSNC7 0.375 0.079 4.73 <.0001 

UNEXABSN7 0.878 0.090 9.75 <.0001 

raceeth_7 1 0.058 0.023 2.51 0.0121 

raceeth_7 2 0.107 0.025 4.23 <.0001 

raceeth_7 3 -0.033 0.025 -1.31 0.1902 

raceeth_7 4 0.052 0.047 1.1 0.2728 

raceeth_7 5 0.000 . . . 

CollegeBoundRev_7 -0.293 0.044 6.66 <.0001 

INSCSUSP7 0.152 0.083 -1.82 0.0691 
B-19 

Table B-18. Model for TOTDISP_8 

Model Term Estimate Standard error tValue Probt 

Intercept -0.82 0.16 -5.23 <.0001 

AbsentDays_7 0.16 0.08 2.1 0.0356 

CollegeBoundRev_7 -1.65 0.21 -8 <.0001 

ConferBehave_7 0.35 0.07 4.96 <.0001 

HowFarSchool_7 0.35 0.10 3.63 0.0003 

NegVideoHours_7 -0.23 0.08 -2.9 0.0038 

TOTDISP7 1.43 0.50 2.83 0.0047 

raceeth_7 1 -0.29 0.09 -3.23 0.0013 

raceeth_7 2 -0.01 0.10 -0.09 0.9271 

raceeth_7 3 -0.23 0.09 -2.44 0.0146 

raceeth_7 4 -0.10 0.18 -0.56 0.5723 

raceeth_7 5 0.00 . . . 

INSCSUSP7 2.90 0.53 5.47 <.0001 

OUTSSUSP7 2.27 0.36 6.38 <.0001 

ParRptHmwkHour_7 -0.52 0.10 -5.04 <.0001 

TRUANCY7 3.36 0.42 7.99 <.0001 

INSCSUSP7*OUTSSUSP7 -6.41 1.09 -5.9 <.0001 

Table B-19. Model for AWARDS_8 

Model Term Estimate Standard error ChiSq ProbChiSq 

Intercept -2.29 0.29 61.57 <.001 

AdvisClassNeed_8 -0.46 0.10 21.81 <.001 

ParPrep_8 1.05 0.18 32.76 <.001 

ExpectPSERev_7 1.08 0.38 8.12 0.004 

ParGrades_8 1.45 0.25 35.01 <.001 

TOTDISP7 -4.75 1.00 22.7 <.001 

AWARDS7*ExpectPSERev_7 1.57 0.19 71.13 <.001 

AWARDS7*TeamSport_8 -0.69 0.16 19.47 <.001 

Table B-20. Size and predicted eighth-grade student records values for each of the five natural 

clusters used for eighth-grade student records imputation 

Predicted values for selected eighth-grade student record variables 

Cluster 

Number 

of 

students 

Percent 

of total HONORS TOTABSNC UNEXABSN TOTDISP AWARDS 

1 243 9.7% -0.584 1.716 1.372 -0.013 -0.516 

2 604 24.1% 0.134 -0.192 -0.527 -0.547 1.020 

3 936 37.3% -0.560 -0.271 -0.007 0.004 -0.495 

4 474 18.9% 1.593 -0.574 -0.750 -0.548 0.496 

5 250 10.0% -0.678 0.899 1.389 2.361 -1.050 
 B-20 

Table B-21. Beta coefficients used to determine a student’s propensity for nonresponse 

Parameter Estimate Standard error 

Wald chisquare Pr > ChiSq 

Intercept 0.27 0.38 0.5 0.5 

Drama_7 0.50 0.23 4.6 0.0 

Grades_7 0.71 0.25 7.8 0.0 

LeagueSports_7 0.34 0.14 5.7 0.0 

ParTalkPolitics_7 -0.46 0.18 6.4 0.0 

TOTDISP7 -1.68 0.59 8.1 0.0 

Volunteerism_7 -0.41 0.16 6.2 0.0 

knowcollcampus_7 0.72 0.25 8.6 0.0 

raceeth_7 (level 1) -0.55 0.31 3.2 0.1 

raceeth_7 (level 2) -0.41 0.31 1.7 0.2 

raceeth_7 (level 3) 0.31 0.33 0.9 0.3 

raceeth_7 (level 4) 0.10 0.56 0.0 0.9 

raceeth_7 (level 5) 0 0 . . 

Band_7 0.58 0.15 14.6 0.0 

ConferBehave_7 -0.76 0.18 18.6 <.01 

ConferProgress_7 1.37 0.22 39.3 <.01 

EnglishHomework_7 1.56 0.46 11.4 0.0 

FriendFreq_7 0.65 0.19 11.9 0.0 

Mobility_7 2.42 0.41 35.0 <.01 

TeacherHelp_7 0.51 0.14 12.9 0.0 

ConferProgress_7*Mobility_7 -1.31 0.37 12.8 0.0 

LUNCH7*Mobility_7 -1.39 0.36 14.8 0.0 

Nonresponse Adjustment for Missing Transcript Data. It was decided that transcript data would not be 

imputed for those students with missing transcript data. Instead, those with missing transcript data would 

be labeled as nonrespondents for transcript analysis47 and given a transcript weight of zero. As when 

students with missing seventh-grade student survey and eighth-grade student survey and parent data were 

weighted as nonrespondents, a nonresponse adjustment was necessary to minimize the effect of those 

nonrespondents. 

The transcript NRA process created weights that, when applied to the remaining respondents, reduced the 

impact of weighing the nonrespondents as zero. To create these NRA weights, the probability of being a 

transcript nonrespondent was predicted for all of the students. That probability of nonresponse was 

estimated with a logistic regression and was based on seventh- and eighth-grade data. Table B-22 

provides a list of the variables used in the model to predict a student’s probability of transcript 

nonresponse. Note that many of the variables were student records variables. The reasons for transcript 

nonresponse among nontransfer students are unclear but probably have to do with school decisions rather 

than student or parent decisions. 

 

47 These students were used in all analyses except the transcript analyses. 
B-21 

Table B-22. Variables and beta coefficients used to predict a student’s probability of transcript 

nonresponse 

Model Term Estimate Standard error ChiSq ProbChiSq 

Intercept 2.79 0.34 68.7 <.0001 

AttendMeetCollPrep_7*LUNCH8 0.71 0.20 12.9 0.0003 

Confer_events_7*HeardCommColl_7 1.69 0.45 14.2 0.0002 

DadHelp_7*LUNCH8 -0.67 0.15 19.7 <.0001 

DontNeedHelp_7*tschool 0.96 0.19 26.6 <.0001 

ESLBIL8*LEP7 2.60 0.71 13.5 0.0002 

EventPTA_7*HeardCommColl_7 -0.94 0.20 21.4 <.0001 

LEP7*OUTSSUSP7 -12.35 3.80 10.6 0.0012 

LEP7*TOTABSNC7 9.26 2.72 11.6 0.0007 

LEP7*TRUANCY7 -3.15 1.59 3.9 0.0482 

LEP7*computerathome_7 -0.91 0.29 10.2 0.0014 

LUNCH7*LUNCH8 1.74 0.17 102.2 <.0001 

LUNCH7*computerathome_7 0.74 0.19 15.2 <.0001 

LUNCH8*TRUANCY7 -3.28 1.17 7.9 0.0051 

LUNCH8*computerathome_7 -0.82 0.17 22.9 <.0001 

ParentEd_7*tschool 1.05 0.27 15.2 <.0001 

computerathome_7*tschool 0.64 0.18 12.6 0.0004 

ClubLeader_7 0.31 0.16 3.9 0.0497 

ConferBehave_7 -0.50 0.14 11.9 0.0006 

EdFor30_7 0.54 0.23 5.6 0.0182 

HeardCommColl_7 -0.43 0.15 7.8 0.0052 

LUNCH7 -1.01 0.19 29.3 <.0001 

LibraryUsage_7 -0.75 0.24 9.7 0.0018 

MathClub_7 -0.40 0.11 13.5 0.0002 

OUTSSUSP7 2.47 0.80 9.6 0.0019 

OtherHomework_7 0.73 0.20 13.0 0.0003 

TalkCollege_7 -0.34 0.14 6.1 0.0134 

tschool -2.68 0.23 141.5 <.0001 

Once the probability of being a transcript nonrespondent was estimated for each student, the students 

were partitioned into one of five groups, based on that probability. Within each of the five groups, the 

weights of the nonrespondents were transferred, proportionally allocated, to the respondents, so that the 

sum of the adjusted weights for the respondents was equal to the sum of the pre-adjusted weights for the 

nonrespondents and respondents combined. At this point, the nonrespondents were given a weight of 

zero. The equation on page B-11 that governed the transfer of weights for seventh-grade student survey 

nonresponse was also applied to these transcript nonrespondents. As with the nonresponse adjustment for 

missing eighth-grade data, weights were adjusted for these data separately for GEAR UP and non-GEAR 

UP students. 
 B-22 

B.4 Variance Estimation 

Variances were estimated using a new resampling method. For a general discussion of resampling 

variance estimation, see appendix A of the WesVar 4.0 manual48 or Wolter.49 A new method was 

developed for the GEAR UP evaluation because of the small number of matched pairs of GEAR UP and 

non-GEAR UP schools. The original design had 20 pairs, but only 36 schools cooperated at baseline, 

including 17 matched pairs, leaving one GEAR UP and one non-GEAR UP unmatched among 

cooperating schools. These two unmatched schools were paired for purposes of variance estimation, 

leading to 18 pairs. The new method was designed to maximize the stability of the variance estimates 

given these conditions. 

The procedure involved creating 18 replicate weights for every student. On a given replicate, a pair of 

schools was given a reduced weight, while the remaining 17 pairs got an increased weight. The formula is 

1 if for 1,...18, and 1,...,18 2

35 otherwise

34

rijk

ri r i

W

⎧ == = ⎪⎪ = ⎨

⎪

⎪⎩

where r indexes the replicate weights, i indexes the pairs, j indexes the schools within a pair, and k

indexes the students within a school. 

All the adjustments for nonresponse and GEAR UP propensity described in other sections of this 

appendix and in appendix E were also applied to the replicate weights. This was done by replicating the 

adjustment factors and then applying the replicated adjustment factors to the replicate weights. For 

example, in the adjustment for student nonresponse in the seventh-grade, the r-th replicated nonresponse 

adjustment factor for students in a nonresponse adjustment cell c was 

rijk

ijk c

rc ijk rijk

ijk c

w

f δ w

∈

∈

=

∑

∑ , 

where 1 if the student is a respondent and 

0 otherwise ijk δ ⎧ = ⎨

⎩

The r-th replicated nonresponse adjusted weight was then 

 where W f W ijk c rijk ijk rc rijk = ∈ δ . 

 

48 Westat. WesVar 4.0 User’s Guide. Rockville, Md: Westat, 2000. 

49 K.M. Wolter. Introduction to Variance Estimation. New York: Springer-Verlag, 1985. 
B-23 

The set of replicate weights appropriate for a certain analysis was used to estimate the variance on a 

statistic t using the following formula: 

( )

18 2

1

17 ˆ() 418 r

r

v t t t

=

= ∑ − , 

where rt is the value of the statistic obtained when the r-th set of replicate weights is used in forming the 

statistic. 

This section closes with some discussion of this variance estimator and two theorems that relate it to 

better known variance estimators. 

Theorem One. For linear statistics restricted to either GEAR UP or non-GEAR UP schools, v t ˆ( ) is 

identical to the standard variance estimator for a two-stage sample where the first stage is a simple 

random sample with replacement. For variance estimation, this is equivalent to a single stage simple 

random sample with replacement as discussed in section 3 of chapter 6 of volume 2 of Hansen, Hurwitz 

and Madow, 1953.50 

Proof: 

Let 

18

1

ijk ijk

i k

t y α

=

= ∑∑ be some linear function of the questionnaire data on sample students in either the 

GEAR UP (j=1) or non-GEAR UP schools (j=2), where ijk y is some numeric measurement on the 

student and αijk is some constant that depends only on the sample design such as 1/18 (average school 

total) or 1/n (average student response). 

The replicated version of this statistic is 

18

1

18 1 35

2 34

r rijk ijk ijk

i k

ijk rjk ijk ijk

k i rk

t wy

y y

α

α α

=

≠

=

= +

∑∑

∑ ∑∑

 

50 M.H. Hansen, W.N. Hurwitz, and W.G. Madow. Sample Survey Methods and Theory. New York: John Wiley and Sons, 1953. 
 B-24 

and so the estimated variance is 

( ) 18 2

1

2 18 18 18

1 1

2 18 18

1

2 18 18

1

17 ˆ() 418

17 1 35 4

18 2 34

17 1 1 4

18 2 34

17 1

18 17

17

18

r

r

ijk rjk ijk ijk ijk ijk

r k ir k i k

ijk rjk ijk ijk

r k ir k

ijk rjk ijk ijk

r k ir k

i

v t t t

y yy

y y

y y

α αα

α α

α α

α

=

=≠=

= ≠

= ≠

= −

⎛ ⎞

= +− ⎜ ⎟ ⎝ ⎠

⎛ ⎞

=− + ⎜ ⎟ ⎝ ⎠

⎛ ⎞

=− + ⎜ ⎟ ⎝ ⎠

= −

∑

∑ ∑ ∑∑ ∑∑

∑ ∑ ∑∑

∑ ∑ ∑∑

2 18 18

1 1

2 18 18

1 1

2 18 18

1 1

1 1

17 17

17 18 18 1

18 17 17 18

18 1

17 18

jk rjk ijk ijk ijk rjk

r k ik k

ijk rjk ijk ijk

r k ik

ijk rjk ijk ijk

r k ik

y yy

y y

y y

α α

α α

α α

= =

= =

= =

⎛ ⎞

+ − ⎜ ⎟ ⎝ ⎠

⎛ ⎞

=− + ⎜ ⎟ ⎝ ⎠

⎛ ⎞ = − ⎜ ⎟ ⎝ ⎠

∑ ∑ ∑∑ ∑

∑ ∑ ∑∑

∑ ∑ ∑∑ (1) 

Note that for αijk =1/18, this simplifies to the standard formula for the variance estimator for a mean 

across schools: 

( )( )

2 18 18

1 1

1 1 ˆ( )

18 17 18 rjk ijk

r k ik

vt y y

= =

⎛ ⎞ = − ⎜ ⎟

⎝ ⎠ ∑ ∑ ∑∑

Theorem Two. For linear statistics comparing GEAR UP or non-GEAR UP schools, v t ˆ( ) is identical to 

the standard variance estimator on a simple random sample with replacement of the difference between 

two variables. 

Proof: 

Let 

18 18

11 2 2

1 1

i ik i i k

ik i k

ty y α α

= =

= − ∑∑ ∑∑ be some linear function of differences between GEAR UP and nonGEAR UP schools. Let i i ik i i k 11 2 2

k k

zy y = − α α ∑ ∑ . Using the same arguments as in the proof of 

Theorem one, we have that 

2 18 18

1 1

18 1 ˆ( ) 17 18 r i

r i

vt z z

= =

⎛ ⎞ = − ⎜ ⎟

⎝ ⎠ ∑ ∑ (2) 

Although the original pairing was not directly used in the primary inferential procedures about the 

outcomes for GEAR UP (see appendix E), the pairing was part of the variance estimation for some 

estimated GEAR UP associations. More specifically, it was used in estimating variances for the estimated 
B-25 

adjusted differences that were prepared using counterfactional projection (CFP) weights. The pairing was 

not used, however, in the variances for the estimates produced by hierarchical linear modeling (HLM). 

Use of the pairing in the variances for estimates based on CFP weights most likely decreased the 

estimated variances relative to what would have been obtained had the original pairing been ignored. This 

was an appropriate reduction because the original pairing was effective in reducing preexisting 

differences between GEAR UP and non-GEAR UP students. 

For estimates based on HLM, the variances estimated by SAS were accepted. 
 B-26 
C-1 

Appendix C 

Index Construction 

The goal of the U.S. Department of Education’s Gaining Early Awareness and Readiness for 

Undergraduate Programs (GEAR UP) program is to significantly increase the number of low-income 

students who seek to enter and succeed in postsecondary education. The National Evaluation of GEAR 

UP seeks to assess the impact that GEAR UP has on postsecondary education preparation for students 

who receive program services. Figure C-1 is a representation of the conceptual framework for GEAR UP 

driving the analysis. Within a context of targeted students, families, schools and communities (Column 

no. 1), GEAR UP projects provide an array of services (Column no. 2). These treatments are expected to 

be derived from research-based best practices. The treatments are intended to result in interim outcomes 

(Column no. 3) that are logically associated with the desired longer term outcomes of the program 

(Column no. 4). The current analysis can only assess the interim outcomes because of the period of 

performance for this evaluation. 

Based on the conceptual framework, we looked for effects among the following groups of potential 

interim outcome variables:51

 Parents’ expectations for their children, 

 Parents’ knowledge about postsecondary education, 

 Parents’ involvement in their children’s education, 

 Students’ expectations about postsecondary education, 

 Students’ knowledge about postsecondary education, 

 Students’ course-taking behavior, 

 Students’ academic achievement, and 

 Students’ attitudes and activities. 

To sharpen hypotheses before examining the data, outcome indexes were formed. Outcome indexes are 

typically done to avoid statistical problems associated with running multiple tests on the same concepts. 

Indexes also increase the statistical power and the ability to discern broad but subtle effects on complex 

concepts or constructs. A disadvantage to using indexes is that the index values themselves have no 

intrinsic meaning because they combine multiple questions. 

 

51 The scope of this analysis does not encompass all of the interim outcome measures displayed in figure C-1. The contents of 

boxes 3a. and 3b. are evaluated, while the contents of boxes 3c. and 3d. are only described. 
 C-2 

Figure C-1. Conceptual framework of the impact of GEAR UP 

1. CONTEXT 2. SERVICES 3. INTERIM 4. LONG-TERM 

 OUTCOMES OUTCOMES 

Source: Westat analysis of HEA 1988 Amendments, 2007. 

1a. Local 

Characteristics 

 Students 

 Families 

 Schools 

 Communities 

1b. Policy Inputs 

 Local 

 State 

 Federal 

2. Projects 

 Academic assistance 

 Mentoring 

 Information on 

postsecondary education 

options 

 Information on student aid 

 Counseling 

 Programs for families 

 Curriculum development 

 Professional development 

 Financial aid incentives 

3a. Families 

 Expectations 

 Knowledge 

 Involvement 

3b. Students 

 Expectations 

 Knowledge 

 Challenging 

courses 

 Attendance, 

grades, on-time 

promotions 

3c. Schools 

 Challenging 

curricula 

 Teacher and staff 

expectations, 

knowledge and 

involvement 

3d. Partners 

 Collaboration 

 Communication 

 Comprehensive 

services 

4. Students 

 Increased 

postsecondary 

education 

enrollment 

 Increased 

postsecondary 

education 

success
C-3 

We built one or more composite indexes for each group based on items from the student and parent 

surveys. We also built composite indexes across the groups, including an overarching index called the 

College Orientation Index, meant to encompass all of the analytic domains. We built these indexes for 

two primary reasons. The first was to sharpen hypotheses, as in clinical trials research, and thereby reduce 

multiple-comparison problems. If a large group of items is analyzed without any grouping, it is well 

known that many false positive results will emerge, which then lead to a more inductive research style in 

which the analyst tries to distinguish patterns in the results. We wanted a more deductive approach where 

we would formulate a very sharp hypothesis and give a high profile to test results for it. The second 

reason for forming the indexes was to increase the power to detect effects along the expected lines. 

Because the indexes are more difficult to interpret than individual questionnaire items, we also analyzed 

the items separately, but we used greater caution in interpreting individual items if the index covering the 

item was not significant. 

The process for building the interim outcome indexes involved intuition, analysis of correlation structure, 

group discussion and outside review by experts on the Technical Working Group. All of this work was 

done using seventh-grade data before examining any eighth-grade data. No strict psychometric test was 

used to establish the reliability of each index. Instead, correlation matrices and Cronbach alpha 

coefficients were calculated for groups of items that were intended to measure the same analytic domain. 

Items that correlated poorly with others were sometimes dropped from the intended index and then either 

shifted to another index or dropped as an interim outcome altogether. Sometimes items that were not 

intended to measure the same analytic domain turned out to be very highly correlated with each other and 

were subsequently grouped together in the same index. Some groups had Cronbach alpha coefficients 

below the range (0.7 to 0.8) that is sometimes considered ideal in batteries of psychometric test items. 

This criterion range, while useful in guiding the design of tests and questionnaires, should not be seen as 

an absolute requirement for useful grouping of items. Even if the items in a group do measure slightly 

different latent variables or factors, the grouping still serves the dual purposes of reducing problems with 

multiple comparisons and increasing statistical power to find effects. On the other hand, it is true that 

those indexes with low Cronbach alpha coefficients are more difficult to interpret. 

For the most part, once items had been grouped together, the index for the group was constructed by 

standardizing each variable (to have mean zero and standard deviation one) and then simply summing the 

standardized variables together. However, in some cases it was necessary to first recode the response 

categories. Because not all questions were originally coded in the same direction, some were recoded to 

make response values align with desired outcomes. For example, Student Question 3 “How important do 

you think it is to work hard in school?” has four possible responses, ranging from “very important” 

(originally coded as “1”) to “not important at all” (originally coded as “4”). When entered into the index, 

this code order was reversed, so that “very important” would be “4” and “not important at all” would be a 

“1.” With such reordering of codes, all responses in the College Orientation Index that indicate a higher 

likelihood of attending college have higher code values than those responses that suggest that future 

college attendance is less likely. 

In addition, answers of “don’t know” were usually treated as missing values and imputed, but they were 

sometimes treated as informative and placed in the scale based on group intuition. Details are provided 

below on each variable. 
 C-4 

C.1 Creation of College Orientation Index 

A summative interim outcome measure of the National Evaluation of GEAR UP is the College 

Orientation Index. This index comprises data from the evaluation’s student and parent surveys. As 

discussed above, it was created using only seventh-grade, self-reported questionnaire data thought to be 

predictive of future enrollment in postsecondary education. The index was developed before examining 

eighth-grade data as a single indicator of the impact of GEAR UP. The index was partially validated using 

another data set as documented in appendix D. 

The College Orientation Index does not include all of the information collected during the evaluation. 

Only eighth-grade transcript information was processed. As a result, the index excludes information such 

as course enrollment, GPA and performance on standardized test scores because there was no way to 

empirically correlate pre-intervention transcript information with other elements of the index and 

therefore no method to combine transcript information with questionnaire information. Analyses of the 

transcript data are, therefore, presented separately. 

A reason the College Orientation Index should not be viewed as the single criterion for the success of 

GEAR UP is that the relative weighting of its different components was arbitrary. It could be that some 

components have higher predictive power than others and would, therefore, require weighting more 

heavily in a single criterion index than others, but this was impossible to determine with the available 

data. Thus, while importance was attached to the estimated impact of GEAR UP on the College 

Orientation Index, it was not treated as the sole indicator of program success or failure. 

The College Orientation Index is a collection of the following six subindexes: 

 Academic measures the student’s view of his or her current performance in school, 

 Performance measures the parent’s view of the student’s performance, 

 ExpectPSE measures the student’s postsecondary aspirations, 

 Pexpect measures the parent’s postsecondary aspirations for the child, 

 StdParTalk measures the student’s report of parent-child discussions, and 

 ReadingHours measures how much time the student spent reading for pleasure. 

Twenty-two variables make up the six College Orientation subindexes, and the resulting Cronbach alpha 

is 0.80. The variables that make up these subindexes were standardized so that they had a mean of 0 and a 

standard deviation of 1. Standardizing the inputs of the College Orientation Index ensured that the 

resulting index would have an easily understood range. 

Below is a description of each of the six subindexes that make up the College Orientation Index and an 

explanation of how the variables that make up the subindexes were altered. All variables were 

standardized before building the index. Cases with partial data were excluded from the correlation 

analysis used to decide how to group the items and how to standardize the variables, but they were 

subsequently included in the analysis by means of imputing missing items. 
C-5 

 Academic Subindex 

This subindex consists of questions from the student survey and measures the student’s view of his or her 

current performance in school (see exhibit C-1). The Cronbach alpha is 0.57 and consists of responses to 

questions on the following topics: 

 How hard the student works in school, 

 How good a student he or she is, 

 How important he or she thinks it is to work hard, 

 What kind of grades the student gets, 

 How often he or she is absent, and 

 How often he or she skips class. 

Exhibit C-1. Example of Academic subindex 

Student Question 1: 

Compared with other students, how hard do you think you work in school?

(Response options) (Survey code) (Index code) 

 Much harder 

 Harder 

 About the same 

 Not as hard 

 Much less hard 

1 

2 

3 

4 

5 

5 

4 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. 

Student Question 2: 

How good a student do you think you are?

(Response options) (Survey code) (Index code) 

 Excellent 

 Good 

 Fair 

 Poor 

1 

2 

3 

4 

4 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. 
 C-6 

Exhibit C-1. Example of Academic subindex (continued) 

Student Question 3: 

How important do you think it is to work hard in school?

(Response options) (Survey code) (Index code) 

 Very Important 

 Important 

 Not too important 

 Not important at all 

1 

2 

3 

4 

4 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. 

Student Question 17: 

Thinking about the last school year, how would you describe your grades?

(Response options) (Survey code) (Index code) 

 Mostly As 

 As and Bs 

 Mostly Bs 

 Bs and Cs 

 Mostly Cs 

 Cs and Ds 

 Mostly Ds or below 

1 

2 

3 

4 

5 

6 

7 

7 

6 

5 

4 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. 

Student Question 31: 

During the past month, how many days were you absent from school?

(Response options) (Survey code) (Index code) 

 None 

 1 or 2 

 3 or 4 

 5 or more 

 Don’t remember 

1 

2 

3 

4 

5 

5 

4 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. 
C-7 

Exhibit C-1. Example of Academic subindex (continued) 

Student Question 33: 

During the past month, how many classes did you skip or cut?

(Response options) (Survey code) (Index code) 

 None 

 1 or 2 

 3 or 4 

 5 or more 

1 

2 

3 

4 

4 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. 

 Performance Subindex 

This subindex consists of parent interview questions that measure the parent’s view of the student’s 

performance (see Exhibit C-2). The alpha is 0.71 and is highly correlated with the Academic subindex. It 

is made up of responses to questions on the following: 

 Student’s understanding of homework, 

 Grades, and 

 Student’s view of the importance of hard work. 

Exhibit C-2. Example of Performance subindex 

Parent Question 6: 

Does (he/she) seem to understand (his/her) homework?

(Response options) (Survey code) (Index code) 

 Always 

 Sometimes 

 Rarely 

 Never 

1 

2 

3 

4 

3 

2 

1 

0 

The code values for this variable were reversed so more desirable responses have 

higher values. 
 C-8 

Exhibit C-2. Example of Performance subindex (continued) 

Parent Questions 16 and 17: 

Overall, what type of student is [child]? (Question 16) 

(Response options) (Survey code) (Index code) 

 Excellent 

 Good 

 Fair 

 Poor 

1 

2 

3 

4 

3 

2 

1 

0 

Since the beginning of the school year, do you think [child] has done excellent, good, 

fair, or poor in the following areas? (Question 17) 

(Response categories) 

 English 

 Science 

 Math 

 History or Social Studies 

 All other subjects 

 

Overall, what type of student is [child]? (Question 16) 

(Response options) (Survey code) (Index code) 

 Excellent 

 Good 

 Fair 

 Poor 

1 

2 

3 

4 

3 

2 

1 

0 

The code value for Parent Question 16 and the five values for Parent Question 17 

were first reversed so more desirable responses have higher values. Then, they were 

averaged, to provide a parent’s overall assessment of his or her child’s academic 

performance. The value of this question only entered the index if the student’s parent 

indicated that the child had homework and provided a response to questions about 

where the child does homework and whether the child understands that homework. 

Parent Question 20: 

How important does [child] think it is to work hard in school?

(Response options) (Survey code) (Index code) 

 Very important 

 Important 

 Not too important 

 Not important at all 

1 

2 

3 

4 

3 

2 

1 

0 

The code values for this variable were reversed so more desirable responses have 

higher values. 
C-9 

 ExpectPSE Subindex 

This subindex is made up of items from the student survey and measures the student’s postsecondary 

aspirations and has a Cronbach alpha of 0.68 (see exhibit C-3). It includes responses to questions on the 

following: 

 Whether or not the student had heard of 4-year colleges, 

 Number of people the student reported talking to about his or her postsecondary 

education, 

 Whether the student thought people who attended college had higher salaries than 

those who did not, 

 How likely it is that the student will go to college, 

 How important the student thought it is to go to college, 

 How far the student thought he or she would go in his or her education, and 

 What sort of education the student thought is required for the job he or she wants to 

have at age 30. 

Exhibit C-3. Example of ExpertPSE subindex 

Student Question 36b: 

Have you heard of the following types of schools: 4-year college or university?

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only “Yes” responses. 

Student Question 37: 

Who do you talk to about continuing your education after high school (Check all that 

apply)

(Response options) (Survey code) (Index code) 

 Parent(s) or guardian 

 Brother(s) or sister(s) 

 Guidance counselor 

 Teacher(s) 

 Principal or assistant principal 

 Religious leader (minister, priest, 

rabbi, etc.) 

 Friend(s) 

 Someone else (who?) 

 No one 

1 

2 

3 

4 

5 

6 

7 

8 

9 

1 

1 

1 

1 

1 

1 

1 

1 

1 

0 

The code values for this variable were changed to count only “Yes” responses. Then 

the number of “Yes” responses for the nine options was summed. 
 C-10 

Exhibit C-3. Example of ExpertPSE subindex (continued) 

Student Question 38: 

In general, do you think a person who finishes college makes more money in a year than 

a person who does not finish college?

(Response options) (Survey code) (Index code) 

 Definitely 

 Probably 

 I doubt it 

 Definitely not 

 Don’t know 

1 

2 

3 

4 

8 

4 

3 

2 

1 

2.5 

The code values for this variable were reordered so more desirable responses have 

higher values. “Don’t know” was placed in the middle of the ordered responses 

because, in this case, it does not necessarily reflect either a positive or negative 

outcome. 

Student Question 40: 

How likely are you to go to college?

(Response options) (Survey code) (Index code) 

 I will definitely go to college 

 Probably 

 May 

 Probably not 

 Definitely not 

 Not decided 

1 

2 

3 

4 

5 

6 

36 

25 

16 

9 

4 

6.25 

The code values for this variable were reversed so more desirable responses have 

higher values, and then they were squared. Squaring increases the distance between 

values for the different possible responses for this question, giving more weight to 

“positive” responses. “Not decided” was considered to be better than “Definitely 

not,” but not as positive as “Probably not.” 

Student Question 41: 

How important is it for you to go to college?

(Response options) (Survey code) (Index code) 

 Very important 

 Somewhat important 

 Not very important 

 Not important at all 

1 

2 

3 

4 

16 

9 

4 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. Then, the reversed values were squared, increasing the distance 

between values for the different possible responses and giving more weight to more 

desired responses. 
C-11 

Exhibit C-3. Example of ExpertPSE subindex (continued) 

Student Question 42: 

How far in school do you think you will get after high school?

(Response options) (Survey code) (Index code) 

 A certificate from a vocational, trade, 

or business school (less than a 2-year 

program) 

 A 2-year degree from a community 

college or an Associates degree 

 A 4-5 year degree from a college or 

university or a Bachelor’s degree 

 A graduate or professional degree 

such as an MA, Ph.D., JD, or MD 

 I’m not going to school after high 

school 

 I don’t know 

1 

2 

3 

4 

5 

8 

2 

3 

4 

5 

1 

2.5 

The code values for this variable were reordered so more desirable responses have 

higher values. “Don’t know” was placed near the middle of the ordered responses 

because, in this case, it was determined to reflect neither a positive nor negative 

outcome. 

Student Question 46: 

How much education do you think you’ll need to get that kind of job when you are 30 

years old? [This question references a list of 19 jobs from Student Question 43.]

(Response options) (Survey code) (Index code) 

 Less than high school 

 High School 

 A certificate from a vocational, trade, 

or business school (less than a 2-year 

program) 

 A 2-year degree from a community 

college or an Associates degree 

 A 4-5 year degree from a college or 

university or a Bachelor’s degree 

 A graduate or professional degree 

such as an MA, Ph.D., JD, or MD 

 Not planning to work 

 Don’t know 

1 

2 

3 

4 

5 

6 

7 

8 

2 

3 

4 

5 

6 

7 

1 

4.5 

The code values for this variable were reordered so more desirable responses have 

higher values. “Don’t know” was placed near the middle of the ordered responses 

because it was determined to reflect neither a positive nor negative outcome. 
 C-12 

 Pexpect Subindex 

This subindex consists of questions from the parent interview and measures the parent’s postsecondary 

aspirations for the child (see exhibit C-4). The Cronbach alpha is 0.58 and correlates well with 

ExpectPSE, with a correlation coefficient of p = 0.36. The subindex is based on responses to questions on 

the following: 

o Discussions about college with the child, 

o Student’s expected ultimate degree, 

o Whether the parent saw the child attending a college away from home, and 

o The affordability of college, as reported by the parent. 

Exhibit C-4. Example of Pexpect subindex 

Parent Question 21: 

Since the beginning of the school year, have you talked to him/her about attending 

college?

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only “Yes” responses. 

Parent Question 23: 

How far in school do you think [child] will get?

(Response options) (Survey code) (Index code) 

 A certificate from a vocational, trade, 

or business school 

 Associates degree 

 Bachelor’s degree 

 Graduate or professional degree 

1 

2 

3 

4 

1 

2 

3 

4 

The code values for this variable were not changed, but they were counted as a 

component in this index only if the parent had indicated a belief that the student 

would continue education after high school. 
C-13 

Exhibit C-4. Example of Pexpect subindex (continued) 

Parent Question 24: 

Do you think [child] will attend a college or other school after high school that is close 

to where you live now?

(Response options) (Survey code) (Index code) 

 Yes 

 No 

 Don’t know 

1 

2 

8 

1 

2 

0 

The code values for this variable were not changed, but they were counted as a 

component in this index only if the parent had indicated a belief that the student 

would continue education after high school. 

Parent Question 28: 

Do you think [child] will be able to afford to attend a 4-year state college or university 

after high school?

(Response options) (Survey code) (Index code) 

 Definitely 

 Probably 

 Not sure 

 I doubt it 

 Definitely not 

1 

2 

3 

4 

5 

2 

1 

0 

-1 

-2 

The code values for this variable were reversed so more desirable responses have 

higher values. They were also centered around 0, to give more desirable responses 

positive values and less desirable responses negative values. 

 StdParTalk Subindex 

This subindex is made up of student survey items and measures the student’s report of parent-child 

discussions on various topics (see exhibit C-5). The Cronbach alpha is 0.78. It contains responses to 

questions on the following: 

o School activities and events; 

o New knowledge from class; 

o Grades; 

o Community, national and world events; and 

o Things that were bothering the students. 
 C-14 

Exhibit C-5. Example of StdParTalk subindex 

Student Question 48: 

In the past month, how often did you talk about the following with either or both of your 

parents or guardians?

(Response categories) 

 School activities or events of 

particular interest to you 

 Things you’ve studied in class 

 Your grades 

 Community, national, and world 

events 

 Things that were bothering you 

 

(Response options) (Survey code) (Index code) 

 Frequently 

 A few times 

 Never 

1 

2 

3 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. The code values for each of the five response categories were summed 

to obtain a single value for these questions. The value of this question entered the 

index only if the student reported having either a mother, a father or a guardian at 

home. 

 Reading Hours Subindex 

This subindex is made up of a question from the student survey and measures how much time the student 

spent reading for pleasure. Because it is only made up of one question, a Cronbach alpha is not 

applicable. 

Exhibit C-6. Reading Hours subindex 

Student Question 8: 

How many hours each week do you spend reading that is not part of your homework?

(Response options) (Survey code) (Index code) 

 None 

 1 hour or less a week 

 Between 2 and 3 hours a week 

 Between 4 and 5 hours a week 

 Between 6 and 7 hours a week 

 8 or more hours a week 

1 

2 

3 

4 

5 

6 

1 

2 

3 

4 

5 

6 

The code values for this variable were not changed. 
C-15 

C.2 Creation of Other Indexes 

Below is a description of several other interim outcome measures not included in the College Orientation 

Index and the interview items that make up each index. 

 ParInvolve Index 

This index was designed to measure the level of parent involvement in their child’s education (see 

exhibit C-7). This index has an alpha of 0.59 and includes items on the frequency and content of 

o Parent-teacher conferences, 

o Parental attendance at school events,52 and 

o Steps taken to find out about college requirements. 

Exhibit C-7. Example of ParInvolve index 

Parent Question 25: 

Since the beginning of the school year, have you received any written information about 

the types of classes (he/she) should be taking now to prepare (himself/herself) for 

college? 

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only “Yes” responses. 

Parent Question 26: 

Since the beginning of the school year, have you attended any meetings that discussed 

the types of classes (he/she) should be taking now to prepare (himself/herself) for 

college?

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only “Yes” responses. 

 

52 Some of these school events are assumed to be GEAR UP events, but survey questions did not ask separately about GEAR UP 

and non-GEAR UP events. (Parents of GEAR UP and non-GEAR UP students were asked the same questions.) 
 C-16 

Exhibit C-7. Example of ParInvolve index (continued) 

Parent Question 27: 

Given that [CHILD] is in the 7th grade, do you feel you have...

(Response options) (Survey code) (Index code) 

 Enough information about college 

entrance requirements 

 Some information but not enough 

about college entrance requirements 

 No information about college 

entrance requirements 

1 

2 

3 

1 

0 

-1 

The code values for this variable were reversed and centered around 0. These 

changes allowed more desirable responses to have positive values and less desirable 

responses to have negative values. 

Parent Question 29: 

Have you attended any workshops for parents that provided you with information about 

financial assistance for your child to attend college?

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only “Yes” responses. 

Parent Question 9: 

Since the beginning of the school year, how many meetings have you had with 

[CHILD’S] teachers? Would you say... 

(Response options) (Survey code) (Index code) 

 One 

 A few 

 Several, or 

 I regularly meet with my child’s 

teacher(s) 

1 

2 

3 

4 

1 

2 

3 

4 

The code values for this variable were not changed. 
C-17 

Exhibit C-7. Example of ParInvolve index (continued) 

Parent Question 14: 

Since the beginning of the school year, have you participated in any of the following 

school activities? 

(Response categories) 

 Back-to-school-night 

 PTA meetings 

 A school event, such as a play or 

sports event 

 Attended a field trip, such as a 

museum or zoo 

 

(Response options) (Survey code) (Index code) 

 Yes 

 No 

 Don’t Know 

1 

2 

8 

1 

0 

0 

The code values for this variable were changed to count only “Yes” responses for 

each of the four response categories. 

 Sdiligent Index 

This index measures how diligent the parent feels the student is about his or her schoolwork. It was 

created from parental reports on the frequency and duration of the child’s homework and has an alpha of 

0.64 (see exhibit C-8). 

Exhibit C-8. Example of Sdiligent index 

Parent Question 4: 

How often does (he/she) do homework at a place other than home...

(Response options) (Survey code) (Index code) 

 Less than once a week 

 1 to 2 times a week 

 3 to 4 times a week 

 5 or more times a week, or 

 Only does it at home 

1 

2 

3 

4 

5 

0.5 

1.5 

3.5 

6 

0 

The code values for this variable were set to a wider scale. The value of this question 

entered the index only if the parent reported that the student received homework. 
 C-18 

Exhibit C-8. Example of Sdiligent index (continued) 

Parent Question 2a: 

How often does (he/she) do homework at home? Is it...

(Response options) (Survey code) (Index code) 

 Less than once a week 

 1 to 2 times a week 

 3 to 4 times a week 

 5 or more times a week 

1 

2 

3 

4 

0.5 

1.5 

3.5 

6 

The code values for this variable were set to a wider scale. The value of this question 

entered the index only if the parent reported that the student received homework but 

completed it somewhere other than at home or in an after-school program. 

Parent Question 5: 

Including at home, in school, during after-school programs, or any other place that 

[CHILD] does (his/her) homework, how much time does [CHILD] spend doing 

homework per week on average? Would you say...

(Response options) (Survey code) (Index code) 

 None 

 Less than 2 hours 

 2-3 hours 

 4-6 hours 

 over 6 hours 

1 

2 

3 

4 

5 

1 

2 

3 

4 

5 

The code values for this variable were not changed. 

 NegJunkHours Index 

This index measures a student’s use of after-school time. It was created from items that measured how 

much time students spent watching television as well as playing video games (see exhibit C-9). The index 

was reverse coded to allow high values to indicate that the student spent little time in those activities. The 

index alpha is 0.53. 
C-19 

Exhibit C-9. Example of NegJunkHours index 

Student Question 10: 

Not including weekends, how many hours a day do you USUALLY watch TV?

(Response options) (Survey code) (Index code) 

 Do not watch TV 

 1 hour or less a day 

 Between 2 and 3 hours a day 

 Between 3 and 4 hours a day 

 Between 4 and 5 hours a day 

 5 or more hours a day 

1 

2 

3 

4 

5 

6 

6 

5 

4 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. Missing values were counted the same as a response of “Do not watch 

TV.” 

Student Question 11: 

Not including weekends, how many hours a day do you USUALLY play video games?

(Response options) (Survey code) (Index code) 

 Do not play video games 

 1 hour or less a day 

 Between 2 and 3 hours a day 

 Between 3 and 4 hours a day 

 Between 4 and 5 hours a day 

 5 or more hours a day 

1 

2 

3 

4 

5 

6 

6 

5 

4 

3 

2 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. Missing values were counted the same as a response of “Do not play 

video games.” 

 HomeworkHours Index 

This index measures how long students spent on homework and was based on the student’s report of time 

spent doing homework, by subject (see exhibit C-10). The index alpha is 0.80, which is fairly high. The 

high alpha is most likely because of the format of the questions that make up the index. The questions are 

in a series and all have a similar format, which often leads to more consistent responses and therefore a 

higher alpha. The analysts tried to combine this index with Sdiligent, but got an alpha of only 0.44. 

Interestingly, the correlation between parental and student reports of homework hours is only 0.08. 
 C-20 

Exhibit C-10. Example of HomeworkHours index 

Student Question 4: 

About how much time do you spend on homework each WEEK? Include the time you 

spend both in and out of school.

(Response categories) 

 Math 

 English/Language Arts 

 Science 

 All other subjects combined 

 

(Response options) (Survey code) (Index code) 

 None 

 Less than 1 hour 

 Between 1 and 3 hours 

 Between 4 and 6 hours 

 7 hours or more 

1 

2 

3 

4 

5 

0 

0.5 

2 

5 

10 

The code values for this variable were altered so that increasingly desirable responses 

have much more weight than less desirable responses. The code values for each of 

the four response categories were summed to obtain the final value for this question. 

 ECBusy Index 

This index measures a student’s extracurricular activities (see exhibit C-11). It has an alpha of 0.70 and 

uses items that indicate “active” extracurricular activities, including 

o Student leadership; 

o Number of school-based extracurricular activities and hours spent on them; 

o Frequency of participation in other activities other than television, video games, 

reading or homework; 

o Parent attendance at school events; and 

o Out-of-school activities. 
C-21 

Exhibit C-11. Example of ECBusy index 

Student Question 13: 

Were you an officer or leader in any of the activities listed[below]?

(Response categories) 

 A team sport such as soccer, 

basketball, baseball, football, field 

hockey, etc. 

 An individual sport such as crosscountry, gymnastics, golf, swimming, 

tennis, track, wrestling, etc. 

 Band, orchestra, chorus, choir, or 

other music group 

 Drama club, school play or musical 

 Student government 

 Cheerleading, pom squad, drill team, 

dance team 

 School yearbook, newspaper, or 

literary magazine 

 Academic clubs, such as Art, 

Computer, Math, Engineering, 

Science, Debate/Forensics, Foreign 

languages, Philosophy 

 Hobby clubs, such as photography 

and chess 

 Future Teachers of America, Future 

Homemakers of American, or other 

vocational education or professional 

clubs 

 

(Response options) (Survey code) (Index code) 

 Yes 

 No 

 Did not participate in any clubs 

1 

2 

3 

3 

2 

1 

Code values for this variable were reversed so more desirable responses have higher 

values. 
 C-22 

Exhibit C-11. Example of ECBusy index (continued) 

Student Question 14: 

Most weeks, how much time do you spend on all activities (such as, sports, clubs, or 

other activities) at your school?

(Response options) (Survey code) (Index code) 

 None 

 Less than 1 hour a week 

 1 to 4 hours a week 

 5 to 9 hours a week 

 10 hours or more a week 

1 

2 

3 

4 

5 

1 

2 

3 

4 

5 

The code values for this variable were not changed. 

Student Question 12 

Have you been in any of the following school activities this school year? 

(Response categories) 

 A team sport such as soccer, basketball, 

baseball, football, field hockey, etc. 

 An individual sport such as cross-country, 

gymnastics, golf, swimming, tennis, track, 

wrestling, etc. 

 Band, orchestra, chorus, choir, or other music 

group 

 Drama club, school play or musical 

 Student government 

 Cheerleading, pom squad, drill team, dance 

team 

 School yearbook, newspaper, or literary 

magazine 

 Academic clubs, such as Art, Computer, 

Math, Engineering, Science, 

Debate/Forensics, Foreign languages, 

Philosophy 

 Hobby clubs, such as photography and chess 

 Future Teachers of America, Future 

Homemakers of American, or other 

vocational education or professional clubs 

 

(Response options) (Survey code) (Index code) 

 Yes 

 No 

 School does not have 

1 

2 

3 

1 

0 

0 

The code values for this variable were changed to count only the number of “Yes” 

responses among the 10 response categories. 
C-23 

Exhibit C-11. Example of ECBusy index (continued) 

Student Question 15: 

How often do you spend time on the following activities outside of school? 

