Part A: Supporting 

Statement for 

Paperwork Reduction 

Act Submission

Study of Teacher 

Preparation Experiences 

and Early Teacher 

Effectiveness

Phase II–Data Collection 

May 2, 2014

Prepared for:

Melanie Ali

Institute of Education Sciences

555 New Jersey Ave, NW

Room 502b

Washington, DC 20208-5500

Submitted by:

Abt Associates Inc.

55 Wheeler Street

Cambridge, MA 02138

In Partnership with:

Belmont Research Associates

The Bench Group

Cornell Survey Research Institute

Dillon-Goodson Research Associates

Education Analytics

Pemberton Research
DRAFT OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Contents ▌pg. i

Part A: Supporting Statement for Paperwork Reduction Act Submission

Table of Contents

A. Justification.............................................................................................................................A-1

Introduction ..............................................................................................................................A-1

A.1 Circumstances Making the Collection of Information Necessary.....................................A-4

A.2 Purposes and Use of the Information Collection ............................................................A-6

A.3 Use of Information Technology and Burden Reduction.................................................A-9

A.4 Efforts to Identify Duplication........................................................................................A-9

A.5 Efforts to Minimize Burden on Small Businesses........................................................A-10

A.6 Consequences of Not Collecting the Information.........................................................A-10

A.7 Special Circumstances Justifying Inconsistencies with Guidelines in 5 CFR 1320.6 ..A-11

A.8 Consultation Outside the Agency .................................................................................A-11

A.8.1 Federal Registrar Announcement................................................................A-11

A.8.2 Consultation Outside the Agency.................................................................A-11

A.8.3 Unresolved Issues.........................................................................................A-11

A.9 Payments or Gifts to Respondents................................................................................A-11

A.10 Assurance of Confidentiality ........................................................................................A-12

A.11 Questions of a Sensitive Nature....................................................................................A-13

A.12 Estimate of Response Burden .......................................................................................A-13

A.13 Estimate of Total Capital and Startup Costs/Operation and Maintenance Costs to 

Respondents or Record-Keepers...................................................................................A-14

A.14 Estimates of Costs to the Federal Government.............................................................A-14

A.15 Changes in Burden........................................................................................................A-14

A.16 Plans for Analysis, Publication and Schedule...............................................................A-15

A.16.1 Analysis Plans ..............................................................................................A-15

A.16.2 Plans for Tabulation and Publication of Results...........................................A-19

A.17 Approval to Not Display Expiration Date ....................................................................A-19

A.18 Exceptions to Item 19 of OMB Form 83-1...................................................................A-19

References..............................................................................................................................A-19
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Abt Associates Inc. Contents ▌pg. ii

Table of Exhibits

Exhibit A-1. Data Collection Plan......................................................................................................A-7

Exhibit A-2. TWG Members and Affiliations..................................................................................A-11

Exhibit A-3. Estimate of Respondent Burden ..................................................................................A-14

Appendices

Appendix 1: District Administrative Records Collection Protocol

Appendix 2: Teacher Survey 
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Abt Associates Inc. Part A: Justification ▌pg. A-1

A. Justification

Introduction

The U.S. Department of Education (ED) is conducting a study examining the relationship between 

teacher preparation experiences and early teacher effectiveness (The Study of Teacher Preparation 

Experiences and Early Teacher Effectiveness, formerly known as The Study of Promising Features of 

Teacher Preparation Programs). This Information Collection Request (ICR) is the second of two ICRs 

for the study. The first ICR (Phase I—Recruitment; OMB-PRA: 1850-0891) requested clearance for 

recruitment activities. This second ICR, Phase II—Data Collection, requests clearance for data 

collection activities (obtaining teacher contact information from districts, collecting data from 

teachers on preparation experiences via an online teacher survey, and obtaining student data from 

districts). The packages have been submitted separately because the process of recruiting districts had 

to begin before the teacher survey was developed and piloted.

1

This study is sponsored by ED’s Institute of Education Sciences (IES) and is being implemented by 

Abt Associates Inc. and its partners: Belmont Research Associates, The Bench Group, Cornell Survey 

Research Institute (SRI), Dillon-Goodson Research Associates, Education Analytics (EA), and 

Pemberton Research (together, the “study team”).

Overview of the Study

Title II, Part A of the Elementary and Secondary Education Act—the Improving Teacher Quality 

State Grants program—focuses on improving teacher quality and increasing the number of highly 

qualified teachers. This study, which is the first of its kind, is about how to improve teacher quality

through more effective preparation of new teachers. It will look at how the nature and intensity of 

preparation experiences are related to teacher effectiveness in promoting student achievement. For the 

purposes of this study, “teacher effectiveness” is defined as teacher value-added (TVA). The study 

will measure TVA using analytic techniques that isolate teacher contributions to student test score

gains. The study has three primary questions:

1) What are the relationships between teacher preparation experiences and teacher effectiveness

in the first year of teaching, measured by teacher value-added? (RQ1)

2) What are the relationships between teacher preparation experiences and teacher effectiveness 

with English learners in the first year of teaching, measured by teacher value-added for 

English learners? (RQ2)

3) Do relationships between teachers’ preparation experiences and teacher effectiveness in the 

first year of teaching differ depending on teachers’ assessments of the usefulness of the 

preparation experiences? (RQ3) 

 

1 At the time of the first ICR, the study design called for an experiment; however, efforts to recruit teacher 

pairs which met the experiment’s requirements were unsuccessful, and therefore a value-added approach is 

now the focus of the study.
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Abt Associates Inc. Part A: Justification ▌pg. A-2

Measuring Preparation Program Experiences 

To answer the research questions, the study needs to identify preparation experiences that could 

reasonably be hypothesized to affect student test scores. The challenge is that little or no research has 

examined relationships between preparation experiences and test scores. (The 2010 National 

Research Council report on teacher preparation highlighted this lack of research.) However, the recent 

Measures of Effective Teaching (MET) Study (Kane & Staiger, 2012) did identify a set of teacher 

practices related to test score gains. The study team used the MET study as a framework for 

identifying preparation experiences that would foster these practices. The survey asks teachers to rate 

the frequency of these experiences in their teacher preparation program.

Specifically, in the MET study, teachers were rated on their instructional practices using four 

different observation systems. This process resulted in each teacher being rated on practices in 32 

domains of instruction. The study team distilled these 32 domains into 12 broad topic areas, which 

form the basis for the teacher survey questions about preparation experiences. This reduction was 

based primarily on data from the MET study on (a) the distribution of teacher ratings on each 

practice, (b) the relationship of teacher ratings on each practice to teacher value-added scores, and (c) 

correlations of the practices across the four measures. For each of the 12 topic areas, the study team 

developed a small set of specific instructional strategies from the coding manuals for the four MET 

measures. The strategies align with teaching behaviors that coders are trained to look for as evidence 

of a teacher’s skill with the measure-specific practices. Finally, the study team conducted cognitive 

interviews with teachers to ensure that the instructional strategies were being interpreted as intended.

The same kind of evidence provided by the MET study to inform the identification of instructional 

practices for the general classroom does not exist for English learner-specific practices. Some 

evidence does exist, however, at the individual strategy level. The study used four research syntheses 

and the 2007 and 2014 IES Practice Guides on instruction for English learners to identify English 

learner-specific instructional strategies that are supported by evidence of improving English learner

achievement (August & Shanahan, 2006; Baker et al., 2014; Calderón, Slavin & Sanchez, 2011; 

Francis, Rivera, Lesaux, Kieffer, & Rivera, 2006; Genesee, Lindholm-Leary, Saunders & Christian, 

2006; Gersten, Baker, Shanahan, Linan-Thompson, Collins & Scarcella, 2007). A set of English 

learner-specific strategies were selected by 1) eliminating redundancies across strategies that were 

identified in multiple reviews, 2) consulting content experts to guide and prioritize the selection of 

strategies, and 3) conducting cognitive interviews with teachers to ensure that the strategies were 

being interpreted as intended. The final set of English learner-specific instructional strategies were 

grouped together into one English learner-specific topic area on the survey.

Sample

An analysis of statistical power indicated that a sample of 6,450 teachers is needed to answer the 

primary research questions with reasonable precision. To meet this sample size, the study aims to 

include as many teachers as possible in recruited districts who teach reading/English language arts 

(ELA) and/or mathematics, the two subject areas consistently tested across states. Because analyses 

will be conducted separately by subject, focusing on elementary-grade teachers increases the 

likelihood that each teacher contributes to both the reading/ELA and mathematics sample, which

reduces the cost of recruiting districts and teachers. Fourth grade is the lower bound for the teacher 

sample due to data availability—proficiency testing typically begins in third grade, which means 

fourth grade is the first grade for which two years of test scores needed to estimate TVA are available 
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-3

(i.e., test scores from grades 3 and 4). The study selected sixth grade as the upper bound because it is 

assumed to be the highest elementary grade.

2

Limiting the study to first-year teachers would minimize issues with recalling preparation 

experiences. However, data on teachers entering the teaching force indicated that meeting the sample 

size requirement would require two years of data collection (i.e., recruiting teachers in 2014-15 and 

again in 2015-16). To limit data collection to one year, the study decided to include teachers in their 

second or third years of teaching for whom TVA in their first year of teaching could be estimated. 

The three-year upper bound is driven by concerns about recalling preparation program experiences 

for teachers who have been teaching for more than three years. 

Teachers in their first through third years will be asked the same questions about their teacher 

preparation experiences. The primary analyses will examine the relationship of teachers’ preparation 

experiences to effectiveness in their first year. For example, a teacher in her second year in 2014-

2015 will be asked about her preparation experiences and those experiences will be related to her 

value-added in the previous year, which corresponds to her first year of teaching.3

The teacher sample will be recruited from a purposive sample of approximately 80 large and 

moderate-sized school districts across the country that can meet the student-teacher data linkage 

requirements for estimating TVA. Targeted districts include the 10 largest districts in the United 

States (based on the expected number of eligible teachers) and other moderate-to-large districts (or 

local education agencies). For the majority of these districts, the study team is currently conducting 

research projects, has existing partnerships, and/or has access to key decision makers. The targeted 

districts are in 33 states and more than 40 percent of them include more than 10 percent English 

learners. Districts will be asked to provide the study team with teacher contact information for 

administering the (online) teacher survey on preparation experiences in spring 2015. The study team 

will also request student data from districts to estimate teacher value-added. The data will include 

student scores on state assessments (reading/ELA and mathematics) and student demographic data. 

Analysis and reporting 

Hierarchical analysis (students nested within classes nested within teachers) will be used to estimate

the relationship between preparation program experiences and student test scores, controlling for 

student, class, teacher, and school baseline covariates. Reading/ELA and Mathematics scores will be 

analyzed separately. For the subset of teachers with five or more English learners, the study will 

examine the relationship between general preparation experiences and the test scores of English 

learners as well as English learner-specific preparation experiences and the test scores of English 

learners. The study team will produce a study report that is expected to be available by fall 2017. 

 

2

In some school districts, some or all of the sixth grade classrooms will be in middle schools. However, data 

from the Common Core indicates that a substantial proportion of sixth grade classrooms will be in elementary 

schools. 

3

If second- or third-year teachers have not taught in an eligible grade or subject in their first year but have in 

their second and/or third year of teaching, they will still be surveyed and included in secondary analyses 

examining the relationship of teacher preparation experiences to teacher effectiveness in the second and/or 

third years of teaching. Only second- or third-year teachers who meet the eligibility criteria in their first year 

of teaching will be included in the sample used to answer the primary research questions.
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Abt Associates Inc. Part A: Justification ▌pg. A-4

Phase II—Data collection request

This ICR seeks clearance to obtain the following data: 

 From school districts:

 Teacher contact information (emails, phone numbers) for first-, second-, and thirdyear teachers in the district in the 2014–15 school year;

 Student data: 

 Reading/ELA and mathematics state assessment data for students in grades 

three to six for four years (2011–12 through 2014–15); 4

 Student demographic data (English learner status, Special Education status,

free/reduced price lunch status, gender, race/ethnicity) for students in each 

year of test data.