(Response categories) 

 Using a personal computer, not 

including school-related work 

 Participating in religious activities 

 Doing volunteer or community 

service beyond any requirements for 

graduation 

 Doing things with your friends 

 Doing things with your mother, 

father, or guardian(s) 

 Doing things with other adults 

 

(Response options) (Survey code) (Index code) 

 Never or almost never 

 Once or twice a month 

 Once or twice a week 

 Every day or almost every day 

1 

2 

3 

4 

1 

2 

3 

4 

The code values for this variable were not changed. The values for each of the six 

response categories were summed to obtain the final value for this question. 

Student Questions 49 and 50: 

Does your mother or female guardian attend school activities or events? 

(Question 49) 

(Response options) (Survey code) (Index code) 

 Yes, often 

 Yes, sometimes 

 No, never 

 I don’t have a mother or female 

guardian 

1 

2 

3 

4 

3 

2 

1 

1 

Does your father or male guardian attend school activities or events? 

(Question 50) 

(Response options) (Survey code) (Index code) 

 Yes, often 

 Yes, sometimes 

 No, never 

 I don’t have a father or male guardian 

1 

2 

3 

4 

3 

2 

1 

1 

The code values for this variable were reversed so more desirable responses have 

higher values. In addition, for the index to register the index code noted above, only 

one of the survey questions needed to meet the criteria. For example, if the original 

item value for either Question 49 or Question 50 was 1, the index code was set to 3. 
 C-24 

Exhibit C-11. Example of ECBusy index (continued) 

Student Question 16: 

Do you spend time doing any of the following activities?

(Response categories) 

 Working on hobbies, arts, or crafts on 

your own 

 Taking classes (music, art, language, 

dance) that are not a t your school 

 Participating in sports or taking sports 

lessons that are not at your school 

 Attending plays or other 

performances at a theater 

 

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only the number of “Yes” 

responses among the four response categories. Missing responses were counted the 

same as a response of “Yes.” 

 KnowPSE Index 

This index measures the student’s knowledge of postsecondary education (see exhibit C-12). It has an 

alpha of 0.59 and includes responses to questions on the following: 

o To whom the student has spoken about the classes needed to graduate from high 

school and get into college, 

o Whether the student has talked with any adults at home about classes necessary to get 

into college, 

o Student’s familiarity with different types of postsecondary education, 

o With whom the student speaks about continuing education after high school, and 

o Whether the student feels people with college degrees earn a higher salary than those 

without college degrees. 
C-25 

Exhibit C-12. Example of KnowPSE index 

Student Question 34: 

Have you talked with your school counselor or someone else at your school about the 

classes you need [below] 

(Response categories) 

 to graduate high school 

 to get into college 

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only “Yes” responses. 

Student Question 35: 

Since the beginning of the school year, have you talked with any adults in your house 

about the classes you need to take to get into college?

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only “Yes” responses. 

Student Question 36: 

Have you heard of the following types of schools [below]:

(Response categories) 

 2-year or community college 

 4-year college or university 

 Vocational, trade, or business school 

(Response options) (Survey code) (Index code) 

 Yes 

 No 

1 

2 

1 

0 

The code values for this variable were changed to count only “Yes” responses. 
 C-26 

Exhibit C-12. Example of KnowPSE index (continued) 

Student Question 37: 

Who do you talk to about continuing your education after high school (Check all that 

apply)

(Response options) (Survey code) (Index code) 

 Parent(s) or guardian 

 Brother(s) or sister(s) 

 Guidance counselor 

 Teacher(s) 

 Principal or assistant principal 

 Religious leader (minister, priest, 

rabbi, etc.) 

 Friend(s) 

 Someone else (who?) 

 No one 

1 

2 

3 

4 

5 

6 

7 

8 

9 

1 

1 

1 

1 

1 

1 

1 

1 

1 

0 

The code values for this variable were changed to count only “Yes” responses. Then 

the number of “Yes” responses for the nine options was summed. 

Student Question 38: 

In general, do you think a person who finishes college makes more money in a year than 

a person who does not finish college?

(Response options) (Survey code) (Index code) 

 Definitely 

 Probably 

 I doubt it 

 Definitely not 

 Don’t know 

1 

2 

3 

4 

8 

4 

3 

2 

1 

2.5 

The code values for this variable were reordered so more desirable responses have 

higher values. “Don’t know” was placed in the middle of the ordered responses 

because, in this case, it does not necessarily reflect either a positive or negative 

outcome. 
D-1 

Appendix D 

Index Validation Using the National Longitudinal Study (NELS:88) 

Because it will be several years before the students participating in this evaluation are old enough to 

enroll in college, interim measures are the only indicators of the Gaining Early Awareness and Readiness 

for Undergraduate Programs’ (GEAR UP’s) effect on students’ college-going rates that are available. The 

analysis in this appendix is a test of the validity of the predictive power of the College Orientation Index 

(described in appendix C) in estimating a student’s likelihood of going to college. 

The National Education Longitudinal Study of 1988 (NELS:88) database was used for this test of the 

predictive capabilities of the College Orientation Index. NELS:88 is a longitudinal survey that started in 

1988 with a nationally representative sample of about 12,000 eighth-graders. The NELS:88 study 

conducted follow-ups with these students and their families and schools in 1990, 1992, 1994 and 2000. 

NELS:88 asked questions about school, parents’ roles in education and students’ education and 

occupational aspirations. Most important, while NELS:88 mirrors some of the aspects of the GEAR UP 

student and parent surveys, it has the advantage of having followed students beyond middle school and 

high school and asked questions about students’ actual college attendance. This makes it possible to 

compare students’ answers with specific NELS:88 questions in eighth grade to the later outcome of 

whether the student actually attended college. 

D.1 Creating a NELS:88 College Orientation Scale 

To validate the GEAR UP College Orientation Index, a College Orientation Index outcome was created 

based on similar questions from NELS:88. While the GEAR UP College Orientation Index consists of 22 

questions from the GEAR UP student and parent surveys, the NELS:88 College Orientation Index 

outcome scale comprises 12 questions from the NELS:88 student and parent surveys that closely mirror 

questions on the GEAR UP College Orientation Index. There were no matches in NELS:88 for 10 

questions on the GEAR UP College Orientation Index, so these components were not included in the 

NELS:88 College Orientation Index. (Exhibit D-1 provides a complete list of the questions and the 

response categories that make up both College Orientation Indexes.) 

The coding for many of the questions in the GEAR UP College Orientation Index was changed so that 

responses that suggest a greater likelihood of attending college had higher values than those that were 

consistent with a lesser likelihood of attending college. In most cases, this meant simply reversing the 

coding but not changing the magnitude of the responses. 

In developing the NELS:88 College Orientation Index, similar changes were made to the coding for 

several of the NELS:88 questions. These changes preserved the magnitude and direction captured in the 

GEAR UP College Orientation Index scale. 
 D-2 

Exhibit D-1. Comparison between GEAR UP variables and NELS:88 variables in their 

respective College Orientation Indexes 

College Orientation 

Index variables 

GEAR UP evaluation questions with 

possible response categories and values 

where pertinent 

NELS:88:88 equivalent question, with 

possible response categories and values 

where pertinent 

ImpWork Student Question 3: 

How important do you think it is to work 

hard in school?

 Very important 

 Important 

 Not too important 

 Not important at all 

Student Question 59h: 

How much do you agree with each of the 

following statements about your school 

and teachers? 

 When I work hard on my schoolwork, 

my teachers praise my efforts. 

- Strongly agree 

- Agree 

- Disagree 

- Strongly disagree 

ReadingHours Student Question 8: 

How many hours each week do you spend 

reading that is not part of your 

homework?

 None 

 1 hour or less a week 

 Between 2 and 3 hours a week 

 Between 4 and 5 hours a week 

 Between 6 and 7 hours a week 

 8 or more hours a week 

Student Question 80: 

How much additional reading do you do 

on your own outside school—not in 

connection with schoolwork? (Do not 

count any reading done for any school 

purpose.)

 None 

 1 hour or less a week 

 2 hours 

 3 hours 

 4-5 hours 

 6 hours or more a week 

Grades Student Question 17: 

Thinking about the last school year, how 

would you describe your grades?

 Mostly As 

 As and Bs 

 Mostly Bs 

 Bs and Cs 

 Mostly Cs 

 Cs and Ds 

 Mostly Ds or below 

Student Question 81: 

For each of the school subjects listed 

below (English, Math, Science, and Social 

Studies), mark the statement that best 

describes your grades from sixth grade up 

till now.

 Mostly As 

 Mostly Bs 

 Mostly Cs 

 Mostly Ds 

 Mostly below Ds 

 Doesn’t apply to me – my classes are 

not graded 
D-3 

Exhibit D-1. Comparison between GEAR UP variables and NELS:88 variables in their 

respective College Orientation Indexes (continued) 

College Orientation 

Index variables 

GEAR UP evaluation questions with 

possible response categories and values 

where pertinent 

NELS:88:88 equivalent question, with 

possible response categories and values 

where pertinent 

AbsentDays Student Question 31: 

During the past month, how many days 

were you absent from school?

 None 

 1 or 2 

 3 or 4 

 5 or more 

 Don’t remember 

Student Question 75: 

How many days of school did you miss 

over the past four weeks?

 None 

 1 or 2 days 

 3 or 4 days 

 5 to 10 days 

 More than 10 days 

SkipClasses Student Question 33: 

During the past month, how many classes 

did you skip or cut?

 None 

 1 or 2 

 3 or 4 

 5 or more 

Student Question 76: 

How often do you cut or skip classes?

 Never or almost never 

 Sometimes, but less than once a 

week 

 Not every day, but at least once a 

week 

 Daily 

LikelyGo 

College 

Student Question 40: 

How likely are you to go to college?

 I will definitely go to college 

 I will probably go to college 

 I may go to college 

 I will probably not go to college 

 I will definitely not go to college 

 I have not decided yet 

Student Question 47: 

How sure are you that you’ll go on for 

further education after leaving high 

school?

 Very sure I’ll go 

 I’ll probably go 

 I probably won’t go 

 Very sure I won’t go 

HowFarSchool Student Question 42: 

How far in school do you think you will 

get after high school?

 A certificate from a vocational, 

trade, or business school (less 

than 2-year program) 

 A 2-year degree from a 

community college or an 

associate’s (A.A.) degree 

 A 4-5 year degree from a 

college or university or a 

bachelor’s (B.A.) degree 

 A graduate or professional 

degree such as a master’s 

(M.A.), doctorate (Ph.D.), law 

(J.D.) or medical (M.D.) degree 

 I’m not going to school after 

high school 

 I don’t know 

Student Question 45: 

As things stand now, how far in school do 

you think you will get?

 Won’t finish high school 

 Will graduate from high school, 

but won’t go any further 

 Will go to vocational, trade, or 

business school after high school 

 Will attend college 

 Will graduate from college 

 Will attend a higher level of school 

after graduating from college 
 D-4 

Exhibit D-1. Comparison between GEAR UP variables and NELS:88 variables in their 

respective College Orientation Indexes (continued) 

College Orientation 

Index variables 

GEAR UP evaluation questions with 

possible response categories and values 

where pertinent 

NELS:88:88 equivalent question, with 

possible response categories and values 

where pertinent 

StdParTalk Student Question 48: 

In the past month, how often did you talk 

about the following with either or both of 

your parents or guardians?

 School activities or events of 

particular interest to you 

 Things you’ve studied in class 

 Your grades 

 Community, national and world 

events 

 Things that were bothering you 

- Frequently 

- A few times 

- Never 

Student Question 36: 

Since the beginning of the school year, 

how often have you discussed the 

following with either or both of your 

parents or guardians?

 Selecting courses or programs at 

school 

 School activities or events of 

particular interest to you 

 Things you’ve studied in class 

- Not at all 

- Once or twice 

- Three or more times 

HmwkUnder Parent Question 6: 

Does (he/she) seem to understand 

(his/her) homework?

 Always 

 Sometimes 

 Rarely 

 Never 

 Don’t know 

Parent Question 74b: 

How much do you agree or disagree with 

each of the following statements 

concerning your eighth grader’s school? 

 The homework assigned is 

worthwhile. 

 Strongly agree 

 Agree 

 Disagree 

 Strongly disagree 

TalkCollege Parent Question 21: 

Since the beginning of the school year, 

have you talked to him/her about 

attending college?

 Yes 

 No 

Parent Question 68: 

How often do you or your spouse/partner 

talk with your eighth grader about his or 

her education plans for after high school?

 Not at all 

 Rarely 

 Occasionally 

 Regularly 
D-5 

Exhibit D-1. Comparison between GEAR UP variables and NELS:88 variables in their 

respective College Orientation Indexes (continued) 

College Orientation 

Index variables 

GEAR UP evaluation questions with 

possible response categories and values 

where pertinent 

NELS:88:88 equivalent question, with 

possible response categories and values 

where pertinent 

UltDegree Parent Question 23: 

How far in school do you think [child] 

will get?

 A certificate from a vocational, 

trade, or business school 

 An associate’s (A.A.) degree 

 A bachelor’s (B.A.) degree 

 A graduate or professional degree 

Parent Question 76: 

How far in school do you expect your 

eighth grader to go?

 Less than a high school diploma 

 GED 

 High school graduate 

 Less than 1 year in a vocational, 

trade, or business school 

 One or 2 years in a vocational, 

trade, or business school 

 Two or more years in a vocational, 

trade, or business schools 

 Less than 2 years of college 

 Two or more years of college 

 Finish a 2-year college program 

 Finish a 4- or 5-year program 

 Masters degree or equivalent 

 Ph.D., M.D., or other advanced 

degree 

College 

Affordable 

Parent Question 28: 

Do you think [child] will be able to afford 

to attend a 4-year state college or 

university after high school?

 Definitely 

 Probably 

 Not sure 

 I doubt it 

 Definitely not 

Parent Question 85: 

The following statements are about 

financial aid for education beyond high 

school. Indicate whether each statement is 

true or false for your family.

 My eighth grader will be able to 

earn most of the money he or she 

will need for schooling beyond 

high school 

 We can pay for our eighth grader’s 

further education without getting 

any outside assistance 

 The family is not willing to go into 

debt for schooling 

 Too much paperwork is required in 

order to apply for financial aid 

 I have not been able to get much 

information on how and where to 

apply for financial aid 

 I do not see any way of getting 

enough money for my eighth 

grader to go to college 

 Other relatives will help pay my 

eighth grader’s college expenses 

 True 

 False 

 We haven’t thought about this yet 
 D-6 

Exhibit D-1. Comparison between GEAR UP variables and NELS:88 variables in their 

respective College Orientation Indexes (continued) 

College Orientation 

Index variables 

GEAR UP evaluation questions with 

possible response categories and values 

where pertinent 

NELS:88:88 equivalent question, with 

possible response categories and values 

where pertinent 

HowHard Student Question 1: 

Compared with other students, how hard 

do you think you work in school? 

 Much harder 

 Harder 

 About the same 

 Not as hard 

 Much less hard 

No match 

HowGood Student Question 2: 

How good a student do you think you are?

 Excellent 

 Good 

 Fair 

 Poor 

No match 

Heard4Year Student Question 36b: 

Have you heard of the following types of 

schools: 

 Four-year college or university? 

 Yes 

 No 

No match 

NumPeople 

TalkedPSE 

Student Question 37: 

Who do you talk to about continuing your 

education after high school? 

 Parent(s) or guardian 

 Brother(s) or sister(s) 

 Guidance counselor 

 Teacher(s) 

 Principal or assistant principal 

 Religious leader (minister, priest, 

rabbi, etc.) 

 Friend(s) 

 Someone else (who?) 

 No one 

No match 

CollegeMore 

Money 

Student Question 38: 

In general, do you think a person who 

finishes college makes more money in a 

year than a person who does not finish 

college? 

 Definitely 

 Probably 

 I doubt it 

 Definitely not 

 Don’t know 

No match 
D-7 

Exhibit D-1. Comparison between GEAR UP variables and NELS:88 variables in their 

respective College Orientation Indexes (continued) 

College Orientation 

Index variables 

GEAR UP evaluation questions with 

possible response categories and values 

where pertinent 

NELS:88:88 equivalent question, with 

possible response categories and values 

where pertinent 

ImpGoCollege Student Question 41: 

How important is it for you to go to 

college? 

 Very important 

 Somewhat important 

 Not very important 

 Not important at all 

No match 

EdFor30 Student Question 46: 

How much education do you think you’ll 

need to get that kind of job when you are 

30 years old? 

 Less than high school 

 A certificate from a vocational, 

trade, or business school (less than 

2-year program) 

 A 2-year degree from a community 

college or an associate’s (A.A.) 

degree 

 A 4- to 5-year degree from a 

college or university or a 

bachelor’s (B.A.) degree 

 A graduate or professional 

degree such as a master’s 

(M.A.), doctorate (Ph.D.), law 

(J.D.) or medical (M.D.) degree 

 Not planning to work 

 Don’t know 

No match 
 D-8 

Exhibit D-1. Comparison between GEAR UP variables and NELS:88 variables in their 

respective College Orientation Indexes (continued) 

College Orientation 

Index variables 

GEAR UP evaluation questions with 

possible response categories and values 

where pertinent 

NELS:88:88 equivalent question, with 

possible response categories and values 

where pertinent 

ParGrades Parent Question 16: 

Overall, what type of student is [child]? 

 Excellent 

 Good 

 Fair 

 Poor 

Parent Question 17: 

Since the beginning of the school year, do 

you think [child] has done excellent, good, 

fair, or poor in the following areas? 

 English 

 Science 

 Math 

 History or Social Studies 

 All other subjects 

 Excellent 

 Good 

 Fair 

 Poor 

No matches 

SimpHard 

Work 

Parent Question 20: 

How important does [child] think it is to 

work hard in school?

 Very important 

 Important 

 Not too important 

 Not important at all 

No match 

CloseCollege Parent Question 24: 

Do you think [child] will attend a college 

or other school after high school that is 

close to where you live now? 

 Yes 

 No 

 Don’t know 

No match 
D-9 

As with the GEAR UP College Orientation Index, after the variables that make up the NELS:88 College 

Orientation Index were recoded, they were standardized so that each of their means was 0 and each of 

their standard deviations was 1. After the individual variables were standardized, they were summed to 

create the NELS:88 College Orientation Index. 

D.2 Testing the NELS:88 College Orientation Scale 

After identifying questions from the NELS:88 study that closely matched those GEAR UP questions that 

make up the GEAR UP College Orientation Index, students’ and parents’ responses on the NELS:88 

questionnaires were used to create a NELS:88 College Orientation Index score for the appropriate 

NELS:88 respondent. (To test the outcome measure, the analyses was limited to those students and 

parents who responded to all of the NELS:88 follow-ups.) The scores resulting from the NELS:88 

College Orientation Index ranged between -29.42 and 13.71. with a median of 0.65 and a mean of 0. 

The next step in the analysis was to test the predictive power of the NELS:88 College Orientation Index 

by noting whether students actually went to college. While running the multiple regression models, other 

factors were also considered that could have affected a student’s likelihood of going to college. The 

factors, besides the NELS:88 College Orientation measure, that were most likely to have influenced a 

student’s likelihood of attending college were parental education, race and family income. A multiple 

regression analysis showed the effect of the three independent variables (NELS:88 College Orientation 

Index, parental education and race) on the dependent variable (whether the student actually attended 

college). 

Family income was used to limit the analysis to those students most similar to the GEAR UP population. 

To this end, the regression equation described effects only for respondents with family incomes of less 

than $20,000. This family income level roughly replicated the income levels in the GEAR UP schools, 

which had National School Lunch Program (NSLP) rates ranging from 50 to 95 percent of the student 

population. Students are eligible for the NSLP if their family’s income is no more than 150 percent of the 

poverty line. In 1988, the year of the NELS:88 Base Year Survey, the poverty level for a family of four 

was $11,997 and the median income for a family of four was $39,051. In 1988, 150 percent of the poverty 

level for a family of four was $17,995.50. The closest income category cutoff on the NELS:88 Base Year 

Survey was $20,000. 

 Independent Variables 

Independent variables in the regression equation came from the NELS:88 Base Year Survey conducted in 

1988 when the students were in eighth grade. In addition to the variables that make up the NELS:88 

College Orientation Index, a composite variable was included on parents’ education (BYPARED), selfreported race from the student survey (BYS31A) and the parent’s report of family income (BYP80). 

Parental education was based on responses to the NELS:88 variable BYPARED, which is a composite of 

several parent questions about parental education. BYPARED characterizes the level of education 

attained by either of the student’s parents. It was constructed using parent questionnaire data (BYP30 and 

BYP31). Student data (BYS34A and BYS34B) were used whenever parent data were either missing or 

not available. Before standardizing with a mean of 0 and standard deviation of 1, the values for this 

categorical variable ranged from 1 to 6, and had the following categories: 
 D-10 

 BYPARED: Did not finish high school.....................1 

 High school graduate or GED...............2 

 Less than a 4-year degree......................3 

 College graduate ...................................4 

 Masters or equivalent............................5 

 Ph.D., M.D., or other ............................6 

Race was based on the NELS:88 variable BYS31A. The original BYS31A variable had the following five 

categories: 

 BYS31A: Asian/Pacific Islander...........................1 

 Hispanic ................................................2 

 Black non-Hispanic ..............................3 

 White non-Hispanic ..............................4 

 American Indian ...................................5 

To fit into the logistic regression equation, each response to the race question was turned into a binomial 

variable. The value for the binomial variable representing the student’s race was 1, while the values for all 

the other race variables was 0. If the student self-reported as white, non-Hispanic, all four other binomial 

race variables were 0. 

In addition, the respondents’ family income was established from the variable BY80. The income variable 

BY80 had 15 income categories. Only those records that indicated the respondents’ family earned less 

than $20,000 were used. 

As described earlier, the inputs into the NELS:88 College Orientation Index and the parental education 

variables were standardized so that the mean is 0 and the standard deviation is 1. This modification 

simplifies the interpretation of the regression coefficients. 

 Dependent Variable 

The dependent variable (whether the student attended college) came from the students’ responses to the 

NELS:88 third followup variable F3PSEATN, which asked students about their postsecondary education 

attendance. This variable was turned into a binomial 1, in which an answer of 0 meant that the student 

was not attending or had not attended college by the time of the third followup (F3PSEATN = 0, 1, 4, or 

5), and an answer of “one” meant that the student had attended or was attending college (F3PSEATN = 2, 

3, 6, or 7). The original coding of F3PSEATN is as follows: 

 F3PSEATN: No PSE.........................................................................0 

 No degree, working toward certificate or license ........1 

 No degree, working toward associate’s .......................2 

 No degree, working toward bachelor’s........................3 

 Some PSE, other ..........................................................4 

 Certificate or license ....................................................5 

 Associate’s degree .......................................................6 

 Bachelor’s degree ........................................................7 
D-11 

D.3 Analyzing the Findings 

Two measures show how well the NELS:88 College Orientation Index predicted actual college-going 

rates. First, the multiple regression equation described earlier shows, for families with less than $20,000 

in total family income, how each factor (NELS:88 College Orientation Index, parental education, and 

race) affected the probability of a respondent attending college. The second measure shows the 

relationship between the NELS:88 College Orientation Index and the other two independent variables 

(parental education and race). 

For families with income less than $20,000, the multiple regression equation takes the form: 

 y = 0.1595(NCB) + 0.3248(PE) + 1.3475(API) + 0.3619 

where: 

 y represents the dependent variable F3PSEATN, so the higher the value for y, the 

more likely the student is to have attended college. 

 NCB is the continuous NELS:88 College Orientation score. With standardized input 

variables, the scores ranged from -29.42 to 13.71, with a mean of 0. 

 PE is the categorical parental education variable. The scores originally ranged from 

one to six but were standardized; the mean was set to 0 with a standard deviation of 1. 

 API is the binomial indicator variable for race where 1 = Asian/Pacific Islander and 

0 = not Asian/Pacific Islander. 

 H is the binomial indicator variable for race where 1 = Hispanic and 1= not Hispanic. 

(The fact that a student was Hispanic did not produce results that were statistically 

different from those from white, non-Hispanic students. Therefore, the coefficient was 

“0” and the variable was not included in this equation.) 

 B is the binomial indicator variable for race where 1 = black, non-Hispanic and 0 = 

not black, non-Hispanic. (The fact that a student was black, non-Hispanic did not 

produce results that were statistically different from those from white, non-Hispanic 

students. Therefore, the coefficient was “0,” and the variable was not included in this 

equation.) 

 AI is the binomial indicator variable for race where 1 = American Indian and 0 = not 

American Indian. (The fact that a student was American Indian did not produce results 

that were statistically different from those from white, non-Hispanic students. 

Therefore, the coefficient was 0 and the variable was not included in this equation.) 

There is no W (Race = white, non-Hispanic) variable because this is the reference group, and these 

respondents are captured when API = 0, H = 0, B = 0 and AI = 0. 
 D-12 

For the family income level measured, the NELS:88 College Orientation Index has a significant and 

positive relationship with the student’s college attendance. In addition, the odds ratio estimates indicated 

that the NELS:88 College Orientation Index was a good predictor of whether a NELS:88 respondent 

would attend college. For families with less than $20,000 in family income, a one-point increase in the 

NELS:88 College Orientation Index make a respondent 2.375 times more likely to attend college. 

D.4 Conclusion 

These tests support the theory that, at least for low-income students, the NELS:88 College Orientation 

Index was a good predictor of whether a student will attend college. The NELS:88 College Orientation 

Index correctly predicted the college-going rate of these children 75 percent of the time. 

Because the NELS:88 College Orientation Index is based on a subset of concepts closely related to the 

GEAR UP College Orientation Index, these results can be extrapolated to the GEAR UP College 

Orientation Index. The general predictive power of both College Orientation Indexes will be similar. In 

fact, because the overall coherence of the GEAR UP College Orientation Index is so high (as explained in 

appendix C), the GEAR UP College Orientation Index, which contains 10 more items than the NELS:88 

College Orientation Index, should have greater predictive capabilities than those of the NELS:88 College 

Orientation Index. Therefore, the evaluation team is confident that the GEAR UP College Orientation 

Index is a valid predictor of future college-going behavior with the caveat that it should not be viewed as 

the single criterion because the relative weighting of its different components was arbitrary. Some 

components of the index may have higher predictive powers than others and would, therefore, require 

weighting more heavily to optimize the predictive power of the index. It was not possible to determine 

optimal weighting with the available data. 
E-1 

Appendix E 

Removal of Baseline Differences 

Several different but related analytic strategies were used for this report. The methods differ in terms of 

controlled covariates, correction of variance estimates for the clustering present in a school-based study 

and robustness of inferences to untestable assumptions. They are laid out in tables E-1 and E-2. Only the 

first three methods are discussed in this appendix. The last two are discussed in appendixes I and H, 

respectively. Table E-1 summarizes the features of each method, while table E-2 shows the outcomes for 

which each analysis method was used. 

A central concept for this analysis concerns whether any particular seventh-grade variable is 

“contaminated.” The need to distinguish between contaminated and uncontaminated variables arose 

because seventh-grade student surveys and parents’ interviews were not collected as early in the school 

year as might have been wished. There is good evidence that some of the programs were very active in 

the early part of that school year, before the student and parent interviews. This meant that not all of the 

seventh-grade variables could be treated as baseline variables. Those variables that appear to have been 

affected by early seventh-grade Gaining Early Awareness and Readiness for Undergraduate Programs 

(GEAR UP) program activities were treated as contaminated variables. Section E.1 provides information 

about which variables were classified as contaminated and about the process used in that classification. 

Subsequent sections provide more detailed information on each method, but here are some brief notes on 

each method. The method of replicated counterfactual projection (CFP) weights is based on propensity 

scoring53 and jackknifing.54 It is a robust method, requiring only very weak distributional assumptions. 

The method of hierarchical linear models (HLM) is probably more powerful statistically and allows fixed 

effects at both the school and student levels, but it requires stronger distributional assumptions. Both 

approaches control on baseline differences in uncontaminated student-variables and both yield standard 

errors on estimated effects that reflect the clustering. The advantage of the HLM approach is that it also 

allowed control on school-level variables. However, this advantage is gained by making stronger 

distribution assumptions than are required for the CFP method. These extra distribution assumptions were 

clearly inappropriate for some outcomes. Thus, the CFP procedure was used for the outcomes that were 

strongly non-Gaussian, while the HLM procedure was used for those outcomes that were approximately 

distributed as Gaussian. 

 

53 P.R. Rosenbaum, and D.B. Rubin. The Central Role of Propensity Score in Observational Studies for Causal Effects. 

Biometrika, 70, 41-55: 1983; P.R. Rosenbaum, and D.B. Rubin. Reducing Bias in Observational Studies Using 

Subclassification on the Propensity Score. Journal of the American Statistical Association, 79, 516-524: 1984; R. Hornik, D. 

Maklan, D. Judkins, and D. Cadell, et al. Evaluation of the National Youth Anti-Drug Media Campaign: Second Semi-Annual 

Report of Findings―April 2001. Rockville, Md.: Westat, 2001. 

54 K.M. Wolter. Introduction to Variance Estimation. New York: Springer-Verlag, 1985. 
 E-2 

Table E-1. Analysis methods 

Method Variables controlled Other features 

Replicated counterfactual 

projection weights 

o Uncontaminated student-level 

variables from the seventh-grade 

parent and student questionnaires 

o Clustering reflected in 

variance estimates 

o Effects of nonresponse 

adjustment reflected in 

variance estimates 

o No assumption about 

probability distribution of 

outcome variable 

HLM with control on 

baseline value of outcome 

o Uncontaminated student-level 

variables from the seventh-grade 

parent and student questionnaires 

o School-level averages of 

uncontaminated student-level 

variables for the seventh-grade 

parent and student questionnaires 

o Student-level seventh-grade 

report on the outcome of interest 

o School-level averages of studentlevel seventh-grade report on the 

outcome of interest 

o Clustering reflected in 

variance estimates 

o Outcome variable assumed to 

be normally distributed 

 

HLM without control on 

baseline value of outcome 

o Uncontaminated student-level 

variables from the seventh-grade 

parent and student questionnaires 

o School-level averages of 

uncontaminated student-level 

variables for the seventh-grade 

parent and student questionnaires 

o Clustering reflected in 

variance estimates 

o Outcome variable assumed to 

be normally distributed 

 

Counterfactual imputations 

(Appendix I) 

o Uncontaminated student-level 

variables from the seventh-grade 

parent and student questionnaires 

o Clustering not reflected in 

variance estimates 

o No assumption about 

probability distribution of 

outcome variable 

Analysis of covariance 

(Appendix H) 

o Uncontaminated student-level 

variables from the seventh-grade 

parent and student questionnaires 

o Uncontaminated student-level 

variables from school records 

o Clustering not reflected in 

variance estimates 

o Outcome variable assumed to 

be normally distributed 
E-3 

Table E-2. Application of analysis methods 

Effects of On Method 

GEAR UP 

application 

of analysis 

methods 

as a whole 

o Course-taking behavior 

o GPAs 

o Percentage of students with grade of B or better 

o Student attendance 

o Percentage of students reporting definite intentions for college 

attendance 

o Percentage of parents who talked with child about college 

o Percentage of parents anticipating postsecondary education for child 

o Percentage of students who think college graduates earn more 

o Information on college planning 

o Parental attendance at parent-teacher conferences and school events 

Replicated 

counterfactual 

projection 

weights 

 

GEAR UP 

as a whole 

o Scale for student expectations about postsecondary education 

(ExpectPSERev) 

o Scale for student’s attitude toward school (Academic) 

o Scale for parent’s perception of student’s attitude toward school 

(Performance) 

o Scale for participation in extracurricular activities (ECBusy) 

o Scale for homework hours (HomeworkHours) 

o Scale for time not spent watching television or playing video games 

(NegJunkHours) 

o Scale for parent’s perception of how hard the student works 

(SDiligent) 

o College Orientation Index (CollegeBoundRev) 

HLM with

control on 

baseline value 

of outcome 

 

GEAR UP 

as a whole 

o Scale for parental expectations for the student’s postsecondary 

education (Pexpect) 

o Discussions about college and course planning (TalkCoursePlanning) 

o Student familiarity with different types of postsecondary institutions 

(HeardOfSchools) 

o Scale for student’s knowledge about postsecondary education 

(KnowPSE) 

o Parental knowledge and involvement (ParInvolve) 

HLM without

control on 

baseline value 

of outcome 

 

GEAR UP 

services 

o College Orientation Index (CollegeBoundRev) Counterfactual 

imputations 

 

GEAR UP 

as a whole 

o Standardized test scores Analysis of 

covariance 
 E-4 

E.1 Identification of Contaminated Baseline Variables 

As mentioned above, the seventh-grade questionnaires were not administered early enough in the school 

year to serve as a true baseline. There was good evidence that the programs were active early that year 

and that those early activities had an impact on some outcome variables, such as knowledge about 

postsecondary education. This raised the difficult question for the evaluation of which, if any, of the 

seventh-grade variables should be controlled in the analysis. Those seventh-grade variables affected by 

early GEAR UP activities were classified as contaminated, and the rest were classified as 

uncontaminated. The decision was made to control only on those that were classified as uncontaminated. 

The task was sensitive because misclassification of variables could lead to either overestimation or 

underestimation of GEAR UP’s effects. If the analysis controlled on contaminated variables, GEAR UP’s 

effects would be underestimated. Alternatively, if uncontaminated variables were treated as contaminated, 

GEAR UP’s effects could be overestimated. 

This problem in the analysis of observation studies is discussed by Rosenbaum in his 1995 textbook 

(pages 61 to 62).55 As a simple example, consider field trips to local colleges and the question of whether 

the GEAR UP program caused an increase in the number of students who went on such field trips during 

their eighth-grade year. Table E-3 shows that these field trips were already much more common in the 

GEAR UP schools early in the seventh grade and that the difference widened by the end of the eighth 

grade from 9 percentage points to 25 percentage points. If it were known that GEAR UP-sponsored 

college field trips started only in the second half of seventh grade, then we would say that the nine-point 

gap is evidence of selection bias and must be removed from estimated GEAR UP effects. One way to do 

that would be to average the gaps among those who did and did not have early seventh-grade trips, 17 and 

27 points, respectively. This would lead to an estimated GEAR UP effect of (0.29)(17)+(1-0.29)(27) = 24 

points, slightly less than the 25 points observed. If on the other hand, we have reason to believe (as we 

do) that the nine-point gap is at least partially due to early GEAR UP activities, then it is more appropriate 

to report the 25-point gap as the GEAR UP effect. If we decide that the seventh-grade report of college 

field trips is contaminated, then we estimate a 25-point effect. If, on the other hand, we decide that the 

variable is uncontaminated, then we report a 24-point effect. 

Table E-3. Illustration of contaminated variable and analysis options (among eighth-grade 

respondents) 

 Attended college campus (%) 

 Early in seventh grade During eighth grade 

School type Total 

Among those who 

had trip early in 

seventh grade 

Among those who 

had no trip early in 

seventh grade 

Total 29 47 61 41 

GEAR UP 33 59 68 55 

Non-GEAR UP 24 34 51 28 

Difference 9 25 17 27 

 

55 P.R. Rosenbaum. Observational Studies. New York: Springer-Verlag, 1995. 
E-5 

Although the difference between the two analyses in this illustration is slight, this was unknowable at the 

time that decisions about covariate admissibility were being made. It is well known that decisions about 

covariates in the analysis of observation studies can be highly influential on the final analyses. This 

section documents the decisions that were made by the study team and the decision process that they 

used. The validity of several findings in this report rests strongly on the appropriateness of these 

decisions. It is important to note that most decisions on contaminated variables were made before 

examining eighth-grade outcome data and were approved by an advisory panel. 

The identification of contaminated variables relied on qualitative information from site visits, theory from 

the model for GEAR UP effects, and identification of counterintuitive patterns in the baseline data 

themselves. As an example of how the qualitative data from site visits were used, the visitors’ reports 

noted that some programs had organized field trips to local colleges early in the year. In another example, 

visitors’ reports noted that GEAR UP activities were often incorporated in PTA meetings and back-toschool nights that usually occur in September and early October—times prior to questionnaire 

administration. The visitors’ reports on these issues argued strongly in favor of treating variables about 

college field trips and parental participation in informational meetings as contaminated. 

As an example of how theory was used, consider that services should be received before effects can be 

generated. So those variables that were most closely related to service delivery (such as attending field 

trips or receiving written information about classes recommended for college preparation) are the ones 

that were most likely to be treated as contaminated. 

Finally, with respect to counterintuitive patterns in the baseline data, it was noted that despite efforts to 

find well-matched comparison schools, it was still the case that GEAR UP schools generally showed 

more signs of social stress and deprivation than did the comparison schools. This pattern was seen both in 

terms of the data from the Common Core of Data (CCD) file used to select the comparison schools and in 

the seventh-grade surveys of students and parents. The methods described in sections E.2 and E.3 were, of 

course, used to remove these baseline differences. However, it was suspicious to find some variables that 

indicated the opposite to be true. One plausible explanation for such variables is that they are 

contaminated, showing the benefits of early GEAR UP activities. 

To summarize, we were most likely to classify a seventh-grade variable as contaminated if (1) we had 

anecdotal reports of GEAR UP activities that could have affected the variable, (2) the variable was 

theoretically closely tied to service delivery, and (3) GEAR UP schools scored higher on the variable, 

when higher means in a direction more consistent with an atmosphere promoting postsecondary 

education. Based on three criteria, tentative decisions were made about which baseline variables should 

be treated as contaminated. This tentative list was then presented to a group of technical experts for 

approval. Based on the evidence outlined above, they concurred that the variables were likely 

contaminated. These decisions were agreed on before the analysis of the eighth-grade data. Subsequently, 

new recodes that were functions of these contaminated variables or closely related to them were also 

added to the list of contaminated variables. Table E-4 provides a list of the contaminated and student 

questionnaire variables, and table E-5 lists the contaminated indexes. Those that showed statistically 

significant differences among the two groups of schools, even after accounting for school-level clustering, 

are noted with an asterisk (*). 
 E-6 

Table E-4. Contaminated baseline student questionnaire variables by GEAR UP status 

(tabulated on eighth-grade completes with nonresponse-adjusted weights) 

 GEAR UP Non-GEAR UP 

Variable Response (%) (%) Difference 

95% Confidence 

interval 

Adultmentor_7 Yes 44.0% 36.9% 7.1 *(0.3,13.9) 

AdvisClassNeed_7 Yes 32.8% 26.0% 6.8 (-1.1,14.7) 

AdvisReadyforColl_7 Yes 30.8% 20.3% 10.5 *(3.4,17.5) 

AdvisReadyforHS_7 Yes 23.1% 19.8% 3.2 (-3.3,9.8) 

ArtsTutother_7 Yes 25.8% 22.2% 3.6 (-2.0,9.2) 

AttendClforColl_7 Yes 40.4% 22.1% 18.3 *(5.8,30.8) 

AttendMeetCollPrep_7 Yes 17.4% 8.8% 8.7 *(1.7,15.7) 

Childpartknow_7 Yes 38.6% 27.4% 11.2 *(4.3,18.1) 

EnufInfo_7 No 46.0% 54.4% -8.4 *(-15.3,-1.4) 

EnufInfo_7 Some 40.8% 34.6% 6.2 *(2.3,10.1) 

EnufInfo_7 Enough 13.2% 10.9% 2.2 (-1.9,6.3) 

Heard2Year_7 Yes 61.7% 51.7% 10.0 *(3.1,16.8) 

knowcollcampus_7 Yes 21.0% 7.8% 13.2 *(5.8,20.7) 

MathTutother_7 Yes 30.7% 29.2% 1.5 (-2.8,5.9) 

PrepMeet_7 Yes 13.0% 5.8% 7.2 *(0.7,13.7) 

SciTutother_7 Yes 22.6% 20.4% 2.1 (-3.2,7.5) 

TalkCollege_7 Yes 81.3% 78.6% 2.7 (-2.9,8.3) 

TalkCounCollEntClasses_7 Yes 30.3% 24.1% 6.2 (-2.3,14.7) 

VisitCollCamp_7 Yes 33.1% 24.4% 8.7 (-0.4,17.8) 

Workshop_7 Yes 9.8% 6.3% 3.5 (-0.2,7.3) 

WritInfo_7 Yes 21.0% 12.4% 8.5 *(2.6,14.5) 

* Statistically significant at the α = 0.05 level. 

NOTE: See Appendix J, Glossary, for a crosswalk of variables with survey items. 

Table E-5. Means of contaminated baseline indexes by GEAR UP status (tabulated on eighthgrade completes with nonresponse-adjusted weights) 

 GEAR UP Non-GEAR UP Difference 

95% Confidence 

interval 

HeardOfSchools_7 0.3 -0.1 0.4 *(0.0,0.7) 

KnowPSE_7 0.4 -0.3 0.7 *(0.1,1.2) 

ParInvolve_7 0.3 -0.3 0.7 *(0.0,1.3) 

ParPrep_7 0.4 -0.4 0.8 *(0.2,1.3) 

pexpect_7 0.0 0.0 0.0 (-0.4,0.4) 

TalkCoursePlanning_7 0.1 -0.3 0.3 (-0.1,0.8) 

* Statistically significant at the α = 0.05 level.`1 

NOTE: See Appendix J, Glossary, for a crosswalk of variables with survey items. 
E-7 

Note that most of the variables that were judged to be contaminated show significant seventh-grade 

difference in the direction of a more positive atmosphere for postsecondary education in GEAR UP 

schools. Some of the differences are quite striking, such as the percentage of students who reported 

attending a class or meeting about getting ready for college (AttendClForColl_7) and the percent of 

parents who reported being aware of their child participating in a field trip to a local college 

(knowcollcampus_7). If we had controlled on these variables in our analyses, we almost certainly would 

have found many fewer effects of the GEAR UP program. We felt that it was appropriate not to control 

on these variables because they passed the criteria discussed above in this section. 

E.2 Replicated Counterfactual Projection Weights 

This procedure is based on propensity scoring and jackknifing. The term CFP weights was coined by 

Westat statisticians,56 but is based on the general work of Paul Rosenbaum and Donald Rubin. More 

specifically, CFP weights are closely related to the “model-based” weights proposed by Rosenbaum.57

The basic idea of CFP weights is simple. In the case of GEAR UP, the students in GEAR UP schools are 

reweighted to resemble the entire study sample and the students in non-GEAR UP schools are also 

reweighted to resemble the entire study sample. For example, students in GEAR UP schools reported 

more class skipping than their counterparts in non-GEAR UP schools. So the CFP weights for classskippers in GEAR UP schools are adjusted down while the CFP weights for class-skippers in non-GEAR 

UP schools are adjusted up, so that when the two samples are tabulated using the CFP weights, the 

weighted frequency of class skipping is similar across the two groups of schools. The reweighted means 

can be viewed as projections to counterfactual universes in which either everyone attends a GEAR UP 

school or no one does. Hence the name. 

Some nice features of this procedure include a lack of need for distribution assumptions about outcome 

variables, control on a rich set of confounders without the need to form a separate model for every 

outcome, robust variance estimation that fully reflects the clustered structure of the data and the ability to 

present complex results in simple form as in the technique known as predictive margins.58 Propensity 

scoring is a procedure in which every student’s probability of belonging to a GEAR UP school (as 

opposed to a comparison school) is modeled in terms of uncontaminated baseline variables. The 

counterfactual projection weights are formed using the propensity scores in such a manner that the GEAR 

UP and non-GEAR UP samples closely resemble each other on a weighted basis. This then induces 

weighted similarity between the two groups in terms of all the variables that entered the propensity model 

as well as in terms of all the variables that were given a chance to enter the model but were omitted 

because of a lack of model significance. This weighted similarity in terms of uncontaminated baseline 

characteristics ensures that weighted differences in outcomes between the two groups are reasonable 

estimates of program effects. The replication is used to provide robust variance estimates as described in 

appendix B. More information is now provided on the propensity scoring and on the formation of the CFP 

weights. 

 

56 R. Hornik, D. Maklan, D. Judkins, and D. Cadell, et al. Evaluation of the National Youth Anti-Drug Media Campaign: Second 

Semi-Annual Report of Findings―April 2001. Rockville, Md.: Westat, 2001. 

57 P.R. Rosenbaum. Model-based Direct Adjustment. Journal of the American Statistical Association, 82, 387–394:1987. 

58 B.I. Graubard, and E.L. Korn. Predictive Margins with Survey Data. Biometrics, 55, 652–659:1999. 
 E-8 

Table E-6 shows the logistic regression model to define each student’s propensity to be in a GEAR UP 

school (as opposed to being in a non-GEAR UP school). Looking at a few of the estimated model 

coefficients, it is evident that minority GEAR UP students were more likely to skip classes than minority 

non-GEAR UP students, that GEAR UP students were less likely to have low hours of television viewing 

and video game playing, that they were less likely to affirm the importance of hard work in school, and 

that their parents were less likely to volunteer in schools. There are also more complex differences 

between the groups in terms of race, pre-seventh grade mobility, student-parent discussions, and the 

education of adults in the household. In addition to the variables shown, many other variables were given 

the chance to enter the model but did not. The small number of terms in the model speaks to the quality of 

initial selection of the non-GEAR UP schools for service as comparison schools. After controlling for the 

variables shown in table E-6, the groups were not, for example, different in terms of family income. 