 From teachers:

 Data to verify sample eligibility, to determine teacher preparation pathway, to 

measure background characteristics, and to assess the frequency and usefulness of 

preparation experiences.

This ICR provides a detailed discussion of the study data collections and the analysis and reporting of 

the data, as well as an overview of the study, including its design and data collection procedures.

Copies of the data collection instruments (the teacher survey and the District Administrative Records 

Collection Protocol) are included in the appendices.

A.1 Circumstances Making the Collection of Information Necessary

Data from this study will be used to identify promising preparation experiences. These results can 

inform efforts of stakeholders invested in teacher preparation, including national, state, and local 

policy makers; teacher preparation programs and certifying institutions; districts; and schools. Policy 

makers and administrators engaged in teacher preparation and certification can learn about which 

preparation experiences are related to teacher effectiveness. Districts and schools seeking objective 

information to guide teacher hiring and placement decisions also may find the results valuable.

The study will address the goals of the authorizing legislation, Title II, Part A of the Elementary and 

Secondary Education Act, section 2121-2123 as amended by No Child Left Behind (20 USC 6621-

6623), one purpose of which is to “increase student academic achievement through strategies such as 

improving teacher...quality.”5 The study goes beyond current research that examines teacher 

preparation programs as a whole and focuses on relationships between preparation experiences and 

effectiveness. This research is particularly critical in the current educational context, in which more 

 

4

For districts that administer state tests in the fall of each year, data will be obtained for students in grades four 

to seven for SY2012–13 through SY2015–16.

5 Other purposes of Title II are to improve principal quality, increase the number of highly qualified teachers, 

and hold local education agencies accountable for increases in student academic achievement. This study is 

most closely related to improving teacher quality through more effective teacher preparation and training. 
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-5

states are implementing teacher evaluation systems and preparation programs are more likely to be 

held accountable for the effectiveness of their graduates. 

Evidence that teachers have a central role in improving educational outcomes has accumulated for

decades (as noted by Hanushek & Rivkin, 2010 and by Price et al., 2013). Training effective teachers 

is therefore central to improving achievement, but there is scant evidence on how to train teachers

effectively. In 2010, a committee of the National Research Council (NRC) reviewed research on

teacher preparation and found that although an evidence base exists about the characteristics that are

valuable for teachers to have, the evidence did not support conclusions about how preparation

programs can develop these characteristics (NRC 2010). There also is a particular concern about how 

to improve the training of novice teachers because they are more likely to teach disadvantaged

students.6

The fact that effectiveness varies between teachers raises the possibility that teacher preparation 

programs could be part of the explanation. But studies of teacher preparation programs have found

little variation between programs. Furthermore, Price et al. (2013) noted that studies of preparation 

programs overstate the heterogeneity of their effects. Some programs had large or small effects but 

the source was sampling error rather than true differences. After adjusting for sampling error, 

differences were in the range of 0.02 to 0.04 standard deviation units, about one or two percentile 

points on standardized tests.

7 Based on this research and simulations carried out by the study team, a 

reasonable conclusion is that program effects are small.

The approach these studies used to measure effects, which groups novice teachers by their program 

(typically a university or college), may explain why the effects are small. Implicitly, this approach 

assumes that preparation experiences vary only because of the program attended. All teacher 

candidates from one program are assumed to have the average experience of that program. If average

experiences in different programs are similar, the result will be small test score differences, as 

research has found. But the approach conceals variation in experiences that may be occurring within

programs, which observations and discussions with preparation program directors suggest is likely. 

What remains to be investigated is whether specific experiences within programs affect test scores. 

This information would be useful for program design and improvement above and beyond knowing 

that a particular teacher preparation program has teacher-candidates that are (slightly) more effective. 

Effectiveness also could be explained by factors related to a teacher’s selection of their preparation 

program. If this were true, and the study does not try to control for these selection factors, they could 

 

6 The National Center for Education Statistics reports that 17 percent of teachers had less than five years of 

experience in low-poverty schools compared to 21 percent of teachers in high-poverty schools 

(http://nces.ed.gov/pubs2009/2009324.pdf, Table 4). Clotfelter et al. (2006) show a similar differential exists 

in North Carolina schools and that the pattern has been stable over time and between elementary, middle, and 

high schools (http://sanford.duke.edu/research/papers/SAN06-08.pdf). 

7 Only one study (Koedel et al., 2012) adjusted for clustering of students within teachers and estimation error in 

program effect estimates. In this study, when using all teacher preparation programs in the sample (average 

number of teachers per program is 54), the standard deviation of program effects was 0.016 for mathematics 

and 0.019 for Communication Arts. When the analysis was limited to teacher preparation programs with at 

least 50 teachers (average number of teachers per program is 83), the variation of program effects effectively 

was zero. 
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Abt Associates Inc. Part A: Justification ▌pg. A-6

bias the relationships between preparation experiences and teacher value added.

8 The study team 

reviewed research on teacher value-added to assess the potential for selection effects and to identify 

additional data that the study could gather to control for selection factors. In particular, research on 

Teach for America (TFA) identified a small set of characteristics related to value-added—

perseverance, leadership skills, and grade point average (GPA) in the last two years of college

(Dobbie, 2011). The study will collect data on two of these three characteristics—perseverance and 

leadership skills—to help control for selection. Perseverance will be measured using the Grit Scale 

(Duckworth & Quinn, 2009). GPA in the last two years of college will not be included due to 

differences between the study sample and samples used in studies of TFA sample. A large proportion 

of teachers in the study sample will have been in teacher education programs in their final two years 

of undergraduate study. Based on reports from preparation program deans, these students will have 

more homogeneous grade point averages than the general student population from which TFA draws 

candidates. This homogeneity makes GPA a weak predictor of value-added for the study sample.

The study team is aware of no published studies that examine the types of training experiences 

teachers receive in their preparation programs and how variation in these experiences relates to 

differential teacher effectiveness. This study will be the first to provide ED with evidence about the 

relationships between preparation experiences and teacher effectiveness and will make a strong 

contribution toward building an evidence base on this critical issue.

A.2 Purposes and Use of the Information Collection

This ICR requests approval for Phase II—Data Collection. The study will administer an online 

teacher survey that will collect information on 1) eligibility; 2) preparation pathway; 3) background 

characteristics; and 4) teacher reports of the frequency and usefulness of preparation experiences. 