Table E-6. Variables and interactions that define membership in a GEAR UP school 

Parameter Estimate Standard error Chi-square 

Wald 

Pr > ChiSq 

Intercept 0.02 0.12 0.04 0.85 

Volunteerism -0.19 0.09 4.46 0.03 

ClassSkipping 0.37 0.08 20.23 <.0001 

ClassSkipping*White -0.63 0.13 23.35 <.0001 

NegJunkHours -0.14 0.04 15.39 <.0001 

ImpWork -0.09 0.04 5.63 0.02 

White*Mobility 0.26 0.05 26.51 <.0001 

White*ParTalkPolitics -0.21 0.07 9.74 0.00 

Mobility*OtherAdultEd -0.02 0.01 4.76 0.03 

This model was then used to form five groups of students of descending propensities of being in a GEAR 

UP school. (Table E-7 provides the number of GEAR UP and comparison students in each of the five 

propensity groups.) Within each of these five groups, the students all had very similar probabilities of 

being a GEAR UP student. The first group identified by the model had characteristics that were least 

consistent with students in GEAR UP schools. Some of the students in this group were in GEAR UP 

schools, but most were not. The last of the five groups contained students with characteristics most 

consistent with the overall seventh-grade student body in the GEAR UP schools. The purpose of these 

five propensity groups was to have collections of similar students in which some attended GEAR UP 

schools and others did not. Within each group, these students could be compared with one another to 

measure the effect of attending a GEAR UP school, which was the major difference between the students 

within a given group. 
E-9 

Table E-7. Makeup of propensity groups, by school attendance 

Propensity group 

(in ascending likelihood of 

attending a GEAR UP school) 

Number of 

GEAR UP students 

Number of 

comparison 

students Total 

1 251 426 677 

2 326 352 678 

3 369 309 678 

4 399 279 678 

5 446 232 678 

Total 1,791 1,598 3,389 

These five propensity groups were then used to form CFP weights in the following way. Within each of 

the five groups, the proportion of students in GEAR UP schools was calculated. Then, for each student in 

a GEAR UP school, his or her original weight59 was divided by that proportion. Finally, the weights for 

each of the comparison students were divided by the proportion of students within the group who were 

not in GEAR UP schools. The following equation provides the formula for the calculation of the CFP 

weights. 

7

(1 )

i i

i i

CFP ij

j gj cj

W W

f f

δ

⎛ ⎞ Ψ −Ψ

= + ⎜ ⎟

⎝ ⎠

∑ (1) 

Where 

WCFPi = the CFP weight for student i 

W7i = seventh-grade, nonresponse-adjusted weight for student i 

δ ij = 

1 if student is in group 

0 otherwise

⎧ i j ⎨

⎩

gj f = the weighted percentage of students within group j who are in GEAR UP schools 

Ψi = 

1 if student attends a GEAR UP school

0 otherwise

⎧ i ⎨

⎩

cj f = weighted percentage of students within group j who are not in GEAR UP schools 

The CFP weights effectively project the experience of GEAR UP participants to the comparison students 

in the counterfactual state that they had belonged to a GEAR UP school. CFP weights also project the 

experience of comparison students to GEAR UP participants in the counterfactual state that they had not 

belonged to a GEAR UP school. 

 

59 Probabilities of student selection were not used in the weighting. Instead, as explained in appendix B, each student started with 

a weight of 1, which was adjusted for nonresponse to the seventh-grade student questionnaire. 
 E-10 

For example, GEAR UP students make up less than one-half of Group no. 1. In the counterfactual 

projection weighting, the GEAR UP students needed to represent what would have happened in Group 

no. 1 if GEAR UP had been a universal program. So the GEAR UP students get a CFP weight of roughly 

671/251=2.67. Continuing the example, non-GEAR UP students make up more than one-half of Group 

no. 1. In the CFP weighting, the non-GEAR UP students need to represent what would have happened if 

the GEAR UP program had not existed. So the non-GEAR UP students get a CFP weight of roughly 

671/426=1.58. We know from the model that Group no. 1 is rich in minority students who do not skip 

classes, in white students who do skip classes, in students who spend less time watching television and 

playing video grams, whose parents volunteer and so on—the same groups that are underrepresented in 

GEAR UP schools and overrepresented in non-GEAR UP schools—so it is appropriate that, when 

generalizing the experience of GEAR UP students, those in Group no. 1 should receive heavier than 

average weights, and when generalizing the experience of non-GEAR UP students, those in Group no. 1 

should receive lighter than average weights 

In summary, through the use of CFP weights, the GEAR UP and comparison students’ weights were 

manipulated so that each of the two counterfactual groups resembled the original combined set of students 

as closely as possible, with respect to the confounders. The analysis then proceeded by simply comparing 

the two counterfactual groups’ eighth-grade outcomes to see if one group had outcomes that were 

different from the other group. 

As support for the proposition that the CFP weights work as intended, refer to table E-8. This table shows 

mean values for the seven variables that entered the propensity model by intervention status and type of 

weight. Note that almost all of the differences between GEAR UP and non-GEAR UP schools are larger 

in absolute value with the ordinary weights than with the CFP weights. Also note that the lack of 

significant differences with even the ordinary weights seems paradoxical with the chi-square tests in table 

E-6, but that the reason for this seeming inconsistency is that the tests in table E-8 have been corrected for 

clustering while those in table E-6 were not. In addition, the sample size in table E-6 is for all seventhgrade respondents, while the sample size in table E-8 is only for eighth-grade respondents. 

Table E-8. Comparisons between GEAR UP and non-GEAR UP schools with ordinary weights 

and with CFP weights 

With ordinary eighth-grade weights With eighth-grade CFP weights 

GEAR 

UP 

NonGEAR UP Difference

95% 

Confidence 

interval 

GEAR 

UP 

NonGEAR UP Difference 

95% 

Confidence 

interval 

ClassSkipping_7 1.20 1.11 0.09 (0.00,0.18) 1.17 1.14 0.04 (-0.01,0.09)

ImpWork_7 -0.05 0.06 -0.11 (-0.28,0.06) 0.00 0.01 -0.02 (-0.14,0.11)

Mobility_7 2.50 2.47 0.03 (-0.21,0.28) 2.45 2.50 -0.05 (-0.21,0.11)

NegJunkHours_7 -0.08 0.08 -0.15 (-0.42,0.11) 0.00 -0.03 0.04 (-0.10,0.18)

OtherAdultEd_7 2.06 2.18 -0.12 (-0.51,0.28) 2.11 2.09 0.03 (-0.15,0.20)

ParTalkPolitics_7 1.71 1.77 -0.06 (-0.13,0.01) 1.74 1.73 0.01 (-0.06,0.07)

Volunteerism_7 0.18 0.22 -0.05 (-0.10,0.01) 0.19 0.20 -0.01 (-0.06,0.04)

White_7 0.36 0.45 -0.08 (-0.20,0.03) 0.43 0.39 0.03 (-0.04,0.11)
E-11 

To be able to judge the significance of any findings from these follow-up comparisons, it is important to 

be able to report the variances of the estimated findings. Two factors affected the variance estimation for 

this evaluation. The first factor, clustering, is due to the fact that there are only 36 schools in the analysis. 

Students from the same schools tend to have similar responses for certain variables. This clustering 

around certain variables tends to differ from school to school. If there were more schools in the study, 

such clustering would have a smaller impact on the analysis. 

The other factor to affect the variance estimates is nonresponse adjustment because of attrition. To lessen 

the effect of their attrition, nonresponse adjustments had to be made to the weighting system. While these 

nonresponse adjustments reduce the risk of bias, they also increase variances. The replication system used 

to estimate variances reflects both the clustering and the nonresponse adjustment, as explained in more 

detail in appendix B. Imputation also has the effect of increasing variances, but no attempt was made to 

reflect the impact of imputation on variance estimates. As a result, tests of significance are probably 

slightly too aggressive, meaning that many effects will appear to be statistically significant. Because few 

significant effects were found, the lack of an adjustment for imputation variance appears not to have been 

an issue. 

E.3 Hierarchical Linear Modeling 

Despite the favorable features of the CFP approach discussed earlier, it does have a weakness. While the 

CFP approach accounts for the variability among schools in the confidence intervals on estimated effects, 

it does not control on school-level differences in estimating the effects themselves. As an example of how 

school-level differences can affect individual growth, consider an excellent student in a school in which 

most of his or her classmates are doing well. Such a student probably progresses differently from an 

excellent student in a school of poorly performing students. To control on these school-level differences, 

a technique known as HLM was used for those outcomes with approximately normal distributions. In 

preparing confidence intervals on estimated effects, the HLM technique, like the replicated CFP 

approach, does reflect the clustering by school, but, unlike the replicated CFP approach, it does not reflect 

the impact of nonresponse adjustment. In addition, it makes some distribution assumptions in estimating 

the confidence intervals. The following equation provides the formula for the HLM model. 

55 5 8

5 10

11 1

5 7 7 77 7

15 21 22 23 24

1

( )

( )[ ] ()

ij i ij ij i i

ij ij i ij i i ij i i i ij

yT x x x

y y y y y ue

δβ β β

β π π β πβ β β

•+ •+

== =

•+ • • • •

=

= +Θ + − + +

Θ − + − + + − + ++

∑∑ ∑

∑

ll l l l l l

ll l

ll l l

l

 (2) 

where 

8

ij y = the eighth-grade outcome variable being modeled 

Ti = 

1 if school is a GEAR UP school

0 otherwise

⎧ i ⎨

⎩

δ = the effect of GEAR UP 
 E-12 

Θijl = 

1 if student in school is in the -th propensity group

0 otherwise

⎧ j i ⎨

⎩

l

ij x l = is the value of the l -th confounder for the student 

i x •l = is the school-level average of l -th confounder 

π ij = the propensity for being in a GEAR UP program, estimated in terms of a row vector of 

student-level baseline covariates ij z

π i• = the school-level average propensity for being in a GEAR UP school, for student i 

7 yij = the baseline value of the outcome (unless it was contaminated by early GEAR UP 

activities in the fall of seventh grade, in which case the term would be dropped from 

the model) 

7 yi• = the school average baseline value of the outcome (unless it was contaminated by early 

GEAR UP activities in the fall of seventh grade, in which case the term would be 

dropped from the model) 

2

i u ~ (0, ) N σ u = a normally distributed set of iid random errors at the school level 

2

ij e ~ (0, ) N σ e = a normally distributed set of iid random errors at the student level 

The coefficients δ , 1 24 β , , K β , 2 σ u , and 2 σ e are the fixed terms in the model, while the ui and the ij e

are the random terms. The coefficients 11 15 22 24 β , , , , and K are the terms that capture the systematic ββ β

impact of baseline school-level differences on individual outcomes. The coefficients 

1 10 16 20 21 23 β , , , , , , , and K K ββ ββ β are the terms that capture the systematic impact of baseline 

individual-level differences on individual outcomes. The coefficients 16 20 23 24 β , , , and K are ββ β

omitted from the models for outcomes judged to have contaminated baselines. All of the fixed terms 

except δ are nuisance parameters, meaning that they need to be estimated but that they do not address the 

effectiveness of the intervention (the GEAR UP program). The intervention is said to have a positive 

effect on the outcome if the estimates value of δ is positive and significantly larger than 0. 

To use HLM, several assumptions had to be made. First, the variable being measured should be normally 

distributed. None of the outcomes were normally distributed, but some had stronger deviations than 

others. HLM was used for those confounders where the assumption of normality was not radically 

violated, and CFP weighting was used for the rest. In addition, for individual binary variables or ones that 

had four or fewer responses, CFP weights were used. Refer to table E-1 for a complete accounting of 

which technique was used for each analysis. 
E-13 

Table E-9 provides the predictor specifications for effect variables. Tables E-10 through 24 provide mainfitted HLM models for each of the outcome variables that were analyzed in this manner. These are the 

tables that were used to decide if GEAR UP had an impact on the variable in question on the total 

population within GEAR UP schools. 

Table E-9. Predictor specifications for effect variables in tables E-10 through E-24 

Variable name Definition 

mP GEAR UP propensity (P), school mean 

mP0 GEAR UP propensity (P), centered on mP 

mBV Baseline (seventh grade) value of the outcome variable 

mBV0 Base variable for that model, centered on mBV 

mCS ClassSkipping_7, school mean 

mCS0 Student deviation from school mean of ClassSkipping_7 

mIW ImpWork_7, school mean 

mIW0 Student deviation from school mean of ImpWork_7 

mMOB Mobility_7, school mean 

mMOB0 Student deviation from school mean of Mobility_7 

mPTP ParTalkPolitics_7, school mean 

mPTP0 Student deviation from school mean of ParTalkPolitics_7 

mNJH NegJunkHours_7, school mean 

mNJH0 Student deviation from school mean of NegJunkHours_7 

rXbeta 0-4 Flag for the rank of the treatment propensity Xbeta, used as a class variable 

mBV0 (rXbeta) 0-4 Student deviation from school mean of rXbeta 

GEAR UP Flag for students in GEAR UP schools 

Table E-19 provides an example of a significant GEAR UP effect. That table indicates that parents of 

GEAR UP students scored higher on ParInvolve than parents of students in comparison schools. This 

finding is adjusted for preexisting differences in the group, both in terms of covariates explicitly shown in 

the model, such as school-level variables and baseline scores for ParInvolve, and in terms of variables that 

went into the GEAR UP propensity model. Table E-15 provides an example of a measurable finding in a 

contaminated variable, which does not take into account baseline score. Both are considered significant 

because the Pr > |t| score for the GEAR UP effect is less than 0.05. 
 E-14 

Additional models were fit to look for interactions of GEAR UP with baseline characteristics such as 

race. The point of these additional models was to see if there was subgroups being affected by GEAR UP 

even if the total population was not affected. 

For subgroup analysis, the form of the model was 

55 5 5 8 7 7

5 10 15

1 11 1 1

77 7 7 7

21 22 23 24

1 1

() ()

[] () ( )

k

ij i l ijl ijl l ijl i l l i l l ijl ijl i l l

l ll l l

k k

ij i i ij i i ijl i ijl ijl i l k i i ij

l l

y T xx x yy

y y y y y ue

δ β ββ β

π π β πβ β β γ γ

•+ •+ • +

= == = =

• • • • •+

= =

= Ω+ Θ + − + + Θ − +

− + + − + + Ω + Ω − ++

∑ ∑∑ ∑ ∑

∑ ∑

 (3) 

where 

Ωijl = 

1 if the student is in the -th subgroup of interest 

0 otherwise,

⎧

⎨

⎩

l

 k = the number of levels of the variable defining subgroups, and 

δ l = the effect of GEAR UP on the subgroup of interest. 

To test the validity of HLM, a large simulation study was conducted. For this simulation, a mock database 

with a certain GEAR UP effect embedded in it, was created. Then HLM was run on that database. Several 

minor errors in the model were noted from the simulation. First, the variance of the random school-level 

effect was overestimated. In addition, the coefficients for the systematic student-level effects were 

underestimated. Luckily, both of these errors occurred in what are known as “nuisance parameters,” so 

the fact that they existed had little effect on the outcome of the simulation. Ultimately, the test was 

successful because HLM provided an estimated GEAR UP effect that was similar to that which had been 

built into the model. For further details on this simulation study, refer to appendix F. 
E-15 

Table E-10. Beta coefficients for HLM for the variable Academic 

Effect* 

Predictor variable 

in equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 -3.77 3.11 -1.21 0.22 

mP0 π ij −π i• β 21 -1.04 1.74 -0.60 0.55 

mBV 

7

i• y β 24 0.62 0.17 3.62 0.00 

mBV0 

7 7

ij − i• y y β 23 0.38 0.05 7.17 <.0001

mCS i•1 x β11 2.50 1.22 2.04 0.04 

mCS0 ij1 − i•1 x x β 6 0.42 0.21 1.95 0.05 

mIW i•2 x β12 0.39 0.70 0.55 0.58 

mIW0 ij 2 − i•2 x x β 7 -0.21 0.08 -2.80 0.01 

mMOB i•3 x β13 -0.20 0.25 -0.78 0.43 

mMOB0 ij3 − i•3 x x β 8 -0.10 0.06 -1.64 0.10 

mPTP i•4 x β14 1.47 1.00 1.46 0.14 

mPTP0 ij 4 − i•4 x x β 9 0.18 0.07 2.57 0.01 

mNJH i•5 x β15 -0.22 0.47 -0.48 0.63 

mNJH0 ij5 − i•5 x x β10 0.10 0.10 0.99 0.32 

rxbeta Θij1 β1 0 -3.02 2.30 -1.31 0.19 

rxbeta Θij2 β 2 1 -2.89 2.37 -1.22 0.22 

rxbeta Θij3 β 3 2 -2.80 2.42 -1.16 0.25 

rxbeta Θij4 β 4 3 -3.19 2.40 -1.33 0.19 

rxbeta Θij5 β 5 4 -3.51 2.44 -1.44 0.15 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.32 0.08 4.03 <.0001

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.19 0.09 2.02 0.04 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.21 0.06 3.33 0.00 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 0.17 0.06 3.06 0.00 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.19 0.08 

Residual 

variance 2 σ e 9.35 0.24 

GEAR UP Ti δ -0.16 0.22 -0.70 0.49 

*See table E-9 for explanation of effect variables. 
 E-16 

Table E-11. Beta coefficients for HLM for the variable CollegeMoreMoney 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

Mp π i• β 22 0.01 1.69 0.01 0.99 

mP0 π ij −π i• β 21 -0.18 0.66 -0.27 0.79 

mBV 

7

i• y β 24 0.43 0.22 1.96 0.05 

mBV0 

7 7

ij − i• y y β 23 0.15 0.04 4.18 <.0001

mCS i•1 x β11 0.76 0.54 1.41 0.16 

mCS0 ij1 − i•1 x x β 6 -0.03 0.07 -0.52 0.60 

mIW i•2 x β12 0.10 0.20 0.52 0.60 

mIW0 ij 2 − i•2 x x β 7 0.05 0.03 2.05 0.04 

mMOB i•3 x β13 0.04 0.14 0.31 0.76 

mMOB0 ij3 − i•3 x x β 8 0.04 0.02 1.93 0.05 

mPTP i•4 x β14 0.42 0.34 1.21 0.22 

mPTP0 ij 4 − i•4 x x β 9 0.05 0.03 1.73 0.08 

mNJH i•5 x β15 0.29 0.12 2.41 0.02 

mNJH0 ij5 − i•5 x x β10 0.05 0.02 2.16 0.03 

rxbeta Θij1 β1 0 -1.73 0.77 -2.24 0.03 

rxbeta Θij2 β 2 1 -1.71 0.78 -2.19 0.03 

rxbeta Θij3 β 3 2 -1.80 0.78 -2.32 0.02 

rxbeta Θij4 β 4 3 -1.70 0.78 -2.18 0.03 

rxbeta Θij5 β 5 4 -1.74 0.78 -2.22 0.03 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.05 0.06 0.90 0.37 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.08 0.06 1.30 0.20 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 -0.04 0.05 -0.78 0.43 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 -0.01 0.06 -0.25 0.81 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.02 0.01 

Residual 

variance 2 σ e 1.08 0.03 

GEAR UP Ti δ -0.03 0.08 -0.34 0.74 

*See table E-9 for explanation of effect variables.
E-17 

Table E-12. Beta coefficients for HLM for the variable CollegeBoundRev 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

Mp π i• β 22 -0.75 12.05 -0.06 0.95 

mP0 π ij −π i• β 21 -2.00 3.58 -0.56 0.58 

mBV 

7

i• y β 24 0.68 0.14 4.89 <.0001

mBV0 

7 7

ij − i• y y β 23 0.61 0.04 14.27 <.0001

mCS i•1 x β11 5.68 3.75 1.51 0.13 

mCS0 ij1 − i•1 x x β 6 0.55 0.46 1.20 0.23 

mIW i•2 x β12 -0.62 2.11 -0.29 0.77 

mIW0 ij 2 − i•2 x x β 7 -0.54 0.20 -2.62 0.01 

mMOB i•3 x β13 -0.87 0.85 -1.03 0.30 

mMOB0 ij3 − i•3 x x β 8 -0.09 0.12 -0.75 0.45 

mPTP i•4 x β14 6.39 3.32 1.92 0.05 

mPTP0 ij 4 − i•4 x x β 9 -0.02 0.19 -0.11 0.91 

mNJH i•5 x β15 0.44 1.79 0.25 0.81 

mNJH0 ij5 − i•5 x x β10 0.39 0.22 1.80 0.07 

rxbeta Θij1 β1 0 -15.49 8.75 -1.77 0.08 

rxbeta Θij2 β 2 1 -14.81 8.93 -1.66 0.10 

rxbeta Θij3 β 3 2 -15.38 9.07 -1.69 0.09 

rxbeta Θij4 β 4 3 -16.14 8.99 -1.80 0.07 

rxbeta Θij5 β 5 4 -16.63 9.24 -1.80 0.07 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.24 0.07 3.42 0.00 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.10 0.06 1.69 0.09 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.10 0.06 1.68 0.09 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 0.01 0.05 0.12 0.90 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 1.49 0.60 

Residual 

variance 2 σ e 62.26 1.59 

GEAR UP Ti δ -0.04 0.61 -0.06 0.95 

*See table E-9 for explanation of effect variables. 
 E-18 

Table E-13. Beta coefficients for HLM for the variable ECBusy 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

Mp π i• β 22 0.92 6.24 0.15 0.88 

mP0 π ij −π i• β 21 -2.58 2.25 -1.15 0.25 

mBV 

7

i• y β 24 0.68 0.11 6.45 <.0001

mBV0 

7 7

ij − i• y y β 23 0.35 0.03 10.22 <.0001

mCS i•1 x β11 -0.56 1.95 -0.29 0.77 

mCS0 ij1 − i•1 x x β 6 -0.07 0.17 -0.43 0.67 

mIW i•2 x β12 0.48 0.66 0.73 0.47 

mIW0 ij 2 − i•2 x x β 7 0.17 0.07 2.32 0.02 

mMOB i•3 x β13 -0.53 0.45 -1.18 0.24 

mMOB0 ij3 − i•3 x x β 8 -0.06 0.06 -1.03 0.30 

mPTP i•4 x β14 0.46 0.91 0.51 0.61 

mPTP0 ij 4 − i•4 x x β 9 0.13 0.09 1.50 0.13 

mNJH i•5 x β15 0.67 0.47 1.43 0.15 

mNJH0 ij5 − i•5 x x β10 0.09 0.08 1.06 0.29 

rxbeta Θij1 β1 0 0.71 3.09 0.23 0.82 

rxbeta Θij2 β 2 1 0.75 3.21 0.23 0.82 

rxbeta Θij3 β 3 2 0.54 3.31 0.16 0.87 

rxbeta Θij4 β 4 3 0.56 3.36 0.17 0.87 

rxbeta Θij5 β 5 4 0.92 3.45 0.27 0.79 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.30 0.05 6.32 <.0001

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.26 0.04 6.13 <.0001

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.10 0.05 2.14 0.03 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 0.09 0.05 1.94 0.05 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.25 0.10 

Residual 

variance 2 σ e 11.78 0.30 

GEAR UP Ti δ -0.33 0.20 -1.66 0.10 

*See table E-9 for explanation of effect variables. 
E-19 

Table E-14. Beta coefficients for HLM for the variable ExpectSERev 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

Mp π i• β 22 1.62 5.38 0.30 0.76 

mP0 π ij −π i• β 21 -3.19 2.22 -1.44 0.15 

mBV 

7

i• y β 24 0.49 0.11 4.34 <.0001

mBV0 

7 7

ij − i• y y β 23 0.36 0.04 9.38 <.0001

mCS i•1 x β11 1.34 1.60 0.84 0.40 

mCS0 ij1 − i•1 x x β 6 -0.18 0.26 -0.71 0.48 

mIW i•2 x β12 0.04 0.61 0.06 0.95 

mIW0 ij 2 − i•2 x x β 7 0.13 0.10 1.35 0.18 

mMOB i•3 x β13 -0.57 0.36 -1.60 0.11 

mMOB0 ij3 − i•3 x x β 8 0.07 0.06 1.30 0.19 

mPTP i•4 x β14 3.62 1.02 3.57 0.00 

mPTP0 ij 4 − i•4 x x β 9 0.17 0.10 1.69 0.09 

mNJH i•5 x β15 0.64 0.53 1.21 0.23 

mNJH0 ij5 − i•5 x x β10 0.16 0.11 1.50 0.13 

rxbeta Θij1 β1 0 -7.65 3.28 -2.33 0.02 

rxbeta Θij2 β 2 1 -7.45 3.38 -2.21 0.03 

rxbeta Θij3 β 3 2 -7.67 3.47 -2.21 0.03 

rxbeta Θij4 β 4 3 -7.67 3.45 -2.22 0.03 

rxbeta Θij5 β 5 4 -7.66 3.58 -2.14 0.03 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.27 0.05 4.95 <.0001

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.21 0.05 4.03 <.0001

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.16 0.05 3.27 0.00 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 0.04 0.06 0.62 0.54 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.25 0.11 

Residual 

variance 2 σ e 15.34 0.39 

GEAR UP Ti δ 0.22 0.24 0.93 0.35 

*See table E-9 for explanation of effect variables. 
 E-20 

Table E-15. Beta coefficients for HLM for the variable HeardOfSchools (contaminated) 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

Mp π i• β 22 -13.49 3.79 -3.56 0.00 

mP0 π ij −π i• β 21 -3.28 1.39 -2.36 0.02 

mCS i•1 x β11 0.40 1.18 0.34 0.73 

mCS0 ij1 − i•1 x x β 6 0.01 0.12 0.11 0.91 

mIW i•2 x β12 -0.17 0.35 -0.48 0.63 

mIW0 ij 2 − i•2 x x β 7 0.07 0.05 1.46 0.14 

mMOB i•3 x β13 -0.14 0.24 -0.61 0.54 

mMOB0 ij3 − i•3 x x β 8 0.08 0.05 1.62 0.11 

mPTP i•4 x β14 0.25 0.76 0.33 0.74 

mPTP0 ij 4 − i•4 x x β 9 0.13 0.07 1.78 0.08 

mNJH i•5 x β15 -1.59 0.38 -4.13 <.0001

mNJH0 ij5 − i•5 x x β10 0.05 0.06 0.92 0.36 

rxbeta Θij1 β1 0 6.26 1.98 3.16 0.00 

rxbeta Θij2 β 2 1 6.32 2.05 3.09 0.00 

rxbeta Θij3 β 3 2 6.41 2.06 3.11 0.00 

rxbeta Θij4 β 4 3 6.43 2.11 3.05 0.00 

rxbeta Θij5 β 5 4 6.70 2.13 3.15 0.00 

Variance of 

school-level 

random effects 2 σ u 0.19 0.07 

Residual 

variance 2 σ e 5.12 0.15 

GEAR UP Ti δ 0.35 0.16 2.23 0.03 

*See table E-9 for explanation of effect variables. 
E-21 

Table E-16. Beta coefficients for HLM for the variable HomeWorkHours 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate

Standard 

error t Value Pr > |t| 

 

Mp π i• β 22 -1.6 1.09 -1.49 0.14 

mP0 π ij −π i• β 21 0.22 0.48 0.47 0.64 

mBV 

7

i• y β 24 0.1 0.13 0.74 0.46 

mBV0 

7 7

ij − i• y y β 23 0.19 0.04 4.24 <.0001

mCS i•1 x β11 0.18 0.36 0.49 0.62 

mCS0 ij1 − i•1 x x β 6 -0.1 0.05 -1.17 0.24 

mIW i•2 x β12 -0 0.10 -0.43 0.67 

mIW0 ij 2 − i•2 x x β 7 0.05 0.02 2.21 0.03 

mMOB i•3 x β13 -0 0.09 -0.10 0.92 

mMOB0 ij3 − i•3 x x β 8 -0 0.02 -0.25 0.80 

mPTP i•4 x β14 -0.3 0.24 -1.45 0.15 

mPTP0 ij 4 − i•4 x x β 9 0.07 0.03 2.55 0.01 

mNJH i•5 x β15 0.13 0.11 1.20 0.23 

mNJH0 ij5 − i•5 x x β10 0.03 0.03 1.03 0.30 

rxbeta Θij1 β1 0 1.37 0.62 2.22 0.03 

rxbeta Θij2 β 2 1 1.32 0.63 2.10 0.04 

rxbeta Θij3 β 3 2 1.25 0.64 1.96 0.05 

rxbeta Θij4 β 4 3 1.21 0.64 1.88 0.06 

rxbeta Θij5 β 5 4 1.24 0.65 1.90 0.06 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.07 0.07 0.98 0.33 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.05 0.07 0.80 0.43 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.04 0.05 0.72 0.47 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 -0.2 0.06 -2.66 0.01 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0 . . . 

Variance of 

school-level 

random effects 2 σ u 0.01 0.01 

Residual 

variance 2 σ e 1.09 0.03 

GEAR UP Ti δ 0.02 0.04 0.39 0.70 

*See table E-9 for explanation of effect variables. 
 E-22 

Table E-17. Beta coefficients for HLM for the variable NegJunkHours 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 -0.72 1.16 -0.62 0.54 

mP0 π ij −π i• β 21 0.33 0.71 0.47 0.64 

mCS i•1 x β11 0.48 0.09 5.18 <.0001 

mCS0 ij1 − i•1 x x β 6 0.32 0.05 6.39 <.0001 

mIW i•2 x β12 0.33 0.48 0.70 0.48 

mIW0 ij 2 − i•2 x x β 7 -0.04 0.07 -0.56 0.57 

mMOB i•3 x β13 -0.25 0.12 -2.09 0.04 

mMOB0 ij3 − i•3 x x β 8 0.03 0.02 1.58 0.12 

mPTP i•4 x β14 -0.11 0.09 -1.25 0.21 

mPTP0 ij 4 − i•4 x x β 9 0.01 0.02 0.75 0.45 

mNJH i•5 x β15 -0.40 0.19 -2.06 0.04 

mNJH0 ij5 − i•5 x x β10 0.02 0.02 0.63 0.53 

rxbeta Θij1 β1 0 1.06 0.60 1.77 0.08 

rxbeta Θij2 β 2 1 1.03 0.62 1.65 0.10 

rxbeta Θij3 β 3 2 0.89 0.65 1.36 0.17 

rxbeta Θij4 β 4 3 0.76 0.66 1.15 0.25 

rxbeta Θij5 β 5 4 0.97 0.67 1.43 0.15 

Variance of 

school-level 

random effects 2 σ u 0.01 0.01 

Residual 

variance 2 σ e 0.88 0.02 

GEAR UP Ti δ -0.03 0.05 -0.70 0.49 

*See table E-9 for explanation of effect variables. 
E-23 

Table E-18. Beta coefficients for HLM for the variable Performance 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 5.73 2.96 1.93 0.05 

mP0 π ij −π i• β 21 0.13 0.98 0.13 0.90 

mBV 

7

i• y β 24 0.30 0.14 2.17 0.03 

mBV0 

7 7

ij − i• y y β 23 0.49 0.04 12.10 <.0001

mCS i•1 x β11 -0.31 0.85 -0.37 0.71 

mCS0 ij1 − i•1 x x β 6 -0.28 0.10 -2.83 0.00 

mIW i•2 x β12 0.15 0.43 0.35 0.73 

mIW0 ij 2 − i•2 x x β 7 0.02 0.04 0.61 0.55 

mMOB i•3 x β13 -0.48 0.23 -2.06 0.04 

mMOB0 ij3 − i•3 x x β 8 0.00 0.04 -0.01 1.00 

mPTP i•4 x β14 1.99 0.78 2.56 0.01 

mPTP0 ij 4 − i•4 x x β 9 0.12 0.06 1.98 0.05 

mNJH i•5 x β15 1.08 0.43 2.53 0.01 

mNJH0 ij5 − i•5 x x β10 0.16 0.04 3.52 0.00 

rxbeta Θij1 β1 0 -4.86 2.21 -2.20 0.03 

rxbeta Θij2 β 2 1 -4.96 2.25 -2.20 0.03 

rxbeta Θij3 β 3 2 -5.08 2.29 -2.22 0.03 

rxbeta Θij4 β 4 3 -5.10 2.29 -2.23 0.03 

rxbeta Θij5 β 5 4 -5.16 2.32 -2.23 0.03 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.11 0.06 1.67 0.10 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 -0.04 0.05 -0.82 0.42 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 -0.06 0.06 -1.05 0.30 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 -0.05 0.06 -0.75 0.45 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.09 0.04 

Residual 

variance 2 σ e 4.21 0.11 

GEAR UP Ti δ 0.09 0.14 0.60 0.55 

*See table E-9 for explanation of effect variables. 
 E-24 

Table E-19. Beta coefficients for HLM for the variable ParInvolve 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 -2.18 5.30 -0.41 0.68 

mP0 π ij −π i• β 21 1.09 1.74 0.63 0.53 

mBV 

7

i• y β 24 0.44 0.12 3.69 0.00 

mBV0 

7 7

ij − i• y y β 23 0.35 0.04 8.39 <.0001

mCS i•1 x β11 -0.40 1.29 -0.31 0.76 

mCS0 ij1 − i•1 x x β 6 -0.29 0.12 -2.31 0.02 

mIW i•2 x β12 0.19 0.47 0.40 0.69 

mIW0 ij 2 − i•2 x x β 7 -0.05 0.08 -0.62 0.54 

mMOB i•3 x β13 0.23 0.31 0.72 0.47 

mMOB0 ij3 − i•3 x x β 8 0.00 0.06 0.03 0.98 

mPTP i•4 x β14 1.01 0.88 1.15 0.25 

mPTP0 ij 4 − i•4 x x β 9 0.16 0.07 2.13 0.03 

mNJH i•5 x β15 -0.33 0.50 -0.66 0.51 

mNJH0 ij5 − i•5 x x β10 0.03 0.06 0.45 0.66 

rxbeta Θij1 β1 0 -0.33 2.84 -0.12 0.91 

rxbeta Θij2 β 2 1 -0.83 2.92 -0.28 0.78 

rxbeta Θij3 β 3 2 -1.34 2.98 -0.45 0.65 

rxbeta Θij4 β 4 3 -1.44 2.93 -0.49 0.62 

rxbeta Θij5 β 5 4 -1.69 3.03 -0.56 0.58 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.04 0.07 0.59 0.55 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.03 0.06 0.55 0.58 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.00 0.06 -0.07 0.94 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 -0.11 0.07 -1.55 0.12 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.20 0.09 

Residual 

variance 2 σ e 11.73 0.30 

GEAR UP Ti δ 0.75 0.19 3.98 <.0001

*See table E-9 for explanation of effect variables. 
E-25 

Table E-20. Beta coefficients for HLM for the variable PExpect (contaminated) 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate 

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 5.81 3.75 1.55 0.12 

mP0 π ij −π i• β 21 -1.67 1.74 -0.96 0.34 

mCS i•1 x β11 -0.03 1.07 -0.03 0.98 

mCS0 ij1 − i•1 x x β 6 -0.05 0.12 -0.40 0.69 

mIW i•2 x β12 0.57 0.47 1.22 0.22 

mIW0 ij 2 − i•2 x x β 7 0.06 0.06 1.16 0.25 

mMOB i•3 x β13 -0.28 0.28 -1.00 0.32 

mMOB0 ij3 − i•3 x x β 8 0.02 0.05 0.35 0.73 

mPTP i•4 x β14 3.05 0.61 4.98 <.0001

mPTP0 ij 4 − i•4 x x β 9 0.34 0.07 4.75 <.0001

mNJH i•5 x β15 1.24 0.32 3.91 <.0001

mNJH0 ij5 − i•5 x x β10 0.17 0.06 2.63 0.01 

rxbeta Θij1 β1 0 -7.64 1.82 -4.20 <.0001

rxbeta Θij2 β 2 1 -7.65 1.91 -4.01 <.0001

rxbeta Θij3 β 3 2 -7.95 1.96 -4.05 <.0001

rxbeta Θij4 β 4 3 -7.90 2.01 -3.94 <.0001

rxbeta Θij5 β 5 4 -7.85 2.02 -3.88 0.00 

Variance of 

school-level 

random effects 2 σ u 0.09 0.05 

Residual 

variance 2 σ e 7.43 0.19 

GEAR UP Ti δ 0.13 0.15 2.02 0.04 

*See table E-9 for explanation of effect variables. 
 E-26 

Table E-21. Beta coefficients for HLM for the variable PPartCB 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 5.13 5.21 0.98 0.33 

mP0 π ij −π i• β 21 -1.39 1.94 -0.72 0.47 

mBV 

7

i• y β 24 0.54 0.14 3.80 0.00 

mBV0 

7 7

ij − i• y y β 23 0.47 0.03 14.04 <.0001 

mCS i•1 x β11 -0.45 1.34 -0.33 0.74 

mCS0 ij1 − i•1 x x β 6 -0.22 0.18 -1.20 0.23 

mIW i•2 x β12 -0.18 0.75 -0.24 0.81 

mIW0 ij 2 − i•2 x x β 7 0.02 0.09 0.28 0.78 

mMOB i•3 x β13 -0.52 0.37 -1.42 0.16 

mMOB0 ij3 − i•3 x x β 8 -0.02 0.07 -0.22 0.82 

mPTP i•4 x β14 3.13 1.26 2.49 0.01 

mPTP0 ij 4 − i•4 x x β 9 0.33 0.11 3.13 0.00 

mNJH i•5 x β15 0.97 0.72 1.36 0.17 

mNJH0 ij5 − i•5 x x β10 0.23 0.08 3.03 0.00 

rxbeta Θij1 β1 0 -6.51 3.93 -1.66 0.10 

rxbeta Θij2 β 2 1 -6.31 4.04 -1.56 0.12 

rxbeta Θij3 β 3 2 -6.64 4.13 -1.61 0.11 

rxbeta Θij4 β 4 3 -6.61 4.11 -1.61 0.11 

rxbeta Θij5 β 5 4 -6.72 4.20 -1.60 0.11 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.16 0.05 3.09 0.00 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.02 0.06 0.36 0.72 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.02 0.05 0.37 0.71 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 -0.04 0.05 -0.83 0.41 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.22 0.10 

Residual 

variance 2 σ e 13.22 0.34 

GEAR UP Ti δ 0.21 0.24 0.89 0.37 

*See table E-9 for explanation of effect variables. 
E-27 

Table E-22. Beta coefficients for HLM for the variable SDiligent 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 4.39 2.07 2.12 0.03 

mP0 π ij −π i• β 21 -1.01 1.05 -0.96 0.34 

mBV 

7

i• y β 24 0.81 0.10 8.47 <.0001

mBV0 

7 7

ij − i• y y β 23 0.21 0.06 3.72 0.00 

mCS i•1 x β11 -0.98 0.63 -1.57 0.12 

mCS0 ij1 − i•1 x x β 6 -0.11 0.09 -1.21 0.23 

mIW i•2 x β12 -0.09 0.30 -0.31 0.76 

mIW0 ij 2 − i•2 x x β 7 0.02 0.04 0.56 0.57 

mMOB i•3 x β13 -0.12 0.16 -0.77 0.44 

mMOB0 ij3 − i•3 x x β 8 0.01 0.04 0.31 0.75 

mPTP i•4 x β14 0.25 0.41 0.61 0.54 

mPTP0 ij 4 − i•4 x x β 9 0.09 0.05 1.95 0.05 

mNJH i•5 x β15 0.19 0.23 0.84 0.40 

mNJH0 ij5 − i•5 x x β10 0.11 0.04 2.46 0.01 

rxbeta Θij1 β1 0 -1.43 1.13 -1.26 0.21 

rxbeta Θij2 β 2 1 -1.47 1.17 -1.26 0.21 

rxbeta Θij3 β 3 2 -1.25 1.20 -1.04 0.30 

rxbeta Θij4 β 4 3 -1.35 1.24 -1.08 0.28 

rxbeta Θij5 β 5 4 -1.20 1.27 -0.94 0.34 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.13 0.08 1.71 0.09 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.10 0.06 1.59 0.11 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.08 0.07 1.17 0.24 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 -0.03 0.06 -0.42 0.67 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.05 0.02 

Residual 

variance 2 σ e 3.02 0.08 

GEAR UP Ti δ -0.05 0.11 -0.42 0.68 

*See table E-9 for explanation of effect variables. 
 E-28 

Table E-23. Beta coefficients for HLM for the variable SPartCB 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 -2.72 8.47 -0.32 0.75 

mP0 π ij −π i• β 21 -1.81 3.36 -0.54 0.59 

mBV 

7

i• y β 24 0.61 0.17 3.59 0.00 

mBV0 

7 7

ij − i• y y β 23 0.51 0.04 12.30 <.0001

mCS i•1 x β11 5.48 3.24 1.69 0.09 

mCS0 ij1 − i•1 x x β 6 0.45 0.41 1.11 0.27 

mIW i•2 x β12 0.08 1.52 0.05 0.96 

mIW0 ij 2 − i•2 x x β 7 -0.33 0.17 -1.95 0.05 

mMOB i•3 x β13 -0.62 0.62 -1.00 0.32 

mMOB0 ij3 − i•3 x x β 8 -0.06 0.09 -0.60 0.55 

mPTP i•4 x β14 4.52 2.46 1.84 0.07 

mPTP0 ij 4 − i•4 x x β 9 -0.12 0.14 -0.83 0.41 

mNJH i•5 x β15 0.12 1.13 0.10 0.92 

mNJH0 ij5 − i•5 x x β10 0.27 0.19 1.41 0.16 

rxbeta Θij1 β1 0 -11.35 5.67 -2.00 0.05 

rxbeta Θij2 β 2 1 -11.07 5.79 -1.91 0.06 

rxbeta Θij3 β 3 2 -11.33 5.91 -1.92 0.06 

rxbeta Θij4 β 4 3 -12.05 5.84 -2.06 0.04 

rxbeta Θij5 β 5 4 -12.39 6.04 -2.05 0.04 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 0.26 0.07 3.62 0.00 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.18 0.07 2.47 0.01 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.15 0.06 2.57 0.01 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 0.01 0.05 0.29 0.77 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.71 0.30 

Residual 

variance 2 σ e 37.15 0.95 

GEAR UP Ti δ -0.12 0.42 -0.27 0.78 

*See table E-9 for explanation of effect variables. 
E-29 

Table E-24. Beta coefficients for HLM for the variable TalkCoursePlanning 

Effect* 

Predictor 

variable in 

equation (2) 

Parameter 

symbol 

Value of 

categorical 

predictor Estimate

Standard 

error t Value Pr > |t| 

 

mP π i• β 22 -5.00 3.44 -1.45 0.15 

mP0 π ij −π i• β 21 -3.51 1.28 -2.75 0.01 

mBV 

7

i• y β 24 0.08 0.15 0.55 0.59 

mBV0 

7 7

ij − i• y y β 23 0.12 0.04 3.19 0.00 

mCS i•1 x β11 0.79 0.92 0.87 0.39 

mCS0 ij1 − i•1 x x β 6 0.18 0.12 1.45 0.15 

mIW i•2 x β12 0.90 0.37 2.42 0.02 

mIW0 ij 2 − i•2 x x β 7 0.17 0.05 3.63 0.00 

mMOB i•3 x β13 -0.20 0.21 -0.95 0.34 

mMOB0 ij3 − i•3 x x β 8 0.04 0.04 1.01 0.31 

mPTP i•4 x β14 1.51 0.66 2.30 0.02 

mPTP0 ij 4 − i•4 x x β 9 0.12 0.05 2.32 0.02 

mNJH i•5 x β15 -0.73 0.28 -2.59 0.01 

mNJH0 ij5 − i•5 x x β10 0.04 0.05 0.80 0.42 

rxbeta Θij1 β1 0 -0.97 1.87 -0.52 0.60 

rxbeta Θij2 β 2 1 -0.87 1.88 -0.46 0.65 

rxbeta Θij3 β 3 2 -0.77 1.92 -0.40 0.69 

rxbeta Θij4 β 4 3 -0.59 1.92 -0.31 0.76 

rxbeta Θij5 β 5 4 -0.49 1.96 -0.25 0.80 

mBV0(rxbeta) ( ) 7

1

7 Θij1 ij1 − i• y y β16 0 -0.02 0.06 -0.31 0.76 

mBV0(rxbeta) ( ) 7

2

7 Θij2 ij2 − i• y y β17 1 0.13 0.06 2.37 0.02 

mBV0(rxbeta) ( ) 7

3

7 Θij3 ij3 − i• y y β18 2 0.05 0.05 1.10 0.27 

mBV0(rxbeta) ( ) 7

4

7 Θij4 ij4 − i• y y β19 3 0.05 0.05 0.99 0.32 

mBV0(rxbeta) ( ) 7

5

7 Θij5 ij5 − i• y y β 20 4 0.00 . . . 

Variance of 

school-level 

random effects 2 σ u 0.11 0.05 

Residual 

variance 2 σ e 5.31 0.14 

GEAR UP Ti δ 0.59 0.15 4.05 <.0001

*See table E-9 for explanation of effect variables. 

F-1 

Appendix F 

Hierarchical Linear Modeling (HLM) Simulation Study 

Although the field of hierarchical linear models has seen a tremendous expansion in use, in part due to 

improved software and textbooks∗

 and has been extensively researched for many more years, one area 

that has not received much attention is whether it is possible to use information about sample subjects 

within clusters to estimate cluster-level covariates and then control on those estimated cluster-level 

covariates in the analysis of individual outcomes. For this study, a small simulation study was undertaken 

to study the issue. This appendix documents the methods and results of that study. 

F.1 Simulation Model 

In this stimulation study, a sample of 80,000 students in 1,000 schools was created, with a constant 80 

students per school. Both school-level and student-level covariates were simulated. The 1,000 schools 

were split into two groups of 500 each with probabilities that were a function of the school-level 

covariates, thereby creating a selection bias. Student-level outcomes were simulated that were a function 

of baseline student-level covariates, baseline school-level covariates, treatment status and random errors 

at both the school and student levels. This simulated data set was then analyzed with the same HLM 

software used to analyze the Gaining Early Awareness and Readiness for Undergraduate Programs 

(GEAR UP) data. 

Before describing the model in more detail, several caveats are noted. First, the numbers of schools and 

students simulated are much larger than was available in the GEAR UP evaluation, although the number 

of students per school was comparable. The idea was to see if the technique would at least work with very 

large sample sizes. It probably does not work as well with smaller sample sizes available in the GEAR UP 

evaluation. Second, only a single replication of the simulation was carried out. Ideally, several hundred 

replications would have been carried out. Time and resources did not permit this level of effort. 

A number of steps were involved in constructing and analyzing the simulated data set. First, a set of 

independent school-level latent variables was constructed. Second, the school-level covariates were used 

to generate a set of independent student-level latent variables. Third, these were mixed to create a 

correlated set of student-level manifest covariates and a latent true baseline score on the outcome variable. 

Fourth, measurement noise was added to the latent true baseline outcome to create a manifest baseline 

outcome. Fifth, the manifest student-level covariates were averaged within schools to create manifest 

school-level covariates. Sixth, the manifest student- and school-level covariates were mixed to create a 

latent student-level treatment propensity. Seventh, the latent student-level treatment propensities were 

averaged within schools to create a preliminary latent school-level treatment propensity. Eighth, these 

preliminary latent school-level treatment propensities were stretched out some to produce greater 

variability across schools. Ninth, a set of 500 schools was randomly selected with probability 

proportionate to the stretched latent school-level treatment propensity. Tenth, the students were classified 

 

∗

 A.S. Bryk, and S.W. Raudenbush. Hierarchical Linear Models: Application and Data Analysis Methods. Newbury Park, 

Calif.: Sage Publications; 1992; P.J. Diggle, K.Y. Liang, and S.L. Zeger. Analysis of Longitudinal Data. Oxford: Clarendon 

Press, 1994; H. Goldstein. Multi-level Statistical Models, 2d ed. London: Arnold, 1995; C.E. McCulloch, and S.R. Searle. 

Generalized, Linear and Mixed Models. New York: John Wiley and Sons, 2001. 
 F-2 

into quintiles of personal treatment propensities. Eleventh, the follow-up outcomes were generated as a 

function of all the other variables generated thus far. Finally, the data set was analyzed using Proc Mixed. 

The latent school-level covariates were generated as 

2 ~ (0, ) L N i τ l l , for i=1 to 1,000 and l =1 to 8, 

with variances 70, 80, 90, 100, 105, 110, 120, and 130. 

The latent student-level covariates were then generated as 

2 ~(, ) ij i g NL l ll σ , for i=1 to 1,000; l =1 to 8, and j=1 to 80, 

with variances 930, 920, 910, 900, 895, 890, 880, and 870. 

The manifest student-level covariates were then generated as 

8

1

~ (0.46) ,784 ij t ijt

t

xN g φ

=

⎛ ⎞ = ⎜ ⎟ ⎝ ⎠ l l ∑ , for i=1 to 1,000; l =1 to 8, and j =1 to 80 

and latent true baseline outcome as 

8

7

9

1

~ (0.46) ,784 T

ij t ijt

t

yN g φ

=

⎛ ⎞ = ⎜ ⎟ ⎝ ⎠ ∑ for i=1 to 1,000; and j =1 to 80, 

where the phi terms were 

 ( .90 .30 .05 .05 .05 .05 .05 .05 

 .05 .90 .30 .05 .05 .05 .05 .05 

 .05 .05 .90 .30 .05 .05 .05 .05 

 .05 .05 .05 .90 .30 .05 .05 .05 

 .05 .05 .05 .05 .90 .30 .05 .05 

 .05 .05 .05 .05 .05 .90 .30 .05 

 .05 .05 .05 .05 .05 .05 .90 .30 

 .30 .05 .05 .05 .05 .05 .05 .90 

 .20 .30 .20 .20 .40 .30 .05 .40) 

The manifest true baseline outcomes were then simulated as 

( ) 7 7 ~ (0.95) ,100 T

ij ij y N y for i=1 to 1,000; and j =1 to 80 

Note that the 100 represents measurement variance and the factor of 0.95 a slight measurement bias. 

These measurement errors were introduced because of concern that the method would not work well if 

they were present. 
F-3 

The manifest school-level covariates were then generated as 

80

1

1

80 i ij

j

x x •

=

l l = ∑ for i=1 to 1,000; and l =1 to 8. 

The student-level logit propensities were then calculated as 

9 9

1 2

1 1

1 ln

1 250

ij

ij i

ij

x x

π

α α

π •

= =

⎛ ⎞ ⎛ ⎞ ⎜ ⎟ = + ⎜ ⎟ ⎝ ⎠ − ⎝ ⎠ ∑ ∑ ll l l

l l

, 

where the alpha parameters are shown in Table F-1. 

Table F-1. Model for student-level treatment propensity 

Variable name Var index l α1l α2l

Renumbered index for 

outcome model 

Volunteerism 1 +0.5 0 n/a 

ClassSkipping 2 -1.5 -0.4 1 

ImpWork 3 -2.0 -0.6 2 

Mobility 4 -1.7 0 3 

ParTalkPolitics 5 -1.9 0 4 

White 6 -0.5 0 n/a 

Other adult 7 -0.4 0 n/a 

NegativeJunkHours 8 -1.9 0 5 

True baseline outcome 9 -0.02 +0.02 n/a 

These were then converted to treatment propensities with the equation 

( )

( )

exp

1 exp

ij

ij

ij

x

x

α

π

α = +

%

%

These were then averaged to the school level 

80

1

1

80 i ij

j

π • π

=

= ∑

and then stretched out as 

( ) { }

{ } { }

0.7 min

MOS 0.15

max min

i i i

i

i i i i

π π

π π

• •

• •

−

= + − , 

with values outside the range of 0 to 1, shrunk back to the nearest boundary of the range. 
 F-4 

These measures of size were then used in a systematic probability, proportionate-to-size sampling 

program that selected 500 of the 1,000 schools as treatment schools. The remainder were treated as 

control schools. 

Students were ranked into five strata of π ij with belonging to a particular stratum indicated by the binary 

flag Θijl for i=1 to 1,000; and j =1 to 80, and l =1 to 5. 

Of the eight student-level covariates and eight school-level covariates, only five were used to generate the 

dependent variable. The renumbering of the covariates is shown in the last column of table F-1. The 

dependent variable (followup outcome) was then simulated as 

55 5 5

8

5 10

11 1 1

5

77 77 7

15 21 22 23 24

1

( )

( )[ ] ( ) ,

ij i ij ij ij i i

TT TT T

ij ij i ij i i ij i i i ij

yT x x x

y y y y y ue

δβ β β

β π π β πβ β β

•+ •+

== = =

•+ • • • •

=

= Θ +Θ + − + +

Θ − + − + + − + ++

∑∑∑ ∑

∑

ll l l l l l l l

ll l l

ll l l

l

where the beta coefficients are given in table F-2, 

~ N(0,9) i u and ~ N(0,16) ij e . 

After generating the population, the same software was used to analyze it as was used for the actual 

analysis, as described in appendix E under the HLM section. Note that the true baseline outcomes (student 

and school level) were used to generate followup outcomes, but that manifest baseline outcomes (student 

and school level) were used in the model fitting to see if the procedure was sensitive to measurement error 

in the baseline outcome. Also note that true propensities were given to the model procedure rather than 

estimated propensities. It would have been a tougher test to force the modeling procedure to use estimated 

propensities, but the test was still fairly stringent. 

Reviewing the test results, several features stand out. First and most important, the treatment effects are 

unbiasedly recovered with tight confidence intervals. (See first five data rows of table F-2.) This was, of 

course, the result that was desired. 

Second, the model failed in sorting out the separate effects of the variables through the propensities. All 

of the coefficients for terms involving the propensities (both categorical and continuous) are extremely 

unstable. Because these are nuisance parameters, this instability is not much of an issue, but it does 

perhaps indicate that it is not very helpful to include the propensities in addition to the variables that 

predict the propensities. A separate run (not shown) was made omitting the terms for the propensities. The 

results of this run for the rest of the model were not appreciably affected despite the fact that more 

variables were used to generate the propensities than were used in the modeling. So it does not appear to 

matter very much whether the propensity scores are added to the model in addition to the variables that 

are important in the propensity model. 

Third, the model produces highly biased estimates of the effects of both the student- and school-level 

covariates. All these estimates are strongly biased toward zero. Again, these are nuisance parameters of 

little interest in the evaluation. However, it does indicate that if one were interested in separately 

estimating the effects of student-level and school-level covariates, it does not work well to estimate the 

school-level covariates as the average of the student-level covariates and then include both in the model. 
F-5 

Table F-2. True and fitted models for followup outcome 

Variable 

Level/ 

index 

True 

parameter

Estimated 

parameter 

Standard 

error 

Treatment effect by propensity stratum 1 -10.0 -10.2 0.2 

 2 -5.0 -5.0 0.2 

 3 0.0 -0.3 0.2 

 4 10.0 10.0 0.2 

 5 15.0 14.8 0.2 

 

Propensity stratum 1 2.0 1.1 12.0 

 2 0.5 0.2 12.0 

 3 -0.2 -0.1 12.0 

 4 -0.1 -0.2 12.0 

 5 0.0 -0.1 12.0 

 

Student-level covariate 1 -3.6 -0.72 0.04 

 2 3.9 0.77 0.06 

 3 -2.0 -0.41 0.04 

 4 12.5 2.49 0.05 

 5 5.2 1.04 0.05 

 

School-level covariate 1 -2.9 -0.580 0.002 

 2 2.2 0.436 0.002 

 3 0.2 0.039 0.002 

 4 2.5 0.499 0.002 

 5 1.1 0.218 0.002 

 

Interaction of baseline outcome with propensity stratum 1 0.0 -0.000 0.003 

 2 0.0 -0.003 0.003 

 3 0.0 -0.002 0.003 

 4 0.0 -0.002 0.003 

 5 0.0 0.0 N/A 

 

Student-level propensity (continuous) 0.01 -5.0 24.0 

School-level average propensity (continuous) -0.2 -3.5 1.3 

Student-level baseline outcome 0.68 0.66 0.03 

School-level average baseline outcome 0.61 0.570 0.002 

School-level random effect 9.0 9.9 0.5 

Student-level random error 16.0 53.0 0.3 
 F-6 

Fourth, the school-level random effect is well estimated, but the residual student-level random error is 

strongly overestimated. This positive bias in the residual variance is no doubt linked to the shrinkage bias 

in the fixed covariates. For some reason, the modeling procedure could not tease out the fixed effects of 

the covariates and as a result found larger residual error than truly existed. Again, the deficiencies in the 

modeling software have no impact on the evaluation report because the treatment effects were very well 

estimated. 
G-1 

Appendix G 

Methodology for Analyzing Transcript Data 

Transcript information consisting of report cards and standardized test scores was requested for all 

Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) and non-GEAR UP 

students participating in the national evaluation with parent consents obtained for these data. Information 

describing the students’ eighth grade was analyzed for the national evaluation. To compare the student 

transcripts across schools, the national evaluation modified the Classification of Secondary School 

Courses (CSSC) developed by the National Center for Education Statistics (NCES) for use with middle 

schools. The CSSC was designed to describe course offerings in secondary education and to provide a 

coherent means for classifying these courses.60 The middle school CSSC developed for the national 

evaluation appears in table G-1. 

To aid in the classification of classes, school course catalogs and master schedules for classes were 

requested from schools. However, several schools were not able to provide course catalogs for their 

middle schools. When course catalogs were not available, information from interviews with guidance 

counselors and school administrative staff was used to interpret student transcripts. 

The national evaluation based its method for analyzing middle school transcripts on two methods used by 

NCES for its high school transcript studies. These two methods are described in Supplemental Note 5: 

NAEP, NELS and HS&B Transcript Studies, which describes two methods used to classify academic 

challenge or difficulty of course work for the transcript studies: Academic Pipelines and Academic 

Rigor.61 

G.1 Academic Pipelines 

The term pipelines is used to note the normal sequencing of courses. The academic pipelines organize 

transcript data into four core subject areas: mathematics, science, English and foreign language. Each 

level within a subject area includes courses either of similar academic challenge and difficulty or at the 

same stage in the learning progression for that subject. Table G-2 shows the progression for each pipeline 

as defined for middle schools at the national evaluation. A student’s placement in the pipeline is based on 

the highest level class completed within the subject area. 

 

60 See NCES’ Web site regarding high school transcript studies sponsored by the U.S. Department of Education 

(http://nces.ed.gov/surveys/hst/courses.asp). 

61 See NCES-Supplemental Note 5: NAEP, NELS and HS&B Transcript Studies for a full description of the methods used for 

NCES’ transcript studies. 
 G-2 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP 

CSSCID Course Description SEa LGb LVc

05 AREA AND ETHNIC 

STUDIES 

Summary of groups of instructional 

programs that describes the history, 

society, politics, culture and economics 

of either a particular geographic region 

or a particular subset of the population 

sharing common racial characteristics 

or common traits and customs. 

 

 

05.01 AREA STUDIES Group of instructional programs that 

describes the history, society, politics, 

culture and economics of a particular 

geographic region. 

 

 

05.0101 Area Studies Survey of social, political, and cultural 

history; Africa, Latin America, China, 

Japan, Russia, India South Pacific, Europe 0 0 2 

05.0102 American Studies, Basic Contemporary issues, culture, domestic 

and international politics, print media 

resources, practical economic issues 0 0 2 

05.0117 Comparative World Cultures Comparative world culture study, 

geography, economics, political science, 

history and humanities 0 0 2 

07 BUSINESS AND OFFICE Summary of groups of instructional 

programs that prepares individuals for 

a variety of activities in planning, 

organizing, directing and controlling all 

business office systems and procedures. 

Includes instruction in preparing, 

transcribing, systematizing and 

preserving written communications and 

records; preparing and analyzing 

financial records; collecting accounts 

and receiving and disbursing money; 

gathering, processing and distributing 

information and mail; operating office 

machines and electronic data processing 

equipment; storing, distributing and 

accounting for inventories of materials; 

operating telephone switchboards and 

delivering messages; and performing 

other business office duties. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-3 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

07.03 BUSINESS DATA 

PROCESSING AND RELATED 

PROGRAMS 

Group of instructional programs that 

prepares individuals to analyze and 

design data processing system 

configurations; write, test, monitor, 

debug and maintain data processing 

programs; and operate computers 

and peripheral and data entry 

equipment. 

 

 

07.0361 Keyboarding Alphabetic and numeric keyboarding 

using touch method 0 0 2 

07.06 SECRETARIAL AND 

RELATED PROGRAMS 

Group of instructional programs that 

prepares individuals to record and 

transcribe communications and to 

provide administrative support. 

 

 

07.0640 Word Processing - Middle School 

Level 

Word processing software and 

equipment, word processing projects 0 0 2 

07.0641 Word Processing 1 Word processing equipment, memory 

typewriters, integrated typing projects, 

transcription and communication skills 1 0 2 

 

07.07 TYPING, GENERAL OFFICE 

AND RELATED PROGRAMS 

Group of instructional programs that 

prepares individuals to record, 

duplicate and retrieve data, including 

classifying, sorting and filing 

correspondence, records and other 

data. Includes instruction in shipping 

and receiving procedures, stock and 

inventory maintenance, and operation 

of office machines. 

 

 

07.0711 Typewriting 1; Typewriting, 

Beginning; Typewriting, Business 

Touch method mastery, speed building, 

interoffice correspondence, stroking 

techniques, manuscripts, letters 1 0 2 

07.0714 Typing - Middle School Level Touch method mastery, speed building, 

interoffice correspondence, 

correspondence projects 0 0 2 

07.0721 Typewriting, Personal; Word 

Processing, Personal 

Touch typewriting, letters; reports, 

footnotes, personal use 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-4 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

08 MARKETING AND 

DISTRIBUTION 

Summary of groups of instructional 

programs that prepares individuals 

for occupations directed toward the 

flow of industrial and consumer goods 

in channels of trade, or the provision 

of services to consumers or users. 

These programs are concerned with 

marketing, sales, distribution, 

merchandising and management, 

including ownership and management 

of enterprises engaged in marketing. 

Instructional programs prepare 

individuals to perform one or more of 

the marketing functions, such as 

selling, buying, pricing, promoting, 

financing, transporting, storing, 

market research and marketing 

management. In addition, 

instructional programs include 

varying emphases on technical 

knowledge of products or services 

marketed, related communication and 

computation skills and abilities and 

attitudes associated with human 

relations and private enterprise. 

 

 

08.03 ENTREPRENEURSHIP Group of instructional programs that 

prepares individuals to perform 

marketing and management functions 

and tasks associated with owning and 

operating a business. 

 

 

08.0312 Student Store - Middle Level Operating school-sponsored student 

supply store 0 0 2 

09 COMMUNICATIONS Summary of groups of instructional 

programs that describe the creation, 

transmission and evaluation of 

messages. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-5 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

09.04 JOURNALISM (MASS 

COMMUNICATIONS) 

Group of instructional programs that 

describes the principles and methods of 

gathering, processing, evaluating and 

disseminating through mass media, 

information about current events and 

issues. 

 

 

09.0410 Journalism - Middle School Level Newspaper study, newspaper production, 

news information gathering, proofreading, 

journalistic writing, production of school 

newspaper 0 0 2 

09.0411 Journalism 1, Newspaper 

Production 1, News Writing 1, 

Writing for Publication 

Newspaper study, newspaper production, 

news information gathering, proofreading, 

journalistic writing 1 0 2 

09.0431 Literary Magazine Advanced writing techniques, literary 

magazine publishing 0 0 2 

09.0440 Yearbook Production - Middle 

School Level 

Producing a publication, format, layout, 

photographs, yearbook design 0 0 2 

09.0441 Yearbook Production 1, 

Publications 1 

Producing a publication, format, layout, 

photographs, yearbook design 1 0 2 

11 COMPUTER AND 

INFORMATION 

Summary of groups of instructional 

programs that describes the coding, 

processing and storage of data through 

repetitious and highly complex 

mathematical operations at high speed, 

and in accordance with strictly defined 

systems and procedures. 

 

 

11.01 COMPUTER AND 

INFORMATION SCIENCES, 

GENERAL 

Group of instructional programs that 

generally describes the coding, 

processing and storage of data through 

repetitious and highly complex 

mathematical operations at high speed, 

and in accordance with strictly defined 

systems and procedures. 

 

 

11.0110 Computer Literacy; Introduction to 

Computers - Middle School Level 

Introductory survey of computer skills and 

awareness that includes using the Internet 

and World Wide Web, keyboarding, 

computer components, uses of computers 

in business and professions; computerbased skills 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-6 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

11.0111 Computer Appreciation; Computer 

Literacy; Computers - Introduction 

Survey course, nontechnical 

presentations, social implications of 

computers, computer familiarization 0 0 2 

11.0130 Computer Applications - Middle 

School Level 

Learning to use computer applications 

products for school-related projects 0 0 2 

11.0131 Computer Applications, Computer 

Sciences 1 

Emphasis on developing usable 

software, team approach 0 0 2 

 

11.02 COMPUTER PROGRAMMING Group of instructional programs that 

describes the methods and procedures 

used in flow charting and writing 

instructions in computer language for 

the direction of computer operation in 

the solution of a problem. 

 

 

11.0211 Computer Programming 1 Flow charts, algorithms, computer 

languages, machine operation, 

documentation 1 0 2 

16 FOREIGN LANGUAGES Summary of groups of instructional 

programs that describes the structure 

and use of language common or 

indigenous to people of the same 

community or nation, the same 

geographical area or cultural 

traditions, including such features as 

sounds, literature, syntax, phonology, 

morphology, semantics, sentences, 

prose and verse, as well as 

development of skills and attitudes 

used in communicating and 

evaluating thoughts and feelings 

through oral and written language. 

 

 

16.01 FOREIGN LANGUAGES, 

MULTIPLE EMPHASIS 

Group of instructional programs that 

describes the language, literature and 

culture of more than one specific 

group of people. 

 

 

16.0110 Foreign Language, Exploratory - 

Middle School Level 

Experiences in a variety of languages 

and cultures over a semester or yearlong period 0 0 2 

16.0111 Foreign Language, Exploratory Language, culture, multiple groups 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-7 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

16.0118 English as a Second Language 1, 

TESOL, ESOL, ESL - Beginning -

Middle School Level 

Basic English structure, limited 

vocabulary, English sounds, oral 

expression, American student life 0 1 2 

16.0119 English as a Second Language 2, 

TESOL, ESOL, ESL - Intermediate 

-Middle School Level 

Study of English language skills, 

increase language control, cultural 

information, composition skills 0 1 2 

16.0120 English as a Second Language 3, 

TESOL, ESOL, ESL - Transition - 

Middle School Level 

Greater English language ability, 

reading, composition, vocabulary 

building, role playing, American culture 0 1 2 

16.0121 English as a Second Language 1, 

TESOL-Beginning 

Basic English structure, limited 

vocabulary, English sounds, oral 

expression, American student life 1 1 2 

16.0122 English as a Second Language 2, 

TESOL-Intermediate 

English language skills, increase 

language control, cultural information, 

composition skills 2 1 2 

16.0123 English as a Second Language 3, 

TESOL-Advanced 

Greater English language ability, 

reading, composition, vocabulary 

building, role playing, American culture 2 1 2 

16.0124 English as a Second Language, 

Skills Laboratory 

Individualized instruction, non-nativeEnglish speakers, skill building 0 1 2 

16.0125 Transitional English Brush-up instruction to enable student to 

make the transition to regular English 

classes 0 1 2 

 

16.05 GERMANIC LANGUAGES Group of instructional programs that 

describes the language, literature and 

culture of people whose native 

language belongs to the Germanic 

branch of Indo-European languages, 

languages such as German, 

Norwegian, Swedish, Danish and 

Yiddish are included in this category. 

 

 

16.0500 Germanic Languages, Other 0 0 2 

16.0511 German 7, German for Survival - 

Middle School Level 

Vocabulary, grammar, culture study, 

dialogues 0 0 2 

16.0512 German 8 - Middle School Level Vocabulary, grammar, culture study, 

composition, dialogues 0 0 2 

16.0513 German 1, German 9 Vocabulary, grammar, culture study, 

dialogues 1 0 2 

16.0514 German 2, German 10, German 11 Vocabulary, grammar, culture study, 

composition and literature 2 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-8 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

16.09 ITALIC LANGUAGES Group of instructional programs that 

describes the language, literature and 

culture of people whose native 

language belongs to the Italic branch 

of Indo-European languages; 

languages such as French, Italian, 

Latin, Portuguese and Spanish are 

included in this category 

 

 

16.0900 Italic Languages, Other 0 0 2 

16.0901 French 7 - Middle School Level Basic vocabulary, grammar, culture 

study, reading, audio lingual approach 0 0 2 

16.0902 French 8 - Middle School Level Vocabulary, grammar, culture study, drill 0 0 2 

16.0903 French 1, French 9 Vocabulary, grammar, culture study, 

dialogues 1 0 2 

16.0904 French 2, French 10 Vocabulary, grammar, culture study, 

French family life and customs 2 0 2 

16.0911 Italian 7 - Middle School Level Basic vocabulary, grammar, culture study 0 0 2 

16.0912 Italian 8 - Middle School Level Vocabulary, grammar, culture study 0 0 2 

16.0913 Italian 1, Italian 9 Vocabulary, grammar, culture study, 

dialogues, conversation 1 0 2 

16.0914 Italian 2, Italian 10 Vocabulary, grammar, culture study, 

composition and literature, Italian and 

American cultural differences 2 0 2 

16.0920 Latin 1, Latin 9, Latin Graffiti for 

Anybody 

Classical Latin structure; prefixes, 

suffixes, root words; Virgil and Livy; 

legendary Rome; comparison of Roman 

and American life; Greek and Roman 

culture 1 0 2 

16.0921 Latin 2 Grammar and syntax, Caesar, culture, 

classics in the original, comparison of 

Roman and American institutions 2 0 2 

16.0931 Spanish 7, Spanish for Survival -

Middle School Level 

Basic vocabulary, grammar, culture 

study, travel information, money 

exchange, phrase books, oral skills 0 0 2 

16.0932 Spanish 8 - Middle School Level Vocabulary, grammar, culture study, 

time, weather, greetings 0 0 2 

16.0933 Spanish 1, Spanish 9, Spanish, 

Beginning 

Vocabulary, grammar, culture study, 

dialogues 1 0 2 

16.0934 Spanish 2, Spanish 10 Vocabulary, grammar, culture study, 

composition and literature, Mexico and 

Spain, history and customs 2 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-9 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

16.13 NON-ENGLISH LANGUAGES 

FOR NATIVE SPEAKERS 

 

 

16.1300 Non-English Languages for Native 

Speaker, Other 0 0 2 

16.1311 Spanish for Native Speakers 1 Reading and writing of Spanish skills for 

Spanish speaking people, culture study 0 1 2 

16.1312 Spanish for Native Speakers 2 0 1 2 

16.1313 Spanish for Native Speakers 3 0 1 2 

16.1361 French for Native Speakers 1 1 1 2 

16.1362 French for Native Speakers 2 2 1 2 

 

16.99 FOREIGN LANGUAGES, 

OTHER 

Group of instructional programs in 

foreign languages not described above. 

 

 

16.9900 Foreign Languages, Other 0 0 2 

17 ALLIED HEALTH Summary of groups of instructional 

programs that prepares individuals to 

assist qualified health professionals in 

providing diagnostic, therapeutic, 

preventive, restorative and 

rehabilitative services to patients in 

health care facilities, the home and the 

community. 

 

 

17.02 DIAGNOSTIC AND 

TREATMENT SERVICES 

Group of instructional programs that 

prepares individuals to use equipment 

and medical materials for diagnostic 

and therapeutic purposes by learning 

to apply roentgen rays and radioactive 

substances; prepare and administer 

radioisotopes; operate 

electrocardiograph, 

electroencephalograph, respiratory or 

dialysis equipment; provide technical 

assistance before, during and after an 

operation; or render medical 

emergency treatment in a variety of 

situations that demand immediate care, 

such as heart attacks, childbirth, 

poisons, burns and shock. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-10 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

17.0211 First Aid; CPR and First Aid; 

Medical Emergencies; Emergency 

Medical Technician 

Cardiopulmonary resuscitation, first aid, 

emergency care, simulated emergencies 

0 0 2 

17.0212 First Aid - Middle School Level Red-Cross certification in First Aid and 

Safety 0 0 2 

 

19 HOME ECONOMICS Summary of groups of instructional 

programs that describes the 

relationship between the physical, 

social, emotional and intellectual 

environment in and of the home and 

family, and development of 

individuals. Includes instruction in the 

natural and social sciences and 

humanities in the development of 

attitudes, knowledge and ability 

pertaining to clothing and textiles, 

consumer education, food and 

nutrition, home management, 

housing, human development and 

family studies and institutional 

management. 

 

 

19.01 HOME ECONOMICS, 

GENERAL 

 

 

19.0100 Home Economics, Other General 0 0 2 

19.99 HOME ECONOMICS, OTHER 

 

19.9900 Home Economics, Other 0 0 2 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-11 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

20 VOCATIONAL HOME 

ECONOMICS 

Summary of groups of instructional 

programs that emphasizes the 

acquisition of competencies (including 

skills and job attitudes) needed for 

securing and holding paid 

employment at the entry and 

advanced levels and/or preparing for 

advancement in occupations that use 

home economics education knowledge 

and skills. Vocational home economics 

education instructional programs are 

developed from home economics 

education subject matter areas to 

meet the unique requirements of the 

specific vocations. Programs that 

prepare individuals for paid 

employment that include (1) services 

to individuals and families; (2) 

assistance to professional home 

economists and professionals in fields 

related to home economics in 

industry, business and public and 

private agencies; and (3) other 

services and/or assistance directly 

related to one or more of the home 

economics subject matter areas, 

offered in formal and/or informal 

settings combined with supervised 

laboratory and work experiences. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-12 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

20.01 CONSUMER AND 

HOMEMAKING HOME 

ECONOMICS 

Group of instructional programs that 

prepares individuals at all educational 

levels for the occupation of 

homemaking, emphasizing the 

acquisition of knowledge and the 

development of understanding 

attitudes, standards, values and skills 

relevant to individual and family life. 

Includes instruction in consumer 

education, food and nutrition, family 

living and parenthood education, 

child growth and development, 

housing and home management 

(including resource management), 

and clothing and textiles that 

emphasize the improvement of the 

home and quality of individual and 

family life and that enhance potential 

employability. These programs 

prepare individuals for the multiple 

roles of homemaker and wage earner. 

 

 

20.0111 Home Economics 7, 

Comprehensive Consumer and 

Homemaking 7, Homemaking 7 -

Middle School Level 

Basic principles, foods and nutrition, 

clothing and textiles, consumer 

education, child care 

0 0 2 

20.0112 Home Economics 8, 

Comprehensive Consumer and 

Homemaking, Homemaking 8 - 

Middle School Level 

Basic principles and concepts, clothing 

and textiles, parenting, interpersonal 

relationships, consumer education, 

nutrition and foods 0 0 2 

20.0119 Adult Roles and Functions, 

Independent Living: Survival 

Skills, Singles Survival - Middle 

School Level 

Basic principles and concepts, clothing 

and textiles, parenting, interpersonal 

relationships, consumer education, 

nutrition and foods 0 0 2 

20.0121 Child Development 8 Middle 

School Level 

Care of small children, safety, play, 

creative activity, dressing and feeding 0 0 2 

20.0122 Child Development 1 Developmental stages, child 

interactions, dressing and feeding 

children 1 0 2 

20.0127 Adolescent Development - Middle 

School Level 

Physical, social and emotional 

development of adolescents, 

understanding of students' own state in 

life, adolescent decision-making skills 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-13 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

20.0131 Clothing 7 - Middle School Level Project sewing, hand sewing, use of 

sewing machine 0 0 2 

20.0132 Clothing 8 - Middle School Level Project sewing, introducing clothing 

construction 1 0 2 

20.0161 Family Health 1, Family Nursing Accident prevention, home nursing 

techniques, diets, community health 

resources 1 0 2 

20.0170 Family Relations, Family 

Sociology, Family Living - Middle 

School Level 

Peer relations, family relations, 

premarital concerns, parenthood, child 

abuse, divorce 0 0 2 

20.0171 Family Relations, Family 

Sociology, Family Living 

Peer relations, family relations, 

premarital concerns, parenthood, child 

abuse, divorce 0 0 2 

20.0172 Marriage Society and Change 

Lifestyles 

Marriage issues, marriage partner choice, 

social trends, male and female relations 0 0 2 

20.0173 Parenthood, Parent Education, 

Parenting 

Parenthood preparation, prenatal care, 

childbirth, infancy 0 0 2 

20.0174 Parenthood, Parent Education, 

Parenting - Middle School Level 

Parenthood preparation, prenatal care, 

childbirth, infancy 0 0 2 

20.0181 Foods and Nutrition 7 - Middle 

School Level 

Introduction to nutrition, introduction to 

basic cooking principles 0 0 2 

20.0182 Foods and Nutrition 8 - Middle 

School Level 

Nutrition, health, preparation of simple 

meals 0 0 2 

20.0188 Nutrition, Fitness Foods Eating patterns, nutrition science, 

consumer aspects, world hunger, fitness 

foods 0 0 2 

 

21 INDUSTRIAL ARTS Summary of groups of instructional 

programs that provides individuals 

with knowledge that (1) pertains to the 

body of related subject matter, or 

related courses, organized for the 

development of understanding about 

all aspects of industry and technology, 

including learning experiences 

involving activities like experimenting, 

designating, constructing, evaluating 

and using tools, machines, materials or 

processes; and (2) assists individuals in 

making informed and meaningful 

occupational choices or that prepares 

them for entry into advanced trade 

and industrial or technical education 

programs. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-14 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

21.01 INDUSTRIAL ARTS Group of instructional programs that 

provides individuals with knowledge 

that (1) pertains to the body of related 

subject matter, or related courses, 

organized for the development of 

understanding about aspects of 

industry and technology, including 

learning experiences involving 

activities such as experimenting, 

designating, constructing, evaluating 

and using tools, materials and 

processes; and (2) assists individuals 

in making informed and meaningful 

occupational choices or that prepares 

them for entry into advanced trade 

and industrial or technical education 

programs. 

 

 

21.0100 Industrial Arts, Other 0 0 2 

21.0101 Industrial Arts 7 - Middle School 

Level 

Introductory course, mechanical 

drawing, woodworking, ceramics, tool 

familiarization 0 0 2 

21.0102 Industrial Arts 8 - Middle School 

Level 

Introductory course, electricity, power 

mechanics, metalwork, tool 

familiarization, wood working 0 0 2 

21.0103 Industrial Arts 1, Shop 1, 

Exploratory, Shop, General, 

Industrial Materials 1, Industrial 

Arts Orientation, Industrial Crafts 1 

Basic skills, woods, metals, plastics, 

occupational orientation 

0 0 2 

21.0127 Introduction to Technology, 

Technology Education 

General course on technology, including 

computers, computer-related and 

computer-controlled technology 0 0 2 

21.0128 Introduction to Technology, 

Technology Education - Middle 

School Level 

General course on technology, including 

computers, computer-related and 

computer controlled technology 0 0 2 

 

22 LAW Summary of groups of instructional 

programs that describes the principles 

and procedures, in the form of 

legislation, decisions, regulations and 

orders, developed and enforced by 

institutions of government to maintain 

social order. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-15 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

22.01 LAW Group of instructional programs that 

describes the principles and 

procedures, in the form of legislation, 

decisions, regulations and orders 

developed and enforced by 

institutions of government in order to 

maintain social order. 

 

 

22.0100 Law, Other 0 0 2 

23 LETTERS Summary of groups of instructional 

programs that describes sounds, 

literature, syntax, phonology, 

semantics, sentences, prose and verse, 

as well as the development of skills 

and attitudes used in communicating 

and evaluating thought and feelings 

through oral and written language. 

 

 

23.01 ENGLISH, GENERAL Group of instructional programs that 

generally describes the skills and 

techniques essential to learning the 

English language. 

 

 

23.0101 English 7 - Middle School Level Reading, writing, listening, speaking 

skills; literature appreciation; vocabulary 

study; mechanics; usage; spelling 0 0 2 

23.0102 English 7, Honors; English 7 - 

Above Grade Level - Middle 

School Level 

Literature and composition; reading, 

writing, listening, speaking skills; text 

preview; study skills 0 0 1 

23.0103 English 8 - Below Grade Level -

Middle School Level 

Literature and composition; reading, 

writing, listening, speaking skills 0 0 3 

23.0104 English 8, English 8 - Average -

Middle School Level 

Reading, writing, listening, speaking 

skills; usage; sentence structure; 

literature appreciation 0 0 2 

23.0105 English 8, Honors, English 8 - 

Above Grade Level - Middle 

School Level 

Literature appreciation; in-depth study 

of reading writing, speaking, listening 

skills 0 0 1 

23.0106 English 1 - Below Grade Level; 

English 9 - Basic; Communication 

Skills, Non College 

Grammar study; literature survey; 

reading, writing speaking, listening 

skills 0 0 3 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-16 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

23.0107 English 1; English 9, Average Grade-level English; genres; reading, 

writing, listening, speaking skills 0 0 2 

23.0108 English 1, Honors; English 9, 

Honors 

Above grade-level English; in-depth 

study of reading, writing, speaking, 

listening skills; general study 0 0 1 

 

23.04 COMPOSITION Group of instructional programs that 

describes the principles and 

techniques of selecting, combining, 

arranging and developing ideas and 

expressing them in appropriate 

written forms such as narration, 

exposition or persuasion. 

 

 

23.0400 Composition, Other 0 0 2 

23.0401 Composition, Expository, Writing 

Practice, Contemporary 

Composition, Expository Writing 

Basic composition structure, models, 

skill improvement 

0 0 2 

23.0402 Writing Laboratory, Writing Skills 

Workshop, Composition, Advanced 

Computer Assisted Writing 

Instruction 

Intensive practice, writing skills, 

laboratory setting 

0 0 2 

23.0404 Vocabulary, Fun With Words, 

College Vocabulary Skill Building, 

Word Power 

Dictionary use, prefixes and suffixes, 

spelling 

0 0 2 

23.0405 Spelling Study of spelling words, assigned lists, 

self-identified lists 0 0 2 

23.0406 Grammar 7, Language Structure 7 -

Middle School Level 

Traditional grammar, transformational 

grammar, structural linguistics 0 0 2 

23.0407 Grammar 8, Language Structure 8 -

Middle School Level 

Traditional grammar, transformational 

grammar, structural linguistics 0 0 2 

23.0408 Grammar 9, Language Structure 9 Traditional grammar, transformational 

grammar, structural linguistics 0 0 2 

23.0413 Handwriting, Penmanship Techniques for and exercises in 

handwriting 0 0 2 

23.0414 Interpersonal Communication Role playing, experiments, games, 

discussions; verbal, nonverbal behavior; 

composition suggestions 0 0 2 

23.0415 Word Study - Remedial Vocabulary improvement, 

pronunciation, prefixes, root meanings 0 0 3 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-17 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

23.12 LANGUAGE ARTS, READING 

23.1201 Reading Development 7, Reading 

Improvement, Remedial Reading, 

Reading Skills, Title 1 Reading, 

Reading Fundamentals, Corrective 

Reading - Middle School Level 

Instruction for students with reading 

difficulties, skill acquisition, reading 

techniques, below-grade-level 

remediation, word attack, comprehension 

0 0 3 

23.1202 Reading Development 8 - Middle 

School Level 

Reading difficulties, continued skill 

building, student needs diagnosis, 

survival reading, critical thinking skills, 

study habits 0 0 3 

23.1211 Reading Development 1, Reading 

Improvement, Remedial Reading, 

Reading Skills, Chapter 1 Reading, 

Reading Fundamentals, Corrective 

Reading 

Instruction for students with reading 

difficulties, skill acquisition, reading 

techniques, below-grade level 

remediation, word attack skills, 

comprehension 1 0 3 

23.1212 Reading Development 2 Reading difficulties, continued skill 

building, student needs diagnosis, 

survival reading, critical thinking skills, 

study habits 2 0 3 

23.13 LANGUAGE ARTS, BASIC 

SKILLS 

 

 

23.1311 Functional English 1, Correlated 

Language Arts 1 

Integrated language arts course designed 

to develop reading and writing skills; 

survival and job-oriented skills; emphasis 

on short reading selections, vocabulary 

from context, and writing paragraphs 1 0 3 

24 LIBERAL AND GENERAL 

STUDIES 

Summary of groups of instructional 

programs that describes the 

foundation necessary for 

understanding self and society through 

an appreciation of the concerns of 

civilization and our common heritage. 

 

 

24.01 LIBERAL AND GENERAL 

STUDIES 

Group of instructional programs that 

describes the foundation necessary for 

understanding self and society through 

an appreciation of the concerns of 

civilization and our common heritage. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-18 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

24.0110 Liberal Studies - Middle School 

Level 

Integrated fields of art, music, literature, 

philosophy 0 0 2 

24.0140 Gifted and Talented Program - 

Middle School Level 

Academic and creative education for 

gifted students, enrichment-subject 

unspecified or broad range of subjects 0 0 2 

24.0141 Gifted and Talented Program Academic and creative education for 

gifted students, enrichment-subject 

unspecified or broad range of subjects 0 0 1 

 

25 LIBRARY AND ARCHIVAL 

SCIENCES 

Summary of groups of instructional 

programs that describes the 

knowledge and skills required to 

develop, organize, store, retrieve, 

administer, and facilitate the use of 

collections of information in such 

formats as books, documents, 

manuscripts, machine-readable 

databases, filmed and recorded 

materials, specimens, and artifacts. 

 

 

25.01 LIBRARY AND ARCHIVAL 

SCIENCES, GENERAL 

Group of instructional programs that 

generally describes the knowledge and 

skills required to develop, organize, 

store, retrieve, administer, and 

facilitate the use of collections of 

information in such formats as books, 

documents, manuscripts, machinereadable databases, filmed and 

recorded materials, specimens, and 

artifacts. 

 

 

25.0110 Library Science, Library Skills - 

Middle School Level 

Library skills development, card catalog, 

Dewey decimal system, audiovisual 

equipment, filing 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-19 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

25.03 LIBRARY ASSISTING Group of instructional programs that 

prepares individuals to assist 

professional librarians. Includes 

instruction in principles, systems, 

processes and procedures in library 

operation; library resources and 

services; processes of acquisition, 

cataloging, storage and display systems; 

discovery and retrieval of requested 

materials; management of books, 

periodicals and other printed materials; 

technological media such as audiovisual 

and education equipment; public 

services such as library loans; and dataprocessing implications for automation 

of records in libraries. 

 

 

25.0310 Library Assistant, Library Aide - 

Middle School Level 

Library procedures, school service, 

audiovisual equipment operation 0 0 2 

25.0311 Library Assistant, Library Aide Library procedures, school service, 

audiovisual equipment operation 0 0 2 

 

26 LIFE SCIENCES Summary of groups of instructional 

programs that describes the systematic 

study of living organisms. 

 

 

26.01 BIOLOGY, GENERAL Group of instructional programs that 

generally describes life forms, including 

the structure, function, reproduction, 

growth, heredity, evolution, behavior 

and distribution of living organisms. 

 

 

26.0111 Science 7, Life Sciences 7 - Middle 

School Level 

Animals, plants, cells; human body 

systems; environment; continuity 0 0 2 

26.0112 Science 7, Life Sciences 7 - Honors 

- Middle School Level 

Animals; plants; cells; human body 

systems; environment; continuity 0 0 1 

26.0121 Biology, Basic 1; Biology, 

Essentials; Biology, Patterns; Life 

Science; Natural Science; Biology, 

Functional 

Basic course, organism level, simplified 

approach, human body, functioning plants, 

functioning animals 

1 0 2 

26.0122 Biology, Basic 2 Second-level basic course in biology for 

students who need a more simplified 

approach 2 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-20 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

26.0131 Biology, General 1; Biology, 

Biology, Regents; Biology, 

Introductory 

Standard course, cellular level, 

community level, ecological relations, 

evolutionary development 1 0 2 

26.0141 Biology, Honors 1 College preparatory course, quantitative 

approach, biosphere, physiology, 

heredity, molecular level 1 0 1 

 

27 MATHEMATICS Summary of groups of instructional 

programs that describes the sciences of 

logical symbolic language and their 

applications. 

 

 

27.01 MATHEMATICS, GENERAL Group of instructional programs that 

generally describes the sciences of 

logical symbolic language and their 

applications. 

 

 

27.0101 Mathematics 7 - Middle School 

Level 

Basic computational skills, problem 

solving techniques, fractions, decimals, 

measurement systems, tables and graphs 0 0 2 

27.0102 Mathematics 7, Accelerate - Middle 

School Level 

Junior high mathematics, 2 years work, 

increased pace, pre-algebra topics 0 0 2 

27.0103 Mathematics 8 - Middle School 

Level 

Arithmetic, metric system, real numbers, 

negative numbers, ratio and proportion, 

exponents 0 0 2 

27.0104 Mathematics 8, Accelerated - 

Middle School Level 

Junior high mathematics, pre-algebra 

topics, increased pace 0 0 2 

27.0105 Unused Code 0 0 2 

27.0106 Mathematics 1, General; 

Mathematics 1, Applied; 

Computational Skills 1 

Mathematical applications, whole 

numbers, fractions, decimals, informal 

geometry, statistics 0 0 2 

 

27.04 PURE MATHEMATICS Group of instructional programs that 

describes number, form, arrangement 

and associated relationships, using 

rigorously defined literal numerical 

and operational symbols. 

 

 

27.0401 Pre-algebra; Algebra Skills; 

Algebra, Principles; Algebra, 

Introduction; Algebra, Basic; 

Algebra, Practical 

Exploratory algebra, practical 

applications, graphing, exponents, 

negative integers, simple equations 

0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-21 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

27.0402 Algebra 1, Part 1 Algebra 1 over 2 years, reduced pace, first 

half of algebra 1 1 0 2 

27.0403 Algebra 1, Part 2 Algebra 1 over 2 years, reduced pace, 

second half of algebra 1 2 0 2 

27.0404 Algebra 1; Algebra, Elementary Graphs, algebraic equations, radicals, linear 

equations, algebraic proofs, mathematical 

symbols 1 0 2 

27.0405 Algebra 2; Algebra, Intermediate Polynomials, irrational numbers, verbal 

problems, logarithms, binomial theorem, 

trigonometry 2 0 2 

27.0421 Mathematics 1, Unified Unified approach, logic, algebra, geometry, 

trigonometry, probability 1 0 2 

27.0427 Unified Mathematics 1, Part 1 Unified mathematics taught over 2 years, 

first year full credit 1 0 2 

27.0428 Unified Mathematics 1, Part 2 Unified mathematics taught over 2 years, 

second year full credit 2 0 2 

 

27.06 BASIC SKILLS 

MATHEMATICS 

 

 

27.0601 Basic Mathematics 1; Mathematics 

Fundamentals; Developmental 

Mathematics; Arithmetic Review; 

Mathematics, Remedial; 

Mathematics, Essentials; 

Mathematics Laboratory; 

Competency Mathematics; 

Mathematics, Basic 

Terminal course; computational skills; 

remedial work; simplified approach, 

decimals; percentages; arithmetic review; 

real-life applications; fractions, decimals, 

and percentages; competency test 

preparation 

0 0 3 

 

30 MULTI- AND 

INTERDISCIPLINARY 

STUDIES 

Summary of groups of instructional 

programs, the components of which, 

derive from two or more separate 

conventional academic instructional 

programs. 