The teacher survey is necessary because information on preparation experiences must be collected 

from teachers directly. Other data for the study—teacher contact information and state assessment 

data—will come from existing district data sources.

All data will be collected by the Abt study team. The schedule, purposes, and uses of the data being 

collected are summarized in Exhibit A-1. Together, the teacher survey and student data will be used 

to estimate the relationships between teachers’ preparation experiences and teacher effectiveness.

 

8 The study team also investigated whether teachers can select preparation experiences. If more or less effective 

teacher candidates select different experiences, a reverse correlation could arise in which effectiveness 

appears to predict experiences. Review of available research and discussions with program directors and 

experts on preparation programs indicated it was unlikely that teacher candidates could select their 

preparation experiences. 
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Abt Associates Inc. Part A: Justification ▌pg. A-7

Exhibit A-1. Data Collection Plan

Schedule Data Collection Respondent Purpose Use

Fall 2014 Teacher contact information 

 Emails and phone numbers

for first-, second- and thirdyear teachers in the district 

in the 2014-15 school year

District Human 

Resources 

Office

 To send teachers 

the survey and 

contact them for 

non-response 

follow-up 

 Contacting 

teachers

Spring 2015 Teacher survey data 

 Years of teaching, grades 

and subjects taught 

 Preparation pathway

 Background characteristics

 Preparation experiences

and usefulness

Teachers  To verify sample 

eligibility9

 To gather data on 

teachers not 

available in 

existing data 

sources

 Eligibility

 Descriptive

 Covariates in 

analysis models

 Independent 

variables in 

analysis models

Fall 2014 and 

Fall 2015

Student data 

 Reading/ELA and 

mathematics state test data

for all students in grades 3–

6 in 2014–15, 2013–14, 

2012–13, and 2011–12 and 

teachers linked to these 

students

 Demographic 

characteristics of students

District 

Testing & 

Accountability 

Office

 To estimate

teacher valueadded in 

teachers’ first 

year of teaching10

 Dependent 

variables in 

analysis models

 Covariates in the 

analysis models

Teacher contact information. The study team will request teacher email addresses and phone 

numbers for all teachers who have been in the district for one, two or three years in fall 2014.

11 (See 

Appendix 1 for the District Administrative Records Collection Protocol, which provides a complete 

list of the teacher data elements that the study team will request from districts.)

Teacher eligibility. The online survey will include questions to confirm that the teacher is eligible to 

be included in the sample to answer the primary or secondary research questions.These questions will 

ask teachers about their year of teaching (in any district) and whether they are or have been 

 

9

 Since districts may only count years of teaching in their district when reporting teachers’ years of experience, 

the survey will ask teachers to confirm that they are in the first, second or third year of their teaching career 

(not limited to their tenure in their current district).

10 These data will also be used to estimate second- and third-year TVA for eligible teachers at no extra cost to 

the study or burden to districts since all four years of data are needed to estimate first-year TVA for first-, 

second- and third-year teachers.

11 The study team will also use student-teacher linkages that are part of the student assessment data requested in 

fall 2014 to further narrow the sample to first-, second-, and third-year teachers who meet the study’s grade 

and subject criteria. This set of teachers will be sent the survey and their eligibility will be confirmed via 

questions at the beginning of the survey.
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Abt Associates Inc. Part A: Justification ▌pg. A-8

responsible for teaching reading/ELA and/or mathematics to at least one classroom of general 

education students in grades 4, 5 or 6 in any of the following school years: 2012-13, 2013-14 or 2014-

15. Only teachers who meet the eligibility criteria for their first year of teaching will be included in 

the sample to answer the primary research questions. (See Appendix 2 for the teacher survey.)

Preparation Pathway. The online survey will be used to collect information about the type of 

preparation program a teacher was/is in (traditional, alternative, TFA), the name of their preparation 

program, where they are in terms of completing their program (e.g., completed, completed/will 

complete at end of first, second or third year of teaching), if they did student teaching, and the 

name(s) of the schools in which they did student teaching, if applicable.

12 These data will be used to 

characterize the sample. In addition, data on the timing of completion of program will be used in 

sensitivity analyses.13 Data on preparation program names will be used to examine the 

generalizability of the sample and to examine between- and within-program variation in preparation 

experiences. 

Teacher background characteristics. The online survey will be used to collect information about 

demographic characteristics (age, gender, race/ethnicity) that will be used to characterize the study 

sample. The survey will also ask about two other teacher characteristics that prior research has shown 

to be related to teacher value-added—perseverance and leadership skills (see Introduction). These 

data will be used to create covariates for use in analysis models.

Preparation experiences. The online survey will collect data on teachers’ preparation experiences

and their assessment of the usefulness of these experiences in their classroom instruction. Teacher 

preparation experiences are defined as the frequency of four types of preparation experiences related 

to 13 topic areas. For each topic area, teachers are asked about experiences related to a small set of 

specific instructional strategies. For each of the instructional strategies, respondents are asked to rate 

the frequency of four types of preparation experiences that teacher candidates might experience as 

part of their teacher preparation program: 

 reading about, hearing about, or seeing a role play of this strategy, such as during 

coursework;

 observing a teacher using this strategy in a K-12 classroom (in videos or during fieldwork or 

student teaching);

 practicing this strategy in a K-12 classroom prior to becoming a full-time teacher; and

 receiving feedback on your use of this strategy, including what you did well or how you 

could improve, from program staff or a cooperating teacher.

 

12 Teach for America and some alternative certification programs (e.g., teacher residency programs) continue to 

provide support to teachers in their second, and sometimes third year in the classroom.

13 Second- and third-year teachers who have not completed their programs at the time of the survey but who will 

be included in the primary analyses because they have first-year TVA will be reporting on preparation 

experiences that are happening after the outcome. The study team expects this to be a small subset of secondand third-year teachers and will conduct sensitivity analyses to determine if excluding these teachers from the 

analyses affects the overall findings. 
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Abt Associates Inc. Part A: Justification ▌pg. A-9

Respondents are also asked to rate how useful their teacher preparation experiences have been for 

their classroom instruction. Data from the frequency items will be used to create measures of 

frequency of preparation experiences for addressing the first and second research questions. Data 

from the usefulness items will be tabulated and used to address the third research question.

Student data. The study team will request reading/ELA and mathematics achievement scores for all 

students in study districts in grades three through six for 2011–12 through 2014–15.

14 Student 

demographic data (English learner status, Special Education status, free/reduced price lunch status, 

gender, race/ethnicity and age) will also be requested. Data for all third through sixth grade students

(including those whose teachers have more than three years of experience) are being requested in 

order to more precisely estimate the models. See Appendix 1 for the District Administrative Records 

Collection Protocol, which specifies the student data elements that the study team will request from 

districts.

A.3 Use of Information Technology and Burden Reduction

The data collection plan reflects sensitivity to issues of efficiency, accuracy, and respondent burden. 

The study will use a combination of mechanical and electronic technology to collect data. For each 

data collection task, the study team has selected the form of technology that enables the collection of 

valid and reliable information in an efficient way while minimizing the burden on district staff and 

teacher respondents. 

During Phase II—Data Collection, districts that agree to participate can provide teacher contact

information and student data to the study team electronically. To minimize burden during data 

collection, a study team member will be assigned as the primary contact for each district and the 

email address and telephone number of this team member will be included on all data requests. The 

study team will accept the teacher contact and student data in whatever file format and structure is 

most convenient for the district and legible for the study team. Because both teacher and student files

contain Personally Identifiable Information (PII), the study team will require that electronic files be

securely transferred by authorized school district staff via Abt’s secure data transfer portal that is 

automatically encrypted. The portal will also allow districts to upload files with minimal effort and 

time. 

The teacher survey will be administered online, allowing teachers to complete the survey easily at a 

time and place most convenient for them. Additionally, online administration can reduce time and 

human error associated with manual data entry because the data will be entered directly by 

respondents and loaded automatically into an electronic data file. The Abt study team will provide a 

dedicated email address and toll-free number for teachers to call for assistance with all aspects of the 

survey.

A.4 Efforts to Identify Duplication

No other large-scale, multi-state study has explored the extent to which teachers’ experiences in their 

preparation programs are associated with effectiveness. Two studies (Boyd et al., 2008; Seidel et al.,

 

14 For districts that administer state tests in the fall of each year, data will be obtained for students in grades four 

through seven for SY2012–13 through SY2015–16.
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Abt Associates Inc. Part A: Justification ▌pg. A-10

2012) link preparation experiences, as measured in surveys; however, both studies are on a smaller 

scale (in a single district (Boyd et al., 2008) or in an individual state (Seidel et al., 2012).

IES has completed several evaluations of alternative pathways to teaching (Constantine et al., 2009; 

Clark et al., 2013), including highly selective alternative routes such as Teach for America and the 

Teaching Fellows Program (Clark et al., 2013). These studies focused on differences between

teachers who select into different preparation pathways, rather than individual experiences teachers 

had in their preparation programs. There have also been studies comparing teachers’ preparation

programs (e.g., Grossman et al., 2008; Boyd et al., 2006). These studies focused on teacher 

preparation program features, but did not examine variation of teachers’ experiences within programs.

The focus of the proposed study on teachers’ preparation experiences, therefore, will provide new 

information not currently available in the field of teacher preparation.

To the extent possible, the study team will use existing data rather than duplicate data collection 

efforts. For example, instead of testing students, the study will use data already collected by districts 

as outcomes. Teacher contact information is also already collected by districts; the study team’s 

request will not require districts to collect any additional data. Data collected in the teacher survey are

not available elsewhere.

A.5 Efforts to Minimize Burden on Small Businesses

The study is purposefully designed to focus on large rather than small districts in order to obtain the 

teacher sample needed in the most efficient manner and to minimize the number of small districts that 

are burdened by this work. 

A.6 Consequences of Not Collecting the Information

The full data collection plan described in this supporting statement is necessary for conducting this 

study, which is consistent with the goals of Elementary and Secondary Education Act, Title II, Part A, 

to raise student achievement through the preparation, training, and recruitment of high-quality 

teachers. There is evidence from multiple research studies that a student’s teacher predicts a 

substantial amount of variation in his or her academic achievement (Chetty et al., 2011, Kane &

Staiger, 2008; Hanushek & Rivkin 201015). And, while research projects such as the MET study have 

helped policy makers and practitioners better understand what good teachers look like in the 

classroom and which instructional strategies and behaviors are linked to teacher effectiveness, the 

field lacks evidence regarding how to produce good teachers. This study will be the first to explore 

this important issue.

The consequences of not collecting specific data in Phase II—Data Collection are described below.

 Should the study fail to collect teacher contact information, it will not be able to administer 

the teacher survey.

 Without collecting teacher survey data, the study team will not be able to measure the 

frequency and usefulness of teachers’ preparation experiences, nor link them to any variation 

in teacher effectiveness.

 

15 See Price et al., 2013 for a review of this research literature on variation in teacher effectiveness.
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-11

 Without collecting the student data, the study team will be unable to generate teacher valueadded scores and link teachers’ preparation experiences to teacher effectiveness.

A.7 Special Circumstances Justifying Inconsistencies with Guidelines in 5 

CFR 1320.6

There are no special circumstances concerning the collection of information in this study.

A.8 Consultation Outside the Agency

A.8.1 Federal Registrar Announcement

This draft is being posted for the purpose of seeking public comments.

A.8.2 Consultation Outside the Agency

The Abt study team assembled a Technical Working Group (TWG) (in consultation with ED) that is 

composed of consultants with various types of expertise in the areas relevant to this study. The TWG

convened in fall 2013 and discussed the study design, recruitment, instrumentation, data collection, 

and analysis and reporting of study findings. Members of the TWG and their affiliation are listed in 

Exhibit A.2.

Exhibit A-2. TWG Members and Affiliations

Name Affiliation

Cory Koedel University of Missouri

David Francis University of Houston 

Mari Koerner Arizona State University

Kata Mihaly RAND Corporation

Steven Rivkin University of Illinois at Chicago 

Suzanne Wilson University of Connecticut 

A.8.3 Unresolved Issues

There are no unresolved issues.

A.9 Payments or Gifts to Respondents

During Phase II—Data Collection, the study team proposes to include a modest incentive of $30 to 

teachers for the completion of the teacher survey, which is estimated to take approximately 35

minutes to complete. All eligible teachers who complete the survey will be sent a $30 Amazon e-gift 

certificate (delivered to them electronically).

The study team has reviewed the research literature on the effectiveness of incentives in increasing 

response rates for surveys. In the Reading First Impact Study commissioned by ED, monetary 

incentives proved to have significant effects on response rates among teachers. A sub-study requested 

by OMB on the effect of incentives on survey response rates for teachers showed significant increases

when an incentive of $15 or $30 was offered to teachers as opposed to no incentive (Gamse et al.,

2008). In another study, Rodgers (2011) offered adult participants $20, $30, or $50 in one wave of a 

longitudinal study and found that offering the highest incentive of $50 showed the greatest 
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-12

improvement in response rates and also had a positive impact on response rates for the next four 

waves.

In 2005, the National Center for Education Evaluation submitted a paper to OMB outlining guidelines 

for incentives for NCEE Evaluation Studies. The teacher survey incentive proposed for the current 

study is consistent with those guidelines, which classified a survey that required 30 minutes of burden 

as “high burden” and recommended a $30 incentive.

A.10 Assurance of Confidentiality

The study team will conduct Phase II–Data Collection activities in accordance with all relevant 

regulations and requirements. These include the Education Sciences Institute Reform Act of 2002, 

Title I, Part E, Section 183, which requires “[all] collection, maintenance, use, and wide 

dissemination of data by the Institute ... to conform with the requirements of section 552 of Title 5, 

United States Code, the confidentiality standards of subsections (c) of this section, and sections 444 

and 445 of the General Education Provisions Act (20 U.S.C. 1232 g, 1232h).” These citations refer to 

the Privacy Act, the Family Education Rights and Privacy Act, and the Protection of Pupil Rights 

Amendment.

In addition, all data collected for the study (Phases I and II) shall remain confidential in accordance 

with Section 552a of Title 5, United States Code, the confidentiality standards subsection (c) and 

sections 444 and 445 of the General Educations Provision Act. Subsection (c) of Section 183, 

referenced above, requires the director of IES to “develop and enforce standards designed to protect 

the confidentiality of persons in the collection, reporting, and publication of data.” The study will also 

adhere to requirements of subsection (d) of Section 183 prohibiting disclosure of individually 

identifiable information as well as making the publishing or inappropriate communication of 

individually identifiable information by employees or staff a felony.

The study team will help maintain the confidentiality of data by requesting that districts provide a 

crosswalk with teacher identification numbers rather than providing student data linked to teacher 

names.

In addition, the following verbatim language will appear on all letters, fact sheets, and other study 

materials:

Per the policies and procedures required by the Education Sciences Reform Act of 2002, Title 

I, Part E, Section 183, responses to this data collection will be used only for statistical 

purposes. The reports prepared for this study will summarize findings across the sample and 

will not associate responses with a specific program, district, or individual. Any willful 

disclosure of such information for nonstatistical purposes, except as required by law, is a 

class E felony.

Data will be presented in aggregate statistical form only. All study staff involved in collecting, 

reviewing, or analyzing individual-level data will be knowledgeable about data security procedures 

and will sign nondisclosure agreements. Respondents will be assured that all information identifying 

them or their school or district will be kept private to the extent allowed by law. The confidentiality 

procedures adopted for this study during all rounds of recruitment, data collection, data processing, 

and analysis consist of the following:
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-13

 All paper files will be converted to an electronic format and the paper files will be shredded 

immediately after they have been converted.

 Electronic data files with sensitive data will be removed from computers and working servers 

in a manner that ensures that the information cannot be recovered.

 At the end of contract with ED, all identifiers will be destroyed.

A.11 Questions of a Sensitive Nature

There are no questions of a sensitive nature included in the information requested in Phase II—Data 

Collection.

A.12 Estimate of Response Burden

The total respondent burden for the data collection effort covered by this clearance request is 5,608

hours, for a total cost to respondents of $187,370. Exhibit A-3 presents time estimates of respondent 

burden for the data collection activities requested for approval in this submission. The burden 

estimates are based on the following assumptions:

 The study team will obtain teacher contact information and student data from 50 district-level 

personnel. The total number of hours for each district is 20 hours. This estimate is based on 

the study team’s prior work with districts in obtaining similar data, as follows:

o Extracting and submitting teacher contact information to the Abt study team will take 

approximately four hours per district.

o Collecting and submitting student data will take 16 hours (8 hours two times during 

the study period).

16

 The total cost to districts is $38,040, based on an hourly wage of $38.04 in May 2012 for 

database administrators.17

 The study team will send surveys to approximately 9,930 fourth- through sixth-grade 

teachers, of which 80 percent, or 7,944 teachers, are expected to complete the online survey. 

The online survey is estimated to take 35 minutes.18

 The total cost to teachers is $149,330, based on an hourly wage of $32.41 in May 2012 for 

elementary and middle school teachers.19

 

16 It would be preferable for districts to provide student data in fall 2014 and again in fall 2015; however, if 

districts are only able to provide student data once during the study period, the study team will work with 

districts to accommodate this schedule.

17 Bureau of Labor Statistics, U.S. Department of Labor, Occupational Employment Statistics, accessed online 

at http://www.bls.gov/oes/current/oes151141.htm (December 23, 2013). 

18 The total number of teachers estimated to complete the survey includes the 6,450 teachers with first-year 

TVA needed to meet sample size requirements for primary analyses plus an additional 1,494 second- and 

third-year teachers who will only have second- and/or third-year TVA and thus be excluded from primary 

analyses but included in secondary analyses (estimates based on data from the Schools and Staffing Survey, 

https://nces.ed.gov/surveys/sass/).
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-14

Exhibit A-3. Estimate of Respondent Burden

Respondent/

Data Collection Activity

# of Respondents

# of Responses

Hours per Response

Total Burden Hours per

Respondent

Total Burden Hours

Hourly Wage per

Respondent

Total Cost per

Respondent

Total Costs

District Staff

Teacher Contact Information 50 1 4 4 200 $38.04 $152.16 $7,608 

Student Data 50 1 16 16 800 $38.04 $608.64 $30,432 

District Subtotal 100 1 20 20 1,000 $76.08 $760.80 $38,040

Teachers (Elementary and Middle)

Teacher Survey 7,944 1 0.58 0.58 4,608 $32.41 $18.80 $149,330 

Total (Districts & Teachers) 8,044 5,608 $187,370 

A.13 Estimate of Total Capital and Startup Costs/Operation and Maintenance 

Costs to Respondents or Record-Keepers

There are no annualized capital, startup, or ongoing operation and maintenance costs involved in 

collecting data in Phase II. 

A.14 Estimates of Costs to the Federal Government

The estimated cost to the federal government of the activities in both Phase I-Recruitment and Phase 

II—Data Collection is $10,454,503. These activities will be carried out over six years (fall 2011 to 

fall 2017). Thus, the average annual cost to the federal government is $1,742,417.

A.15 Changes in Burden

This is an addendum package to a clearance request that was approved in June 2012 to conduct study 

recruitment activities (see OMB Control Number 1850-0891). Completion of the data collection 

activities described in this addendum package requires additional burden totaling 5,608 hours.

 

19 Bureau of Labor Statistics, U.S. Department of Labor, Occupational Employment Statistics, accessed online 

at http://www.bls.gov/oes/current/oes_nat.htm (December 23, 2013). Since some sixth-grade teachers may 

teach in middle schools, the burden estimate uses the hourly rate for elementary and middle school teachers, 

rather than the rate for elementary school teachers only.
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-15

A.16 Plans for Analysis, Publication and Schedule

A.16.1 Analysis Plans

This section presents the study’s estimation approach for addressing the three primary research 

questions.

1. What are the relationships between teacher preparation experiences and teacher 

effectiveness in the first year of teaching, measured by teacher value-added?

To address the first research question, the study team will analyze relationships between teacher 

preparation program experiences (TPPEs) and teacher effectiveness, measured by value-added. 

TPPEs are defined as the frequency of specific types of preparation experiences related to the 

representative instructional strategies within each key instructional topic area. For each topic area, 

four analytic variables representing the four types of preparation experiences will be created: 1) 

opportunities to “read about, hear about, or see a role play of the strategies, such as during 

coursework;” 2) opportunities to “observe a teacher using the strategies in a K-12 classroom (in 

videos or during fieldwork or student teaching);” 3) opportunities to “practice the strategies in a K-12 

classroom prior to becoming a full-time teacher;” and 4) opportunities to “receive feedback on your 

use of the strategies, including what you did well or how you could improve, from program staff or a 

cooperating teacher.” These TPPE measures will be used as explanatory variables in the analytic 

models. 

Overview of Approach

The relationship of TPPEs will be examined separately for reading/ELA and mathematics but the 

analysis approach will be identical. For both outcomes, the study team will combine data from 

different school districts and grade levels to estimate relationships between TPPEs and value-added. 

May et al. (2009) argue that the decision of whether to combine data across grades or states should be 

driven primarily by a study’s research questions. Combining scores across grades or states is 

appropriate when the study’s questions are about student performance on state tests. Combining 

scores is inappropriate when the study’s questions are about attainment of specific skills. Because the 

current study’s primary research questions fall into the first category—relating TPPEs to value-added, 

as measured by student performance on state tests—combining data across states and grades is 

appropriate. 

The study will use a two-stage approach to analyze the relationship between preparation experiences 

and value-added. The first stage will produce TVA scores for each teacher. Each TVA score is a 

measure of the extent to which a teacher’s students experienced achievement growth over a school 

year, adjusting for student characteristics. In this stage, achievement scores will first be standardized 

using state and year means and standard deviations. The study then will fit models using data from 

each unique combination of state, grade, and year, which will yield a set of state/grade/year-specific 

TVA scores. In participating districts, test scores of all students in relevant grades will be used in the 

stage 1 analysis. The use of all student data in the relevant grades will increase the precision of the 

estimated coefficients and resulting TVA score estimates. 

In stage 2, the set of state/grade/year-specific TVA scores will be combined into a single data set. 

Using the combined data set, regression models will be estimated with the TVA score as the 

dependent variable and one or more TPPE measures as independent variables, as well as grade and 
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-16

state dummies, and other statistical controls. Only the TVA scores of teachers who have completed 

the survey on preparation experiences will be used in the second stage analysis. Each of the two 

stages is described in more detail below. 

Analytic Model for Stage 1

The stage 1 analysis will produce a TVA estimate for each teacher. The approach will utilize a 

hierarchical linear modeling (HLM) framework, which is common in education research. The analytic

model is a three-level hierarchical linear model with students (level-1) nested in classes (level-2), and

classes nested in teachers (level-3).

20 The level-1 model has student prior year scores and other

student characteristics as covariates. The level-2 model includes average student measures ‘centered’ 

at the teacher-level mean (the overall mean at the teacher level will be subtracted from the classroom 

mean). The level-3 model includes these covariates aggregated to the teacher-level. In the level-3

model, the dependent variable is the conditional TVA and the level-3 residual is the part of the TVA 

that has not been explained by covariates. The level-3 residuals from the stage 1 analyses are used as 

the dependent variable in the stage 2 analysis. Note that the model does not include dummies (“fixed 

effects”) for schools.21

Specifically, the level-1 model, or student-level model is:

 =  + ∑ 





(-.) + 

The level-2 model or class-level model is:

 =  + ∑ 





(. - .. ) +

The level-3 model or teacher-level model is:

 =  + ∑ 





(..) + ∑ 





() + 

where, in the level-1 model,

is the spring reading/ELA or mathematics achievement test score from i

th student (

i in 1,2,...,n) in the j

th class, ( j in 1,2,..., J), nested in the kth teacher (k in 1,2,...,K

teachers).

 

20 The study assumes that more than half of fifth- and sixth-grade teachers will teach more than one class in a 

single school year.

21 Inclusion of fixed effects for schools limits the analysis sample to teachers from schools where there is more 

than one eligible teacher in the school and where two or more teachers have different values on the TPPE 

measures of interest. This approach could result in a very small analysis sample that would be a poor 

representation of the full sample of teachers that will be surveyed. 

Yijk
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-17

(X –X. ) is the m

th of M student characteristics (e.g., prior year test score, gender, 

race/ethnicity age, English learner status, free/reduced price lunch status),

centered at the class-level mean.

is the student-level error, assumed distributed normal with mean zero and variance

α is the covariate adjusted mean of achievement scores for the j

th class of the kth

teacher.

In the level-2 model,

(X. - X.. ) are the student characteristics aggregated up to class-level means, and centered

around the teacher’s mean.

is the class-level error, assumed distributed normal with mean zero and variance

In the level-3 model,

 is the conditional mean of achievement scores for the k

th teacher (i.e., the

conditional TVA score)

 is the conditional grand mean (predicted mean for teachers when all teacher-level

covariates are zero).

(..) are the means of student characteristics for the k

th teacher, averaged over all of the

classes taught by the k

th teacher.

() are measures of school characteristics (e.g., percent LEP, percent FRPL), and

dummies for district.

 is the teacher-level error, assumed distributed normal with mean zero and variance

As mentioned above, this model will be fit separately for each unique combination of state, grade, and 

school year. The fitted models will produce an estimated TVA “score” (the level-3 residual ) and its 

standard error. 

Analytic Model for Stage 2

In stage 2, a data set will be created that merges teachers’ TPPE measures and their TVA scores from 

stage 1. Regression models will be used to estimate the relationships between TPPEs and TVA 

scores. These models will use the TVA as the dependent variable and TPPE measures, measures of 

ijk e

2

e

ujk

2

u

2

k
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-18

perseverance and leadership (which are collected via the survey to account for selection), and 

indicator variables for state, grade, and teachers’ years of experience at the time of the survey as 

explanatory variables.22 The outcome variable in the model (TVA score) will be weighted inversely 

proportional to the square of the standard error of the TVA score, which means teachers with more 

precisely estimated TVA scores will receive more weight in the estimation.

2. What are the relationships between teacher preparation experiences and effectiveness with 

English learners in the first year of teaching, measured by teacher value-added for English 

learners? 

To address the second research question about relationships of TPPEs to value-added for English 

learners, the models described in the previous section will be fit to subsets of data consisting of 

student outcomes for English learners, and teachers of classes that have a minimum of five English 

learners. Specifically, in the stage 1 models that yield TVA estimates, all of the student-level (level-1) 

outcomes and covariate data will be specific to only English learner students. For the class-level 

(level-2) and teacher-level (level-3) covariates that represent aggregates of student characteristics, the 

data from all students (both English learners and non-English learners) will be aggregated such that 

these measures will represent the characteristics of all of the students in a teacher’s class or classes. 

These models will yield state, grade, and year-specific TVA estimates that pertain to only English 

learners. Only teachers with at least five English learners and their English learner-specific TVA 

estimates will be used in the stage 2 models. Measures of TPPEs will include general measures (i.e., 

the same measures as will be assessed in the primary research question) and TPPEs that are English 

learner-specific. 

3. Do relationships between teachers’ preparation experiences and effectiveness in the first 

year of teaching differ depending on teacher assessments of the usefulness of the 

experiences? 

In addition to rating the frequency of specific types of preparation experiences related to key 

instructional topic areas, teachers are also asked on the survey to rate the usefulness of their TPPEs. 

To answer this research question, descriptive data will be tabulated from the usefulness items to 

describe teachers’ perceptions of the usefulness of TPPEs for first, second and third year teachers 

separately, and for all teachers combined. The stage 2 analytic models described above will also be 

estimated, but in each model, the TPPE measure of interest will be replaced with a dichotomous 

variable for usefulness: 1 = useful (if TPPE is rated as useful or very useful), 0 = not useful (if TPPE 

rated as not useful or a little useful). The coefficient for the usefulness variable will represent the 

relationship between the perceived usefulness of a TPPE and TVA. That is, it will address the

question of whether TPPEs that are rated as useful are more strongly associated with teacher 

effectiveness than TPPEs that are rated as not useful.

A secondary research question about the usefulness of TPPEs is whether teachers’ assessment of the 

usefulness of their experiences changes over time. A descriptive analysis will compare the 

 

22 Some teachers may have multiple TVA records. If there are more than a negligible number of teachers with 

multiple records, the model will be fit as a two-level hierarchical model with repeated observations at level-1 

and teachers at level-2.
OMB Supporting Statement Study of Promising Features of Teacher Preparation Programs

Abt Associates Inc. Part A: Justification ▌pg. A-19

proportions of teachers who describe a TPPE as useful among the first-, second-, and third-year 

teacher samples.

A.16.2 Plans for Tabulation and Publication of Results

The Abt study team will disseminate the results of the Study of Teacher Preparation Experiences and 

Early Teacher Effectiveness in a single report expected to be released by fall 2017. 

The report will include a description of the study design and findings from all three primary research 

questions. More specifically, the report will include:

 Descriptive analyses of the characteristics of the study sample;

 Analyses of the relationships between preparation experiences and teachers’ effectiveness in 

their first year of teaching (RQ1);

 Analyses of the relationships between preparation experiences and teachers’ effectiveness 

with English learners in their first year of teaching for the subset of teachers with five or more 

English learners in their first-year classroom (RQ2); and 

 Analyses of whether the relationships between preparation experiences and teachers’ 

effectiveness in their first year of teaching differ depending on teachers’ evaluations of the 

usefulness of the preparation experiences in instruction (RQ3).

These analyses will be carried out using hierarchical linear modeling to take into account nesting 

(e.g., the nesting of students and classes within teachers) and will incorporate student covariates to 

maximize precision. 

A.17 Approval to Not Display Expiration Date

No exemption is requested. The data collection instruments will display the expiration date. 

A.18 Exceptions to Item 19 of OMB Form 83-1

The submission describing data collection requires no exemptions to the Certificate for Paperwork 

Reduction Act (5 CFR 1320.9).

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