 

 

30.01 BIOLOGICAL AND PHYSICAL 

SCIENCES 

Group of instructional programs that 

describes either a general synthesis of one 

or more of the biological and physical 

sciences (for example, applied science or 

general science), or a specialization that 

draws from the biological and physical 

sciences (for example, environmental 

science and studies). 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-22 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

30.0101 Science, Unified 7; Science, Basic; 

Science, General; Science Ideas; 

Science Workshop; Science, 

Applied; Physical and Life Science 

- Middle School Level 

Survey course, life sciences, chemistry, 

physics, multidisciplinary approach, 

simplified approach 

0 0 2 

30.0102 Science, Unified 7 - Honors; 

Science, Basic; Science, General; 

Science Ideas; Science Workshop; 

Science, Applied; Physical and Life 

Science, Honors - Middle School 

Level 

Survey course, life sciences, chemistry, 

physics, multidisciplinary approach, 

simplified approach 

0 0 1 

30.0103 Science, Unified 8; Science, Basic; 

Science, General; Science Ideas; 

Science Workshop; Science, 

Applied; Physical and Life Science 

Middle School Level 

Survey course, life sciences, chemistry, 

physics, multidisciplinary approach, 

simplified approach 

0 0 2 

30.0104 Science, Unified 8; - Honors; 

Science, Basic; Science, General; 

Science Ideas; Science Workshop; 

Science, Applied; Physical and Life 

Science, Honors - Middle Level 

Survey course, life sciences, chemistry, 

physics, multidisciplinary approach, 

simplified approach 

0 0 1 

30.0111 Science, Unified; Science, Basic; 

Science, General; Science Ideas; 

Science Workshop; Science, 

Applied; Physical and Life Science 

Survey course, life sciences, chemistry, 

physics, multidisciplinary approach, 

simplified approach 

0 0 2 

30.0112 College Pre-Science Skills Problem solving, laboratory techniques, 

scientific reading and writing, college 

preparatory skills and concepts 0 0 2 

30.0130 Outdoor Education - Middle School 

Level 

Resident camp, environmental study, 

science field experiences, 

interdisciplinary approach 0 0 2 

30.0131 Outdoor Education Resident camp, environmental study, 

science field experiences, 

interdisciplinary approach 0 0 2 

 

30.04 HUMANITIES AND SOCIAL 

SCIENCES 

Group of instructional programs that 

describes either a general synthesis of 

one or more of the humanities and 

social sciences (e.g., humanities), or a 

specialization that draws from the 

humanities and social sciences (for 

example, behavioral science, classical 

civilization or human development). 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-23 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

30.0401 Humanities, People and Their 

Culture, CORE - Middle School 

Level 

Problem solving, laboratory techniques, 

scientific reading and writing; college 

preparatory skills and concepts 0 0 2 

30.0411 Humanities, People and Their 

Culture 

Integration of history and literature; 

combination of literature, music and art 

of a selected period; interdisciplinary 

study of social sciences, anthropology, 

geography, history, psychology 0 0 2 

 

30.06 SYSTEMS SCIENCE Group of instructional programs that 

describes a multidisciplinary 

approach to the study of innate 

complexity that by synthesizing 

systemic findings from the natural, 

social, technological, behavioral and 

life sciences and other specialized 

fields brings holistic perspectives to 

the solution of problems within a 

general context. 

 

 

30.0621 Environmental Science, 

Environmental Issues, Human 

Communities, People Technology 

and the Environment 

Water pollution, conservation, forestry, 

air pollution 

0 0 2 

 

30.07 WOMEN'S STUDIES Group of instructional programs that 

describes the history, society, politics, 

culture and economics of women. 

 

 

30.0711 Women's Studies; Women in 

American Society 

Role of American woman; colonial 

period to the present; women in art, 

literature, business, politics, education, 

science 0 0 2 

 

31 PARKS AND RECREATION Summary of groups of instructional 

programs that describes the principles 

and procedures of providing parks 

and recreational facilities and services 

for the benefit of the general public. 

 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-24 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

31.01 PARKS AND RECREATION, 

GENERAL 

Group of instructional programs that 

generally describes the principles and 

procedures of providing parks and 

recreational facilities and services for 

the benefit of the general public. 

 

 

31.0111 Recreation Aide Recreation program assistance 0 0 2 

 

32 BASIC SKILLS Summary of groups of instructional 

programs that describes the 

fundamental career and employment 

skills a person is normally thought to 

need in order to function productively 

in society. 

 

 

32.01 BASIC SKILLS, CAREERS 

AND EMPLOYMENT 

(FORMERLY BASIC SKILLS 

OTHER) 

Group of instructional programs that 

describes the fundamental career and 

employment skills a person is 

normally thought to need in order to 

function in society. 

 

32.0102 Career Preparation, So You Want A 

Job, Business Opportunities, Job 

Entry Training, College and Career 

Planning, Guidance 

Job application, interviewing, 

promotional opportunities, work ethic, 

test taking, educational requirements 

0 0 2 

32.0103 Career Exploration; Vocations, 

Introduction; Career Development; 

Work Observational Experience; 

Career Education; Occupational 

Exploratory Program 

Business community exploration, career 

observation unpaid experiences, site 

visits, career planning 

0 0 2 

 

32.02 BASIC SKILLS, GENERAL 

 

32.0200 Basic Skills, General, Other 0 0 2 

32.0201 Resource Room (Non Special Ed) 0 0 2 

32.0202 Resource Room (Non Special Ed) -

Middle School Level 0 0 2 

32.0210 Study Dynamics - Middle School 

Level 

Study skill improvement; note-taking; 

research, paper preparation 0 0 2 

32.0211 Study Dynamics Study skill improvement; note-taking; 

research paper preparation 0 0 2 

32.0230 Individualized Academic Program -

Middle School Level 

Dropout prevention, college preparation, 

tutorial assistance (e.g., project AVID) 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-25 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

32.0231 Individualized Academic Program Dropout prevention, college preparation, 

tutorial assistance (e.g., project AVID) 0 0 2 

33 CITIZENSHIP AND CIVIC 

ACTIVITIES 

Summary of groups of instructional 

programs that describes how 

individuals can facilitate 

governmental functions and 

contribute to the well-being of their 

community through civic action. 

 

 

33.01 CITIZENSHIP AND CIVIC 

ACTIVITIES 

Group of instructional programs that 

describes how individuals can 

facilitate governmental functions and 

contribute to the well-being of their 

community through civic action. 

 

 

33.0111 Student Assistant, Teacher 

Assistant, Laboratory Assistant, 

Teacher Cadet, Office Aide, 

Instructional Assistant, Clerical 

Aide, School Service 

School service, background enrichment, 

teacher support, bulletin board 

maintenance 

0 0 2 

33.0121 Pep Squad, Cheerleading Rallies, competitions, athletic event 

performance 0 0 2 

33.0131 Student Government; Assembly School communications, school 

activities, class representation 0 0 2 

33.0141 Tutoring, Peer Tutoring Practical tutoring experience, assisting 

classmates, class environment 

development, materials production 0 0 2 

33.0151 Community Service, Community 

Involvement 

Volunteer program, community 

agencies, experiential learning 0 0 2 

 

34 HEALTH-RELATED 

ACTIVITIES 

Summary of groups of instructional 

programs that describes the 

promotion of the health of individuals. 

 

 

34.01 HEALTH-RELATED 

ACTIVITIES 

Summary of groups of instructional 

programs that describes the 

promotion of the health of individuals. 

 

 

34.0109 Physical Education 7 - Middle 

School Level 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-26 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

34.0111 Physical and Health Education 7, 

Physical Education 7 - Middle 

School Level 

Health attitudes, safety, sportsmanship, 

team play 

0 0 2 

34.0112 Physical and Health Education 8, 

Physical Education 8 - Middle 

School Level 

Health attitudes, safety, sportsmanship, 

team play 

0 0 2 

34.0113 Physical and Health Education 9, 

Physical Education 9, Health Safety 

and Physical Education 9 

Dual sports, team sports, skill mastery, 

game rules 

0 0 2 

34.0121 Adaptive Physical Education 

(Multihandicapped)/(Nonregular 

program) 

Nonregular program, muscle imbalance, 

posture problems, breathing problems, 

motor disabilities 0 0 2 

34.0131 Health 7, Health Science 7 - Middle 

School Level 

Body care, disease prevention, body 

functions, narcotics, safety practices 0 0 2 

34.0132 Health 8, Health Science 8 - Middle 

School Level 

Body care, disease prevention, body 

functions, narcotics, safety practices 0 0 2 

34.0133 Health 9, Health Science 9 Body care, disease prevention, body 

functions, narcotics, safety practices 0 0 2 

34.0141 Drugs Alcohol and Tobacco Drug education, narcotics, alcoholism, 

tobacco use 0 0 2 

34.0171 Life Saving Swimming rescues, equipment rescues, 

respiratory emergencies 0 0 2 

34.0181 Safety Safety practices, daily living situation 0 0 2 

34.0191 Sex Education, Human Sexuality 

and Reproduction 

Human physiology, reproduction, family 

planning 0 0 2 

 

35 INTERPERSONAL SKILLS Summary of groups of instructional 

programs that describes how to 

effectively live and interact with 

others, social organization, being a 

congenial friend and companion, 

establishing courses of action for 

others and influencing others to 

follow. 

 

 

35.01 INTERPERSONAL SKILLS 

 

35.0100 Interpersonal Skills, Other 0 0 2 

35.0111 Interpersonal Relationships Personal roles, individuals in society 0 0 2 

35.0112 Human Relations, Interpersonal 

Relationships; Peer Relationships -

Middle School Level 

Understanding relationships and peer 

group influences, dealing with peer 

pressure, adolescent relationships 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-27 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

35.0121 Building Human Relationship Values clarification, communication skills, 

meeting individual and shared goals and 

needs 0 0 2 

35.0131 Peer Counseling Students serve as leaders with individuals or 

in peer counseling groups to work on 

problem solving, mutual support, values 

clarification, counseling, networking 0 0 2 

35.0140 Dropout Prevention - Middle 

School Level 

Communities and cities in schools, other 

intervention programs 0 0 2 

35.0141 Dropout Prevention Communities and cities in schools 0 0 2 

 

36 LEISURE AND 

RECREATIONAL ACTIVITIES 

Summary of groups of instructional 

programs that describes the development 

of an appreciation for and competency in 

recreational and leisure-related activities. 

 

 

36.01 LEISURE AND 

RECREATIONAL ACTIVITIES 

Group of instructional programs that 

describes the development of an 

appreciation for and competency in 

recreational and leisure-related activities. 

 

 

36.0192 Experiential Outdoor Education Outdoor leadership training, using the urban 

community or wilderness as a classroom for 

various subject area instruction that includes 

programs like Outdoor School, Outward 

Bound 0 0 2 

36.0193 Experiential Outdoor Education - 

Middle School Level 

Outdoor leadership training, using the urban 

community or wilderness as a classroom for 

various subject area instruction that includes 

programs like Outdoor School, Outward 

Bound 0 0 2 

 

37 PERSONAL AWARENESS Summary of groups of instructional 

programs that describes a person's selfperception, values, attitudes, beliefs and 

emotional responses. 

 

 

37.01 PERSONAL AWARENESS Group of instructional programs that 

describes a person's self-perception, 

values, attitudes, beliefs and emotional 

responses. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-28 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

37.0111 Personal Development Techniques, 

Personal Grooming and Fashion, 

Personal Management, Personal 

Culture, Youth and Decisions, 

Teens Today, Human Studies, 

Self-Development 

Personal awareness, beauty techniques, 

self-confidence, goal setting, time 

management 

0 0 2 

37.0121 Coping with Personal Problems, 

Personal Adjustment 

Adjusting to problems, divorce, stress, 

test anxiety, sexual relations 0 0 2 

37.0131 Self-Perception, Self-Image Building a positive self image, barriers 0 0 2 

 

38 PHILOSOPHY AND RELIGION Summary of groups of instructional 

programs that describes the critical 

examination of the categories for 

describing reality, the nature and 

contexts of human experience, the 

methodology of rational inquiry and 

criteria of practice philosophy; and 

the investigation of organized forms, 

beliefs and practices related to eternal 

principles or transcendent spiritual 

entities (religion). 

 

 

38.02 RELIGION Group of instructional programs that 

describes the origin, histories, 

organized forms, beliefs, worship and 

practices of specific religions. 

 

38.0203 Scripture; Testaments, Old and 

New; Christian and Hebrew 

Scriptures; Bible Studies 

Life of Christ; Old Testament and New 

Testament, analysis and interpretation 

0 0 2 

 

40 PHYSICAL SCIENCES Summary of instructional programs 

that describes inanimate objects, 

processes of matter, energy and 

associated phenomena. 

 

 

40.01 PHYSICAL SCIENCES, 

GENERAL 

Group of instructional programs that 

generally describes the major topics, 

concepts, processes and 

interrelationships of nonliving matter 

and associated phenomena. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-29 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

40.0111 Science 8, Physical Science 8 - 

Middle School Level 

Basic physical science, chemistry, 

physics, laboratory experimentation 0 0 2 

40.0112 Science 8, Physical Science 8 - 

Middle School Level 

Basic physical science, chemistry, 

physics, laboratory experimentation 0 0 2 

40.0121 Physical Science, Science 9, 

Chemistry and Physics 

Introductory course, basic scientific 

principles, chemistry, physics, structure 

of matter, scientific observation 0 0 2 

 

40.06 GEOLOGICAL SCIENCES Group of instructional programs that 

describes the history of the earth and 

other celestial bodies especially as 

recorded in rocks. 

 

 

40.0611 Earth Science; Earth Science 9; 

Earth Science, General 

Survey course, geology, astronomy, 

meteorology, fossils 0 0 2 

45 SOCIAL SCIENCES Summary of groups of instructional 

programs that describes the 

substantive portions of behavior, past 

and present activities, interactions, 

and, organizations of people 

associated together for religious, 

benevolent, cultural, scientific, 

political, patriotic or other purposes. 

 

 

45.01 SOCIAL SCIENCES, GENERAL Group of instructional programs that 

generally describes the major 

principles and perspectives of the 

social sciences. 

 

 

45.0111 Social Science, Introduction; Social 

Studies, Introduction; Social 

Studies Skills 

Social science branches, research 

methods, social studies preparation 

0 0 2 

 

45.07 GEOGRAPHY Group of instructional programs that 

describes the earth and its life; the 

description of land, sea and air; and 

the distribution of plant and animal 

life, including human beings and 

industries. 

 

 

45.0701 Geography 8 - Middle School Level United States and world geography 0 0 2 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-30 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

45.0704 World Geography, Cultural and 

Physical Geography 

Major world geographic areas; 

interrelationships between people and habitat; 

political, social, cultural, and economic 

geography 0 0 2 

45.0709 Human and Cultural Geography, 

Man and His Environment 

Cultural groups and their geographical 

locations 0 0 2 

45.08 HISTORY Group of instructional programs that 

describes the past, including the recording, 

gathering, criticizing, synthesizing and 

interpreting evidence about past events. 

 

 

45.0801 History and Geography 7 - Middle 

School Level 

Survey of world history and world geography, 

map reading, state history and cultural 

development 0 0 2 

45.0802 Our Cultural Heritage 7 - Middle 

School Level 

Study of United States history, exploration, 

colonization, early United States government 0 0 2 

45.0803 Social Studies 7, Honors - Middle 

School Level 

Chronological United States history, 

presidential administrations, political 

movements, independent study, research 

projects 0 0 2 

45.0804 United States History 8 - Middle 

School Level 

Nineteenth and 20th century history, current 

problems 0 0 2 

45.0805 Social Studies 8 - Middle School 

Level 

Chronological United States history, 

presidential administrations, political 

movements, constitution foreign policy trends 0 0 2 

45.0806 Social Studies 8, Honors - Middle 

School Level 

Chronological United States history, 

presidential administrations, political 

movements, constitution foreign policy trends 0 0 2 

45.0807 United States History, State and 

Local; State History and 

Government; State History 

History, culture, contemporary issues, 

government institutions 

0 0 2 

45.10 POLITICAL SCIENCE AND 

GOVERNMENT 

Group of instructional programs that 

describes the description and analysis of 

political institutions and processes, 

including the origin, development, 

geographical units, forms, sources of 

authority, powers, purposes, functions and 

operations of government. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-31 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

45.1001 Civics, Community Civics Citizenship responsibilities and 

government, introduction; federal, state 

and local government; organization and 

function 0 0 2 

45.1002 State and Local Government Functions of government, state and local 

level 0 0 2 

45.1003 Government, Basic; Government 

and Contemporary American 

Problems 

Study of United States voting 

procedures; court operations; local, state 

and national lawmaking 0 0 2 

 

50 VISUAL AND PERFORMING 

ARTS 

Group of instructional programs that 

generally describes the historic 

development, aesthetic qualities and 

creative processes of two or more of 

the visual and performing arts. 

 

 

50.01 VISUAL AND PERFORMING 

ARTS, GENERAL 

Group of instructional programs that 

generally describes the historic 

development, aesthetic qualities and 

creative processes of two or more of 

the visual and performing arts. 

 

 

50.0110 Aesthetics, Art, Music, Drama, 

Dance Survey - Middle Level 

Interrelated arts 

0 0 2 

50.0111 Aesthetics, Art, Music, Drama, 

Dance Survey 

Enrichment course, interrelated arts 

0 0 2 

 

50.02 CRAFTS Group of instructional programs that 

describes how to increase one's skills 

to fashion objects in a specialized area 

of handwork. 

 

 

50.0211 Crafts 7 - Middle School Level Fabrics, fiber, paper leather; 

decorations; creative expression 0 0 2 

50.0212 Crafts 8 - Middle School Level Fabrics, fiber, paper, leather; 

decorations; creative expression 0 0 2 

50.0213 Crafts 9; Creative Crafts 9 Fiber, fabric, leather, metal, wood, 

plastic; weaving; macramé; 

woodcarving; jewelry; enameling; 

stitchery 1 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-32 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

50.0261 Ceramics 7 Slab, coil, modeling, sculpting; beginning 

wheel throwing techniques; glazing, firing 0 0 2 

50.0262 Ceramics 8 Clay objects; ceramic ware; forming; 

firing; glazing 0 0 2 

50.03 DANCE Group of instructional programs that 

describes the performance and 

choreography of various kinds of 

dances, including but not limited to 

ballet, modern, jazz, ethnic and folk 

dance. 

 

 

50.0311 Modern Dance for Beginners 9, 

Rhythm and Dance 9 

Locomotor warm-ups, class 

improvisations, history of dance, theories 

of movement, methods of choreography 1 0 2 

 

50.04 DESIGN Group of instructional programs that 

describes the theories, techniques and 

creative processes for more effectively 

performing the function of 

communicating feelings, ideas and 

information through use of materials 

and media to create two-or threedimensional visual affects. 

 

 

50.0411 Graphic Design Art vocations, basic lettering styles 0 0 2 

50.05 DRAMATIC ARTS Group of instructional programs that 

describes the development, theory and 

processes of creating live performances 

through human expressive modalities. 

 

 

50.0511 Stagecraft 9; Acting Fundamentals 

9; Theater Arts 1 

Set design, construction, improvisation, 

lighting 0 0 2 

50.07 FINE ARTS Group of instructional programs that 

describes the organization of materials 

and media for two-or three-dimensional 

visual affects that communicate ideas 

and express emotion and are considered 

primarily in relation to aesthetic criteria 

of judgments of beauty or 

meaningfulness. 

 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-33 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

50.0701 Fine Arts 7, Art 7 - Middle School 

Level 

Development of sculpture, architecture, 

printing; color; shapes; space; texture 0 0 2 

50.0702 Fine Arts 8, Art 8 - Middle School 

Level 

Principles of design and elements of art 0 0 2 

50.0704 Art 1, Art 9 Principles of design and elements of art 1 0 2 

 

50.09 MUSIC Group of instructional programs that 

describes the art and science of 

combining sounds of various timbre in 

harmonic, rhythmic or melodic forms 

which are artistically expressive. 

 

50.0901 Music 7 Music Introduction - 

Middle School Level 

Rhythm, melody, harmony introduction, 

ear training 0 0 2 

50.0902 Music 8 - Middle School Level Rhythm, melody, harmony introduction, 

ear training 0 0 2 

50.0903 Band 7 - Middle School Level Training skills, preparatory work, 

instrumental skill development 0 0 2 

50.0904 Band 7 - Advanced Middle School 

Level 

Marching, concert band 

0 0 2 

50.0905 Band 8 - Middle School Level Training for band 0 0 2 

50.0906 Band 8 Advanced - Middle School 

Level 

Phrasing, individual technique, sound 

production 0 0 2 

50.0907 Band 9 - Middle School Level Training for beginning band 0 0 2 

50.0908 Band 9 Advanced - Middle School 

Level 

Sight reading ability, instrumental 

proficiency, performance by audition 0 0 2 

50.0912 Orchestra 7 - Middle School Level Music reading and performance, skill 

development 0 0 2 

50.0913 Orchestra 7 Advanced - Middle 

School Level 

Music reading and performance, skill 

development 0 0 2 

50.0914 Orchestra 8 - Middle School Level Music playing and performance 0 0 2 

50.0915 Orchestra 8 Advanced - Middle 

School Level 

Music playing and performance 

0 0 2 

50.0916 Orchestra 9 Music playing and performance 0 0 2 

50.0917 Orchestra 9 Advanced Section playing, audition, performance 0 0 2 

50.0935 Chorus 7 - Middle School Level Practice for special productions, basic 

music reading, tone production, 

intonation and rhythm 0 0 2 

50.0936 Chorus 7 Advanced - Middle 

School Level 

All-state, all-county auditions, pitch 

matching, intonation, tone quality, 

rhythm, sight-reading 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-34 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

50.0937 Chorus 8 - Middle School Level Practice for special productions, pitch 

matching, intonation, tone quality, 

rhythm, sight-reading 0 0 2 

50.0938 Chorus 8 Advanced - Middle 

School Level 

All-state, all-county auditions, advanced 

pitch matching, intonation, tone quality, 

rhythm, sight-reading 0 0 2 

50.0939 Chorus 9 Participation in special chorus, music 

reading, tone production, intonation and 

rhythm 0 0 2 

50.0940 Chorus 9 All-state, all-county audition, balance, 

sound, voice production 0 0 2 

50.0953 Music History 7 - Middle School 

Level 

Music history, Renaissance to the 

present 0 0 2 

50.0954 Music History 8; Music through the 

Ages - Middle School Level 

Performance, theory, musical history, 

jazz, popular music, elements of musical 

structure, 20th century music 0 0 2 

50.0955 Music History 9; Contemporary 

Music 9; Pop Music History 9 - 

Middle School Level 

History of American music, 20th 

century music 

0 0 2 

 

54 ACADEMICALLY FOCUSED 

SELF-CONTAINED SPECIAL 

EDUCATION PROGRAMS 

 

 

54.1 FUNCTIONAL 

MATHEMATICS 

 

 

54.1002 General Mathematics Skills - 

Middle School Level 

Applications for independent 

functioning, precomputation skills, time, 

money, fundamental mathematical 

processes 0 0 2 

54.1102 Functional Consumer Mathematics 

- Middle School Level 

Budgeting, shopping, financial planning, 

taxes, loans 0 0 2 

54.1202 Functional Vocational Mathematics 

- Middle School Level 

Calculation, measurement, job skills, 

practical shop uses, skill development 0 0 2 

 

54.2 FUNCTIONAL ENGLISH 

 

54.2012 Functional Language Arts 1 - 

Middle School Level 

Provides a unified approach to 

instruction in speaking, reading, and 

writing 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-35 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

54.2102 Functional Reading - Middle 

School Level 

Word recognition, reading vocabulary, 

reading signs, spelling, word attack 

skills 0 0 2 

54.2202 Functional Oral Communication - 

Middle School Level 

Speaking intelligibly, listening and 

understanding directions 0 0 2 

54.2302 Functional Writing - Middle School 

Level 

Basic sentence structure, spelling, 

personal and business letters, completing 

application forms, penmanship 0 0 2 

54.2402 Functional Academics - Middle 

School Level 

Individualized academic curriculum, 

study skills, specialized academic 

support (not specified elsewhere) 0 0 2 

 

54.3 FUNCTIONAL LIFE SKILLS 

 

54.3002 Activities of Daily and Family 

Living - Middle School Level 

Functioning in the community, local 

transportation systems, budgeting, home 

and personal maintenance, family 

responsibilities 0 0 2 

54.3102 Social/Behavioral Skills - Middle 

School Level 

Follow accepted rules and standards, 

friendship problem solving, self-control, 

personal interactions 0 0 2 

54.3202 Functional Leisure and Recreational 

Skills - Middle School Level 

Management of free time, team 

behavior, recreation skills, rules, 

preparation for activities, selection of 

appropriate attire, maintenance of 

equipment 0 0 2 

54.3301 Functional Health - Middle School 

Level 

Principles of cleanliness and hygiene, 

sex education, proper diet, grooming, 

emergency procedures, medical care 0 0 2 

54.3402 Functional Transition Skills - 

Middle School Level 

Planning for future independent living or 

employment, skills for adult living, 

should include a work readiness 

component 0 0 2 

54.4 FUNCTIONAL SCIENCE AND 

SOCIAL STUDIES 

 

 

54.4002 Functional Science - Middle School 

Level 

Science concepts applied to daily living; 

simplified science, using household 

chemicals; safety; the human body; 

caring for animals 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-36 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

54.4502 Functional Social Skills - Middle 

School Level 

Simplified principles of social science, 

structure of local government and 

election process, community resources 

and agencies, local geography, finding 

addresses and using public 

transportation 0 0 2 

54.9402 Handicapped Developmental 

Support Services - Middle School 

Level 

Gross and fine motor skills, visual 

perception development, eye-hand 

coordination 0 0 2 

55 CAREER PREPARATION AND 

EXPLORATION FOR 

SELF-CONTAINED SPECIAL 

EDUCATION PROGRAMS 

 

 

55.0 CAREER PREPARATION AND 

EXPLORATION 

 

 

55.0002 General Prevocational Preparation - 

Middle School Level 

Classroom-based employability skills, 

job behaviors, safety, self-reliance 0 0 2 

55.0102 Career Exploration - Middle School 

Level 

Generalized job interests and aptitudes, 

manual dexterity and motor integration 0 0 2 

55.0402 Combined Vocational and 

Academic Preparation - Middle 

School Level 

Includes career exploration, 

prevocational skills, academic 

curriculum, social and survival skills 0 0 2 

 

56 SUBJECT AREA PROGRAMS 

AND SERVICES IN 

RESOURCES AND 

MAINSTREAM SPECIAL 

EDUCATION PROGRAM 

 

56 SUBJECT AREA SERVICES 

 

56.2300 Special Education Language Arts Not elsewhere classified learning 

problems English, basic resource 

English, resource language arts, English 

and language skills, vocabulary 

development 0 0 2 

56.2301 Resource Language Arts and 

English 

Resource English, resource language 

arts, learning problems English, basic 

English and language skills, vocabulary 

development 0 0 3 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-37 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

56.2311 Resource Reading Resource reading, word attack skills, 

vocabulary development, comprehension 

and interpretation 0 0 3 

56.2320 Special Education Writing - Middle 

School Level 

Not elsewhere classified 

0 0 2 

56.2321 Resource Writing Resource writing, sentence and paragraph 

development, forms and applications, letter 

writing 0 0 2 

56.2341 Resource Language Arts and 

English 7 - Middle School Level 

Resource English; resource language arts; 

learning problems English; basic and 

language skills; spelling handwriting, 

vocabulary development; developmental 

English ESE AAP 0 0 2 

56.2342 Resource Language Arts and 

English 8 - Middle School Level 

Resource English, resource language arts; 

learning problems English; basic language 

skills; spelling, handwriting, vocabulary 

development; developmental English ESE 

AAP 0 0 2 

56.2343 Resource Reading - Middle School 

Level 

Resource reading, word attack skills, 

vocabulary development, comprehension 

and interpretation 0 0 2 

56.2700 Special Education Mathematics Not elsewhere classified 0 0 2 

56.2701 Resource General Mathematics Resource mathematics, learning problems 

mathematics, calculating devices, money 

management, basic mathematics skills 0 0 2 

56.2702 Resource General Mathematics 7 - 

Middle School Level 

Resource mathematics, learning problems 

mathematics, calculating devices, money 

management, basic mathematics skills 0 0 2 

56.2703 Resource General Mathematics 8 - 

Middle School Level 

Resource mathematics, learning problems 

mathematics, calculating devices, money 

management, basic mathematics skills 0 0 2 

 

56.32 RESOURCE VOCATIONAL 

COURSES 

 

 

56.3201 Resource Career Exploration and 

Pre-Vocational Skills 

Resource career preparation, employability 

skills, job readiness, job interests, career 

options 0 0 2 

56.3202 Resource Career Exploration and 

Prevocational Skills - Middle 

School Level 

Resource career preparation, employability 

skills, job readiness, job interests, career 

options 0 0 2 a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
 G-38 

Table G-1. Middle school CSSC developed for National Evaluation of GEAR UP (continued) 

CSSCID Course Description SEa LGb LVc

56.4001 Resource General Science Combined basic science study, life 

science, human body, physical science, 

basic science concepts, applied science 0 0 2 

56.4002 Resource General Science - Middle 

School Level 

Combined basic science study, life 

science, human body, physical science, 

basic science concepts, applied science 0 0 2 

56.4501 Resource Social Studies Citizenship; resource social studies; 

learning problems social studies; 

consumer skills, history and geography 0 0 2 

56.4502 Resource Social Studies - Middle 

School Level 

Citizenship; resource social studies; 

learning problems social studies; 

consumer skills, history and geography 0 0 2 

 

56.9 GENERAL RESOURCE 

SERVICES 

 

 

56.9001 General Tutorial Services Individualized instructional assistance to 

support regular courses, as needed study 

or survival skills support 0 0 2 

56.9002 General Tutorial Services - Middle 

School Level 

Individualized instructional assistance to 

support regular courses, as-needed study 

or survival skills support 0 0 2 

56.9101 Resource Study Skills Study skills, resource study skills, 

learning problems 0 0 2 

56.9102 Resource Study Skills - Middle 

School Level 

Study skills, resource study skills, 

learning problems 0 0 2 

56.9201 School and Social Survival Skills Strategies for negotiating school, school 

behavior 0 0 2 

56.9202 School and Social Survival Skills -

Middle School Level 

Strategies for negotiating school, school 

behavior 0 0 2 

56.9209 School and Social Survival Skills, 

not for credit 0 0 2 

56.9301 Resource Survival Skills General survival skills, independent 

living, social skills, daily living skills 0 0 2 

56.9302 Resource Survival Skills - Middle 

School Level 

General survival skills, independent 

living, social skills, daily living skills 0 0 2 

56.9401 Handicap Specific Support Services Speech therapy, mobility training, 

auditory or visual training 0 0 2 

56.9402 Handicap Specific Support Services 

-Middle School Level 

Speech therapy, mobility training, 

auditory or visual training 0 0 2 

 

99.9911 UNKNOWN, CODE LATER 0 0 2 

a SE flag identifies whether a course is non-special education, self-contained special education or resource-level special education. 

b LG is a language flag that identifies whether course is taught in English or a language other than English. 

c LV is a level flag that identifies the academic level of the course (regular, honors, remedial, advanced placement or international baccalaureate). 
G-39 

Table G-2. Course codes for each academic pipeline 

Academic pipelines Course codes* 

Mathematics progression 

No mathematics 

Remedial only 27.0601, 56.2701, 56.2702, 56.2703, 54.1002, 54.1102 

Nonacademic: 

 Below grade 27.0101, 27.0102 

 On grade 27.0103 

 Honors and above grade 27.0104, 27.0106 

Academic preliminary 27.0401 

Academic 27.0402, 27.0404, 27.0421, 27.0428 

Science progression 

No science 

Remedial science only (None) 

Life sciences and physical science survey 

 Below grade 30.0101, 30.0102, 26.0111 

 On grade 30.0103 

 Honors and above grade 30.0104 

Chemistry and physics 

 On grade 40.0111 

 Honors and above grade 40.0112 

English progression 

No English 

Remedial English only (None) 

Below grade level 23.0101, 23.0102, 23.0103, 23.1201, 23.1211 

On grade 23.0104, 23.0402, 23.0407,23.1202, 23.1311 

Honors and above grade 23.0105, 23.0107 

Foreign language progression 

No foreign language 

Below grade level 16.0931 

On grade level 16.0902, 16.0932 

Above grade level 16.0933, 16.0934 

* Codes refer to the CSSC as modified by the national evaluation for use in middle schools. 

Adjustments were made for academic classes that were identified as honors, advanced placement (AP) or 

international baccalaureate classes. These classes were treated as honors and above-grade classes as 

shown in table G-3. For example, a course titled “Eighth Grade Mathematics” on a student’s transcript 

would be coded 27.0103. Additional information from the school might indicate that this particular class 

was being taught as an honors class. This information was captured in a separate field and was used to 

elevate the class to the honors and above grade level. In this example, the class would be treated the same 

as a class titled “Honors Eighth Grade Mathematics” or “Mathematics 8, Accelerated” (i.e., modified 
 G-40 

CSSC code 27.0104). Classes that were identified as ninth grade or higher level classes were also treated 

as honors and above-grade classes. 

Table G-3. Adjustments to class codes with honors identifiers 

Academic pipeline Class code* Honors and above-grade code* 

Mathematics 27.0103 27.0104 

 

Science 30.0103, 40.0111 30.0104, 40.0112 

English 23.0104, 23.0402, 23.0407, 

23.1202, 23.1311 

23.0105, 23.0107 

 

Foreign language 16.0902, 16.0932 16.0933, 16.0934 

* Codes refer to the CSSC as modified by the national evaluation for use in middle schools. 

Similar to adjustments for classes identified as honors, academic classes taken by eighth-graders that had 

a grade level code of seven were treated as below grade level. On-grade and below-grade classes that 

were identified as remedial or resource were treated as remedial classes as seen in table G-4. Additional 

adjustments were not made to classes identified as special education. 

Table G-4. Adjustments to class codes with remedial or resource identifiers 

Academic pipeline On-grade class code Below grade code 

Mathematics 27.0103 27.0101, 27.0102 

 

Science 30.0103, 40.0111 30.0101, 30.0102, 26.0111 

English 23.0104, 23.0402, 23.0407, 

23.1202, 23.1311 

23.0101, 23.0102, 23.0103, 23.1201, 

23.1211 

 

Foreign language 16.0902, 16.0932 16.0931 

* Codes refer to the CSSC as modified by the national evaluation for use in middle schools. 

G.2 Academic Rigor 

Academic rigor or difficulty of a student’s course load was determined by identifying the number of 

classes the student completed that were considered to be above grade level. For example, if the student 

took honors English, algebra, eighth-grade science and Spanish in eighth grade, the student’s academic 

rigor score would be two because honors English and algebra would be counted as above grade level. 
G-41 

G.3 Grade Point Average (GPA) 

Because many middle schools in the national evaluation did not report GPAs for their students, an 

academic GPA was calculated for all students. The academic GPA was based on student grades for 

classes in the four core subject areas: English, mathematics, science and foreign language. If a school 

reported grades by semester for year-long classes, an average grade for the class for the year was first 

calculated. An overall GPA was then calculated. 

H-1 

Appendix H 

Analysis of Standardized Test Scores 

While standardized test scores were collected for nearly all students in the National Evaluation of Gaining 

Early Awareness and Readiness for Undergraduate Programs (GEAR UP) for whom parental consent was 

obtained, the tests administered to students varied across schools according to district and state policies. 

The 32 schools in the national evaluation that provided standardized test scores were spread across seven 

states. Collectively these schools administered 13 different standardized tests to eighth-graders during the 

2001–02 school year. 

Scores from different standardized tests are not compatible, so analyzing them together as a separate 

measure was not feasible. It is possible, however, to analyze the test scores of students who took the same 

test, which is why this limited analysis is only presented as an appendix. Two of the 13 standardized tests 

were administered to students at several schools in the evaluation. One of the tests was a nationally 

normed test (Test A). Test A was administered to students enrolled in six schools located in two states. 

These six schools represent three matched sets of GEAR UP and non-GEAR UP schools. 

Test A included separate reading and mathematics components. The reading component of the test was 

administered in the same schools as the mathematics component with the exception of one school, which 

did not administer the reading test to eighth-graders. Among the students in these schools in the 

evaluation, about 350 students received Test A mathematics scores and about 300 received Test A reading 

scores. 

The other test used in this analysis (Test B), was a state-normed test. Five schools administered both the 

reading and mathematics components of Test B to eighth-graders during the 2001–02 school year. Four of 

the five schools represented two pairs of matched schools. The fifth school is a GEAR UP school. More 

than 400 students received reading and mathematics test scores across the five schools. 

For both tests, eighth-grade scores (from tests administered during the 2001–02 school year) were 

analyzed. Ideally, baseline scores would have been compared with eighth-grade scores, but no adequate 

baseline scores were accessible. Tests taken during the seventh grade occurred too far into the school year 

to provide an accurate baseline, and sixth-grade scores were unavailable. Instead of comparing eighthgrade scores to previous tests, models were created from uncontaminated seventh-grade questionnaire 

items. (For a more detailed explanation of uncontaminated variables, see Appendix E on Removal of 

Baseline Differences.) These models controlled for differences between GEAR UP and comparison 

students, beyond those that were controlled through the selection of the non-GEAR UP comparison 

schools. Through these models, a main effect for treatment status (GEAR UP versus non-GEAR UP 

school) can be interpreted as a GEAR UP effect on test scores, as long as the model assumptions hold. 

But, there were some indications of model assumption violations, which led to the use of nonparametric 

tests for GEAR UP effects on test scores. In these nonparametric tests, the GEAR UP and non-GEAR UP 

students were grouped by their predicted scores, and their test scores were compared within groups, to 

estimate any GEAR UP effect on test scores. 
 H-2 

H.1 Analysis of Test A 

To analyze the effect of GEAR UP on Test A scores, separate models for predicting Test A mathematics 

and reading scores were created. By using such models, comparisons between predicted and actual test 

scores could be made for both the treatment (GEAR UP) and control (non-GEAR UP) students. These 

comparisons indicate whether GEAR UP students performed significantly differently on Test A than their 

non-GEAR UP counterparts, after controlling for the variables used in the predictions. 

 Normalizing Test A Scores 

For the models to work, the students’ test scores would need to be fairly normally distributed. Because the 

raw scores for Test A were not normally distributed, several steps were taken to minimize the impact of 

their nonnormality. The first step was to modify the test scores using a probit transformation. The probit 

transform put the test scores on a scale ranging from -∞ to ∞. Figures H-1 and H-2 show the results of the 

probit transform, which helped somewhat, but still did not produce a normal distribution of the scores for 

Test A reading or mathematics. Although the probit transformed scores were not centered at 0, this was 

understandable because the population in the evaluation was composed of predominately lower 

performing students. 

Figure H-1. Histogram of Test A probit reading scores 
H-3 

Figure H-2. Histogram of Test A probit mathematics scores 

The next step in the attempt to normalize the test scores was to perform a Box-Cox transformation on the 

probit transformed scores. With this second transformation, the residual scores met the standard for 

normality and then could be analyzed with the models to be explained below. Figures H-3 and H-4 are 

histograms of these transformed scores. 

Figure H-3. Histogram of Box-Cox transformed Test A probit reading scores with 

lambda=1.17931 
 H-4 

Figure H-4. Histogram of Box-Cox transformed Test A probit mathematics scores with 

lambda=0.924138 

 Creating the Test A Models 

Because the scores were reasonably close to normal, models to predict Test A reading and mathematics 

scores were created. The models attempted to isolate the student and parent variables that best predict 

Test A reading and mathematics scores. Not all students’ scores were used in the formation of the models, 

however. If a student had a standardized residual with an absolute value of more than three, it was 

considered an outlier and omitted. The models were, therefore, formed using 294 Test A reading scores 

and 354 Test A mathematics scores. In addition, only uncontaminated seventh-grade variables were used 

in the models to preserve any early GEAR UP effects that could have occurred in the fall of seventh 

grade. 

Next, a series of step-wise searches for main effects and interactions was performed. In this process, the 

models were first fit with main effects. Then, the models for interaction terms involving main effects of 

over 0.05 percent significance were created. Tables H-1 and H-2 show the variables that entered the 

separate models for reading and mathematics, respectively. 
H-5 

Table H-1. Seventh-grade variables used to predict Test A reading scores 

Obs Effect Estimate 

Standard 

error tValue Probt 

1 Intercept 2.498 0.340 7.35 <.0001 

2 Black_7 -0.390 0.151 -2.59 0.01 

3 TalkHouseCollEntClasses_7 -0.306 0.086 -3.57 4E-04 

4 AdultHangFreq_7 -0.560 0.139 -4.03 <.0001 

5 CollegeBoundRev_7 2.328 0.398 5.84 <.0001 

6 ComputerFreq_7 0.344 0.123 2.79 0.006 

7 DontNeedHelp_7 -0.294 0.120 -2.46 0.015 

8 ESLBIL7 -0.366 0.112 -3.27 0.001 

9 Grades_7 0.705 0.224 3.14 0.002 

10 HowHard_7 -0.603 0.223 -2.7 0.007 

11 ImpGoCollege_7 -1.270 0.266 -4.77 <.0001 

12 Mobility_7 0.354 0.131 2.71 0.007 

13 ParGrades_7 0.447 0.248 1.8 0.073 

14 ParTalkPolitics_7 -1.300 0.267 -4.87 <.0001 

15 White_7 -0.393 0.380 -1.03 0.302 

16 computerathome_7 0.354 0.089 3.96 <.0001 

17 pimphardwork_7 0.397 0.180 2.2 0.028 

18 TalkHouseCollEntClasses_7*HowHard_7 -0.854 0.325 -2.63 0.009 

19 DontNeedHelp_7*HowHard_7 -0.782 0.247 -3.17 0.002 

20 ESLBIL7*ParGrades_7 1.376 0.336 4.1 <.0001 

21 Mobility_7*White_7 1.438 0.500 2.87 0.004 

22 Tschool -0.006 0.097 -0.06 0.953 

* All numeric variables rescaled linearly from 0 to 1. 

The fitted models were used to generate predicted Test A reading and mathematics scores for each 

student. Figures H-5 and H-6 demonstrate how actual scores compared with predicted Test A reading and 

mathematics scores, separately. Each point in these figures represents a group of test scores; there are 50 

groups. The figures show that the model predicts actual test scores fairly well. 

Note that the line in Figures H-5 and H-6 is a 45o line, not a model fit line. The points tend to lie below 

the 45o line because of technical issues concerning the universe transformation of predicted scores of the 

Box-Cox transform. The important feature is that points do lie fairly close to a straight line. 

 Analyzing the Residuals of the Test A Reading and Mathematics Models 

Interpreting the results of the models required the use of a t-statistic. For the p value of a t-statistic to be 

correct, the residuals of the model must be normally distributed. Therefore, before any results from the 

model can be interpreted, it must be determined whether the residuals are normally distributed. 
 H-6 

Table H-2. Seventh-grade variables used to predict Test A mathematics scores 

Obs Effect Estimate StdErr tValue Probt 

1 Intercept 3.003 0.300 10.01 <.0001 

2 Firstlanguage_7 -0.148 0.057 -2.61 0.0094 

3 ParentHelp_7 -0.173 0.081 -2.13 0.0337 

4 TalkCounHSGradClasses_7 0.217 0.162 1.34 0.18 

5 Black_7 -0.316 0.091 -3.47 0.0006 

6 CollegeBoundRev_7 0.278 0.392 0.71 0.4779 

7 CollegeClose_7 -0.432 0.102 -4.25 <.0001 

8 ESLBIL7 -0.208 0.062 -3.34 0.0009 

9 FatherGoCollege_7 0.138 0.060 2.3 0.0219 

10 GENDER -0.159 0.158 -1 0.3175 

11 Grades_7 -0.413 0.286 -1.45 0.1491 

12 Hispanic_7 -0.081 0.069 -1.17 0.2432 

13 IEP7 -0.214 0.085 -2.52 0.0121 

14 ImpGoCollege_7 -0.449 0.155 -2.9 0.0039 

15 ImpWork_7 -0.527 0.174 -3.02 0.0027 

16 MathClub_7 0.510 0.086 5.94 <.0001 

17 MathHomework_7 0.450 0.145 3.11 0.002 

18 OtherHelp_7 -0.125 0.058 -2.16 0.0317 

19 ParGrades_7 0.418 0.183 2.28 0.0231 

20 ScienceHomework_7 -0.282 0.181 -1.56 0.1198 

21 Black_7*GENDER 1.848 0.495 3.73 0.0002 

22 FatherGoCollege_7*OtherHelp_7 0.494 0.222 2.22 0.0269 

23 GENDER*ScienceHomework_7 -0.575 0.236 -2.44 0.0153 

24 Grades_7*ImpWork_7 -0.526 0.108 -4.85 <.0001 

25 tschool -0.126 0.055 -2.27 0.0236 

* All numeric variables rescaled linearly from 0 to 1. 

Figure H-5. Grouped actual versus predicted Test A reading scores 

NOTE: Line is a 45° line, not a model fit line. 
H-7 

Figure H-6. Grouped actual versus predicted Test A mathematics scores 

NOTE: Line is a 45° line, not a model fit line. 

Six different tests for normality were performed on each set of residuals. A set of residuals must have 

passed all of these tests to have been considered normal. The tests used in this exercise included a 

scatterplot of standardized residuals; a normal curve superimposed on a histogram of the residuals; a QQ 

plot for normality; and the Kolmogorov-Smirnov, Cramer-von Mises and Anderson-Darling tests. 

The residuals from the Test A reading model did not pass the Kolmogorov-Smirnov test and barely 

passed the Cramer-von Mises and Anderson-Darling tests. Table H-3 outlines the statistic and p value for 

each of these tests. For the residuals to have passed any of these tests, the p value must have been greater 

than 0.05. 

Table H-3. Goodness of fit tests for normal distribution of residuals from the Test A reading 

model 

Test Statistic p Value 

Kolmogorov-Smirnov D 0.056 Pr > D 0.023 

Cramer-von Mises W-Sq 0.116 Pr > W-Sq 0.073 

Anderson-Darling A-Sq 0.741 Pr > A-Sq 0.054 

Because the residuals from the Test A reading model were not normally distributed, parametric tests like 

the model outlined in table H-1 could not be used to determine whether GEAR UP students had Test A 

reading scores that were significantly different from those of students in non-GEAR UP schools. A 

nonparametric test, to be described later, would provide some additional information on this question. 

The residuals for the Test A mathematics model, on the other hand, did pass all of the tests for normality. 

Thus, the parameters outlined in table H-2 can be reliably interpreted. The most important parameter in 

this discussion was number 25, tschool (treatment school status). This variable indicated whether the 

student attended a GEAR UP school. Because the estimate for this variable was negative, it appears that 
 H-8 

GEAR UP caused a worsening of student performance on the mathematics section of Test A. To further 

explain this finding, a nonparametric analysis was performed and is discussed below. 

 Performing Nonparametric Analyses of Test A Reading and Mathematics Scores 

A nonparametric analysis was performed to provide more information about the inconclusive findings for 

the reading component of Test A and the finding of negative GEAR UP impact on the mathematics 

component of Test A. For these analyses, the students were clustered into 10 groups for each test subject 

based on their predicted Test A scores for that subject. Within each of the 10 groups, the students were 

divided into two groups, based on whether they had attended a GEAR UP school. 

For each of the resulting 10 groups, figures H-7 and H-8 show the relationship between predicted and 

actual Test A reading and mathematics scores, respectively. In figure H-7, each treatment group (GEAR 

UP) was almost horizontally lined up with its corresponding control group indicating that the predicted 

scores for both groups were similar. The lines were nonparallel and actually crossed one another, 

indicating that there is not a consistent difference in the scores between GEAR UP and non-GEAR UP 

students. The validity of this finding is not affected by the lack of normality of the residuals described 

above. 

Figure H-7. Actual Test A reading scores by predicted Test A reading scores, by treatment 

school status 
H-9 

Figure H-8. Actual Test A mathematics scores by predicted Test A mathematics scores, by 

treatment school status 

The results for Test A mathematics scores were somewhat different. The parametric model shown in table 

H-2 indicates that there was an overall negative effect of GEAR UP on Test A mathematics scores. Figure 

H-8 provides further information on this finding. For one-half of the figure, the matched nodes were 

horizontally and vertically close to one another indicating that Test A mathematics scores for GEAR UP 

and non-GEAR UP students were similar. However, the third through the seventh pairs are further apart 

than the other pairs. (Students were grouped by increasing predicted Test A mathematics scores, so of 

these five groups, Group three had the lowest predicted Test A mathematics score, and the seventh group 

had the highest.) In the third, fourth, and seventh groups, it appears that students in the non-GEAR UP 

group performed better on the mathematics component of Test A. For Groups five and six, GEAR UP 

students had higher Test A mathematics scores. The differences in test scores somewhat cancel each other 

out in an overall measure. But, because non-GEAR UP students outscored GEAR UP students in three 

groups, while the opposite was true in only two groups, a small overall negative GEAR UP effect, 

outlined in the previous step of the analysis, was detected. 

H.2 Analysis of Test B 

The analysis of Test B took the same path as that taken for Test A, so the explanation of the Test B 

process will not be as detailed as the discussion for Test A. 

Actual Test A 

mathematics 

score 

Predicted Test A mathematics
 H-10 

 Normalizing Test B Scores 

As with Test A, the Test B scores had to be normally distributed for the p values on GEAR UP effects to 

be valid. First, the scores were modified using a probit transform, putting the test scores on a scale 

ranging from -∞ to ∞. Next, a Box-Cox transformation was performed on the probit transform scores. 

After this procedure, the scores were sufficiently normalized to proceed with the creation of the models. 

 Creating the Test B Models 

The procedure for creating the Test B models was the same as that for Test A. As with Test A, the score 

of any student that had a standardized residual with an absolute value over three was considered an outlier 

and omitted. In addition, only uncontaminated seventh-grade variables were used in the models. The 

models were formed on 407 Test B reading scores and 395 Test B mathematics scores. 

A series of step-wise searches for main effects and interactions was then performed, first fitting the model 

with main effects. Then, the models for interaction terms involving main effects of over 0.05 percent 

significance were created. Tables H-4 and H-5 show the variables that entered the separate models for 

reading and mathematics, respectively. 

Table H-4. Seventh-grade variables used to predict Test B reading scores 

Obs Effect Estimate Standard error tValue Probt 

1 Intercept 1.935 0.309 6.27 <.0001 

2 ChessClub_7 -0.470 0.176 -2.67 0.0079 

3 ComputerFreq_7 0.355 0.135 2.63 0.0089 

4 Black_7 -0.908 0.273 -3.33 0.001 

5 ClubHours_7 0.969 0.199 4.87 <.0001 

6 ESLBIL7 -0.664 0.155 -4.29 <.0001 

7 EdFor30_7 0.883 0.213 4.14 <.0001 

8 HeardVocEd_7 -0.262 0.109 -2.39 0.0171 

9 Hobbies_7 0.326 0.114 2.86 0.0044 

10 Kim38R_7 0.427 0.152 2.8 0.0054 

11 OtherSchoolHelp_7 -0.421 0.107 -3.95 <.0001 

12 ParGrades_7 -0.704 0.453 -1.55 0.1209 

13 ParentEd_7 0.906 0.200 4.53 <.0001 

14 UncleHelp_7 -0.280 0.109 -2.58 0.0103 

15 VolunteerFreq_7 -0.575 0.236 -2.44 0.0152 

16 hmwkundr_7 0.728 0.227 3.21 0.0014 

17 ClubHours_7*GrParentGoCollege_7 -0.548 0.208 -2.64 0.0086 

18 Grades_7*ParGrades_7 2.256 0.414 5.45 <.0001 

19 tschool -0.035 0.110 -0.32 0.7508 

* All numeric variables rescaled linearly from 0 to 1. 
H-11 

Table H-5. Seventh-grade variables used to predict Test B mathematics scores 

Obs Effect Estimate Standard error tValue Probt 

1 Intercept 1.025 0.163 6.29 <.0001 

2 ClubHours_7 0.181 0.081 2.24 0.0256 

3 CollegeMoreMoney_7 0.352 0.083 4.23 <.0001 

4 NegTVHours_7 0.193 0.077 2.49 0.0134 

5 AbsentDays_7 0.241 0.081 2.97 0.0031 

6 AnySibling_7 0.178 0.047 3.78 0.0002 

7 ESLBIL7 0.426 0.247 1.73 0.0851 

8 Firstlanguage_7 -0.262 0.047 -5.62 <.0001 

9 FriendOpImport_7 -0.321 0.103 -3.12 0.0019 

10 Grades_7 0.718 0.132 5.42 <.0001 

11 NumAdult_7 -0.192 0.059 -3.26 0.0012 

12 ParTalkPolitics_7 0.139 0.060 2.31 0.0214 

13 ParentEd_7 0.350 0.086 4.05 <.0001 

14 UncleHelp_7 -0.142 0.044 -3.19 0.0015 

15 performance_7 0.667 0.122 5.48 <.0001 

16 ESLBIL7*Grades_7 -1.002 0.338 -2.96 0.0033 

17 EnglishHomework_7*computerathome_7 0.400 0.158 2.53 0.0118 

18 LikelyGoCollege_7*OtherSchoolHelp_7 -0.357 0.064 -5.6 <.0001 

19 OtherSchoolHelp_7*computerathome_7 0.256 0.069 3.7 0.0003 

20 tschool -0.040 0.045 -0.87 0.3824 

* All numeric variables rescaled linearly from 0 to 1. 

 Analyzing the Residuals of the Test B Reading and Mathematics Models 

As with Test A, the residuals from the Test B models had to meet tests for normality. The residuals from 

both the Test B reading and Test B mathematics models failed at least one of the tests for normality. 

Scatterplots of standardized residuals for the Test B reading and Test B mathematics models were created 

to ensure that the models adequately predicted actual Test B scores. These scatterplots were similar to 

those for Test A, which were displayed in figures H-5 and H-6. In the scatterplots for Test B, figures H-9 

and H-10, obvious diagonal bands appeared, indicating that the residuals were not normally distributed. 
 H-12 

Figure H-9. Standardized residual analysis of Test B reading scores 

Figure H-10. Standardized residual analysis of Test B mathematics scores 
H-13 

Because the residuals for Test B reading and mathematics were not normally distributed, the results of the 

Test B reading and Test B mathematics models cannot be accurately interpreted using parametric tests 

such as the models outlined in tables H-4 and H-5. 

 Performing Nonparametric Analyses of Test B Reading and Mathematics Scores 

As with the Test A reading model, the Test B model was unable to provide evidence of an effect of 

GEAR UP on Test B reading or mathematics scores. Thus, the nonparametric analysis was again used to 

provide additional information. The same procedure was followed as for the nonparametric analysis of 

Test A. Figures H-11 and H-12 show the relationship between Test B reading and Test B mathematics 

scores, respectively, for each of the 10 groups created. 

Figure H-11. Actual Test B reading scores by predicted Test A reading score, by treatment school 

status 
 H-14 

Figure H-12. Actual Test B reading scores by predicted Test A mathematics score, by treatment 

school status 

In both cases, each treatment (GEAR UP) group was approximately horizontally lined up with its 

comparison (non-GEAR UP) group, indicating that the predicted scores for both groups were similar. The 

lines were nonparallel and crossed one another. This indicated that there was not a consistent difference in 

the scores between GEAR UP and non-GEAR UP students. 

H.3 Conclusions 

Based on a limited number of schools that had comparable standardized test data, the students in 

comparison (non-GEAR UP) schools performed slightly better than students in GEAR UP schools on the 

mathematics section of Test A, a nationally normed test. Further analysis suggests that this phenomenon 

was driven largely by one subgroup of students. There was no significant difference in scores between 

GEAR UP and non-GEAR UP students for the reading portion of the nationally normed test. 

On the state-normed test (Test B), there was no significant difference in standardized test scores between 

GEAR UP and non-GEAR UP students for either the reading or mathematics components of the test. 
I-1 

Appendix I 

Methodology for Analyzing Program Activity Records 

Arrangements were made with GEAR UP staff to collect information on the participation of each student, 

as well as his or her parents, in services offered by the program. These arrangements were made with the 

primary goal of being able to determine which services and combinations of services were more effective 

than others. This original goal proved impossible to achieve because only six of the 18 GEAR UP 

projects submitted complete information on the activities they provided to students and parents. The data 

were sufficient, however, to examine differences in effects based on individual students’ levels of 

participation in program activities. 

No effects of the program as a whole on the College Orientation Index were detected. It was noted, 

however, that while some services reached all students in a project (such as curriculum reform or teacher 

training), actual participation in many types of GEAR UP services varied greatly among students. This 

raised the question of whether students who actively participated in proffered services might have 

experienced a positive effect on their College Orientation Indexes even though such effects were not 

detected on the wider student body. Answering this question became the secondary use of the program 

activity records data (or participation data). 

The first step in this analysis was to determine a single scale for measuring participation. Since there were 

19 service categories in the edited participation data, this was not a trivial issue. The second step was to 

identify an appropriate comparison group for the students with high participation. Consideration was 

given to comparing them with the other students in the GEAR UP schools—those that had low levels of 

participation. Concerns about potential selection biases with this approach, however, led to the decision to 

draw a control sample from the non-GEAR UP schools. After the control sample had been drawn, the 

third and final step was to calculate the effects and appropriate estimates of sampling error. This appendix 

provides more detail on each of the steps. 

I.1 Participation Scale 

Given the small number of schools with adequate participation data and a desire to simplify analysis and 

clarify presentation, it was decided to develop and use a single participation scale. We considered a 

variety of alternatives62 but in the end decided to simply add together participation hours across all 

reported activities into a variable called TotalDose. This was done with the full knowledge that hours on a 

college field trip might be much more efficacious than a comparable number of hours spent in tutoring, 

but no viable alternate choice was identified. Table I-1 shows the number of participation hours by 

service category as well as how these correlate with TotalDose. TotalDose is dominated by 

 

62 In particular, we tried to use the data on all students from GEAR UP schools to develop a model of which services might be 

more effective than others, but the results from this effort were not compelling, perhaps due to strong selection biases within

the GEAR UP schools, such as would be expected if participation was a function of perceived individual need for the service. 

We also tried a factor analysis, but this resulted in negative weights for some activities. 
 I-2 

AcademicDose and OtherDose but also has high correlation with CareerOtherDose, CollegeDose, and 

OtherPDose. 

Table I-1. Participation hours by service category and correlation with TotalDose and with first 

two factors 

Service category Mean hours Standard error hours Correlation with TotalDose 

Students 

AcademicCareerDose 0.3 1.1 0.00 

AcademicCollegeDose 0.9 2.7 0.06 

AcademicDose 17.2 35.4 0.76 

AcademicLifeSkillsDose 0.1 0.8 0.04 

AcademicOtherDose 1.0 6.9 0.07 

CareerCollegeDose 0.2 1.2 0.09 

CareerDose 5.6 6.1 0.44 

CareerOtherDose 0.6 0.9 0.67 

CollegeDose 7.3 9.5 0.71 

CollegeOtherDose 0.4 1.4 -0.02 

LifeSkillsDose 0.5 1.1 0.08 

MentoringDose 0.3 2.0 0.08 

MultiDose 4.2 10.2 0.08 

OtherDose 24.8 35.5 0.83 

Parents 

CollegeLifeSkillsPDose 0.2 0.6 0.02 

CollegeOtherPDose 0.1 0.3 0.03 

CollegePDose 1.7 2.9 0.08 

LifeSkillsPDose 0.5 1.5 0.36 

OtherPDose 2.3 4.9 0.68 

Table I-2 shows how this variable was distributed across the six GEAR UP schools with usable 

participation data. Clearly, School no. 6 either provided many more service hours to their students or did a 

better job of tracking participation. The unevenness of the participation hours across the schools is an 

important additional caveat. 
I-3 

Table I-2. Distribution of total participation hours across six responding schools 

Participation hours over 2 years 

School Minimum Median Mean Maximum 

Standard 

deviation 

1 10.3 58.1 66.6 180.3 27.4 

2 1.0 17.3 33.4 180.8 41.4 

3 0.0 8.0 6.5 8.2 2.4 

4 0.0 12.0 31.9 187.3 43.3 

5 14.3 66.5 64.7 147.0 25.3 

6 0.0 164.0 166.0 466.0 76.0 

I.2 Drawing a Control Sample for the non-GEAR UP Schools 

The control sample was drawn in a multistep process and involved three types of schools—GEAR UP 

schools with good participation data, GEAR UP schools with insufficient participation data, and nonGEAR UP schools. The first step was to build a model for total participation hours within the six GEAR 

UP schools with two years of good participation data. This model was then applied to students from nonGEAR UP schools as well as students from nonresponding GEAR UP schools (those with fewer than two 

years of good data) to obtain predicted hours. Students were then stratified on the basis of predicted 

participation hours. Within these strata, students from the non-GEAR UP and nonresponding GEAR UP 

schools were randomly matched with students from responding GEAR UP schools. Actual participation 

hours were then copied over onto the student with unknown participation hours from the student with 

known participation hours. This imputation was repeated five times for each student with unknown 

participation. 

Students in the non-GEAR UP and nonresponding GEAR UP schools, were ranked into quintiles on the 

basis of these imputed participation hours. Non-GEAR UP students in the top quintile of imputed 

participation hours were taken as the control sample. More detail on each of these steps follows. 

 Model for Total Participation Hours 

A linear model for the optimal Box-Cox transform of TotalDose was fit using a stepwise search (Box).63

A search of first-order interactions among the most significant terms was also made, but none were found. 

Table I-3 shows the final model, and figure I-1 shows a scatterplot of predicted versus actual TotalDose. 

The R2

 was 0.39. As in modeling nonresponse or GEAR UP assignment propensity, the point of the 

modeling was not to obtain a fuller understanding of the participation decision process. Rather, the point 

was to simply have a solid basis for imputing counterfactual participation hours in the non-GEAR UP 

schools. Also, given the uneven levels of participation across schools, projection of these results to all 

GEAR UP schools might be problematic. 

 

63 TotalDose was slightly right shifted away from 0 and then exponentiated by 0.28621 to obtain the Box-Cox transform; G.E.P. 

Box, and D.R. Cox. An Analysis of Transformations. Journal of the Royal Statistical Society B, 26, 211-252: 1964. 
 I-4 

Table I-3. Model for total participation hours (TotalDose) 

Seventh-grade predictor Estimate Standard error t-statistics value P value 

Intercept 7.4 0.7 10.34 <.001 

Firstlanguage_7 -1.0 0.4 -2.69 0.007 

TeacherHelp_7 1.1 0.3 3.43 0.001 

raceeth_7 1 -1.4 0.5 -2.85 0.005 

raceeth_7 2 -0.9 0.5 -1.92 0.056 

raceeth_7 3 2.9 0.5 5.52 <.001 

raceeth_7 4 -1.9 1.2 -1.51 0.132 

raceeth_7 5 0.0 . . . 

ClubLeader_7 1.0 0.4 2.43 0.015 

Confer_events_7 1.4 0.6 2.36 0.019 

ParTalkEvents_7 0.7 0.4 2.05 0.041 

pexpect_7 1.1 0.6 1.85 0.065 

ClubLeader_7*TakingClasses_7 -1.2 0.4 -2.86 0.004 

Figure I-1. Scatter plot of predicted and observed TotalDose in six schools with adequate 

participation data* 

*Units are in participation minutes rather than hours in this plot. 
I-5 

Considering the scatter plot, it is clear that the model is far from perfect. There is strong evidence of 

heteroscedasticity, missed higher order effects and non-normality. The model was therefore not used to 

directly impute total participation hours in the comparison schools. Instead, the model was used to stratify 

all students. For this use, the model is adequate. Note for example, that among students with predicted 

doses of at least 3,000 minutes, very few have doses under 1,000 minutes. Table I-4 provides more 

information about the effectiveness of the stratification. Discrimination is best at the high end of 

participation, but there is a strong general pattern of increased participation across the strata. 

Table I-4. Statistics about the imputation strata in the six GEAR UP schools with adequate 

participation data 

 Hours of participation over two years 

Imputation stratum Number of students Average Standard error 

1 68 27 28 

2 62 26 32 

3 69 39 39 

4 70 41 45 

5 62 45 44 

6 64 60 59 

7 55 89 78 

8 53 125 74 

9 68 174 74 

 Multiple Hot-Deck Imputations 

After the sample in all three types of schools had been stratified, actual participation hours were imputed 

for all the students in the GEAR UP schools with inadequate data, and counterfactual participation hours 

were imputed for all the students in the non-GEAR UP schools. This was done using a hot-deck 

imputation procedure in which each student from each nonresponding GEAR UP school and each student 

from each non-GEAR UP school was randomly matched with a student from the same stratum from a 

responding GEAR UP school. This was done five times independently of each other so as to be able to 

estimate variances better as is described in the next section. 

On each of the five replicates, the imputed responses within each school category were used to divide 

each sample into quintiles. The highest quintile in each category was then used as the treatment or 

comparison group. 

I.3 Estimation of Effects 

Consideration was given to just comparing outcomes across the groups, but it was decided for this 

analysis that it would better to create an adjusted change score that controls for a student’s starting point. 

This was done by first fitting a model for change in the College Orientation Index in terms of baseline 

variables and then subtracting predicted change from actual change. This model is shown in table I-5. The 

parameters apply to a Box-Cox transformation of Unexplained Growth that was used to improve 
 I-6 

normality.64 The R2

 was 0.05. The model was formed in terms of baseline variables other than the 

baseline values of the outcome indices such as College Orientation Index. The second set of variables was 

omitted from the model in an attempt to avoid adjusting change for regression to the mean. However, an 

alternate model with those variables included did find significant regression to the mean. Variables 

associated with high baseline scores on the College Orientation Index may end up with negative 

coefficients in the growth-readiness model (because the regression to the mean is in a sense flowing 

through them), thereby complicating any analysis of the model. As an example of this, it seems unlikely 

that valuing mothers’ opinions about education actually causes a decrease in the College Orientation 

Index. Indeed, there is a high positive correlation between valuing mothers’ opinions and baseline scores 

on the College Orientation Index. Thus the model is included for documentation rather than as an aid to 

predicting which students are likely to experience improvements on the College Orientation Index. The 

importance of the model is in terms of the better controlled measure of change it provides. 

Table I-5. Model for change in College Orientation Index in terms of baseline variables other 

than baseline versions of primary outcome indexes* 

Effect Estimate Standard error t-statistics value Probability 

Intercept 83.4 2.9 29.0 <.001 

ConferBehave_7 1.9 0.9 2.1 0.036 

EventBacktoSchool_7 -1.6 0.6 -2.5 0.012 

HeardCommColl_7 1.4 0.7 2.0 0.046 

HeardVocEd_7 -1.8 0.7 -2.6 0.009 

Mobility_7 -2.1 0.9 -2.4 0.015 

MotherOpImport_7 -12.1 2.8 -4.3 <.001 

PostSecPlan_7 1 3.1 1.4 2.2 0.027 

PostSecPlan_7 2 6.9 1.6 4.3 <.001 

PostSecPlan_7 3 3.2 0.7 4.7 <.001 

PostSecPlan_7 4 0.0 . . . 

EventFieldTrip_7 -3.1 1.0 -3.2 0.002 

EventPTA_7 2.3 0.7 3.4 0.001 

TeamSport_7 -14.6 4.3 -3.4 0.001 

* As noted in the text, interpretation of these model parameters is hazardous because regression to the mean was strongly present. Thus, 

variables that are predictive of a high seventh-grade score on the College Orientation Index may be negatively related to change in the College 

Orientation Index. 

After the model had been fit, predicted scores were subtracted from actual change scores to yield the 

Unexplained Growth index. Given the low R2

 for the Growth model, the impact of this adjustment was 

modest. The correlation between the raw change in the College Orientation Index and the Unexplained 

Growth index was 0.98. Scores on this adjusted change measure were then averaged within the highest 

reported or imputed quintile of participation hours by school category to produce the estimates shown in 

Table I-6 and discussed in Chapter 3 under the heading “Effects of Participation in GEAR UP Services on 

College Orientation.” 

 

64 The Box-Cox transform was calculated by shifting the change scores so they were all positive and the exponentiating by 

1.17931. After the model had been fit, the reverse transformation was applied to predicted values to obtain predicted change in

the College Orientation Index. 
I-7 

Table I-6. Effects of intense participation in GEAR UP services on unexplained growth in the 

College Orientation Index 

Group 

Top quintile of students in terms of actual 

or imputed participation hours 

Average score on unexplained 

growth in College Orientation 

Index 

95% 

Confidence 

interval 

1 GEAR UP schools with complete 

participation data 0.24 (-1.19,1.68) 

2 GEAR UP schools with incomplete 

participation data 0.18 (-0.95,1.32) 

3 Non-GEAR UP schools -1.67 * (-2.62,-0.71) 

1–3 Participation Effect 1.91 * (0.18,3.64) 

NOTES: The number -0.0 indicates that the true value of this number is less than zero, but more than -0.1. Detail may not sum to totals because 

of rounding. 

No weights were used and there was no correction for clustering, unlike the techniques used for all other 

analyses in chapter 3. The confidence intervals shown in table I-6 were estimated using Rubin’s formula 

for post-imputation variance estimation, assuming that the students in each school group were a simple 

random sample with replacement.65 Some additional detail on the variance calculation is given below. 

Let irj y be the score on Unexplained Growth for the j-th student within the i-th school group on the r-th 

repeated imputation and let ir n be the number of students in that school group on that imputation. Then 

the estimated standard error on the average response was 

( ) ( )

5 5 2 2 . . ..

11 1

1 1 61 ˆ 5 1 54

ir n

i irj ir ir i

rj r ir

s y y y y

n == =

= + − − − ∑∑ ∑ , 

where 

.

1

1 ir n

ir irj

ir j

y y

n =

= ∑ is the average Unexplained Growth score for the i-th school group on the r-th 

imputation and 

5

.. .

1

1

5 i ir

r

y y

=

= ∑ is the overall average Unexplained Growth score for the i-th school group across all five 

imputations. 

 

65 D.B. Rubin. Multiple Imputation after 18+ Years. Journal of the American Statistical Association, 91, 473-489: 1996. 

J-1 

Appendix J 

Glossary 

This appendix contains the definitions of the variables used in the analyses reported in The Early 

Outcomes of the GEAR UP Program—Final Report (see Table J-1, which starts on page J-4). Explanation 

of each of the columns used in that table is provided here. 

 Variable Name. Identifies the names of the variables used throughout the analysis 

and the report. 

 Variable Type. Identifies each variable’s type. An explanation of each type appears 

on page J-2. 

 Definition. Gives the meaning of each variable. 

 Source: Instrument. Identifies the data collection instrument from which the variable 

originates. 

 Source: Item(s). Provides the information on each variable’s source. For example, 

SQ34b_8 refers to question number 34b of the student survey. 

- SQ = student survey, 

- PQ = parent interview, 

- _7 = seventh grade, 

- _8 = eighth grade, and 

- SIM = student administrative records. 

If a variable is a computed variable, the names of the variables used to create that 

variable are provided. 

 Part of an Index. If the variable is part of an index, the index is identified in this 

column. 

Explanation of the codes used in the Variable Type column are provided below. 

 Anti-PSE Ordinal. Responses to these questions form an ordinal scale with lower 

values corresponding to behavior more consistent with college-oriented knowledge, 

attitudes and behaviors. 
 J-2 

 Binary. Only two possible answer categories (“yes” and “no”) were printed on the 

questionnaire. The response that is more consistent with college-oriented knowledge, 

attitudes and behaviors has a value of 1, while the other has a value of 0. (A few of the 

binary variables were standardized to have 0 mean and unit standard deviation on a 

particular set of cases, but generally, most are coded 1 or 0.) 

 Binary C. Several answer categories were printed in the questionnaire for these 

questions, but they are all coded as either 1 (for responses more consistent with 

college-oriented knowledge, attitudes, and behaviors) or as 0 (for the others). 

 Binary DK. These questions are similar to binary ones, except the answer category of 

“don’t know,” was printed in the questionnaire. Responses of “don’t know” are scored 

as a 0. 

 Binary DNH. These questions are similar to binary ones, except the answer category 

of School Does Not Have, was printed in the questionnaire. Responses of “School 

Does Not Have” are scored as 0. 

 Binary Student Information Matrix (SIM). These are SIM questions with only two 

possible responses. There were, however, a number of missing or “don’t know” values 

for students. These values were dropped. The remaining values were changed so that a 

student that exhibited the trait that the variable represents were given a 1 for that 

variable, and the rest were given a 0. (The Gender variable was an exception, because 

the values were 1 for male and 2 for female.) 

 Calculated Binary. Calculated variables were created by the researchers. They are 

based on specific student or parent interview questions, SIM information or a 

combination of items from those sources. This type of calculated variable indicates the 

presence of a trait with a 1 and the absence of that trait with a 0. 

 Calculated Number. Calculated variables were created by the researchers. They are 

based on specific student or parent interview questions, SIM information or a 

combination of items from those sources. This type of calculated variable provides a 

number, usually a count of something or a grade point average (GPA). 

 Count. The responses to these questions are simply a count of some type of activity. 

Extreme outliers were dropped. 

 Index. Variables are summations of several other variables when higher values 

correspond to behavior more consistent with college-oriented knowledge, attitudes 

and behaviors. 

 Indicator. Variables are represented by either a number or a series of letters that 

allow the researcher to determine specific characteristics of the case studied. For the 

purposes of these data, the number is an identifier and the letters indicate which cases 

have complete information from different sources. 

 Multinomial. Several categorical responses are permitted to these questions, and the 

possible responses cannot be ranked in any order. 
J-3 

 Neutral Ordinal. Several categorical responses are permitted to these questions, and 

the possible responses can be ranked in an order, but not one that correlates with 

activity that is more or less consistent with college-oriented knowledge, attitudes and 

behaviors. 

 Pro-Postsecondary Education (PSE) Ordinal. Responses to these questions form an 

ordinal scale, with higher values corresponding to behavior more consistent with 

college-oriented knowledge, attitudes and behaviors. (When the original ordering had 

high values corresponding to less pro-college characteristics, the order was reversed in 

creating these variables.). 

 Pro-PSE Ordinal DK. Responses to these questions form an ordinal scale, with 

higher values corresponding to behavior more consistent with college-oriented 

knowledge, attitudes and behaviors. Responses of “don’t know” are assigned values 

that are in the middle of the other response values.

 Predicted. Variables indicate a specific predicted value for some characteristic. These 

values are used in analysis. 

 Weight. Variables indicate replicate weights used in the analyses. 
J-4 

Table J-1. Definitions of variables used in the analyses report Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

AbsentDays_7 Pro-PSE 

ordinal 

How many days student reported being absent from school in the past month 

7th-grade Student Survey 

SQ31_7 

AbsentDays_8 Pro-PSE 

ordinal 

How many days student reported being absent from school in the past month 

8th-grade Student Survey 

SQ31_8 

AboveEnglish Calculated 

binary 

Whether student was in an English class considered above his or her grade level 

Transcript data Not applicable for 

transcript variables 

AboveFLanguage Calculated 

binary 

Whether student was in a foreign language class considered above his or her grade level 

Transcript data Not applicable for 

transcript variables 

AboveMathematics Calculated 

binary 

Whether student was in a mathematics class considered above his or her grade level 

Transcript data Not applicable for 

transcript variables 

AboveScience Calculated 

binary 

Whether student was in a science class considered above his or her grade level 

Transcript data Not applicable for 

transcript variables 

Academic_7 Index A measure of student’s attitude 

toward school. This variable is contained in table 3-2d. 

7th-grade Student Survey 

HowHard_7, HowGood_7, ImpWork_7, GradeAbsentDays_7, SkipClasses_7 

Academic_8 Index A measure of student’s attitude 

toward school. This variable is contained in table 3-2d. 

8th-grade Student Survey 

HowHard_8, HowGood_8, ImpWork_8, GradeAbsentDays_8, SkipClasses_8 
J-5

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

AcademicGPA Calculated 

number 

Student’s GPA for academic courses 

Transcript data Not applicable for 

transcript variables 

AcademicRigor1 Calculated 

number 

Number of pipelines completed at or above grade level 

Transcript data Not applicable for 

transcript variables 

AcademicRigor2 Calculated 

number 

Number of pipelines completed above grade level 

Transcript data Not applicable for 

transcript variables 

AdultHangFreq_7 Neutral 

ordinal 

How often student reported doing things with adults, other than their parent(s) or guardian(s), outside of school (higher values indicate activity occurring more frequently) 

7th-grade Student Survey 

SQ15f_7 

AdultHangFreq_8 Neutral 

ordinal 

How often student reported doing things with adults, other than their parent(s) or guardian(s), outside of school (higher values indicate activity occurring more frequently) 

8th-grade Student Survey 

SQ15f_8 

Adultmentor_7 Binary C How often student reported 

meeting with an adult mentor such as a Big Brother or Big Sister 

7th-grade Student Survey 

SQ23a_7 

Adultmentor_8 Binary C How often student reported 

meeting with an adult mentor such as a Big Brother or Big Sister 

8th-grade Student Survey 

SQ23a_8 
J-6 

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

AdvisClassNeed_7 Binary Whether student reported talking 

with a school counselor or someone else at the school about the classes needed to get into college 

7th-grade Student Survey 

SQ34b_7 

AdvisClassNeed_8 Binary Whether student reported talking 

with a school counselor or someone else at the school about the classes needed to get into college 

8th-grade Student Survey 

SQ34b_8 

AdvisReadyforColl_7 Binary Whether student reported having 

a one-on-one counseling or advising session about getting ready for college 

7th-grade Student Survey 

SQ25a_7 

AdvisReadyforColl_8 Binary Whether student reported having 

a one-on-one counseling or advising session about getting ready for college 

8th-grade Student Survey 

SQ25a_8 

AdvisReadyforHS_7 Binary Whether student reported having 

a one-on-one counseling or advising session about getting ready for high school 

7th-grade Student Survey 

SQ24a_7 

AdvisReadyforHS_8 Binary Whether student reported having 

a one-on-one counseling or advising session about getting ready for high school 

8th-grade Student Survey 

SQ24a_8 

AnySibling_7 Binary DK Parent report of whether student 

had an older sibling 

7th-grade Parent Interview 

PQ34_7 
J-7

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

AnySibling_8 Binary DK Parent report of whether student 

had an older sibling 

8th-grade Parent Interview 

PQ34_8 

ArtsTutother_7 Binary C Whether student reported 

receiving English or language arts tutoring from someone other than a family member 

7th-grade Student Survey 

SQ21a_7 

ArtsTutother_8 Binary C Whether student reported 

receiving English or language arts tutoring from someone other than a family member 

8th-grade Student Survey 

SQ21a_8 

AttendClforColl_7 Binary Whether student reported 

attending a class or meeting about getting ready for college 

7th-grade Student Survey 

SQ26a_7 

AttendClforColl_8 Binary Whether student reported 

attending a class or meeting about getting ready for college 

8th-grade Student Survey 

SQ26a_8 

AttendMeetCollPrep_7 Binary C Whether parent reported 

attending meetings on preparatory curricula. This variable is contained in table 3-3c. 

7th-grade Parent Interview 

PQ13a_7 

AttendMeetCollPrep_8 Binary Whether parent reported 

attending meetings on preparatory curricula. This variable is contained in table 3-3c. 

8th-grade Parent Interview 

PQ13a_8 

AttendPlays_7 Binary Whether student reported 

attending play or other performances at a theater 

7th-grade Student Survey 

SQ16d_7 
J-8 

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

AttendPlays_8 Binary Whether student reported 

attending play or other performances at a theater 

8th-grade Student Survey 

SQ16d_8 

Awards7 Binary SIM Whether student received any 

honors or awards during 7th grade 

7th-grade SIM Not applicable for S

variables 

Awards8 Binary SIM Whether student received any 

honors or awards during 8th grade 

8th-grade SIM Not applicable for S

variables 

BabysittingHours_7 Neutral 

ordinal 

How long each week student reported babysitting younger siblings (higher values indicate more time spent babysitting) 

7th-grade Student Survey 

SQ9_7 

BabysittingHours_8 Neutral 

ordinal 

How long each week student reported babysitting younger siblings (higher values indicate more time spent babysitting) 

8th-grade Student Survey 

SQ9_8 

Band_7 Binary DNH Whether student reported 

participating in the school band, orchestra, chorus, choir or other music group that year 

7th-grade Student Survey 

SQ12c_7 

Band_8 Binary DNH Whether student reported 

participating in the school band, orchestra, chorus, choir or other music group that year 

8th-grade Student Survey 

SQ12c_8 

Black Calculated 

binary 

Whether student was AfricanAmerican, not Hispanic Student Survey, SIM, and Parent 

Interview 

SQ56, SQ57, SIM information, PQ43, PQ44, in that order 
J-9

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

BorBetterAdvEnglish Calculated 

binary 

Whether student had a grade of “B” or better in an advanced English course 

Transcript data Not applicable for 

transcript variables 

BorBetterAdvForeign Calculated 

binary 

Whether student had a grade of “B” or better in an advanced foreign language course 

Transcript data Not applicable for 

transcript variables 

BorBetterAdvMathematics Calculated 

binary 

Whether student had a grade of “B” or better in an advanced mathematics course 

Transcript data Not applicable for 

transcript variables 

BorBetterAdvScience Calculated 

binary 

Whether student had a grade of “B” or better in an advanced science course 

Transcript data Not applicable for 

transcript variables 

Cheerleading_7 Binary DNH Whether student reported 

participating in the school cheerleading, pom squad, drill team or dance team that year 

7th-grade Student Survey 

SQ12f_7 

Cheerleading_8 Binary DNH Whether student reported 

participating in the school cheerleading, pom squad, drill team or dance team that year 

8th-grade Student Survey 

SQ12f_8 

ChessClub_7 Binary DNH Whether student reported 

participating in the school hobby clubs such as photography and chess that year 

7th-grade Student Survey 

SQ12i_7 

ChessClub_8 Binary DNH Whether student reported 

participating in the school hobby clubs such as photography and chess that year 

8th-grade Student Survey 

SQ12i_8 
J-10

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Childpartknow_7 Binary Whether parent reported learning 

about the child’s activities through a letter or written notice 

7th-grade Parent Interview 

PQ12a_7 

Childpartknow_8 Binary Whether parent reported learning 

about the child’s activities through a letter or written notice 

8th-grade Parent Interview 

PQ12a_8 

ChurchFreq_7 Neutral 

ordinal 

How often student reported spending time participating in religious activities outside of school (higher values indicate activity occurring more frequently) 

7th-grade Student Survey 

SQ15b_7 

ChurchFreq_8 Neutral 

ordinal 

How often student reported spending time participating in religious activities outside of school (higher values indicate activity occurring more frequently) 

8th-grade Student Survey 

SQ15b_8 

ClassSkipping_7 Anti-PSE 

ordinal 

Student’s report of how many classes he or she skipped or cut during the past month. Same as SkipClasses_7, except order of coding. 

7th-grade Student Survey 

SQ33_7 

ClubHours_7 Pro-PSE 

ordinal 

How much average weekly time student reported spending on all school activities like sports and clubs 

7th-grade Student Survey 

SQ14_7 
J-11

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ClubHours_8 Pro-PSE 

ordinal 

How much average weekly time student reported spending on all school activities like sports and clubs 

8th-grade Student Survey 

SQ14_8 

ClubLeader_7 Binary DK Whether student reported serving 

as an officer in any of the activities from NumSchoolAct_7 

7th-grade Student Survey 

SQ13_7 

ClubLeader_8 Binary DK Whether student reported serving 

as an officer in any of the activities from NumSchoolAct_8 

8th-grade Student Survey 

SQ13_8 

CollegeAffordable_7 Pro-PSE 

ordinal 

How likely parent thinks it is that the student will be able to afford to attend a 4-year postsecondary institution 

7th-grade Parent Interview 

PQ28_7 

CollegeAffordable_8 Pro-PSE 

ordinal 

How likely parent thinks it is that the student will be able to afford to attend a 4-year postsecondary institution 

8th-grade Parent Interview 

PQ28_8 

CollegeBound_7 Index Overall measure of how well 

student is progressing on the path to postsecondary education 

7th-grade Student Survey 

Academic_7, Performance_7, ExpectPSE_7, PexpStdParTalk_7, ReadingHours_7 

CollegeBound_8 Index Overall measure of how well 

student is progressing on the path to postsecondary education 

8th-grade Student Survey 

Academic_8, Performance_8, ExpectPSE_8, PexpStdParTalk_8, ReadingHours_8 
J-12

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

CollegeBoundRev_7 Index Revised version of overall 

measure of how well student is progressing on the path to postsecondary education 

7th-grade Student Survey 

Academic_7, Performance_7, ExpectPSERev_7, Pexpect_7, StdParTReadingHours_7 

CollegeBoundRev_8 Index Revised version of overall 

measure of how well student is progressing on the path to postsecondary education 

8th-grade Student Survey 

Academic_8, Performance_8, ExpectPSERev_8, Pexpect_8, StdParTReadingHours_8 

CollegeClose_7 Binary DK Percentage of parents who 

anticipated college or other postsecondary school attendance for their child. This variable is contained in table 3-2c. 

7th-grade Parent Interview 

PQ22_7, PQ24_7 

CollegeClose_8 Binary DK Percentage of parents who 

anticipated college or other postsecondary school attendance for their child. This variable is contained in table 3-2c. 

8th-grade Parent Interview 

PQ22_8, PQ24_8 

CollegeMoreMoney_7 Pro-PSE 

ordinal DK 

How sure student is about the assertion that someone with a college degree earns more money than someone who does not finish college 

7th-grade Student Survey 

SQ38_7 

CollegeMoreMoney_8 Pro-PSE 

ordinal DK 

How sure student is about the assertion that someone with a college degree earns more money than someone who does not finish college 

8th-grade Student Survey 

SQ38_8 
J-13

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ComputerAtHome_7 Binary Parent report of whether there is a 

computer in the home 

7th-grade Parent Interview 

PQ38_7 

ComputerAtHome_8 Binary Parent report of whether there is a 

computer in the home 

8th-grade Parent Interview 

PQ38_8 

ComputerFreq_7 Neutral 

ordinal 

How often student reported spending time using a personal computer outside of school (higher values indicate activity occurring more frequently) 

7th-grade Student Survey 

SQ15a_7 

ComputerFreq_8 Neutral 

ordinal 

How often student reported spending time using a personal computer outside of school (higher values indicate activity occurring more frequently) 

8th-grade Student Survey 

SQ15a_8 

Confer_events_7 Index Measure of how often parent 

attends meetings with teachers and school events 

7th-grade Parent Interview 

ConferFreq_7, NumEventType_7 

Confer_events_8 Index Measure of how often parent 

attends meetings with teachers and school events 

8th-grade Parent Interview 

ConferFreq_8, NumEventType_8 

ConferBehave_7 Index Number of meetings parent has 

reported having with the student’s teacher about behavioral problems 

7th-grade Parent Interview 

PQ10b_7, ConferFr

ConferBehave_8 Index Number of meetings parent has 

reported having with the student’s teacher about behavioral problems 

8th-grade Parent Interview 

PQ10b_8, ConferFr
J-14

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ConferFreq_7 Pro-PSE 

ordinal 

Number of meetings parent has reported having with the child’s teachers since the beginning of the school year 

7th-grade Parent Interview 

PQ8_7, PQ9_7 

ConferFreq_8 Pro-PSE 

ordinal 

Number of meetings parent has reported having with the child’s teachers since the beginning of the school year 

8th-grade Parent Interview 

PQ8_8, PQ9_8 

ConferHomework_7 Index Number of meetings parent has 

reported having with the student’s teacher about problems with a specific homework assignment 

7th-grade Parent Interview 

PQ10a_7, ConferFr

ConferHomework_8 Index Number of meetings parent has 

reported having with the student’s teacher about problems with a specific homework assignment 

8th-grade Parent Interview 

PQ10a_8, ConferFr

ConferOther_7 Index Number of meetings parent has 

reported having with the student’s teacher about a reason other than the ones from ConferBehave_7, ConferHomework_7 or ConferProgress_7 

7th-grade Parent Interview 

PQ10d_7, ConferFr
J-15

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ConferOther_8 Index Number of meetings parent has 

reported having with the student’s teacher about a reason other than the ones from ConferBehave_8, ConferHomework_8 or ConferProgress_8 

8th-grade Parent Interview 

PQ10d_8, ConferFr

ConferProgress_7 Index Number of meetings parent has 

reported having with the student’s teacher about the student’s overall academic performance 

7th-grade Parent Interview 

PQ10c_7, ConferFr

ConferProgress_8 Index Number of meetings parent has 

reported having with the student’s teacher about the student’s overall academic performance 

8th-grade Parent Interview 

PQ10c_8, ConferFr

CutClass_8 Binary Whether student skipped classes 

at least once in past month 

8th-grade Student survey 

SkipClasses_8 

DadHelp_7 Neutral 

ordinal 

How frequently student reported that father or male guardian helped with homework (higher values indicate more frequent help) 

7th-grade Student Survey 

SQ6_7 

DadHelp_8 Neutral 

ordinal 

How frequently student reported that father or male guardian helped with homework (higher values indicate more frequent help) 

7th-grade Student Survey 

SQ6_8 
J-16

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

DefColMoreMoney_7 Binary C Percentage of students who think 

college graduates earn higher salaries than others. This variable is contained in table 3-3a. 

7th-grade Student Survey 

SQ38a_7 

DefColMoreMoney_8 Binary C Percentage of students who think 

college graduates earn higher salaries than others. This variable is contained in table 3-3a. 

8th-grade Student Survey 

SQ38a_8 

DefGoCollege_7 Binary C Percentage of students who say 

they will “definitely” go to college. This variable is contained in table 3-2a. 

7th-grade Student Survey 

SQ40_7 

DefGoCollege_8 Binary C Percentage of students who say 

they will “definitely” go to college. This variable is contained in table 3-2a. 

8th-grade Student Survey 

SQ40_8 

DontNeedHelp_7 Binary C Student’s report that he or she 

never needs homework help from either parent or guardian 

7th-grade Student Survey 

SQ5_7, SQ6_7 

DontNeedHelp_8 Binary C Student’s report that he or she 

never needs homework help from either parent or guardian 

8th-grade Student Survey 

SQ5_8, SQ6_8 

Drama_7 Binary DNH Whether student reported 

participating in the school drama club, school play or musical that year 

7th-grade Student Survey 

SQ12d_7 
J-17

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Drama_8 Binary DNH Whether student reported 

participating in the school drama club, school play or musical that year 

8th-grade Student Survey 

SQ12d_8 

ECBusy_7 Index Measure of student’s 

participation in extracurricular activities. This variable is contained in table 3-2d. 

7th-grade Student Survey 

Clubleader_7, ClubHours_7, NumSchoolAct_7, ExtraFreq_7, ParentAttends_7, NumOutAct_7 

ECBusy_8 Index Measure of student’s 

participation in extracurricular activities. This variable is contained in table 3-2d. 

8th-grade Student Survey 

Clubleader_8, ClubHours_8, NumSchoolAct_8, ExtraFreq_8, ParentAttends_8, NumOutAct_8 

EdFor30_7 Pro-PSE 

ordinal DK 

How much education student thinks he or she will need to get the kind of job chosen in ProfAspiration_7 by age 30 

7th-grade Student Survey 

SQ46_7 

EdFor30_8 Pro-PSE 

ordinal DK 

How much education student thinks he or she will need to get the kind of job chosen in ProfAspiration_8 by age 30 

8th-grade Student Survey 

SQ46_8 

EnglishGPA Calculated 

number 

Student’s GPA for English courses 

Transcript data Not applicable for 

transcript variables 
J-18

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

EnglishHomework_7 Neutral 

ordinal 

How much time a week student reported spending on English and language arts homework (higher values indicate more time studying) 

7th-grade Student Survey 

SQ4b_7 

EnglishHomework_8 Neutral 

ordinal 

How much time a week student reported spending on English and language arts homework (higher values indicate more time studying) 

8th-grade Student Survey 

SQ4b_8 

EnglishPipeline Calculated 

number 

Highest level of English taken during SY2001–02 

Transcript data Not applicable for 

transcript variables 

EnufInfo_7 Pro-PSE 

ordinal 

Whether parent reported receiving some or enough information on entrance requirements. This variable is contained in table 3-3c. 

7th-grade Parent Interview 

PQ27_7 

EnufInfo_8 Pro-PSE 

ordinal 

Whether parent reported receiving some or enough information on entrance requirements. This variable is contained in table 3-3c. 

8th-grade Parent Interview 

PQ27_8 

ESLBil7 Binary SIM Student was in an English as a 

second language or bilingual program during 7th grade 

7th-grade SIM Not applicable for S

variables 

ESLBil8 Binary SIM Student was in an English as a 

second language or bilingual program during 8th grade 

8th-grade SIM Not applicable for S

variables 
J-19

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

EventBacktoSchool_7 Binary DK Percentage of parents who 

reported attending back-toschools nights. This variable is contained in table 3-3d. 

7th-grade Parent Interview 

PQ14a_7 

EventBacktoSchool_8 Binary DK Percentage of parents who 

reported attending back-toschools nights. This variable is contained in table 3-3d. 

8th-grade Parent Interview 

PQ14a_8 

EventFieldTrip_7 Binary DK Percentage of parents who 

reported attending a field trip, such as to a museum or the zoo. This variable is contained in table 3-3d. 

7th-grade Parent Interview 

PQ14d_7 

EventFieldTrip_8 Binary DK Percentage of parents who 

reported attending a field trip, such as to a museum or the zoo. This variable is contained in table 3-3d. 

8th-grade Parent Interview 

PQ14d_8 

EventPlaySport_7 Binary DK Percentage of parents who 

reported attending a school event, like a play or sporting event. This variable is contained in table 3-3d. 

7th-grade Parent Interview 

PQ14c_7 

EventPlaySport_8 Binary DK Percentage of parents who 

reported attending a school event, like a play or sporting event. This variable is contained in table 3-3d. 

8th-grade Parent Interview 

PQ14c_8 
J-20

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

EventPTA_7 Binary DK Percentage of parents who 

reported attending PTA meetings. This variable is contained in table 3-3d. 

7th-grade Parent Interview 

PQ14b_7 

EventPTA_8 Binary DK Percentage of parents who 

reported attending PTA meetings. This variable is contained in table 3-3d. 

8th-grade Parent Interview 

PQ14b_8 

ExAbsnc7 Count Number of excused absences for 

student during the 7th grade 

7th-grade SIM Not applicable for S

variables 

ExAbsnc8 Count Number of excused absences for 

student during the 8th grade 

8th-grade SIM Not applicable for S

variables 

ExpectPSE_7 Index Measure of student’s 

expectations about postsecondary education 

7th-grade Student Survey 

LikelyGoCollege_7ImpGoCollege_7, HowFarSchool_7, EdFor30_7 

ExpectPSE_8 Index Measure of student’s 

expectations about postsecondary education 

8th-grade Student Survey 

LikelyGoCollege_8ImpGoCollege_8, HowFarSchool_8, EdFor30_8 

ExpectPSERev_7 Index Revised version of ExpectPSE, 

which measures student’s expectations about postsecondary education. This variable is contained in table 3-2a. 

7th-grade Student Survey 

ExpectPSE_7, Heard4Year_7, NumPeopleTalkedPCollegeMoreMoney
J-21

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ExpectPSERev_8 Index Revised version of ExpectPSE, 

which measures student’s expectations about postsecondary education. This variable is contained in table 3-2a. 

8th-grade Student Survey 

ExpectPSE_8, Heard4Year_8, NumPeopleTalkedPCollegeMoreMoney

Expel7 Count Number of expulsions for student 

during 7th grade 

7th-grade SIM Not applicable for S

variables 

Expel8 Count Number of expulsions for student 

during 8th grade 

8th-grade SIM Not applicable for S

variables 

ExTardy7 Count Number of excused tardies for 

student during 7th grade 

7th-grade SIM Not applicable for S

variables 

ExTardy8 Count Number of excused tardies for 

student during 8th grade 

8th-grade SIM Not applicable for S

variables 

ExtraFreq_7 Index Frequency that student reported 

using a computer, participating in religious activities, volunteering, spending time with friends, doing things with family or spending time with other adults 

7th-grade Student Survey 

ComputerFreq_7, ChurchFreq_7, VolunteerFreq_7, FriendFreq_7, FamilyFreq_7, AdultHangFreq_7 

ExtraFreq_8 Index Frequency that student reported 

using a computer, participating in religious activities, volunteering, spending time with friends, doing things with family or spending time with other adults 

8th-grade Student Survey 

ComputerFreq_8, ChurchFreq_8, VolunteerFreq_8, FriendFreq_8, FamilyFreq_8, AdultHangFreq_8 
J-22

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

FamilyFreq_7 Neutral 

ordinal 

How often student reported spending time doing things with a parent or guardian, outside of school (higher values indicate activity occurring more frequently) 

7th-grade Student Survey 

SQ15e_7 

FamilyFreq_8 Neutral 

ordinal 

How often student reported spending time doing things with a parent or guardian, outside of school (higher values indicate activity occurring more frequently) 

8th-grade Student Survey 

SQ15e_8 

FatherGoCollege_7 Binary DK Whether student reported that his 

or her father or male guardian attended college 

7th-grade Student Survey 

SQ47b_7 

FatherGoCollege_8 Binary DK Whether student reported that his 

or her father or male guardian attended college 

8th-grade Student Survey 

SQ47b_8 

FatherOpImport_7 Pro-PSE 

ordinal 

Importance student places on his or her father or male guardian’s opinions about the student’s education plans 

7th-grade Student Survey 

SQ18a_7 

FatherOpImport_8 Pro-PSE 

ordinal 

Importance student places on his or her father or male guardian’s opinions about the student’s education plans 

8th-grade Student Survey 

SQ18a_8 

FirstGen Calculated 

Binary 

Whether any of the adults in household attended a 2- or 4-year college program 

7th-grade Student Survey 

SQ47a_7, SQ47b_7 
J-23

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Firstlanguage_7 Binary Whether student reported 

English as first language he or she learned to speak at home 

7th-grade Student Survey 

SQ58_7 

FirstLanguage_8 Binary Whether student reported 

English as first language he or she learned to speak at home 

8th-grade Student Survey 

SQ58_8 

FriendFreq_7 Neutral 

ordinal 

How often student reported spending time doing things with friends outside of school (higher values indicate activity occurring more frequently) 

7th-grade Student Survey 

SQ15d_7 

FriendFreq_8 Neutral ordinal How often student reported 

spending time doing things with friends outside of school (higher values indicate activity occurring more frequently) 

8th-grade Student Survey 

SQ15d_8 

FriendHelp_7 Binary Whether student reported 

receiving homework help from a classmate or friend 

7th-grade Student Survey 

SQ7e_7 

FriendHelp_8 Binary Whether student reported 

receiving homework help from a classmate or friend 

8th-grade Student Survey 

SQ7e_8 

FriendOpImport_7 Pro-PSE 

ordinal 

Importance student places on his or her friends’ opinions about student’s education plans 

7th-grade Student Survey 

SQ18c_7 

FriendOpImport_8 Pro-PSE 

ordinal 

Importance student places on his or her friends’ opinions about student’s education plans 

8th-grade Student Survey 

SQ18c_8 
J-24

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ForeignLanguageGPA Calculated 

number 

Student’s GPA for foreign language courses 

Transcript data Not applicable for 

transcript variables 

ForeignLanguagePipeline Calculated 

number 

Highest level of foreign language taken during SY2001-02 

Transcript data Not applicable for 

transcript variables 

Gender Binary SIM Student’s gender (“1” for male, 

“2” for female) 

SIM Not applicable for S

variables 

GoodCaseS7 Indicator Whether 7th grade SIM 

contained any information 

7th-grade SIM Not applicable for S

variables 

GoodForms8 Indicator A list of good 8th grade forms 

received for student, with “T” for student questionnaire, “P” for parent questionnaire and “S” for SIM 

8th-grade Student Survey, Parent Interview and SIM 

All items in all three source instruments 

Government_7 Binary DNH Whether student reported 

participating in student government that year 

7th-grade Student Survey 

SQ12e_7 

Government_8 Binary DNH Whether student reported 

participating in student government that year 

8th-grade Student Survey 

SQ12e_8 

Grade8Resp Indicator Whether student was considered 

an 8th grade respondent (required either student or parent questionnaire) 

8th-grade Student and Parent Interview 

All items in both soinstruments 

Grades_7 Pro-PSE 

ordinal 

Student’s report of his or her own grades 

7th-grade Student Survey 

SQ17_7 

Grades_8 Pro-PSE 

ordinal 

Student’s report of his or her own grades 

8th-grade Student Survey 

SQ17_8 
J-25

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

GrParentGoCollege_7 Binary DK Whether student reported that a 

grandparent attended college 

7th-grade Student Survey 

SQ47d_7 

GrParentGoCollege_8 Binary DK Whether student reported that a 

grandparent attended college 

8th-grade Student Survey 

SQ47d_8 

HaveLibraryCard_7 Binary DK Parent’s report of whether 

anyone in the household had a library card 

7th-grade Parent Interview 

PQ40_7 

HaveLibraryCard_8 Binary DK Parent’s report of whether 

anyone in the household had a library card 

8th-grade Parent Interview 

PQ40_8 

Heard2Year_7 Binary Whether student had ever heard 

of a 2-year or community college. Same as HeardCommColl_7, except imputation algorithm. 

7th-grade Student Survey 

SQ36a_7 

Heard2Year_8 Binary Whether student had ever heard 

of a 2-year or community college. Same as HeardCommColl_8, except imputation algorithm. 

8th-grade Student Survey 

SQ36a_8 

Heard4Year_7 Binary Whether student had ever heard 

of a 4-year college or university 

7th-grade Student Survey 

SQ36b_7 

Heard4Year_8 Binary Whether student had ever heard 

of a 4-year college or university 

8th-grade Student Survey 

SQ36b_8 

HeardCommColl_7 Binary Whether student had ever heard 

of a 2-year or community college. Same as Heard2Year_7, except imputation algorithm. 

7th-grade Student Survey 

SQ36a_7 
J-26

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

HeardCommColl_8 Binary Whether student had ever heard 

of a 2-year or community college. Same as Heard2Year_7, except imputation algorithm. 

8th-grade Student Survey 

SQ36a_8 

HeardOfSchools_7 Binary C Whether student is familiar with 

different types of postsecondary institutions. This variable is contained in table 3-3a. 

7th-grade Student Survey 

Heard2Year_7, Heard4Year_7, HeardVocEd_7 

HeardOfSchools_8 Binary C Whether student is familiar with 

different types of postsecondary institutions. This variable is contained in table 3-3a. 

8th-grade Student Survey 

Heard2Year_8, Heard4Year_8, HeardVocEd_8 

HeardVocEd_7 Binary Whether student had ever heard 

of a vocational, trade or business school 

7th-grade Student Survey 

SQ36c_7 

HeardVocEd_8 Binary Whether student had ever heard 

of a vocational, trade or business school 

8th-grade Student Survey 

SQ36c_8 

HHIncome_7 Neutral ordinal Parent’s report of the total 

household income (higher values indicate higher income) 

7th-grade Parent Interview 

PQ42_7 

HHIncome_8 Neutral ordinal Parent’s report of the total 

household income (higher values indicate higher income) 

8th-grade Parent Interview 

PQ42_8 

Highest3rdCB Calculated 

binary 

Whether student was a member in the highest third of 7th grade students with respect to CollegeBound Rev_7 

7th-grade Student and Parent Interviews 

CollegeBound Rev_
J-27

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Hispanic Calculated 

binary 

Whether student was of Hispanic ethnicity of any race 

Student Survey, SIM, and Parent Interview 

SQ56, SQ57, SIM information, PQ43, PQ44, in that order 

Hmwkundr_7 Pro-PSE 

ordinal DK 

Combinations of parent questions asking (1) whether student receives homework, (2) where the student most often completes his or her homework and (3) how well the student seems to understand the homework 

7th-grade Parent Interview 

PQ1_7, PQ3_7, PQ

Hmwkundr_8 Pro-PSE 

ordinal DK 

Combinations of parent questions asking (1) whether or not the student receives homework, (2) where the student most often completes his or her homework and (3) how well the student seems to understand the homework 

8th-grade Parent Interview 

PQ1_8, PQ3_8, PQ

Hobbies_7 Binary Whether student reported 

working on hobbies, arts or crafts on his or her own time 

7th-grade Student Survey 

SQ16a_7 

Hobbies_8 Binary Whether student reported 

working on hobbies, arts or crafts on his or her own time 

8th-grade Student Survey 

SQ16a_8 

HomeworkHours_7 Pro-PSE 

ordinal 

How much time student spent on homework. This variable is contained in table 3-2d. 

7th-grade Student Survey 

SQ4a_7, SQ4b_7, SSQ4d_7 
J-28

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

HomeworkHours_8 Pro-PSE 

ordinal 

How much time student spent on homework. This variable is contained in table 3-2d. 

8th-grade Student Survey 

SQ4a_8, SQ4b_8, SSQ4d_8 

Honors7 Binary SIM Student was in an honors or 

gifted and talented program during 7th grade 

7th-grade SIM Not applicable for S

variables 

Honors8 Binary SIM Student was in an honors or 

gifted and talented program during 8th grade 

8th-grade SIM Not applicable for S

variables 

HowFarSchool_7 Pro-PSE 

ordinal DK 

How far the student feels he or she will go after high school 

7th-grade Student Survey 

SQ42_7 

HowFarSchool_8 Pro-PSE 

ordinal DK 

How far the student feels he or she will go after high school 

8th-grade Student Survey 

SQ42_8 

HowGood_7 Pro-PSE 

ordinal 

Student’s report of how good a student he or she is 

7th-grade Student Survey 

SQ2_7 

HowGood_8 Pro-PSE 

ordinal 

Student’s report of how good a student he or she is 

8th-grade Student Survey 

SQ2_8 

HowHard_7 Neutral ordinal Student’s report of how hard he 

or she works in school, compared with other students (higher values indicate that the student works harder) 

7th-grade Student Survey 

SQ1_7 

HowHard_8 Neutral ordinal Student’s report of how hard he 

or she works in school, compared with other students (higher values indicate that the student works harder) 

8th-grade Student Survey 

SQ1_8 
J-29

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

IEP7 Binary SIM Student had an Individualized 

Education Plan during the 7th grade 

7th-grade SIM Not applicable for S

variables 

IEP8 Binary SIM Student had an Individualized 

Education Plan during the 8th grade 

8th-grade SIM Not applicable for S

variables 

ImpGoCollege_7 Pro-PSE 

ordinal 

How important student thinks it is for him or her to attend college 

7th-grade Student Survey 

SQ41_7 

ImpGoCollege_8 Pro-PSE 

ordinal 

How important student thinks it is for him or her to attend college 

8th-grade Student Survey 

SQ41_8 

ImpWork_7 Pro-PSE 

ordinal 

Student’s report of how important he or she thinks it is to work hard in school 

7th-grade Student Survey 

SQ3_7 

ImpWork_8 Pro-PSE 

ordinal 

Student’s report of how important he or she thinks it is to work hard in school 

8th-grade Student Survey 

SQ3_8 

InScSusp7 Count Number of in-school suspensions 

for student during 7th grade 

7th-grade SIM Not applicable for S

variables 

InScSusp8 Count Number of in-school suspensions 

for student during 8th grade 

8th-grade SIM Not applicable for S

variables 

InternetAccess_7 Binary Parent’s report of whether or not 

he or she has Internet access 

7th-grade Parent Interview 

PQ39_7 

InternetAccess_8 Binary Parent’s report of whether or not 

he or she has Internet access 

8th-grade Parent Interview 

PQ39_8 
J-30

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

InternetFreq_7 Neutral ordinal Student’s report of how often he 

or she used Internet each week (higher values indicate more frequent use) 

7th-grade Student Survey 

SQ52_7 

InternetFreq_8 Neutral ordinal Student’s report of how often he 

or she used Internet each week (higher values indicate more frequent use) 

8th-grade Student Survey 

SQ52_8 

JSCHOLID Indicator School ID (same as first three 

digits of student ID) 

None JSCHOLID was randomly created 

None – JSCHOLID randomly created 

Kim38R_7 Pro-PSE 

ordinal DK 

How sure student is about assertion that someone with a college degree earns more money than someone who does not finish college 

7th-grade Student Survey 

SQ38_7 

Kim38R_8 Pro-PSE 

ordinal DK 

How sure student is about assertion that someone with a college degree earns more money than someone who does not finish college 

8th-grade Student Survey 

SQ38_8 

Knowcollcampus_7 Binary DK Whether the parent reported 

student’s participation in a college campus visit since the beginning of the year 

7th-grade Parent Interview 

PQ11e_7 

KnowCollCampus_8 Binary DK Whether the parent reported 

student’s participation in a college campus visit since the beginning of the year 

8th-grade Parent Interview 

PQ11e_8 
J-31

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

KnowPSE_7 Index Student’s knowledge of 

postsecondary education. This variable is contained in table 3-3a. 

7th-grade Student Survey 

TalkCoursePlanningHeardofSchools_7, NumPeopleTalkedPCollegeMoreMoney

KnowPSE_8 Index Student’s knowledge of 

postsecondary education. This variable is contained in table 3-3a. 

8th-grade Student Survey 

TalkCoursePlanningHeardofSchools_8, NumPeopleTalkedPCollegeMoreMoney

LeagueSports_7 Binary Whether student reported 

participating in sports or taking sports lessons that are not at school 

7th-grade Student Survey 

SQ16c_7 

LeagueSports_8 Binary Whether student reported 

participating in sports or taking sports lessons that are not at school 

8th-grade Student Survey 

SQ16c_8 

LEP7 Binary SIM Whether student was designated 

as limited English proficient during 7th grade 

7th-grade SIM Not applicable for S

variables 

LEP8 Binary SIM Whether student was designated 

as limited English proficient during 7th grade 

8th-grade SIM Not applicable for S

variables 

LibraryUsage_7 Binary DK Parent’s report of whether 

anyone in the household uses a library card 

7th-grade Parent Interview 

PQ41_7 

LibraryUsage_8 Binary DK Parent’s report of whether 

anyone in the household uses a library card 

8th-grade Parent Interview 

PQ41_8 
J-32

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

LikelyGoCollege_7 Pro-PSE 

ordinal DK 

Student’s report of how likely he or she is to go to college 

7th-grade Student Survey 

SQ40_7 

LikelyGoCollege_8 Pro-PSE 

ordinal DK 

Student’s report of how likely he or she is to go to college 

8th-grade Student Survey 

SQ40_8 

Lowest3rdCB Calculated 

binary 

Whether student was a member in the lowest third of 7th grade students with respect to CollegeBound Rev_7 

7th-grade Student and Parent Interview 

CollegeBound Rev_

Lunch7 Binary SIM Student participated in the free or 

reduced-priced lunch program during 7th grade 

7th-grade SIM Not applicable for S

variables 

Lunch8 Binary SIM Student participated in the free or 

reduced-priced lunch program during 8th grade 

8th-grade SIM Not applicable for S

variables 

MathematicsClub_7 Binary DNH Whether student reported 

participating in the school’s academic clubs that year 

7th-grade Student Survey 

SQ12h_7 

MathematicsClub_8 Binary DNH Whether student reported 

participating in the school’s academic clubs that year 

8th-grade Student Survey 

SQ12h_8 

MathematicsGPA Calculated 

number 

Student’s GPA for mathematics courses 

Transcript data Not applicable for 

transcript variables 

MathematicsHomework_7 Neutral ordinal How much time a week student 

reported spending on mathematics homework (higher values indicate more time spent) 

7th-grade Student Survey 

SQ4a_7 
J-33

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

MathematicsHomework_8 Neutral ordinal How much time a week student 

reported spending on mathematics homework (higher values indicate more time spent) 

8th-grade Student Survey 

SQ4a_8 

MathematicsPipeline Calculated 

number 

Highest level of mathematics taken during SY2001–02 

Transcript data Not applicable for 

transcript variables 

MathematicsTutother_7 Binary C Student’s report of how often, 

since the beginning of the school year, he or she received mathematics tutoring from someone other than a family member 

7th-grade Student Survey 

SQ20a_7 

MathematicsTutother_8 Binary C Student’s report of how often, 

since the beginning of the school year, he or she received mathematics tutoring from someone other than a family member 

8th-grade Student Survey 

SQ20a_8 

Middle3rdCB Calculated 

binary 

Whether student was a member in the middle third of 7th grade students with respect to CollegeBound Rev_7 

7th-grade Student and Parent Interview 

CollegeBound Rev_

MissSchfrwrong_7 Binary C Whether student reported 

skipping or cutting school, or reported missing school because he or she did not feel like going, was unprepared for a test or homework or wanted to spend time with friends not at school 

7th-grade Student Survey 

SQ32e_7, SQ32f_7SQ32g_7, SQ33_7 
J-34

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

MissSchfrwrong_8 Binary C Whether student reported 

skipping or cutting school, or reported missing school because he or she did not feel like going, was unprepared for a test or homework or wanted to spend time with friends not at school 

8th-grade Student Survey 

SQ32e_8, SQ32f_8SQ32g_8, SQ33_8 

Mobility_7 Neutral ordinal Student’s report of the number of 

different schools he or she has attended since first grade (higher values indicate attending a greater number of schools) 

7th-grade Student Survey 

SQ62_7 

Mobility_8 Neutral ordinal Student’s report of the number of 

different schools he or she has attended since first grade (higher values indicate attending a greater number of schools) 

8th-grade Student Survey 

SQ62_8 

MomHelp_7 Neutral ordinal How frequently student reported 

that the mother or female guardian helped with homework (higher values indicate more frequent help) 

7th-grade Student Survey 

SQ5_7 

MomHelp_8 Neutral ordinal How frequently student reported 

that the mother or female guardian helped with homework (higher values indicate more frequent help) 

8th-grade Student Survey 

SQ5_8 

MotherGoCollege_7 Binary DK Whether student reported that his 

or her mother or female guardian attended college 

7th-grade Student Survey 

SQ47a_7 
J-35

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

MotherGoCollege_8 Binary DK Whether student reported that his 

or her mother or female guardian attended college 

8th-grade Student Survey 

SQ47a_8 

MotherOpImport_7 Pro-PSE 

ordinal 

Importance student places on his or her mother’s opinions about the student’s education plans 

7th-grade Student Survey 

SQ18b_7 

MotherOpImport_8 Pro-PSE 

ordinal 

Importance student places on his or her mother’s opinions about the student’s education plans 

8th-grade Student Survey 

SQ18b_8 

NegJunkHours_7 Pro-PSE 

ordinal 

Time spent not watching TV or playing video games. This variable is contained in table 3-2d. 

7th-grade Student Survey 

NegTVHours_7, NegVideosHours_7 

NegJunkHours_8 Pro-PSE 

ordinal 

Time spent not watching TV or playing video games. This variable is contained in table 3-2d. 

8th-grade Student Survey 

NegTVHours_8, NegVideosHours_8 

NegTVHours_7 Pro-PSE 

ordinal 

Student’s report of how many hours per weekday he or she usually watched TV 

7th-grade Student Survey 

SQ10_7 

NegTVHours_8 Pro-PSE 

ordinal 

Student’s report of how many hours per weekday he or she usually watched TV 

8th-grade Student Survey 

SQ10_8 

egVideoHours_7 Pro-PSE 

ordinal 

Student’s report of how many hours per weekday he or she usually played video games 

7th-grade Student Survey 

SQ11_7 
J-36

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

NegVideoHours_8 Pro-PSE 

ordinal 

Student’s report of how many hours per weekday he or she usually played video games 

8th-grade Student Survey 

SQ11_8 

NoFather_7 Binary C Whether, in response to 

DadHelp_7, the student reported not having a father or male guardian at home 

7th-grade Student Survey 

SQ6_7 

NoFather_8 Binary C Whether, in response to 

DadHelp_8, the student reported not having a father or male guardian at home 

8th-grade Student Survey 

SQ6_8 

NumAdult_7 Count Number of adults the parent 

reported as living in the home, including the respondent 

7th-grade Parent Interview 

PQ32_7 

NumAdult_8 Count Number of adults the parent 

reported as living in the home, including the respondent 

8th-grade Parent Interview 

PQ32_8 

NumConfType_7 Count Count of the different types of 

conferences the parent reported having with the student’s teacher 

7th-grade Parent Interview 

ConferHomework_7ConferBehave_7, ConferProgress_7, ConferOther_7 

NumConfType_8 Count Count of the different types of 

conferences the parent reported having with the student’s teacher 

8th-grade Parent Interview 

ConferHomework_8ConferBehave_8, ConferProgress_8, ConferOther_8 
J-37

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

NumEventType_7 Count Summation of the number of 

different types of school events in which parent has participated since the beginning of the school year 

7th-grade Parent Interview 

EventBacktoSchoolEventPTA_7, EventPlaySport_7, EventFieldTrip_7 

NumEventType_8 Count Summation of the number of 

different types of school events in which parent has participated since the beginning of the school year 

8th-grade Parent Interview 

EventBacktoSchoolEventPTA_8, EventPlaySport_8, EventFieldTrip_8 

NumHelpers_7 Count Count of different types of people 

from whom the student reported receiving homework assistance 

7th-grade Student Survey 

TeacherHelp_7, OtherSchoolHelp_7UncleHelp_7, SiblingHelp_7, FriendHelp_7, OtherHelp_7 

NumHelpers_8 Count Count of different types of people 

from whom the student reported receiving homework assistance 

8th-grade Student Survey 

TeacherHelp_8, OtherSchoolHelp_8UncleHelp_8, SiblingHelp_8, FriendHelp_8, OtherHelp_8 

NumOutAct_7 Count Count of different types of outof-school activities in which the 

student reported participating 

7th-grade Student Survey 

Hobbies_7, TakingClasses_7, LeagueSports_7, AttendPlays_7 

NumOutAct_8 Count Count of different types of outof-school activities in which the 

student reported participating 

8th-grade Student Survey 

Hobbies_8, TakingClasses_8, LeagueSports_8, AttendPlays_8 
J-38

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

NumPeopleTalkedPSE_7 Count Count of different types of people 

from whom the student reported talking about continuing education after high school 

7th-grade Student Survey 

SQ37a_7 through S

NumPeopleTalkedPSE_8 Count Count of different types of people 

from whom the student reported talking about continuing education after high school 

8th-grade Student Survey 

SQ37a_8 through S

NumSchoolAct_7 Count Count of different types of inschool activities in which the 

student reported participating 

7th-grade Student Survey 

TeamSport_7, SoloSport_7, Band_Drama_7, GovernmCheerleading_7, Yearbook_7, MatheClub_7, Chessclub_VocClub_7 

NumSchoolAct_8 Count Count of different types of inschool activities in which the 

student reported participating 

8th-grade Student Survey 

TeamSport_8, SoloSport_8, Band_Drama_8, GovernmCheerleading_8, Yearbook_8, MatheClub_8, Chessclub_VocClub_8 

NumSibling_7 Count Parent’s report of how many 

siblings the student had 

7th-grade Parent Interview 

PQ35_7 

NumSibling_8 Count Parent’s report of how many 

siblings the student had 

8th-grade Parent Interview 

PQ35_8 

OlderSibGoCollege_7 Binary DK Whether student reported that an 

older sibling attended college 

7th-grade Student Survey 

SQ47c_7 
J-39

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

OlderSibGoCollege_8 Binary DK Whether student reported that an 

older sibling attended college 

8th-grade Student Survey 

SQ47c_8 

OverallGPA Calculated 

number 

Student’s overall GPA Transcript data Not applicable for 

transcript variables 

OtherAdultEd_7 Pro-PSE 

ordinal 

Parent’s report of highest education level among all of the adults in the household, excluding the respondent 

7th-grade Parent Interview 

PQ33_7 

OtherAdultEd_8 Pro-PSE 

ordinal 

Parent’s report of highest education level among all of the adults in the household, excluding the respondent 

8th-grade Parent Interview 

PQ33_8 

OtherHelp_7 Binary Whether student reported 

receiving homework help from someone other than those mentioned in TeacherHelp_7, OtherSchoolHelp_7, UncleHelp_7, SiblingHelp_7, FriendHelp_7 

7th-grade Student Survey 

SQ7f_7 

OtherHelp_8 Binary Whether student reported 

receiving homework help from someone other than those mentioned in TeacherHelp_8, OtherSchoolHelp_8, UncleHelp_8, SiblingHelp_8, FriendHelp_8 

8th-grade Student Survey 

SQ7f_8 
J-40

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

OtherHomework_7 Neutral ordinal How much time a week student 

reported spending on homework other than that mentioned in MathematicsHomework_7, EnglishHomework_7, ScienceHomework_7 (higher values indicate more time spent) 

7th-grade Student Survey 

SQ4d_7 

OtherHomework_8 Neutral ordinal How much time a week student 

reported spending on homework other than that mentioned in MathematicsHomework_7, EnglishHomework_7, ScienceHomework_7 (higher values indicate more time spent) 

8th-grade Student Survey 

SQ4d_8 

OtherSchoolHelp_7 Binary Whether student reported 

receiving homework help from someone at school other than a teacher 

7th-grade Student Survey 

SQ7b_7 

OtherSchoolHelp_8 Binary Whether student reported 

receiving homework help from someone at school other than a teacher 

8th-grade Student Survey 

SQ7b_8 

OutSSusp7 Count Number of out-of-school 

suspensions for student during 7th grade 

7th-grade SIM Not applicable for S

variables 

OutSSusp8 Count Number of out-of-school 

suspensions for student during 8th grade 

8th-grade SIM Not applicable for S

variables 
J-41

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ParentAttends_7 Pro-PSE 

ordinal 

Does the student’s mother or female guardian or father or male guardian attend school activities or events 

7th-grade Student Survey 

SQ49_7, SQ50_7 

ParentAttends_8 Pro-PSE 

ordinal 

Does the student’s mother or female guardian or father or male guardian attend school activities or events 

8th-grade Student Survey 

SQ49_8, SQ50_8 

ParentEd_7 Pro-PSE 

ordinal 

Parent’s report of his or her highest education level 

7th-grade Parent Interview 

PQ31_7 

ParentEd_8 Pro-PSE 

ordinal 

Parent’s report of his or her highest education level 

8th-grade Parent Interview 

PQ31_8 

ParentHelp_7 Neutral ordinal Frequency that student reported 

receiving homework help from either parent (higher values indicate more frequent help) 

7th-grade Student Survey 

MomHelp_7, DadH

ParentHelp_8 Neutral ordinal Frequency that student reported 

receiving homework help from either parent (higher values indicate more frequent help) 

8th-grade Student Survey 

MomHelp_8, DadH

ParGrades_7 Pro-PSE 

ordinal 

Parent’s report of what type of student he or she thinks the child is, and how well the parent thinks the student has done since the beginning of the school year, in subjects other than science, mathematics and history or social studies 

7th-grade Parent Interview 

PQ16_7, PQ17a_7 - PQ17e_7 
J-42

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ParGrades_8 Pro-PSE 

ordinal 

Parent’s report of what type of student he or she thinks the child is, and how well the parent thinks the student has done, since the beginning of the school year, in subjects other than science, mathematics and history or social studies 

8th-grade Parent Interview 

PQ16_8, PQ17a_8 - PQ17e_8 

ParInvolve_7 Pro-PSE 

ordinal 

Measure of parent knowledge and involvement. This variable is contained in table 3-3b. 

7th-grade Parent Interview 

ParPrep_7, Confer_events_7 

ParInvolve_8 Pro-PSE 

ordinal 

Measure of parent knowledge and involvement. This variable is contained in table 3-3b. 

8th-grade Parent Interview 

ParPrep_8, Confer_events_8 

ParPrep_7 Pro-PSE 

ordinal 

Measure of how prepared parent feels about preparing the student to attend college 

7th-grade Parent Interview 

WritInfo_7, PrepMeEnufInfo_7, Worksh

ParPrep_8 Pro-PSE 

ordinal 

Measure of how prepared parent feels about preparing the student to attend college 

8th-grade Parent Interview 

WritInfo_8, PrepMeEnufInfo_8, Worksh
J-43

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ParRptHmwkFreq_7 Neutral ordinal Combination of parent questions 

asking (1) if the child receives homework, (2) if the child ever does homework at home, (3) how often the child does homework at home, (4) where the child most often completes homework and (5) how often the child does homework at a place other than home (higher values indicate homework done more frequently) 

7th-grade Parent Interview 

PQ1_7, PQ2_7, PQPQ4_7, PQ2a_7 

ParRptHmwkFreq_8 Neutral ordinal Combination of parent questions 

asking (1) if the child receives homework, (2) if the child ever does homework at home, (3) how often the child does homework at home, (4) where the child most often completes homework and (5) how often the child does homework at a place other than home (higher values indicate homework done more frequently) 

8th-grade Parent Interview 

PQ1_8, PQ2_8, PQPQ4_8, PQ2a_8 

ParRptHmwkHelp_7 Neutral ordinal How often parent reported 

helping the student with homework (higher values indicate help provided more frequently) 

7th-grade Parent Interview 

PQ7_7 
J-44

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ParRptHmwkHelp_8 Neutral ordinal How often parent reported 

helping the student with homework (higher values indicate help provided more frequently) 

8th-grade Parent Interview 

PQ7_8 

ParRptHmwkHour_7 Neutral ordinal Parent’s report of student does 

homework at home and how much time the child spends doing homework per week, on average (higher values indicate more time spent on homework) 

7th-grade Parent Interview 

PQ1_7, PQ2_7, PQPQ3_7, PQ5_7 

ParRptHmwkHour_8 Neutral ordinal Parent’s report of student does 

homework at home and how much time the child spends doing homework per week, on average (higher values indicate more time spent on homework) 

8th-grade Parent Interview 

PQ1_8, PQ2_8, PQPQ3_8, PQ5_8 

ParTalkBother_7 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about things that were bothering him or her 

7th-grade Student Survey 

SQ48e_7 

ParTalkBother_8 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about things that were bothering him or her 

8th-grade Student Survey 

SQ48e_8 

ParTalkEvent_7 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about school activities or events of particular interest to him or her 

7th-grade Student Survey 

SQ48a_7 
J-45

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ParTalkEvent_8 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about school activities or events of particular interest to him or her 

8th-grade Student Survey 

SQ48a_8 

ParTalkGrades_7 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about his or her grades 

7th-grade Student Survey 

SQ48c_7 

ParTalkGrades_8 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about his or her grades 

8th-grade Student Survey 

SQ48c_8 

ParTalkPolitics_7 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about community, national and world events 

7th-grade Student Survey 

SQ48d_7 

ParTalkPolitics_8 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about community, national and world events 

8th-grade Student Survey 

SQ48d_8 

ParTalkSubject_7 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about things that the student has studied in class 

7th-grade Student Survey 

SQ48b_7 

ParTalkSubject_8 Pro-PSE 

ordinal 

Frequency that student reported talking with parents about things that the student has studied in class 

8th-grade Student Survey 

SQ48b_8 
J-46

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Performance_7 Index Measure parent’s perception of 

their student’s attitude. This variable is contained in table 3-2d. 

7th-grade Parent Interview 

Hmwkundr_7, ParGrades_7, Simphardwork_7 

Performance_8 Index Measure parent’s perception of 

their student’s attitude. This variable is contained in table 3-2d. 

8th-grade Parent Interview 

Hmwkundr_8, ParGrades_8, Simphardwork_8 

PExpect_7 Index Measure of parent’s expectations 

for their child. This variable is contained in table 3-2b. 

7th-grade Parent Interview 

TalkCollege_7, ultdegree_7, collegeclose_7, collegeAffordable_7 

PExpect_8 Index Measure of parent’s expectations 

for their child. This variable is contained in table 3-2b. 

8th-grade Parent Interview 

TalkCollege_8, ultdegree_8, collegeclose_8, collegeAffordable_8 

PImpHardWork_7 Pro-PSE 

ordinal 

How important parent thinks it is that the child works hard in school 

7th-grade Parent Interview 

PQ19_7 

PImpHardWork_8 Pro-PSE 

ordinal 

How important parent thinks it is that the child works hard in school 

8th-grade Parent Interview 

PQ19_8 
J-47

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

PostSecPlan_7 Pro-PSE 

ordinal 

Student’s reported likelihood of going to college, and of those that do not plan to continue his or her education after high school, whether he or she made that decision because he or she plans to join the military service, wants to start a family or needs to take care of his or her family 

7th-grade Student Survey 

SQ39e_7, SQ40_7, SQ39f_7 

PostSecPlan_8 Pro-PSE 

ordinal 

Student’s reported likelihood of going to college, and of those that do not plan to continue his or her education after high school, whether he or she made that decision because he or she plans to join the military service, wants to start a family or needs to take care of his or her family 

8th-grade Student Survey 

SQ39e_8, SQ40_8, SQ39f_8 

PrepMeet_7 Binary DK Whether parent reported 

attending any meetings that discussed the types of classes the student should be taking to prepare for college 

7th-grade Parent Interview 

PQ26_7 

PrepMeet_8 Binary DK Whether parent reported 

attending any meetings that discussed the types of classes the student should be taking to prepare for college 

8th-grade Parent Interview 

PQ26_8 
J-48

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

ProfAspiration_7 Binary C Student’s report of which of 

several listed occupations comes closest to describing the job he or she expects or plans to have by age 30 

7th-grade Student Survey 

SQ45_7 

ProfAspiration_8 Binary C Student’s report of which of 

several listed occupations comes closest to describing the job he or she expects or plans to have by age 30 

8th-grade Student Survey 

SQ45_8 

RaceEth_7 Multinomial Student’s report of his or her own 

race/ethnicity “1” for white (except Hispanic), “2’ for black (including black Hispanic), “3” for Hispanic (except black Hispanic), “4” for Asian, and “5” for American Indian or Alaska 

7th-grade Student Survey 

SQ56_7, SQ57_7 

ReadingHours_7 Pro-PSE 

ordinal 

Time each week the student reported as spent reading, aside from homework 

7th-grade Student Survey 

SQ8_7 

ReadingHours_8 Pro-PSE 

ordinal 

Time each week the student reported as spent reading, aside from homework 

8th-grade Student Survey 

SQ8_8 
J-49

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

RevParDKCount_7 Count Count of the times a parent 

replied “don’t know” on parent questions asking (1) whether student receives homework, (2) how often the student does homework at home, (3) where the student most often completes his or her homework, (4) how often the student does homework at a place other than home, (5) how much average time the student spends doing homework per week, (6) how well the student seems to understand the homework, (7) whether or not the student has participated in tutoring and (8) whether or not the student has visited a job site 

7th-grade Parent Interview 

PQ1_7, PQ2_7, PQPQ3_7, PQ4_7, PQPQ6_7, PQ11a_7-P
J-50

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

RevParDKCount_8 Count Count of the times a parent 

replied “don’t know” on parent questions asking (1) whether or not the student receives homework, (2) how often the student does homework at home, (3) where the student most often completes his or her homework, (4) how often the student does homework at a place other than home, (5) how much average time the student spends doing homework per week, (6) how well the student seems to understand the homework, (7) whether or not the student has participated in tutoring and (8) whether or not the student has visited a job site 

8th-grade Parent Interview 

PQ1_8, PQ2_8, PQPQ3_8, PQ4_8, PQPQ6_8, PQ11a_8-P

ScienceGPA Calculated 

number 

Student’s GPA for science courses 

Transcript data Not applicable for 

transcript variables 

ScienceHomework_7 Neutral ordinal How much time a week student 

reported spending on science homework (higher values indicate more time spent) 

7th-grade Student Survey 

SQ4c_7 

ScienceHomework_8 Neutral ordinal How much time a week student 

reported spending on science homework (higher values indicate more time spent) 

8th-grade Student Survey 

SQ4c_8 
J-51

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

SciencePipeline Calculated 

number 

Highest level of science taken during SY2001–02 

Transcript data Not applicable for 

transcript variables 

SciTutother_7 Binary C Frequency student reported 

receiving science tutoring from someone outside his or her family since the beginning of the year 

7th-grade Student Survey 

SQ22a_7 

SciTutother_8 Binary C Frequency student reported 

receiving science tutoring from someone outside his or her family since the beginning of the year 

8th-grade Student Survey 

SQ22a_8 

SDiligent_7 Index Measure of how hard parent feels 

the student works. This variable is contained in table 3-2d. 

7th-grade Parent Interview 

ParRptHmwkFreq_ParRptHmwkHour_

SDiligent_8 Index Measure of how hard parent feels 

the student works. This variable is contained in table 3-2d. 

8th-grade Parent Interview 

ParRptHmwkFreq_ParRptHmwkHour_

SiblingEd_7 Pro-PSE 

ordinal 

Parent’s report of highest education level among the student’s older siblings that have lived with the child 

7th-grade Parent Interview 

PQ36_7 

SiblingEd_8 Pro-PSE 

ordinal 

Parent’s report of highest education level among the student’s older siblings that have lived with the child 

8th-grade Parent Interview 

PQ36_8 

SiblingHelp_7 Binary Whether student reported 

receiving homework help from a brother or sister 

7th-grade Student Survey 

SQ7d_7 
J-52

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

SiblingHelp_8 Binary Whether student reported 

receiving homework help from a brother or sister 

8th-grade Student Survey 

SQ7d_8 

Simphardwork_7 Pro-PSE 

ordinal 

How important parent thinks the child thinks it is to work hard in school 

7th-grade Parent Interview 

PQ20_7 

Simphardwork_8 Pro-PSE 

ordinal 

How important parent thinks the child thinks it is to work hard in school 

8th-grade Parent Interview 

PQ20_8 

SkipClasses_7 Pro-PSE 

ordinal 

Student’s report of how many classes he or she skipped or cut during the past month 

7th-grade Student Survey 

SQ33_7 

SkipClasses_8 Pro-PSE 

ordinal 

Student’s report of how many classes he or she skipped or cut during the past month 

8th-grade Student Survey 

SQ33_8 

SoloSport_7 Binary DNH Whether student reported 

participating in an individual sport at school that year 

7th-grade Student Survey 

SQ12b_7 

SoloSport_8 Binary DNH Whether student reported 

participating in an individual sport at school that year 

8th-grade Student Survey 

SQ12b_8 

StdParTalk_7 Pro-PSE 

ordinal 

Measure of student’s reports of how frequently they talk with a parent or guardian about different topics 

7th-grade Student Survey 

ParTalkEvent_7, ParTalkSubject_7, ParTalkGrades_7, ParTalkPolitics_7, ParTalkBother_7 
J-53

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

StdParTalk_8 Pro-PSE 

ordinal 

Measure of student’s reports of how frequently they talk with a parent or guardian about different topics 

8th-grade Student Survey 

ParTalkEvent_8, ParTalkSubject_8, ParTalkGrades_8, ParTalkPolitics_8, ParTalkBother_8 

TakingClasses_7 Binary Whether student reported taking 

classes that are not at his or her school 

7th-grade Student Survey 

SQ16b_7 

TakingClasses_8 Binary Whether student reported taking 

classes that are not at his or her school 

8th-grade Student Survey 

SQ16b_8 

TalkCollege_7 Binary Percentage of parents who talked 

with their child about college. This variable is in table 3-2c. 

7th-grade Parent Interview 

PQ21_7 

TalkCollege_8 Binary Percentage of parents who talked 

with their child about college. This variable is contained in table 3-2c. 

8th-grade Parent Interview 

PQ21_8 

TalkCounCollEntClasses_7 Binary Whether student reported talking 

with a school counselor or someone else at the school about the classes needed to get into college 

7th-grade Student Survey 

SQ34b_7 

TalkCounCollEntClasses_8 Binary Whether student reported talking 

with a school counselor or someone else at the school about the classes needed to get into college 

8th-grade Student Survey 

SQ34b_8 
J-54

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

TalkCounHSGradClasses_7 Binary Whether student reported talking 

with a school counselor or someone else at the school about the classes needed to graduate from high school 

7th-grade Student Survey 

SQ34a_7 

TalkCounHSGradClasses_8 Binary Whether student reported talking 

with a school counselor or someone else at the school about the classes needed to graduate from high school 

8th-grade Student Survey 

SQ34a_8 

TalkCoursePlanning_7 Pro-PSE 

ordinal 

Measure of student’s discussions about college and course planning. This variable is contained in table 3-3a. 

7th-grade Student Survey 

TalkCounHSGrad classes_7, TalkCounCollEnt classes_7, TalkHouseCollEnt classes_7 

TalkCoursePlanning_8 Pro-PSE 

ordinal 

Measure of student’s discussions about college and course planning. This variable is contained in table 3-3a. 

8th-grade Student Survey 

TalkCounHSGrad classes_8, TalkCounCollEnt classes_8, TalkHouseCollEnt classes_8 

TalkHouseCollEntClasses_7 

Binary Whether student reported talking 

with any adult in the household about the classes needed to take to get into college since the beginning of the school year 

7th-grade Student Survey 

SQ35_7 
J-55

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

TalkHouseCollEntClasses_8 

Binary Whether student reported talking 

with any adult in the household about the classes needed to take to get into college since the beginning of the school year 

8th-grade Student Survey 

SQ35_8 

TeacherHelp_7 Binary Whether student reported 

receiving homework help from a teacher at school 

7th-grade Student Survey 

SQ7a_7 

TeacherHelp_8 Binary Whether student reported 

receiving homework help from a teacher at school 

8th-grade Student Survey 

SQ7a_8 

TeacherOpImport_7 Pro-PSE 

ordinal 

Importance student places on his or her favorite teacher’s opinions about the student’s education plans 

7th-grade Student Survey 

SQ18f_7 

TeacherOpImport_8 Pro-PSE 

ordinal 

Importance student places on his or her favorite teacher’s opinions about the student’s education plans 

8th-grade Student Survey 

SQ18f_8 

TeamSport_7 Binary DNH Whether student reported 

participating in the school’s team sports that year 

7th-grade Student Survey 

SQ12a_7 

TeamSport_8 Binary DNH Whether student reported 

participating in the school’s team sports that year 

8th-grade Student Survey 

SQ12a_8 

TotAbsnc7 Count Total number of absences for 

student (excused and unexcused) during 7th grade 

7th-grade SIM Not applicable for S

variables 
J-56

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

TotAbsnc8 Count Total number of absences for 

student (excused and unexcused) during 8th grade 

8th-grade SIM Not applicable for S

variables 

TotDisp7 Count Total number of disciplinary 

actions taken against student in 7th grade 

7th-grade SIM Not applicable for S

variables 

TotDisp8 Count Total number of disciplinary 

actions taken against student in 8th grade 

8th-grade SIM Not applicable for S

variables 

TotSusp7 Count Total number of suspensions for 

student during 7th grade 

7th-grade SIM Not applicable for S

variables 

TotSusp8 Count Total number of suspensions for 

student during 8th grade 

8th-grade SIM Not applicable for S

variables 

TotTardy7 Count Total number of tardies for 

student (excused and unexcused) during 7th grade 

7th-grade SIM Not applicable for S

variables 

TotTardy8 Count Total number of tardies for 

student (excused and unexcused) during 8th grade 

8th-grade SIM Not applicable for S

variables 

Truancy_7 Anti-PSE 

ordinal 

Number of days the student reported being absent from school in previous month 

7th-grade Student Survey 

SQ31_7 

Truancy_8 Anti-PSE 

ordinal 

Number of days the student reported being absent from school in previous month 

8th-grade Student Survey 

SQ31_8 

Truancy7 Count Number of truancies for student 

during 7th grade 

7th-grade SIM Not applicable for S

variables 
J-57

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Truancy8 Count Number of truancies for student 

during 8th grade 

8th-grade SIM Not applicable for S

variables 

Ultdegree_7 Pro-PSE 

ordinal 

Parent’s report of whether student will continue education after high school and how far the parent thinks the student will go in school 

7th-grade Parent Interview 

PQ22_7, PQ23_7 

Ultdegree_8 Pro-PSE 

ordinal 

Parent’s report of whether student will continue education after high school and how far the parent thinks the student will go in school 

8th-grade Parent Interview 

PQ22_8, PQ23_8 

UncleHelp_7 Binary Whether student reported 

receiving homework help from an adult in the home other than a parent or guardian 

7th-grade Student Survey 

SQ7c_7 

UncleHelp_8 Binary Whether student reported 

receiving homework help from an adult in the home other than a parent or guardian 

8th-grade Student Survey 

SQ7c_8 

UnExAbsn7 Count Number of unexcused absences 

for student during 7th grade 

7th-grade SIM Not applicable for S

variables 

UnExAbsn8 Count Number of unexcused absences 

for student during 8th grade 

8th-grade SIM Not applicable for S

variables 

UnExTard7 Count Number of unexcused tardies for 

student during 7th grade 

7th-grade SIM Not applicable for S

variables 

UnExTard8 Count Number of unexcused tardies for 

student during 8th grade 

8th-grade SIM Not applicable for S

variables 
J-58

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

VisitCollCamp_7 Binary Whether student reported visiting 

a college campus since the beginning of the year 

7th-grade Student Survey 

SQ29a_7 

VisitCollCamp_8 Binary Whether student reported visiting 

a college campus since the beginning of the year 

8th-grade Student Survey 

SQ29a_8 

VocClub_7 Binary DNH Whether student reported 

participating in the school’s vocational education or professional clubs that year 

7th-grade Student Survey 

SQ12j_7 

VocClub_8 Binary DNH Whether student reported 

participating in the school’s vocational education or professional clubs that year 

8th-grade Student Survey 

SQ12j_8 

VolunteerFreq_7 Neutral ordinal How often student reported doing 

volunteer or community service beyond any requirements for high school graduation (higher values indicate activity occurring more frequently) 

7th-grade Student Survey 

SQ15c_7 

VolunteerFreq_8 Neutral ordinal How often student reported doing 

volunteer or community service beyond any requirements for high school graduation (higher values indicate activity occurring more frequently) 

8th-grade Student Survey 

SQ15c_8 
J-59

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Volunteerism_7 Binary Whether parent reported 

volunteering at child’s school since the beginning of the school year 

7th-grade Parent Interview 

PQ14aa_7 

Volunteerism_8 Binary Whether parent reported 

volunteering at child’s school since the beginning of the school year 

8th-grade Parent Interview 

PQ14aa_8 

wgt01 Weight Replicate baseweight 1 Not applicable for 

weights 

Not applicable for w

wgt02 Weight Replicate baseweight 2 Not applicable for 

weights 

Not applicable for w

wgt03 Weight Replicate baseweight 3 Not applicable for 

weights 

Not applicable for w

wgt04 Weight Replicate baseweight 4 Not applicable for 

weights 

Not applicable for w

wgt05 Weight Replicate baseweight 5 Not applicable for 

weights 

Not applicable for w

wgt06 Weight Replicate baseweight 6 Not applicable for 

weights 

Not applicable for w

wgt07 Weight Replicate baseweight 7 Not applicable for 

weights 

Not applicable for w

wgt08 Weight Replicate baseweight 8 Not applicable for 

weights 

Not applicable for w

wgt09 Weight Replicate baseweight 9 Not applicable for 

weights 

Not applicable for w
J-60

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

wgt10 Weight Replicate baseweight 10 Not applicable for 

weights 

Not applicable for w

wgt11 Weight Replicate baseweight 11 Not applicable for 

weights 

Not applicable for w

wgt12 Weight Replicate baseweight 12 Not applicable for 

weights 

Not applicable for w

wgt13 Weight Replicate baseweight 13 Not applicable for 

weights 

Not applicable for w

wgt14 Weight Replicate baseweight 14 Not applicable for 

weights 

Not applicable for w

wgt15 Weight Replicate baseweight 15 Not applicable for 

weights 

Not applicable for w

wgt16 Weight Replicate baseweight 16 Not applicable for 

weights 

Not applicable for w

wgt17 Weight Replicate baseweight 17 Not applicable for 

weights 

Not applicable for w

wgt18 Weight Replicate baseweight 18 Not applicable for 

weights 

Not applicable for w

White_7 Calculated 

binary 

Whether student was white, not Hispanic 

Student Survey, SIM, and Parent Interview 

SQ56, SQ57, SIM information, PQ43, PQ44, in that order 

Workshop_7 Binary Whether parent reported 

attending workshops on financial aid. This variable is contained in table 3-3c. 

7th-grade Parent Interview 

PQ29_7 
J-61

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Workshop_8 Binary Whether parent reported 

attending workshops on financial aid. This variable is contained in table 3-3c. 

8th-grade Parent Interview 

PQ29_8 

WritInfo_7 Binary DK Whether parent reported 

receiving written materials on preparatory curricula. This variable is contained in table 3-3c. 

7th-grade Parent Interview 

PQ25_7 

WritInfo_8 Binary DK Whether parent reported 

receiving written materials on preparatory curricula. This variable is contained in table 3-3c. 

8th-grade Parent Interview 

PQ25_8 

XBetaForCFP_7 Predicted Predicted logit propensity for 

membership in GEAR UP school 

Not applicable for predicted values 

Not applicable for predicted values 

XBetaTOTABS8 Predicted Predicted total absences as 

reported on SIM. Used to form clusters for 8th grade SIM imputation 

Not applicable for predicted values 

Not applicable for predicted values 

XBetaTOTDISP8 Predicted Predicted total disciplinary 

actions as reported on SIM. Used to form clusters for 8th grade SIM imputation 

Not applicable for predicted values 

Not applicable for predicted values 

XBetaUNEXABS8 Predicted Predicted total unexcused 

absences as reported on SIM. Used to form clusters for 8th grade SIM imputation 

Not applicable for predicted values 

Not applicable for predicted values 
J-62

Table J-1. Definitions of variables used in the analyses report (continued) Variable name Variable type Definition 

Source: 

Instrument 

Source: 

Item(s) 

Yearbook_7 Binary DNH Whether student reported 

participating in the school yearbook, newspaper and literary magazine that year 

7th-grade Student Survey 

SQ12g_7 

Yearbook_8 Binary DNH Whether student reported 

participating in the school yearbook, newspaper and literary magazine that year 

8th-grade Student Survey 

SQ12g_8 
 K-1 

Appendix K 

Data Collection Instruments 

Seventh-Grade Student Survey 
 K-4 
 K-5 
 K-6 
 K-7 
 K-8 
 K-9 
 K-10 
 K-11 
 K-12 
 K-13 
 K-14 
 K-15 
 K-16 
 K-17 
 K-18 
 K-19 
 K-20 
 K-21 
 K-22 
 K-23 
 K-24 
 K-25 
 K-26 
 K-27 
 K-28 
 K-29 
 K-30 
 K-31 
 K-32 
 K-33 

Eighth-Grade Student Survey 
 K-36 
 K-37 
 K-38 
 K-39 
 K-40 
 K-41 
 K-42 
 K-43 
 K-44 
 K-45 
 K-46 
 K-47 
 K-48 
 K-49 
 K-50 
 K-51 
 K-52 
 K-53 
 K-54 
 K-55 
 K-56 
 K-57 
 K-58 
 K-59 
 K-60 
 K-61 
 K-62 
 K-63 

Seventh-Grade Parent Interview 
 K-66 

National Evaluation of GEAR UP 

Parent Survey

INTRODUCTION 

I-1. [Hello, My name is (INTERVIEWER) and I’m calling about a research study that your child’s school is 

participating in sponsored by the United States Department of Education.] 

 May I speak to the person who is most knowledgeable about [CHILD] and (his/her) activities? 

 [WHEN PARENT/GUARDIAN OR MOST KNOWLEDGEABLE ADULT IS ON THE LINE:] The U.S. 

Department of Education is conducting an important study about children’s educational experiences. I 

have some questions about [CHILD’S NAME] that will take about 30 minutes. Your participation is 

voluntary. Everything you say will be confidential and nothing you say will be reported individually 

about you, or your family. Those participating in the study will receive a telephone calling card valued 

at $10. 

I-2. What is your relationship to [CHILD]? 

MOTHER OR STEPMOTHER ................ 1 

FATHER OR STEPFATHER................... 2 

GRANDMOTHER OR GRANDFATHER. 3 

OTHER RELATIVE ................................. 4 

GUARDIAN ............................................. 5 

OTHER (SPECIFY) _______________ 6 

A. PARENTAL INVOLVEMENT 

First I’m going to ask you some questions about [CHILD’S] homework. 

1. Does [CHILD] receive homework? 

YES ......................................................... 1 

NO .......................................................... 2 (GO TO QUESTION 8) 

DON’T KNOW ........................................ 8 (GO TO QUESTION 8) 

2. Does [CHILD] ever do homework at home? 

YES ......................................................... 1 

NO........................................................... 2 (GO TO QUESTION 3) 

DON’T KNOW ........................................ 8 (GO TO QUESTION 3) 

2a. How often does (he/she) do homework at home? Is it... 

Less than once a week, .......................... 1 

1 to 2 times a week, ................................ 2 

3 to 4 times a week, or............................ 3 

5 or more times a week?......................... 4 

DON'T KNOW ......................................... 8 
K-67 

3. Where does (he/she) complete (his/her) homework most often? (CIRCLE ONE) 

IN SCHOOL............................................ 1 

AT HOME ............................................... 2 

IN AN AFTER-SCHOOL PROGRAM..... 3 

OTHER (SPECIFY) ________________ 4 

DON’T KNOW ........................................ 8 (GO TO QUESTION 7) 

4. How often does (he/she) do homework at a place other than home... 

Less than once a week,.......................... 1 

1 to 2 times a week,................................ 2 

3 to 4 times a week,................................ 3 

5 or more times a week, or..................... 4 

Only does it at home?............................. 5 

DON'T KNOW......................................... 8 

5. Including at home, in school, during after-school programs, or any other place that [CHILD] does 

(his/her) homework, how much time does [CHILD] spend doing homework per week on average? 

Would you say... 

None, ...................................................... 1 

Less than 2 hours,.................................. 2 

2-3 hours,................................................ 3 

4-6 hours,................................................ 4 

over 6 hours,........................................... 5 

DON'T KNOW......................................... 8 

6. Does (he/she) seem to understand (his/her) homework? Would you say... 

Always, ................................................... 1 

Sometimes,............................................. 2 

Rarely, .................................................... 3 

Never, ..................................................... 4 

DON'T KNOW......................................... 8 

7. How often do you help (him/her)with homework? Would you say... 

Never, ..................................................... 1 

Less than once a week,.......................... 2 

1 to 2 times a week,................................ 3 

3 to 4 times a week, or ........................... 4 

5 or more times a week .......................... 5 

Now I have a few questions about [CHILD’S] teacher. 

8. Since the beginning of the school year, have you met with any of [CHILD’S] teachers? 

YES......................................................... 1 

NO .......................................................... 2 (GO TO QUESTION 11) 

DON’T KNOW ........................................ 8 (GO TO QUESTION 11) 
 K-68 

9. Since the beginning of the school year, how many meetings have you had with [CHILD’S] 

teachers? Would you say... 

One,................................................................................................ 1 

A few, ............................................................................................. 2 

Several, or ...................................................................................... 3 

I regularly meet with my child’s teacher(s)..................................... 4 

10. In general, what was the purpose of the meeting(s)? Was it... (CIRCLE ONE ON EACH LINE) 

 DON’T 

 YES NO KNOW

a. To discuss a problem with a specific homework assignment?.. 1 2 8 

b. To discuss behavioral problems?........................................... 1 2 8 

c. To discuss overall academic performance/progress?............ 1 2 8 

d. Some other reason (SPECIFY)?_______________________ 1 2 8 

11. Since the beginning 

of the school year, 

has [CHILD] 

participated in the 

following activities: 

∏ (IF YES) How helpful was the activity? 

Was it very helpful, helpful, not too helpful, or 

not helpful at all? 

 

ACTIVITIES YES NO

DON'T 

KNOW

∏ Very 

Helpful Helpfu

l

Not too 

Helpful

Not Helpful 

At All

a. Tutoring 1 2 8 ∏ 1 2 3 4 

b. Mentoring 1 2 8 ∏ 1 2 3 4 

c. Counseling 1 2 8 ∏ 1 2 3 4 

d. Workshops 1 2 8 ∏ 1 2 3 4 

e. College campus visit 1 2 8 ∏ 1 2 3 4 

f. Job site visit 1 2 8 ∏ 1 2 3 4 

(IF RESPONDENT ANSWERS NO OR DON’T KNOW TO ALL ACTIVITIES GO TO Q 13)

12. How did you learn about the activities that (he/she) is participating in? Was it ... (CIRCLE ALL THAT 

APPLY) 

 

From a letter or written notice?............................................................. 1 

[CHILD’S] teacher?............................................................................... 2 

A phone call from someone other than [CHILD’S] teacher? ................ 3 

From [CHILD]?...................................................................................... 4 

Another parent? .................................................................................... 5 

You asked someone?........................................................................... 6 

From some other source (SPECIFY)?_________________________ 7 
K-69 

The next questions are about the types of school events you have attended this school year. 

13. I am going to read a list of events you may have attended for [CHILD]. Please tell me if you have 

attended the event more than once, once, or never. Since the beginning of the school year, how 

often have you ... 

 More than 

once Once Never

 

a. Attended a meeting on college preparation... 1 2 3 

 

b. Attended a meeting on study skills ............. 1 2 3 

 

c. Attended some other meeting ................... 1 2 3 

 

d. Visited a college..................................... 1 2 3 

 

e. Attended class at college or university......... 1 2 3 

14. Since the beginning of the school year, have you participated in any of the following school 

activities? 

 DON’T 

 YES NO KNOW

a. Back-to-school-night .............................................................. 1 2 8 

b. PTA meetings ........................................................................ 1 2 8 

c. A school event, such as a play or sports event ..................... 1 2 8 

d. Attended a field trip, such as a museum or zoo .................... 1 2 8 

 14a. Since the beginning of the school year, have you volunteered at your child's school? 

YES......................................................... 1 

NO .......................................................... 2 

B. PARENT’S SATISFACTION 

Now I have a few questions about [CHILD’S] experiences this school year at (his/her) current school. 

15. Thinking about [CHILD'S] school would you say you are very satisfied, somewhat satisfied, somewhat 

dissatisfied or very dissatisfied, with ..... 

 Very 

Satisfied

Somewhat 

Satisfied

Somewhat 

Dissatisfied

Very 

Dissatisfied

 

a. (His/Her) education ................................... 1 2 3 4 

b. The school's approach towards college 

preparation ................................................ 1 2 3 4 

c. The level of discipline maintained in the 

classroom by [CHILD'S] teacher ............... 1 2 3 4 

d. The respect that teachers and students 

have for each other ................................... 1 2 3 4 

e. The level of discipline maintained in the 

school by the principal and the assistant 

principal..................................................... 1 2 3 4 

f. The school's encouragement of family 

involvement ............................................... 1 2 3 4 
 K-70 

C. CHANGE IN ACADEMIC PERFORMANCE, ATTITUDE OR BEHAVIOR 

16. Overall, what type of student is [CHILD]? Would you say ... 

Excellent,................................................. 1 

Good,....................................................... 2 

Fair, ......................................................... 3 

Poor?....................................................... 4 

17. Since the beginning of the school year, do you think [CHILD] has done excellent, good, fair, or poor 

in the following areas? 

 Excellent Good Fair Poor

 

a. English ............................................. 1 2 3 4 

b. Science ............................................ 1 2 3 4 

c. Math ................................................. 1 2 3 4 

d. History or social studies................... 1 2 3 4 

e. All other subjects.............................. 1 2 3 4 

18. Parents generally learn how well their child is doing in school through a variety of ways. I’m going to 

read a list of ways. Please tell me if each way was very helpful, helpful, not too helpful or not helpful at 

all for you. 

 

Very 

Helpful Helpful

Not too 

Helpful

Not 

Helpful 

at All

NOT 

APPLICABLE

 

a. Parent/teacher conferences............. 1 2 3 4 5 

b. Homework sign-off........................... 1 2 3 4 5 

c. Report cards .................................... 1 2 3 4 5 

d. Talking to my child ........................... 1 2 3 4 5 

e. Phone calls from teacher(s)............. 1 2 3 4 5 

f. Notes from teacher(s) ...................... 1 2 3 4 5 

19. How important do you think it is that [CHILD] works hard in school? Would you say... 

Very important,........................................ 1 

Important, ................................................ 2 

Not too important, or ............................... 3 

Not important at all?................................ 4 

20. How important does [CHILD] think it is to work hard in school? Would you say... 

Very important,........................................ 1 

Important, ................................................ 2 

Not too important, or ............................... 3 

Not important at all?................................ 4 
K-71 

D. PARENT EXPECTATIONS 

Now, I am going to ask you some questions about your expectations for [CHILD]. 

21. Since the beginning of the school year, have you talked to (him/her) about attending college? 

YES......................................................... 1 

NO .......................................................... 2 

22. Do you think (he/she) will continue (his/her) education after high school? (CHILD DOES NOT HAVE 

TO CONTINUE EDUCATION RIGHT AFTER HIGH SCHOOL) 

YES......................................................... 1 

NO .......................................................... 2 (GO TO SECTION E) 

DON’T KNOW ....................................... 8 (GO TO SECTION E) 

23. How far in school do you think [CHILD] will get? Would you say ... 

A certificate from a vocational, trade or business school, ............. 1 

An Associate's (AA) degree,.......................................................... 2 

A Bachelor’s (BA) degree, ............................................................. 3 

A graduate or professional degree? .............................................. 4 

24. Do you think (he/she) will attend a college or other school after high school that is close to where you 

live now? 

YES......................................................... 1 

NO .......................................................... 2 

DON'T KNOW......................................... 8 

E. KNOWLEDGE OF COLLEGE ENTRANCE REQUIREMENTS 

Many people believe that it is never too soon to start preparing for college. I know that [CHILD] is only in the 7th

grade, but I’m going to ask you the following questions about preparing for college. 

25. Since the beginning of the school year, have you received any written information about the types 

of classes (he/she) should be taking now to prepare (himself/herself) for college? 

YES......................................................... 1 

NO .......................................................... 2 

DON’T KNOW ........................................ 8 

26. Since the beginning of the school year, have you attended any meetings that discussed the types 

of classes (he/she) should be taking now to prepare (himself/herself) for college? 

YES......................................................... 1 

NO .......................................................... 2 

DON’T KNOW ........................................ 8 
 K-72 

27. Given that [CHILD] is in the 7th grade, do you feel you have... 

 [IF CHILD IS NOT GOING TO COLLEGE, ASK FOR GENERAL OPINION ANYWAY] 

Enough information about college entrance requirements................... 1 

Some information but not enough about college entrance requirements.. 2 

No information about college entrance requirements?.......................... 3 

F. KNOWLEDGE OF POSTSECONDARY EDUCATION COSTS 

28. Do you think [CHILD] will be able to afford to attend a 4-year state college or university after high 

school? When answering this question please take into account your family's resources and any other 

financial sources such as financial aid from the government. Would you say... 

 [IF CHILD IS NOT GOING TO COLLEGE, ASK FOR GENERAL OPINION ANYWAY] 

Definitely,................................................. 1 

Probably, ................................................. 2 

Not sure,.................................................. 3 

I doubt it,.................................................. 4 

Definitely not? ......................................... 5 

29. Have you attended any workshops for parents that provided you with information about financial 

assistance for your child to attend college? 

YES ......................................................... 1 

NO........................................................... 2 (GO TO QUESTION 30) 

29a. How helpful was the information? Was it ... 

Very helpful, ............................................ 1 

Helpful, .................................................... 2 

Not too helpful, or.................................... 3 

Not helpful at all? .................................... 4 

30. How much do you think it costs today to attend each of the following types of institutions for 1 year? 

I’m interested in an estimate that includes the cost of room, board, and tuition for 1 year. 

a. Community college or junior college? .................................... $__________________ 

b. Four-year state college or university? .................................... $__________________ 

c. Four-year private college or university? ................................. $__________________ 
K-73 

G. EDUCATION BACKGROUND 

Now I have a few questions about you and the other adult(s) in your household. 

31. What is the highest grade or year of school that you have completed including college or vocational 

training? 

UP TO 8TH GRADE........................................................................ 1 

9TH TO 11TH GRADE...................................................................... 2 

12TH BUT NO DIPLOMA................................................................ 3 

HIGH SCHOOL DIPLOMA OR EQUIVALENT.............................. 4 

VOC/TECH PROGRAM AFTER HIGH SCHOOL BUT NO 

 VOC/TECH DIPLOMA ........................................................... 5 

VOC/TECH DIPLOMA AFTER HIGH SCHOOL............................ 6 

SOME COLLEGE BUT NO DEGREE ........................................... 7 

ASSOCIATE’S DEGREE............................................................... 8 

BACHELOR’S DEGREE ............................................................... 9 

GRADUATE OR PROFESSIONAL SCHOOL BUT NO DEGREE 10 

GRADUATE OR PROFESSIONAL SCHOOL WITH DEGREE .... 11 

OTHER ____________________________................................. 12 

32. Including yourself, how many adults live in your home who are 18 years of age or older? 

 |___|___| 

# OF ADULTS 

(IF 1 GO TO Q34, IF GREATER THAN 1 ASK Q33.) 

33. Among all of the adults in your household, other than yourself, what is the highest grade or year of 

school completed including college or vocational training? 

UP TO 8TH GRADE........................................................................ 1 

9TH TO 11TH GRADE...................................................................... 2 

12TH BUT NO DIPLOMA................................................................ 3 

HIGH SCHOOL DIPLOMA OR EQUIVALENT.............................. 4 

VOC/TECH PROGRAM AFTER HIGH SCHOOL BUT NO 

 VOC/TECH DIPLOMA ........................................................... 5 

VOC/TECH DIPLOMA AFTER HIGH SCHOOL............................ 6 

SOME COLLEGE BUT NO DEGREE ........................................... 7 

ASSOCIATE’S DEGREE............................................................... 8 

BACHELOR’S DEGREE ............................................................... 9 

GRADUATE OR PROFESSIONAL SCHOOL BUT NO DEGREE 10 

GRADUATE OR PROFESSIONAL SCHOOL WITH DEGREE .... 11 

OTHER_____________________________................................ 12 
 K-74 

Now I would like to talk about [CHILD’S] siblings. 

34. Does [CHILD] have any older siblings? By sibling I am referring to biological, step, half, and adopted 

brother and/or sister. 

YES ........................................................ 1 

NO .......................................................... 2 (GO TO QUESTION 38) 

DON’T KNOW ........................................ 8 (GO TO QUESTION 38) 

35. How many older siblings does [CHILD] have? 

 |___|___| 

# OF SIBLINGS 

36. What is the highest grade or year of school completed so far by any older siblings who have lived 

with [CHILD]? Include college or vocational training. 

UP TO 8TH GRADE ........................................................................ 1 

9TH TO 11TH GRADE ...................................................................... 2 

12TH BUT NO DIPLOMA ................................................................ 3 

HIGH SCHOOL DIPLOMA OR EQUIVALENT .............................. 4 

VOC/TECH PROGRAM AFTER HIGH SCHOOL BUT NO 

 VOC/TECH DIPLOMA............................................................ 5 

VOC/TECH DIPLOMA AFTER HIGH SCHOOL ............................ 6 

SOME COLLEGE BUT NO DEGREE............................................ 7 

ASSOCIATE’S DEGREE ............................................................... 8 

BACHELOR’S DEGREE ................................................................ 9 

GRADUATE OR PROFESSIONAL SCHOOL BUT NO DEGREE 10 

GRADUATE OR PROFESSIONAL SCHOOL WITH DEGREE..... 11 

OTHER _____________________________ ............................... 12 

37. How old is that sibling? 

|___|___| 

 AGE 

H. BACKGROUND INFORMATION 

38. Do you have a computer in your home? 

YES ......................................................... 1 

NO........................................................... 2 

39. Do you have internet access? 

YES ......................................................... 1 

NO........................................................... 2 
K-75 

40. Does anyone in your household have a library card? 

YES......................................................... 1 

NO .......................................................... 2 (GO TO QUESTION 42) 

DON'T KNOW......................................... 8 (GO TO QUESTION 42) 

41. Does anyone in your household use their library card? 

YES......................................................... 1 

NO .......................................................... 2 

DON'T KNOW......................................... 8 

42. In studies like this, households are sometimes grouped according to income. What was the total 

income of all persons in your household over the past year, including salaries or other earnings, 

interest, retirement, public assistance and so on for all household members? 

$10,000 OR LESS.................................. 1 

$10,001 TO $20,000............................... 2 

$20,001 TO $30,000............................... 3 

$30,001 TO $40,000............................... 4 

$40,001 TO $50,000............................... 5 

OVER $50,000 ....................................... 6 

REFUSED............................................... 7 

DON’T KNOW ........................................ 8 

43. Do you consider yourself Hispanic or Latino? 

YES......................................................... 1 

NO .......................................................... 2 

44. How do you describe yourself? (CIRCLE ALL THAT APPLY) 

American Indian or Alaska Native .......... 1 

Asian....................................................... 2 

Black or African American ...................... 3 

Native Hawaiian or Other Pacific Islander 4 

White....................................................... 5 

Now I have a few questions to help us contact you again. 

(PLEASE COMPLETE THE LOCATING INFORMATION THAT IS ATTACHED TO THE 

RESPONDENT INFORMATION SHEET) 

Eighth-Grade Parent Interview 
 K-78 

National Evaluation of GEAR UP 

Parent Survey 

INTRODUCTION 

I-1. [Hello, My name is (INTERVIEWER) and I’m calling on behalf of the U.S. Department of Education to 

follow up on an important education study that we did last year. 

 May I speak to the person who is most knowledgeable about [CHILD] and (his/her) activities? 

 [WHEN PARENT/GUARDIAN OR MOST KNOWLEDGEABLE ADULT IS ON THE LINE:] The U.S. 

Department of Education is conducting an important study about children’s educational experiences. 

We spoke with someone in your household last year about [CHILD]. I have some questions about 

[CHILD] that will take about 30 minutes. Your participation is voluntary. Everything you say will be 

confidential and nothing you say will be reported individually about you or your family. Those 

participating in the study will receive a telephone card valued at $10. 

I-2. What is your relationship to [CHILD]? 

MOTHER OR STEPMOTHER ................ 1 

FATHER OR STEPFATHER................... 2 

GRANDMOTHER OR GRANDFATHER. 3 

OTHER RELATIVE ................................. 4 

GUARDIAN ............................................. 5 

OTHER (SPECIFY) _______________ 6 

A. PARENTAL INVOLVEMENT 

First I’m going to ask you some questions about [CHILD’S] homework. 

1. Does [CHILD] receive homework? 

YES ......................................................... 1 

NO .......................................................... 2 (GO TO QUESTION 8) 

DON’T KNOW ........................................ 8 (GO TO QUESTION 8) 

2. Does [CHILD] ever do homework at home? 

YES ......................................................... 1 

NO........................................................... 2 (GO TO QUESTION 3) 

DON’T KNOW ........................................ 8 (GO TO QUESTION 3) 

2a. How often does (he/she) do homework at home? Is it... 

Less than once a week, .......................... 1 

1 to 2 times a week, ................................ 2 

3 to 4 times a week, or............................ 3 

5 or more times a week?......................... 4 

DON'T KNOW ......................................... 8 
K-79 

3. Where does (he/she) complete (his/her) homework most often? (CIRCLE ONE) 

IN SCHOOL............................................ 1 

AT HOME ............................................... 2 

IN AN AFTER-SCHOOL PROGRAM..... 3 

OTHER (SPECIFY) ________________ 4 

DON’T KNOW ........................................ 8 (GO TO QUESTION 7) 

4. How often does (he/she) do homework at a place other than home... 

Less than once a week,.......................... 1 

1 to 2 times a week,................................ 2 

3 to 4 times a week,................................ 3 

5 or more times a week, or..................... 4 

Only does it at home?............................. 5 

DON'T KNOW......................................... 8 

5. Including at home, in school, during after-school programs, or any other place that [CHILD] does 

(his/her) homework, how much time does [CHILD] spend doing homework per week on average? 

Would you say... 

None, ...................................................... 1 

Less than 2 hours,.................................. 2 

2-3 hours,................................................ 3 

4-6 hours,................................................ 4 

over 6 hours,........................................... 5 

DON'T KNOW......................................... 8 

6. Does (he/she) seem to understand (his/her) homework? Would you say... 

Always, ................................................... 1 

Sometimes,............................................. 2 

Rarely, .................................................... 3 

Never, ..................................................... 4 

DON'T KNOW......................................... 8 

7. How often do you help (him/her) with homework? Would you say... 

Never, ..................................................... 1 

Less than once a week,.......................... 2 

1 to 2 times a week,................................ 3 

3 to 4 times a week, or ........................... 4 

5 or more times a week .......................... 5 

Now I have a few questions about [CHILD’S] teacher. 

8. Since the beginning of the school year, have you met with any of [CHILD’S] teachers? 

YES......................................................... 1 

NO .......................................................... 2 (GO TO QUESTION 11) 

DON’T KNOW ........................................ 8 (GO TO QUESTION 11) 
 K-80 

9. Since the beginning of the school year, how many meetings have you had with [CHILD’S] 

teachers? Would you say... 

One,................................................................................................ 1 

A few, ............................................................................................. 2 

Several, or ...................................................................................... 3 

I regularly meet with my child’s teacher(s)..................................... 4 

11. In general, what was the purpose of the meeting(s)? Was it... (CIRCLE ONE ON EACH LINE) 

 DON’T 

 YES NO KNOW

a. To discuss a problem with a specific homework assignment?.. 1 2 8 

b. To discuss behavioral problems?........................................... 1 2 8 

c. To discuss overall academic performance/progress?............ 1 2 8 

d. Some other reason (SPECIFY)?_______________________ 1 2 8 

11. Since the beginning 

of the school year, 

has [CHILD] 

participated in the 

following activities: 

∏ (IF YES) How helpful was the activity? 

Was it very helpful, helpful, not too helpful, or 

not helpful at all? 

 

ACTIVITIES YES NO

DON'T 

KNOW

∏ Very 

Helpful Helpfu

l

Not too 

Helpful

Not Helpful 

At All

a. Tutoring 1 2 8 ∏ 1 2 3 4 

b. Mentoring 1 2 8 ∏ 1 2 3 4 

c. Counseling 1 2 8 ∏ 1 2 3 4 

d. Workshops 1 2 8 ∏ 1 2 3 4 

e. College campus visit 1 2 8 ∏ 1 2 3 4 

f. Job site visit 1 2 8 ∏ 1 2 3 4 

(IF RESPONDENT ANSWERS NO OR DON’T KNOW TO ALL ACTIVITIES GO TO Q 13)

12. How did you learn about the activities that (he/she) is participating in? Was it ... (CIRCLE ALL THAT 

APPLY) 

 

From a letter or written notice?............................................................. 1 

[CHILD’S] teacher?............................................................................... 2 

A phone call from someone other than [CHILD’S] teacher? ................ 3 

From [CHILD]?...................................................................................... 4 

Another parent? .................................................................................... 5 

You asked someone?........................................................................... 6 

From some other source (SPECIFY)?_________________________ 7 
K-81 

The next questions are about the types of school events you have attended this school year. 

13. I am going to read a list of events you may have attended for [CHILD]. Please tell me if you have 

attended the event more than once, once, or never. Since the beginning of the school year, how 

often have you ... 

 More than 

once Once Never

 

a. Attended a meeting on college preparation... 1 2 3 

 

b. Attended a meeting on study skills ............. 1 2 3 

 

c. Attended some other meeting ................... 1 2 3 

 

d. Visited a college..................................... 1 2 3 

 

e. Attended class at college or university......... 1 2 3 

14. Since the beginning of the school year, have you participated in any of the following school 

activities? 

 DON’T 

 YES NO KNOW

a. Back-to-school-night .............................................................. 1 2 8 

b. PTA meetings ........................................................................ 1 2 8 

c. A school event, such as a play or sports event ..................... 1 2 8 

d. Attended a field trip, such as a museum or zoo .................... 1 2 8 

 14a. Since the beginning of the school year, have you volunteered at your child's school? 

YES......................................................... 1 

NO .......................................................... 2 
 K-82 

B. PARENT’S SATISFACTION 

Now I have a few questions about [CHILD’S] experiences this school year at (his/her) current school. 

15. Thinking about [CHILD'S] school would you say you are very satisfied, somewhat satisfied, somewhat 

dissatisfied or very dissatisfied, with ..... 

 Very 

Satisfied

Somewhat 

Satisfied

Somewhat 

Dissatisfied

Very 

Dissatisfied

 

a. (His/Her) education.................................... 1 2 3 4 

b. The school's approach towards college 

preparation................................................. 1 2 3 4 

c. The level of discipline maintained in the 

classroom by [CHILD'S] teacher................ 1 2 3 4 

d. The respect that teachers and students 

have for each other.................................... 1 2 3 4 

e. The level of discipline maintained in the 

school by the principal and the assistant 

principal...................................................... 1 2 3 4 

f. The school's encouragement of family 

involvement................................................ 1 2 3 4 

C. CHANGE IN ACADEMIC PERFORMANCE, ATTITUDE OR BEHAVIOR 

16. Overall, what type of student is [CHILD]? Would you say ... 

Excellent,................................................. 1 

Good,....................................................... 2 

Fair, ......................................................... 3 

Poor?....................................................... 4 

17. Since the beginning of the school year, do you think [CHILD] has done excellent, good, fair, or poor 

in the following areas? 

 Excellent Good Fair Poor

 

a. English ............................................. 1 2 3 4 

b. Science ............................................ 1 2 3 4 

c. Math ................................................. 1 2 3 4 

d. History or social studies................... 1 2 3 4 

e. All other subjects.............................. 1 2 3 4 
K-83 

18. Parents generally learn how well their child is doing in school through a variety of ways. I’m going to 

read a list of ways. Please tell me if each way was very helpful, helpful, not too helpful or not helpful at 

all for you. 

 

Very 

Helpful Helpful

Not too 

Helpful

Not 

Helpful 

at All

NOT 

APPLICABLE

 

a. Parent/teacher conferences............. 1 2 3 4 5 

b. Homework sign-off ........................... 1 2 3 4 5 

c. Report cards..................................... 1 2 3 4 5 

d. Talking to my child............................ 1 2 3 4 5 

e. Phone calls from teacher(s) ............. 1 2 3 4 5 

f. Notes from teacher(s) ...................... 1 2 3 4 5 

19. How important do you think it is that [CHILD] works hard in school? Would you say... 

Very important, ....................................... 1 

Important,................................................ 2 

Not too important, or............................... 3 

Not important at all? ............................... 4 

20. How important does [CHILD] think it is to work hard in school? Would you say... 

Very important, ....................................... 1 

Important,................................................ 2 

Not too important, or............................... 3 

Not important at all? ............................... 4 

D. PARENT EXPECTATIONS 

Now, I am going to ask you some questions about your expectations for [CHILD]. 

21. Since the beginning of the school year, have you talked to (him/her) about attending college? 

YES......................................................... 1 

NO .......................................................... 2 

22. Do you think (he/she) will continue (his/her) education after high school? (CHILD DOES NOT HAVE 

TO CONTINUE EDUCATION RIGHT AFTER HIGH SCHOOL) 

YES......................................................... 1 

NO .......................................................... 2 (GO TO SECTION E) 

DON’T KNOW ....................................... 8 (GO TO SECTION E) 

23. How far in school do you think [CHILD] will get? Would you say ... 

A certificate from a vocational, trade or business school, ............. 1 

An Associate's (AA) degree,.......................................................... 2 

A Bachelor’s (BA) degree, ............................................................. 3 

A graduate or professional degree? .............................................. 4 
 K-84 

24. Do you think (he/she) will attend a college or other school after high school that is close to where you 

live now? 

YES ......................................................... 1 

NO........................................................... 2 

DON'T KNOW ......................................... 8 

E. KNOWLEDGE OF COLLEGE ENTRANCE REQUIREMENTS 

Many people believe that it is never too soon to start preparing for college. I know that [CHILD] is only in the 8th

grade, but I’m going to ask you the following questions about preparing for college. 

25. Since the beginning of the school year, have you received any written information about the types 

of classes (he/she) should be taking now to prepare (himself/herself) for college? 

YES ......................................................... 1 

NO........................................................... 2 

DON’T KNOW ......................................... 8 

26. Since the beginning of the school year, have you attended any meetings that discussed the types 

of classes (he/she) should be taking now to prepare (himself/herself) for college? 

YES ......................................................... 1 

NO........................................................... 2 

DON’T KNOW ......................................... 8 

27. Given that [CHILD] is in the 8th grade, do you feel you have... 

 [IF CHILD IS NOT GOING TO COLLEGE, ASK FOR GENERAL OPINION ANYWAY] 

Enough information about college entrance requirements................... 1 

Some information but not enough about college entrance requirements.. 2 

No information about college entrance requirements?.......................... 3 

F. KNOWLEDGE OF POSTSECONDARY EDUCATION COSTS 

28. Do you think [CHILD] will be able to afford to attend a 4-year state college or university after high 

school? When answering this question please take into account your family's resources and any other 

financial sources such as financial aid from the government. Would you say... 

 [IF CHILD IS NOT GOING TO COLLEGE, ASK FOR GENERAL OPINION ANYWAY] 

Definitely,................................................. 1 

Probably, ................................................. 2 

Not sure,.................................................. 3 

I doubt it,.................................................. 4 

Definitely not? ......................................... 5 

29. Have you attended any workshops for parents that provided you with information about financial 

assistance for your child to attend college? 

YES ......................................................... 1 

NO........................................................... 2 (GO TO QUESTION 30) 
K-85 

29a. How helpful was the information? Was it ... 

Very helpful,............................................ 1 

Helpful,.................................................... 2 

Not too helpful, or ................................... 3 

Not helpful at all?.................................... 4 

30. How much do you think it costs today to attend each of the following types of institutions for 1 year? 

I’m interested in an estimate that includes the cost of room, board, and tuition for 1 year. 

a. Community college or junior college?.................................... $__________________ 

b. Four-year state college or university?.................................... $__________________ 

c. Four-year private college or university? ................................ $__________________ 

G. EDUCATION BACKGROUND 

Now I have a few questions about you and the other adult(s) in your household. 

31. What is the highest grade or year of school that you have completed including college or vocational 

training? 

UP TO 8TH GRADE........................................................................ 1 

9TH TO 11TH GRADE...................................................................... 2 

12TH BUT NO DIPLOMA................................................................ 3 

HIGH SCHOOL DIPLOMA OR EQUIVALENT.............................. 4 

VOC/TECH PROGRAM AFTER HIGH SCHOOL BUT NO 

 VOC/TECH DIPLOMA ........................................................... 5 

VOC/TECH DIPLOMA AFTER HIGH SCHOOL............................ 6 

SOME COLLEGE BUT NO DEGREE ........................................... 7 

ASSOCIATE’S DEGREE............................................................... 8 

BACHELOR’S DEGREE ............................................................... 9 

GRADUATE OR PROFESSIONAL SCHOOL BUT NO DEGREE 10 

GRADUATE OR PROFESSIONAL SCHOOL WITH DEGREE .... 11 

OTHER ____________________________................................. 12 

32. Including yourself, how many adults live in your home who are 18 years of age or older? 

 |___|___| 

# OF ADULTS 

(IF 1 GO TO Q34, IF GREATER THAN 1 ASK Q33.) 
 K-86 

33. Among all of the adults in your household, other than yourself, what is the highest grade or year of 

school completed including college or vocational training? 

UP TO 8TH GRADE ........................................................................ 1 

9TH TO 11TH GRADE ...................................................................... 2 

12TH BUT NO DIPLOMA ................................................................ 3 

HIGH SCHOOL DIPLOMA OR EQUIVALENT .............................. 4 

VOC/TECH PROGRAM AFTER HIGH SCHOOL BUT NO 

 VOC/TECH DIPLOMA............................................................ 5 

VOC/TECH DIPLOMA AFTER HIGH SCHOOL ............................ 6 

SOME COLLEGE BUT NO DEGREE............................................ 7 

ASSOCIATE’S DEGREE ............................................................... 8 

BACHELOR’S DEGREE ................................................................ 9 

GRADUATE OR PROFESSIONAL SCHOOL BUT NO DEGREE 10 

GRADUATE OR PROFESSIONAL SCHOOL WITH DEGREE..... 11 

OTHER_____________________________ ................................ 12 

Now I would like to talk about [CHILD’S] siblings. 

34N. Does [CHILD] have any siblings? By sibling I am referring to biological, step, half, and adopted 

brother and/or sister. 

YES ........................................................ 1 

NO .......................................................... 2 (GO TO QUESTION 38) 

DON’T KNOW ........................................ 8 (GO TO QUESTION 38) 

35a. How many younger siblings does [CHILD] have? By younger siblings I am referring to brothers or 

sisters who are the same age or younger. 

 |___|___| 

# OF SIBLINGS 

35. How many older siblings does [CHILD] have? 

 |___|___| 

# OF SIBLINGS 
K-87 

36. What is the highest grade or year of school completed so far by this/these older siblings? We are 

only interested in siblings who liven with [CHILD]. Include college or vocational training. 

UP TO 8TH GRADE........................................................................ 1 

9TH TO 11TH GRADE...................................................................... 2 

12TH BUT NO DIPLOMA................................................................ 3 

HIGH SCHOOL DIPLOMA OR EQUIVALENT.............................. 4 

VOC/TECH PROGRAM AFTER HIGH SCHOOL BUT NO 

 VOC/TECH DIPLOMA ........................................................... 5 

VOC/TECH DIPLOMA AFTER HIGH SCHOOL............................ 6 

SOME COLLEGE BUT NO DEGREE ........................................... 7 

ASSOCIATE’S DEGREE............................................................... 8 

BACHELOR’S DEGREE ............................................................... 9 

GRADUATE OR PROFESSIONAL SCHOOL BUT NO DEGREE 10 

GRADUATE OR PROFESSIONAL SCHOOL WITH DEGREE .... 11 

OTHER _____________________________............................... 12 

37. How old is that sibling? 

|___|___| 

 AGE 

H. BACKGROUND INFORMATION 

38. Do you have a computer in your home? 

YES......................................................... 1 

NO .......................................................... 2 

39. Do you have internet access? 

YES......................................................... 1 

NO .......................................................... 2 

40. Does anyone in your household have a library card? 

YES......................................................... 1 

NO .......................................................... 2 (GO TO QUESTION 42) 

DON'T KNOW......................................... 8 (GO TO QUESTION 42) 

41. Does anyone in your household use their library card? 

YES......................................................... 1 

NO .......................................................... 2 

DON'T KNOW......................................... 8 
 K-88 

42. In studies like this, households are sometimes grouped according to income. What was the total 

income of all persons in your household over the past year, including salaries or other earnings, 

interest, retirement, public assistance and so on for all household members? 

$10,000 OR LESS................................... 1 

$10,001 TO $20,000 ............................... 2 

$20,001 TO $30,000 ............................... 3 

$30,001 TO $40,000 ............................... 4 

$40,001 TO $50,000 ............................... 5 

OVER $50,000 ........................................ 6 

REFUSED ............................................... 7 

DON’T KNOW ......................................... 8 

43. Do you consider yourself Hispanic or Latino? 

YES ......................................................... 1 

NO........................................................... 2 

44. How do you describe yourself? (CIRCLE ALL THAT APPLY) 

American Indian or Alaska Native........... 1 

Asian ....................................................... 2 

Black or African American....................... 3 

Native Hawaiian or Other Pacific Islander 4 

White ....................................................... 5 

Now I have a few questions to help us contact you again. 

(PLEASE COMPLETE THE LOCATING INFORMATION THAT IS ATTACHED TO THE 

RESPONDENT INFORMATION SHEET) 
Student Information Matrix 

(Administrative Records Data) 
 K-90 

SIM: 
Activity Records Forms 
 K-92 

One-On-One Scheduled Student Activities: 
 K-93 

Student Group Activity Attendance Form: 
 K-94 

Parent Group Activity Attendance Form: