Head Start Performance Measures Center 

Family and Child Experiences Survey 

(FACES 2000) 

Technical Report

February 2006 
Head Start Performance Measures Center 

Family and Child Experiences Survey (FACES 2000) 

Technical Report 

February 2006 

Prepared for: Maria Woolverton 

Office of Planning, Research and Evaluation 

Administration for Children and Families 

U.S. Department of Health and Human Services 

Washington, DC 

Prepared by: 

Westat: Nicholas Zill, Gary Resnick, Kwang Kim, Kevin 

O’Donnell, Alberto Sorongon, Yair Ziv, Souma Alva 

Xtria: Ruth Hubbell McKey, Shefali Pai-Samant, Cheryl Clark 

The CDM Group, Inc: Robert O'Brien, Mary Ann D'Elio 

This report was prepared for the Administration for Children and Families, U.S. Department of Health 

and Human Services (DHHS) under contract HHS-105-96-1912, Head Start Quality Research

Consortium's Performance Measures Center. 

 
TABLE OF CONTENTS

Chapter Page

EXECUTIVE SUMMARY .................................................................................................. E-1 

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

1 DEMOGRAPHIC CHARACTERISTICS OF HEAD START 

CHILDREN AND THEIR FAMILIES ........................................................... 1-1 

2 COGNITIVE GAINS MADE BY HEAD START CHILDREN AND 

THEIR ACHIEVEMENT IN KINDERGARTEN .......................................... 2-1 

2.1 Research Questions............................................................................. 2-1 

2.1.1 Composition of the Child Assessment ................................ 2-2 

2.2 Findings .............................................................................................. 2-3 

2.2.1 Emergent Literacy and Mathematics Skills of Head Start 

Children Compared with those of the General Population 

of Preschoolers.................................................................... 2-3 

2.2.1.1 Majority Entered Head Start with Academic 

Skills Below National Norms.............................. 2-3 

2.2.1.2 Diversity in Skills at Program Entry.................... 2-4 

2.2.2 Change in Knowledge and Skills Over the Head Start Year 2-4 

2.2.2.1 Gains in Vocabulary Knowledge and Writing 

Skills.................................................................... 2-5 

2.2.2.2 Gains in Book Knowledge, Color Naming, 

Design Copying, One-to-One Counting, and 

Social Awareness................................................. 2-7 

2.2.2.3 Greater Gains for those Who Entered with 

Lower Skills......................................................... 2-7 

2.2.3 Emergent Literacy Gains of Language-Minority Children . 2-8 

2.2.3.1 Knowing the Meaning of English Words............ 2-9 

2.2.3.2 Identifying Letters in English.............................. 2-10 

2.2.3.3 Changes in English Language Skills Versus 

Changes in Spanish Skills ................................... 2-10 

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FACES 2000 Technical Report iii March 06 
TABLE OF CONTENTS (CONTINUED) 

Chapter Page

2.2.4 Growth of Knowledge and Skills in Kindergarten.............. 2-11 

2.2.5 Differences in Gains in Knowledge and Skills Between 

Children Who Attend One Year of Head Start Versus 

those Who Attend for Two Years ....................................... 2-12 

2.2.5.1 Children Who Attend Head Start for Two Years 

Show Greater Entry to Graduation Gains than 

those Who Attend for One Year.......................... 2-12 

2.3 Conclusions......................................................................................... 2-14 

3 CHANGES IN SOCIAL COMPETENCE THROUGH THE HEAD START 

 YEARS ............................................................................................................ 3-1 

3.1 Research Questions............................................................................. 3-1 

3.2 Measures............................................................................................. 3-2 

3.2.1 Teacher Report.................................................................... 3-2 

3.2.1.1 Cooperative Classroom Behavior of Head Start 

Children ............................................................... 3-2 

3.2.1.2 Problem Behavior of Head Start Children........... 3-2 

3.2.2 Parent Report....................................................................... 3-3 

3.2.2.1 Social Skills and Approaches to Learning........... 3-3 

3.2.2.2 Behavior Problems .............................................. 3-3 

3.3 Findings .............................................................................................. 3-4 

3.3.1 Do Children Show Significant Gains in Cooperative 

Classroom Behavior and Social Skills and Significant 

Declines in Problem Behavior During the Head Start

Years?.................................................................................. 3-4 

3.3.2 Do Children Graduating from Head Start Programs After 

Two Years Show More Cooperative Classroom Behavior 

and Social Skills and Less Problem Behavior than 

Children Who had One Year of Head Start?....................... 3-5 

3.3.3 How do Gains Vary Across Behavior Areas Among 

Children Who Enter the Program with Different Levels 

of Cooperative Classroom Behavior, Social Skills, and Problem

Behavior? ............................................................................ 3-6 

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FACES 2000 Technical Report iv March 06 
TABLE OF CONTENTS (CONTINUED) 

Chapter Page

3.4 Conclusions......................................................................................... 3-7 

4 CURRICULUM, FAMILY, PROGRAM, AND CLASSROOM

 CHARACTERISTICS..................................................................................... 4-1 

4.1 Research Questions............................................................................. 4-1 

4.2 Methods .............................................................................................. 4-2 

4.3 Findings .............................................................................................. 4-2 

4.3.1 Head Start Teachers Report Using a Specific Curriculum,

Receiving Training, and Having Access to their Curriculum 4-2 

4.3.1.1 Types of Curricula............................................... 4-2 

4.3.1.2 Curricular Training and Support.......................... 4-3 

4.3.1.3 Teacher Access to Curricula................................ 4-3 

4.3.1.4 Teacher Satisfaction with Curricula .................... 4-3 

4.3.2 Relationship Between Curricula and Family, Program, 

and Classroom Characteristics............................................ 4-4 

4.3.2.1 Relationship Between Curricula and Family

Characteristics ..................................................... 4-4 

4.3.2.2 Relationship Between Curricula and Program

Characteristics ..................................................... 4-4 

4.3.2.3 Relationship Between Curricula and Classroom

Quality ................................................................. 4-5 

4.3.2.4 Other Curricula and Classroom Quality .............. 4-7 

4.4 Summary of Findings.......................................................................... 4-8 

5 QUALITY IN HEAD START CLASSROOMS ............................................. 5-1 

5.1 Conceptual Framework and Research Questions ............................... 5-1 

5.2 Analytic Methods................................................................................ 5-4 

5.3 Findings .............................................................................................. 5-9 

5.3.1 What is the Quality of Head Start Classrooms in 

2000-2001, and How Does it Compare to the Quality 

Reported in 1997-1998?...................................................... 5-9 

5.3.2 What are the Backgrounds, Qualifications and 

Experiences of Head Start Teachers in 2000-2001 and Were 

There any Changes from the Earlier Cohort (1997-1998)?. 5-15 

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FACES 2000 Technical Report v March 06 
TABLE OF CONTENTS (CONTINUED) 

Chapter Page

5.3.3 How are Teaching Qualifications and Experience Related 

to Attitudes and Knowledge of Early Childhood Education 

and How are these Factors Linked to Quality in Head Start 

Classrooms? ........................................................................ 5-22 

5.3.4 Do Factors Beyond the Classroom, Such as the Types of 

Curricula Head Start Programs Provide, the Average

Teacher Salaries, and Characteristics of Families Served 

by the Head Start Program Explain Variations in the

Quality of Head Start Classrooms? ..................................... 5-26 

5.4 Summary and Conclusions ................................................................. 5-37 

6 RELATIONSHIP OF PROGRAM, CLASSROOM, AND CHILD AND 

FAMILY CHARACTERISTICS TO CHILDREN'S COGNITIVE GAINS 

IN HEAD START ........................................................................................... 6-1 

6-1 Conceptual Framework....................................................................... 6-2 

6.2 Research Questions............................................................................. 6-4 

6.3 Analysis Method................................................................................. 6-5 

6.4 Findings .............................................................................................. 6-7 

6.4.1 Use of an Integrated Curriculum......................................... 6-26 

6.4.2 Higher Teacher Salary Levels............................................. 6-27 

6.4.3 Teachers with Bachelor’s or Associate’s Degrees or 

Higher.................................................................................. 6-28 

6.4.4 Full-Day Versus Part-Day Classes...................................... 6-28 

6.4.5 More Frequent Parental Reading to Children ..................... 6-29 

6.4.6 Attending Head Start for More than One Year ................... 6-31 

6.5 Child: Staff Ratio, More Individual Attention, and Teacher’s

Positive Attitudes and Knowledge About Early Childhood 

Educational Practices.......................................................................... 6-33 

6.6 Child: Staff Ratio and More Individual Attention .............................. 6-33 

6.7 Teacher’s Positive Attitudes and Knowledge About Early

Childhood Educational Practices........................................................ 6-35 

6.8 Summary and Discussion.................................................................... 6-35 

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FACES 2000 Technical Report vi March 06 
TABLE OF CONTENTS (CONTINUED) 

Chapter Page

7 RELATIONSHIP OF PROGRAM, CLASSROOM, AND CHILD AND 

FAMILY CHARACTERISTICS TO CHILDREN'S SOCIAL BEHAVIOR 

IN HEAD START ........................................................................................... 7-1 

7.1 Conceptual Framework and Research Questions ............................... 7-1 

7.2 Analysis Method................................................................................. 7-2 

7.3 Findings .............................................................................................. 7-3 

7.3.1 Are Head Start Program Characteristics Predictive of 

Children’s Social Behaviors? .............................................. 7-3 

7.3.2 Are Head Start Classroom Characteristics Predictive of 

Children’s Social Behaviors? .............................................. 7-5 

7.3.3 Are Child and Family Characteristics Predictive of 

Children’s Social Behavior?................................................ 7-8 

7.3.4 Do Head Start Program and Classroom Characteristics 

Explain Children’s Social Development Over and Above

Child and Family Characteristics? ...................................... 7-23 

7.4 Summary and Conclusions ................................................................. 7-25 

8 HEAD START CHILDREN WITH DISABILITIES: SOCIAL-EMOTIONAL

AND COGNITIVE DEVELOPMENTAL OUTCOMES ............................... 8-1 

8.1 Introduction......................................................................................... 8-1 

8.2 Methodology....................................................................................... 8-1 

8.3 Findings .............................................................................................. 8-3 

8.4 Conclusion .......................................................................................... 8-9 

8.5 Discussion........................................................................................... 8-9 

9 FAMILY STRUCTURE AND FAMILY CHANGES .................................... 9-1 

9.1 Introduction......................................................................................... 9-1 

9.2 The FACES 2000-2003 Longitudinal Sample.................................... 9-2 

9.2.1 Mothers’ Characteristics ..................................................... 9-4 

9.2.2 Family and Household Characteristics................................ 9-5 

9.2.3 Mothers’ Health and Wellbeing .......................................... 9-6 

9.3 Mothers’ Characteristics and Children’s Cognitive Outcomes........... 9-7 

9.4 Summary and Conclusions ................................................................. 9-12 

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FACES 2000 Technical Report vii March 06 
TABLE OF CONTENTS (CONTINUED) 

Chapter Page

10 FAMILY RISK FACTORS, PARENTAL INVOLVEMENT, AND 

HEAD START’S PROTECTIVE ROLE ........................................................ 10-1 

10.1 Research Questions............................................................................. 10-1 

10.2 Findings .............................................................................................. 10-1 

10.2.1 Prevalence of Family and Parental Risk Factors and 

their Relationship to Children’s Outcomes......................... 10-2 

10.2.2 Family Involvement and its Relationship to School 

Readiness ............................................................................ 10-14 

10.2.3 Head Start’s Protective Role for Families and Children ..... 10-20 

10.3 Summary............................................................................................. 10-23 

11 PREDICTIVE VALIDITY OF COGNITIVE AND BEHAVIORAL 

MEASURES: RELATIONSHIPS WITHIN AND ACROSS COGNITIVE 

AND SOCIAL DEVELOPMENTAL DOMAINS.......................................... 11-1 

11-1 Research Questions............................................................................. 11-1 

11-2 Findings .............................................................................................. 11-2 

11.2.1 Children’s Scores on the FACES Instruments at the End 

of Head Start Predict Kindergarten Outcomes.................... 11-2 

11.2.2 FACES Behavioral Ratings at the End of Head Start 

Predict Children’s Social Competence in Kindergarten...... 11-6 

11.2.3 Behavior Ratings at the End of Head Start Predict Reading 

Skills and General Knowledge at the End of Kindergarten 11-12 

11.2.4 Head Start Fall-to-Spring Gain Scores from the FACES 

Battery Predict Kindergarten Outcomes ............................. 11-16 

11.2.5 Head Start Fall-to-Spring Change Scores from the Behavior 

Ratings Predict Social Competence in Kindergarten .......... 11-17 

11.2.6 Head Start Fall-to-Spring Change Scores from the Behavior 

Ratings Predict Reading Skills and General Knowledge at 

the End of Kindergarten ...................................................... 11-19

11.2.7 Children’s Scores on the FACES Instruments and Behavior 

Ratings at the End of Head Start Predict Promotion to 

First Grade........................................................................... 11-21 

11.3 Conclusions......................................................................................... 11-23 

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FACES 2000 Technical Report viii March 06 
TABLE OF CONTENTS (CONTINUED) 

Chapter Page

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

List of Appendices 

Appendix

A METHODOLOGY .......................................................................................... A-1 

List of Tables 

1-1 Demographic characteristics of Head Start children and families – 

 Fall 2000 .......................................................................................................... 1-2 

1-2 Demographic characteristics of Head Start children and families by years of 

enrollment in Head Start program – Fall 2000 ................................................ 1-4 

2-1 Fall 2000 mean scores (SD) for FACES assessment measures on entry into 

 Head Start ........................................................................................................ 2-4 

2-2 Mean scores (SD) for FACES measures from Fall 2000, Spring 2001, and 

 Fall-Spring difference ...................................................................................... 2-6 

2-3 Fall 2000 – Spring 2001 mean gain scores (SD) for FACES assessment 

 measures........................................................................................................... 2-8 

2-4 Fall 2000, Spring 2001, and Fall-to-Spring gain vocabulary scores for 

language-minority, language-majority, and combined groups of children ...... 2-9 

2-5 Fall 2000, Spring 2001, and Fall-to-Spring gain letter-word identification 

scores for language-minority, language-majority, and combined groups of 

 children ............................................................................................................ 2-10 

2-6 Vocabulary skills in English and Spanish of Head Start children from 

 Spanish-speaking language-minority families................................................. 2-11 

2-7 Letter-word identification skills in English and Spanish of Head Start 

children from Spanish-speaking language-minority families.......................... 2-11 

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FACES 2000 Technical Report ix March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

2-8 Norm-referenced scores at end of Head Start and end of kindergarten and 

Head Start-to-kindergarten gain scores............................................................ 2-12 

2-9 Child assessment “entry-graduation” means (SD) for Fall, Spring and 

Fall-Spring gain scores for one-year Head Start graduates and two-year 

Head Start graduates........................................................................................ 2-13 

3-1 Means and standard deviations of social competence scores at Head Start 

entry and graduation ........................................................................................ 3-4 

3-2 Means and standard deviations of social competence scores at Head Start 

graduation as a function of length of Head Start participation (1 vs. 2 years). 3-5 

3-3 Mean scores of children in quartiles representing most and least desirable 

social competence scores at the beginning and end of Head Start participation 3-6 

3-4 Means and standard deviations of social competence gain scores (from entry

to graduation) of children scoring in the most and least desirable quartiles.... 3-7 

4-1 The majority of teachers used either Creative Curriculum or High/Scope...... 4-3 

4-2 Teachers liked their respective curricula for a variety of reasons.................... 4-4 

4-3 Most teachers from the northeast, midwest, and west used Creative Curriculum

or High/Scope, while majority of teachers from the south used other curricula 

 ......................................................................................................................... 4-5 

4-4 The majority of urban teachers used either Creative Curriculum or High/Scope 

while the majority of rural teachers used Creative Curriculum....................... 4-5 

4-5 The classrooms of teachers who used Creative Curriculum or High/Scope had 

significantly higher average ECERS-R total scores and ECERS-R language 

scores than classrooms of teachers who used other curricula.......................... 4-6 

4-6 The classrooms of teachers who used Creative Curriculum or High/Scope had 

significantly higher quality composite scores than classrooms using other 

 curricula ........................................................................................................... 4-6 

4-7 Type of curricula and classroom quality scores............................................... 4-7 

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FACES 2000 Technical Report x March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

5-1 Comparison of ECERS/ECERS-R categorical scores, Fall 1997, Fall 2000 

and Spring 2001, percent of classrooms.......................................................... 5-11 

5-2 Comparison of lead teacher backgrounds, FACES Fall 1997 through 

 Spring 2002...................................................................................................... 5-16 

5-3 Comparison of teacher experiences and qualifications, Fall 2000 through 

 Spring 2002...................................................................................................... 5-17 

5-4 Teacher attitudes and knowledge correlated with teacher backgrounds and 

 qualifications, Fall 2000 (N=257).................................................................... 5-22 

5-5 Correlation of teacher backgrounds, qualifications and experience with 

classroom quality, Fall 2000 (N=257). ............................................................ 5-24 

5-6 Teacher attitudes and knowledge correlated with classroom quality indicators, 

Fall 2000 (N=257) ........................................................................................... 5-25 

5-7 Multi-level model predicting ECERS-R mean score from teacher factors, 

controlling for program-level effects (N=265), Fall 2000 ............................... 5-29 

5-8 Multi-level model predicting ECERS-R language scale scores from teacher 

factors, controlling for program-level effects (N=265), Fall 2000 .................. 5-30 

5-9 Multi-level model predicting assessment profile individualizing scores from

teacher factors, controlling for program-level effects (N=265), Fall 2000...... 5-31 

5-10 Multi-level model predicting Arnett caregiver interaction scale scores from

teacher factors, controlling for program-level effects (N=265), Fall 2000...... 5-33 

5-11 Multi-level model predicting quality factor score from teacher factors, 

controlling for program-level effects (N=265), Fall 2000 ............................... 5-34 

5-12 Multi-level model predicting child-adult ratio from teacher factors,

controlling for program-level effects (N=265), Fall 2000 ............................... 5-35 

5-13 Summary of program- and classroom-level factors predicting classroom

 quality, Fall 2000 ............................................................................................. 5-36 

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FACES 2000 Technical Report xi March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

6-1 Percentage of variance accounted for by the child-level model and the 

combined model with program-, classroom-, and child-level factors, and 

the difference in the proportions...................................................................... 6-8 

6-2 Three-level regression models of PPVT-III Vocabulary scale scores of Head 

Start children upon Head Start entry, Head Start graduation, and scale score 

gains from entry to graduation......................................................................... 6-9 

6-3 Three-level regression models of WJR Letter-Word ID scale scores of Head 

Start children upon Head Start entry, Head Start graduation, and scale score 

gains from entry to graduation......................................................................... 6-11 

6-4 Three-level regression models of WJR Applied Problems scale scores of 

Head Start children upon Head Start entry, Head Start graduation, and scale 

score gains from entry to graduation ............................................................... 6-13 

6-5 Three-level regression models of WJR Dictation scale scores of Head Start 

children upon Head Start entry, Head Start graduation, and scale score gains 

 from entry to graduation .................................................................................. 6-15 

6-6 Three-level regression models of Book Knowledge scores of Head Start 

children upon Head Start entry, Head Start graduation, and scale score gains 

 from entry to graduation .................................................................................. 6-17 

6-7 Three-level regression models of Color Naming scores of Head Start children 

upon Head Start entry, Head Start graduation, and scale score gains from entry

 to graduation .................................................................................................... 6-19 

6-8 Three-level regression models of Design Copying scores of Head Start children 

upon Head Start entry, Head Start graduation, and scale score gains from entry

 to graduation .................................................................................................... 6-21 

6-9 Three-level regression models of One-to-One Counting scores of Head Start 

children upon Head Start entry, Head Start graduation, and scale score gains 

 from entry to graduation .................................................................................. 6-23 

6-10 Three-level regression models of Social Awareness scores of Head Start 

children upon Head Start entry, Head Start graduation, and scale score gains 

 from entry to graduation .................................................................................. 6-25 

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FACES 2000 Technical Report xii March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

7-1 Independent and dependent variables used in the analyses ............................. 7-4 

7-2 Three-level regression models of parent-reported Withdrawn Behavior 

scores in Head Start entry, graduation, and entry-graduation gains ................ 7-6 

7-3 Three-level regression models of teacher-reported Social Skills scores in 

Head Start entry, graduation, and entry-graduation gains ............................... 7-7 

7-4 Three-level regression models of teacher-reported Aggressive Behavior 

scores in Head Start entry, graduation, and entry-graduation gains ................ 7-10 

7-5 Three-level regression models of teacher-reported Hyperactive Behavior 

scores in Head Start entry, graduation, and entry-graduation gains ................ 7-12 

7-6 Three-level regression models of teacher-reported Withdrawn Behavior 

scores in Head Start entry, graduation, and entry-graduation gains ................ 7-14 

7-7 Three-level regression models of parent-reported Social Skills scores in 

Head Start entry, graduation, and entry-graduation gains ............................... 7-16 

7-8 Three-level regression models of parent-reported Aggressive Behavior 

scores in Head Start entry, graduation, and entry-graduation gains ................ 7-18 

7-9 Three-level regression models of parent-reported Hyperactive Behavior 

scores in Head Start entry, graduation, and entry-graduation gains ................ 7-20 

7-10 Variance accounted by program-, classroom-, and child- and family-level 

models in social behavior outcomes................................................................ 7-22 

7-11 Variance accounted by the combined program- and classroom-level model 

in social behavior outcomes............................................................................. 7-23 

7-12 Variance accounted by child- and family-level models and the addition 

program- and class-level models to the combined models.............................. 7-24 

8-1 Disability categories for children with disabilities (Spring 2001)................... 8-3 

8-2 Characteristics of children with disabilities and their families........................ 8-4 

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FACES 2000 Technical Report xiii March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

8-3 Characteristics of the families of children with disabilities and the families 

of children without disabilities (Fall 2000)...................................................... 8-5 

8-4 Parent- and teacher-reported social-emotional outcomes for both children 

with disabilities and children without disabilities (Fall 2000) 

 [bivariate results] ............................................................................................. 8-5 

8-5 Cognitive developmental outcomes for both children with disabilities 

and children without disabilities (Fall 2000) [bivariate results] ...................... 8-6 

8-6 Parent- and teacher-reported social-emotional outcomes for both children 

with disabilities and children without disabilities (Fall 2000) 

 [multivariate results]........................................................................................ 8-7 

8-7 Cognitive developmental outcomes for both children with disabilities 

and children without disabilities (Fall 2000) [multivariate results]................. 8-7 

8-8 Parent- and teacher-reported social-emotional outcomes for both children 

with disabilities and children without disabilities (Fall 2000 – Spring 2001) 

 [multivariate results]........................................................................................ 8-8 

8-9 Cognitive developmental outcomes for both children with disabilities 

and children without disabilities (Fall 2000 – Spring 2001) 

 [multivariate results]........................................................................................ 8-8 

9-1 Changes in mother’s and other family characteristics of children in the Head 

Start program at various time points: FACES 2000-2003 ............................... 9-3 

9-2 Changes in health and wellbeing of mothers of children in the Head Start 

program at various time points: FACES 2000-2003........................................ 9-6 

9-3 Means and standard deviations of children’s cognitive outcomes in 

Spring 2002 in relation to selected mother’s characteristics 

(Fall 2000-Spring 2002)................................................................................... 9-9 

9-4 Relationship between longitudinal change in mothers’ marital status and 

various cognitive outcomes in Spring 2002: FACES 2000 

(Fall 2000-Spring 2002)................................................................................... 9-10 

9-5 Relationship between longitudinal change in family structure and various 

cognitive outcomes in Spring 2002: FACES 2000 (Fall 2000-Spring 2002) .. 9-11 

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FACES 2000 Technical Report xiv March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

10-1 Significant group differences between moderately or severely depressed 

parents and mildly or not at all depressed parents on selected family

 factors .............................................................................................................. 10-3 

10-2 Significant partial correlations between parental depression and child 

behavior and cognitive outcomes..................................................................... 10-4 

10-3 Significant adjusted odds ratios and 95 percent confidence intervals for 

parental depression, exposure to violence, domestic violence, alcohol use, 

and involvement with the criminal justice system........................................... 10-5 

10-4 Significant group differences between parents who did and did not screen 

positive for domestic violence on parental depression and child behavior...... 10-8 

10-5 Significant group differences between families with involvement in the 

criminal justice system and families with no involvement in the criminal 

justice system on child behavior and cognitive outcomes............................... 10-11 

10-6 Significant group differences between families with fewer than four risks 

and families with four or more risks on child behavior, child cognitive 

outcomes, and parent variables........................................................................ 10-13 

10-7 Significant partial correlations between family activities with the child and 

child behavior and cognitive outcomes............................................................ 10-15 

10-8 Significant partial correlations between family activities with parent 

 outcomes.......................................................................................................... 10-16 

10-9 Significant partial correlations between parenting style and child and 

 parent outcomes............................................................................................... 10-16 

10-10 Significant partial correlations between parental involvement at Head Start 

and child behavior and child cognitive outcomes............................................ 10-19 

10-11 Significant Head Start moderators of negative outcomes associated with 

 risk factors........................................................................................................ 10-21 

11-1 Pearson’s product moment correlation coefficients between FACES

assessment scores at end of Head Start and Reading and General Knowledge 

scale scores at end of kindergarten .................................................................. 11-3 

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FACES 2000 Technical Report xv March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

11-2 Summary of multiple linear regression analysis for FACES assessment 

scores at end of Head Start predicting Reading and General Knowledge scale 

scores at end of kindergarten ........................................................................... 11-3 

11-3 Summary of multiple linear regression analysis for norm reference FACES 

assessment scores at end of Head Start predicting Reading and General 

Knowledge scale scores at end of kindergarten............................................... 11-5 

11-4 Summary of multiple linear regression analysis for criterion reference 

FACES assessment scores at end of Head Start predicting Reading and 

General Knowledge scale scores at end of kindergarten ................................. 11-6 

11-5 Summary of hierarchical regression analysis for FACES assessment 

scores at end of Head Start predicting Reading and General Knowledge scale 

scores at end of kindergarten ........................................................................... 11-7 

11-6 Pearson’s product moment correlation coefficients between FACES

behavior ratings at end of Head Start and teacher ratings of cooperative 

classroom behavior and total problem behaviors at end of kindergarten......... 11-8 

11-7 Summary of multiple linear regression analysis for FACES behavior 

ratings at end of Head Start predicting teacher ratings of cooperative 

classroom behavior and total problem behaviors at end of kindergarten......... 11-9 

11-8 Summary of multiple linear regression analysis for FACES teacher ratings 

at end of Head Start predicting teacher ratings of cooperative classroom

behavior and total problem behaviors at end of kindergarten.......................... 11-10 

11-9 Summary of multiple linear regression analysis for FACES parent ratings 

at end of Head Start predicting teacher ratings of cooperative classroom

behavior and total problem behaviors at end of kindergarten.......................... 11-11 

11-10 Summary of hierarchical regression analysis for FACES behavior 

ratings at end of Head Start predicting teacher ratings of cooperative 

classroom behavior and total problem behaviors at end of kindergarten......... 11-12 

11-11 Pearson’s product moment correlation coefficients between FACES

behavior ratings at end of Head Start and Reading and General Knowledge 

scale scores at end of kindergarten .................................................................. 11-13 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report xvi March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

11-12 Summary of multiple linear regression analysis for FACES behavior 

ratings at end of Head Start predicting Reading and General Knowledge scale 

scores at end of kindergarten ........................................................................... 11-14 

11-13 Summary of hierarchical regression analysis for FACES behavior 

ratings at end of Head Start predicting Reading and General Knowledge scale 

scores at end of kindergarten ........................................................................... 11-15 

11-14 Pearson’s product moment correlation coefficients between FACES

assessment gain scores during Head Start and Reading and General

Knowledge scale scores at end of kindergarten............................................... 11-17 

11-15 Summary of multiple linear regression analysis for FACES gain scores 

during Head Start predicting Reading and General Knowledge scale scores at 

end of kindergarten .......................................................................................... 11-18 

11-16 Pearson’s product moment correlation coefficients between FACES behavior 

ratings gain scores at end of Head Start and teacher ratings of cooperative 

classroom behavior and total problem behaviors at end of kindergarten......... 11-19 

11-17 Summary of multiple linear regression analysis for FACES behavior rating 

gain scores at end of Head Start predicting teacher ratings of cooperative 

classroom behavior and total problem behaviors at end of kindergarten......... 11-20 

11-18 Pearson’s product moment correlation coefficients between FACES

behavior ratings gain scores during Head Start and Reading and General 

Knowledge scale scores at end of kindergarten............................................... 11-20 

11-19 Summary of multiple linear regression analysis for FACES behavior rating 

gain scores during Head Start predicting Reading and General Knowledge 

scale scores at end of kindergarten .................................................................. 11-21 

11-20 Summary of multiple logistic regression analysis for FACES assessment 

scores at end of Head Start predicting teacher decision to have child repeat 

 kindergarten .................................................................................................... 11-22 

11-21 Summary of multiple logistic regression analysis for teacher behavior ratings 

and parent behavior ratings at end of Head Start predicting teacher decision to 

have child repeat kindergarten ........................................................................ 11-23 

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FACES 2000 Technical Report xvii March 06 
TABLE OF CONTENTS (CONTINUED) 

List of Tables (Continued) 

Table Page

11-22 Summary of multiple logistic regression analysis for FACES assessment 

scores, teacher behavior ratings, and parent behavior ratings at end of Head 

Start predicting teacher decision to have child repeat kindergarten ............... 11-24 

List of Figures

Figure

1 Head Start program performance measures conceptual framework ................ 7 

2 FACES 2000 study design............................................................................... 10 

5-1 A conceptual model of program- and classroom-level factors explaining 

quality in Head Start ........................................................................................ 5-2 

5-2 Classroom quality in Head Start compared with other preschool and child 

 care settings...................................................................................................... 5-10 

6-1 Analytical model of multi-level factors predicting classroom quality and 

children’s achievement and gains in the Head Start year ................................ 6-3 

10-1 The prevalence of depression among Head Start parents in Fall 2000............ 10-3 

10-2 The frequency of parents’ exposure to crime in their neighborhoods and their 

 homes............................................................................................................... 10-6 

10-3 The frequency of substance use in the home ................................................... 10-9 

10-4 The frequency of family participation in Head Start activities........................ 10-18 

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FACES 2000 Technical Report xviii March 06 
EXECUTIVE SUMMARY 

In 1997, Head Start launched the Family and Child Experiences Survey (FACES), a study 

with a nationally representative sample of Head Start programs to describe the characteristics, 

experiences, and outcomes for children and families served by Head Start. It also explores the

relationships among family and program characteristics and outcomes. In 1997, the FACES design 

included a nationally representative sample of 3,200 3- and 4-year old children and their families in 40 

programs. The FACES 2000 sample includes 2,800 children and their families in 43 different Head Start

programs across the nation. 

Each cohort of FACES employs a nationally stratified sample of Head Start programs, 

centers, classrooms, children, and parents. FACES 2000 features four phases of data collection and

follows 3- and 4-year-old children from program entry, through one or two years of program experience, 

with followup in the Spring of kindergarten. The FACES 2000 battery has four main components: the 

direct child assessment, parent interview, teacher and staff interviews, and classroom observations.

Although there is no non-Head Start comparison group in FACES, the use of assessment measures with

national norms permits comparisons between the skills of children in the sample and children of the same

ages in the norming samples. 

ES.1 Study Findings 

FACES provides information about the knowledge and skills that children have when they

enter the Head Start program and the gains they make during the Head Start year and the first year of 

elementary school. It also describes the quality of Head Start classrooms, and factors that help explain 

variations in quality across Head Start classrooms. In addition, FACES 2000 data provide insight into the

relationship of program and classroom characteristics to children’s outcomes, as well as the relationship 

of family and parental characteristics to children’s outcomes. 

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FACES 2000 Technical Report E-1 March 06 
ES.2 Who is Head Start Serving? 

 According to data from FACES 2000, Head Start is serving a diverse population of

children. Slightly more than one-third (35 percent) of Head Start children were White 

followed closely by African American (32 percent) and Hispanic (28 percent). The

majority of children (62 percent) were four and five years of age and 38 percent of the 

children were three years of age. Slightly more than two-fifths (41 percent) of the

families were located in the southern region of the country and the vast majority of the 

families (70 percent) were situated in urban/suburban areas. 

 Head Start families face numerous risks and challenges that are related to children’s

well being. Parents (mother or father) of Head Start children had a high school

diploma or GED (41 percent), had a vocational/technical diploma or an Associate’s 

degree (30 percent), or had a Bachelor’s degree or higher (6 percent). Parents 

reported working on a full-time basis (39 percent) or on a part-time basis (14 percent),

and 34 percent of parents were not in the labor force. 

 The majority of Head Start families reported monthly family incomes of either $500 

to $999 (27 percent) or $1,000 to $1,499 (25 percent). Nearly one-half (48 percent) of 

the children resided in dual-parent families whereas more than one-half (52 percent) 

of children resided in other family arrangements. One-half (50 percent) of the Head

Start families were comprised of 4 to 5 persons. 

ES.3 Head Start Children’s Cognitive and Social-Emotional Outcomes 

 Cognitive assessment data from FACES 2000 showed that most children entered Head 

Start with early literacy and math skills well below national averages. However, there 

was considerable diversity in skill levels among Head Start children. At Head Start 

entry, the highest quarter of Head Start children were at or above the national average 

(50th percentile) in early language and number skills, while the lowest quarter of 

children ranked in the lowest 2 percent of all U.S. preschoolers in these areas. 

 Children made gains toward national averages during the Head Start year, especially 

with respect to vocabulary knowledge and early writing skills. Children who entered 

the program with lower levels of knowledge and skill showed larger gains during the

program year, yet still lagged considerably behind national averages. Children who 

started with higher assessment scores in the Fall wound up with higher scores in the 

Spring, but did not show the same level of gains as those with lower baseline scores. 

 Language-minority children in Head Start showed significant gains in English

vocabulary skills without declines in their Spanish vocabulary skills. They did not 

gain in letter recognition skills. 

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FACES 2000 Technical Report E-2 March 06 
 Children who graduated after two years of Head Start made greater gains from entry 

to graduation than those who spent only one year in Head Start. Typically, children 

who graduate Head Start after 2 years enter with lower skills than one-year graduates.

However, by the time both groups leave Head Start, they achieve similar levels of 

performance.

 Head Start graduates also showed further progress toward national averages during

kindergarten. Gains of between one-quarter to more than three-quarters of a standard 

deviation were observed in vocabulary, early math, and early writing skills during 

kindergarten. Most Head Start graduates could identify the letters of the alphabet by 

the end of kindergarten and more than half could recognize beginning sounds of 

words. Further, Head Start graduates achieved early writing scores near the national 

norm by the end of kindergarten. Nevertheless, Head Start graduates remained behind 

their more advantaged peers in vocabulary and early math. 

 FACES 2000 findings indicate that teachers reported significant positive changes on 

measures of social competence from Head Start entry to graduation. 

 The findings also indicate that children who spent 2 years in Head Start were reported 

by teachers to display higher levels of cooperative classroom behavior and social

skills and less hyperactive behavior at the end of Head Start compared to children who 

spent only 1 year in Head Start. 

 Children entering Head Start with the lowest levels of social skills, and those who 

entered Head Start with the highest levels of problem behaviors, gained the most 

during their participation in Head Start. Although these children did not close the gap

between themselves and other children, they did narrow it significantly.

 At the beginning of the Head Start year children’s disability status was highly 

associated with both social-emotional and cognitive developmental outcomes. On

average, children with disabilities did not perform as well as other children on all

baseline social-emotional and cognitive outcomes with the exception of book

knowledge. White children were more likely than African American children to have 

a diagnosed disability, and boys were more likely than girls to have a disability,

consistent with findings from other studies. Speech and language impairments 

constituted the largest group within the disabilities categorization. 

 In addition, children with disabilities did not progress as well as other children on 

more than half (9 of 16) of the cognitive and social-emotional outcomes, including 

parent- and teacher-reported hyperactivity, withdrawn behavior, total problem 

behaviors, early math skills, perceptual–motor skills, and book knowledge. There 

were no statistically significant differences on the remaining seven outcomes between

the two groups. 

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FACES 2000 Technical Report E-3 March 06 
ES.4 Head Start Program’s Use of Curricula 

 Findings from FACES 2000 indicate that the great majority of Head Start programs 

use a curriculum, with the goal of providing a planned, developmentally appropriate 

early childhood program for children. Most teachers reported using a single 

curriculum. The most frequently used curricula are the Creative Curriculum 

(39.1 percent) and High/Scope curriculum (20 percent). Further, 93 percent of 

teachers reported receiving training in their curriculum, and 92 percent reported

receiving ongoing support. 

 Data from FACES 2000 also indicate a relationship between program characteristics 

and the type of curriculum used. Specifically, classrooms using a curriculum other 

than the Creative Curriculum or High/Scope curriculum served the poorest Head Start 

families and the highest percentage of non-White children. There was also regional 

variation in curricula used by classrooms. More teachers from the Northeast (78.7 

percent), Midwest (59.4 percent), and West (69.4 percent) used either the Creative 

Curriculum or High/Scope curriculum compared to any other type of curricula, while 

the majority of teachers from the South (54.4 percent) used a curriculum other than 

the Creative Curriculum or High/Scope curriculum.

 Findings also demonstrate a relationship between type of curriculum and classroom

quality. Classrooms using Creative Curriculum or High/Scope had significantly higher 

scores on three measures of classroom quality (the Early Childhood Environment

Rating Scales-Revised—ECERS-R—Total score, ECERS-R Language subscale score,

and a Quality Composite score) than classrooms using curricula categorized as

“Other.” Analyses were also conducted separating the “Other” curricula category into 

Widely Available Curricula and All Other Curricula. Classrooms using Creative 

Curriculum, High/Scope curriculum, and Widely Available Curricula had similar 

average ECERS-R Total scores and ECERS-R Language subscale scores, with 

classrooms using All Other Curricula receiving lower average scores on these 

instruments. However, on the Quality Composite measure, classrooms using Creative 

Curriculum or High/Scope had similar scores, with classrooms using either Widely 

Available Curricula or All Other Curricula receiving lower marks. Multivariate 

analyses also showed significant differences between classrooms using Creative

Curriculum or High/Scope compared to All Other Curricula on all three classroom 

quality scores. 

ES.5 Quality in Head Start Classrooms 

 Head Start classrooms continue to show good levels of quality, based on the indicators 

of quality measured in FACES 2000 in the Fall 2000, Spring 2001, and Spring 2002. 

These levels of quality are consistent from FACES 1997, and the consistency is 

evident across a wide variety of the indicators, including child:adult ratio, teacherchild interactions, and classroom activities and materials. In fact, FACES shows that

Head Start has a better, more limited range of quality than that seen in child care 

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FACES 2000 Technical Report E-4 March 06 
centers and preschools in several other national studies, with few Head Start 

classrooms scoring below minimal quality. 

 Head Start teachers are qualified and experienced (although as a group they do not 

have the same level of credentials as public school teachers), and there appear to be

substantially more teachers with higher educational attainment in this cohort

compared with the 1997 FACES cohort. Head Start teachers in 2000 are younger, 

compared with those in 1997-1998, and more of them have been teaching in 

Head Start for two years or less. These newer teachers are also the ones most likely to 

have a graduate school degree. 

 Classrooms with higher levels of quality are those whose teachers have higher levels 

of education, experience, and knowledge and attitudes of early childhood education

practices. The relationship between teacher education and classroom quality is

explained by teacher’s attitudes and knowledge of early childhood education 

practices. Teachers who are more educated have more positive attitudes and 

knowledge, which translates into higher levels of classroom quality. 

 Programs using one of the two most widely used integrated early childhood curricula 

(i.e., High/Scope and Creative Curriculum) also have teachers with positive attitudes

and knowledge about early childhood education practice. Both of these factors appear

to have the strongest effect on teacher sensitivity and responsiveness compared with 

other indicators of quality.

 Multilevel analyses suggest that variations in the quality of Head Start classrooms 

may be explained by characteristics of the families and children they serve, by the

curriculum used in the program, and by teacher attitudes and knowledge about early 

childhood education practice. The results suggest that Head Start classroom quality 

may be affected by factors beyond the classroom door that are characteristics of the 

program and the families who participate. 

ES.6 Relationship of Program and Classroom Characteristics to Children’s Outcomes 

 Program- and classroom-level variables provided unique and significant contributions

to the prediction of children’s assessment scores at Head Start entry and graduation, as

well as gains from entry to graduation. Analysis of data from FACES 2000 showed

that children’s cognitive gains in Head Start were significantly related to use of the 

High/Scope, higher teacher salaries, teachers' educational credentials (Bachelor's

degrees or Associate’s degrees or higher), and provision of preschool services for a 

longer period each day.

 For each cognitive measure, children who attended Head Start for two years showed 

greater graduation scores and greater entry to graduation gains compared to their peers

who attended Head Start for only one year. 

 Surprisingly, within the narrow range of child:staff ratios in Head Start, higher

child:staff ratios were associated with greater entry-graduation achievement gains in 

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FACES 2000 Technical Report E-5 March 06 
some of the cognitive outcomes. Further, teachers’ scores on a scale assessing their 

knowledge of early childhood education practices were negatively linked with 

children’s cognitive outcomes. 

 The strongest predictors of children’s social behaviors were predictors at the child and 

family level, mainly the child’s age, gender, disability status, and number of years 

spent in Head Start, as well as the presence of both biological or adoptive parents in

the house and the existence of books in the home. Most child and family 

characteristics had stronger links with the social behavior variables than program or 

classroom characteristics. 

 The program- and especially the classroom-level characteristics showed relatively low

power to predict children’s social behaviors. Nonetheless, the addition of the program 

and classroom levels to the child- and family-level set of characteristics did result in 

higher explanatory power of the combined model over and above the child- and 

family-level model by itself. This addition was significantly higher in almost half of 

the variables examined. Thus, the inclusion of program- and classroom-level sets of

variables in the combined models increased the models’ overall fit to the data. This

finding supports the expectation that the Head Start experience may serve to 

compensate for child and family disadvantages. 

 Differences in cognitive gains between programs and classrooms possessing certain 

quality indicators (such as the use of High/Scope, higher teacher salaries, teachers

with Bachelor's or Associate's degrees or higher, and provision of preschool services 

for a longer period each day) and programs and classrooms without those features, 

while statistically significant, were relatively modest in magnitude. By itself, each of

the differences was not large enough to close the gap between where Head Start 

children typically end up at the end of the program year and the average achievement

levels of American children at the start of elementary school. 

 The ECERS-R Language subscale was not associated with greater gains on any of the

cognitive measures. The failure to find significant links between children’s cognitive 

gains in Head Start and class-level scores on the ECERS-R Language subscale may

have to do with the generally good quality of Head Start classrooms and the limited

range of variation in classroom quality that FACES found in its national samples of 

programs and classes. Studies encompassing broader ranges of quality of childcare 

and early education facilities have shown greater variations in classroom quality 

measures and significant relationships between quality measures and children’s gains. 

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FACES 2000 Technical Report E-6 March 06 
ES.7 Changes in Head Start Families Over Time

 Data from FACES 2000 indicate that the condition of Head Start children’s families 

and especially their mothers has generally remained the same or marginally improved

as children move from Head Start to kindergarten. Although not all mothers reside in

the household of their children, the percentage remains consistently over 90 percent. 

A high percentage of mothers are also single, never married mothers. Over 40 percent

of households have only the mother (and no father) residing in the child’s household. 

 The longitudinal analysis shows evidence of an improvement in the socioeconomic 

status of households over the years. The data show that a greater percentage of 

households report higher levels of monthly income in Spring 2002 and Spring 2003.

Moreover, a smaller percentage of households remains in poverty or depends on

welfare as children move through the Head Start program and on to kindergarten.

 Examining the relationship between these mothers’ and household characteristics and

children’s cognitive outcomes using the FACES 2000 data shows that a change in the

family situation represented in terms of a change in mothers’ marital status or 

coresidence with parents bears little relationship to children’s cognitive outcomes. 

Instead, household characteristics such as parents’ education and household poverty

status are more important. While greater parents’ education results in better cognitive

outcomes, the poor household economic situation is associated with lower assessment 

scores. 

ES.8 Relationship of Family and Parental Characteristics to Children’s Outcomes 

 One-quarter of the parents were classified as moderately or severely depressed.

Parents who were more depressed reported that their children had more problem 

behaviors and fewer positive social behaviors, a finding supported by the teachers’

reports of children’s behavior. Their children also had lower scores on one-to-one 

counting, creativity, design copying, early writing, letter identification, and early math

assessments. 

 More than one-fifth of the parents reported they had witnessed violent crime.

Five percent reported being victims of violent crime in the neighborhood, while a 

similar percentage reported being victims of violence in their homes. Almost 

10 percent of the children were reported to have witnessed domestic violence during 

the previous year. Less than 2 percent of the children were reported to have been 

victims of violent crime or victims of domestic violence. Positive correlations were 

found between increased exposure to neighborhood violence and reports of child 

problem behavior, while children in more violent neighborhoods had lower 

assessment scores on the color naming and book knowledge assessments. 

 Almost 13 percent of the parents indicated that they have been victims of domestic

violence. Teachers and parents reported children in these families had more overall 

problem behaviors. 

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FACES 2000 Technical Report E-7 March 06 
 Almost one-half of the Head Start children lived in households with at least one

individual who smoked cigarettes and about two-fifths of the households reported 

having at least one individual who drank alcohol. Living in a household with someone 

who drinks increased the risk of parental depression, while the children in these

homes were reported to have more overall problem behavior and scored lower on 

vocabulary, color naming, and social awareness assessments. 

 Almost one-fifth of the parents reported that someone in their household had been 

arrested and charged with a crime. Children in these families were more than 3 times 

more likely to have been a witness to violent crime or domestic violence in the past 

year. These children were also 3 times more likely to have been a victim of domestic

violence or violent crime. These children had lower vocabulary scores, and were

reported by both parents and teachers to be more aggressive and have more overall 

problem behaviors. 

 At least one of a set of selected risk factors was evident in over 90 percent of the

families. Nearly one-quarter of the families had four or more risk factors. Children in 

the families with four or more risk factors had lower parent ratings on emergent

literacy and higher teacher and parent ratings of problem behavior. In the assessments,

these children scored lower on design copying, color naming, one-to-one counting, 

book knowledge, vocabulary, early math, early writing, and letter identification.

 Analyses of child-level data show that Head Start children whose parents read to them

more often show greater gains and graduation scores on some measures. 

 Families engaged their children in a number of weekly and monthly activities. The 

number of activities was positively correlated with positive child behaviors and

emergent literacy and negatively correlated with problem behaviors. In particular, the 

weekly activities had positive correlations with scores on the social awareness, color 

naming, one-to-one counting, book knowledge, vocabulary, early math, early writing, 

and letter identification tasks. 

 Higher authoritative parenting style scores were significantly positively correlated 

with children’s social awareness, but not with any of the other cognitive measures. On 

the other hand, higher authoritarian scores were significantly negatively correlated

with comprehension, color naming, vocabulary, and early math assessments. 

 More than two-thirds of parents had attended parent-teacher conferences, observed in 

their children’s classrooms for at least 30 minutes, or met with a Head Start staff

member in their homes. Parent involvement in Head Start was positively correlated 

with parental reports of positive social behavior and higher emergent literacy skills 

and negatively correlated with aggressive and overall problem behavior. Children

whose parents were more involved in Head Start scored higher on vocabulary, book

knowledge, early writing, early math, and letter identification tasks. 

 Parent involvement at Head Start, parent reports that they and their children had

positive experiences at Head Start, or parent satisfaction with the program

significantly moderated relationships between risk factors (e.g., parental depression, 

exposure to violence and domestic violence, substance use, and involvement with the 

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FACES 2000 Technical Report E-8 March 06 
criminal justice system) and many negative child behavior and lower cognitive 

outcomes. These findings suggest that Head Start may play an important role in 

protecting families and children from the challenges that low-income families face. 

ES.9 Predictive Validity of the FACES Cognitive and Behavioral Measures 

 The FACES measures have strong predictive validity with outcomes at the end of 

kindergarten. As an indicator of early literacy skills, the cognitive measures show 

strong associations with reading ability at the end of the kindergarten year. As an

indicator of school adjustment and social competence, the behavior ratings 

demonstrate ability to predict kindergarten behaviors that promote learning. The

instruments used in FACES also predict whether a child gets promoted to first grade. 

 The instruments used in FACES may tap different types of abilities (“inside-out” or 

decoding skills vs. “outside-in” or comprehension skills) that are important for 

children’s future reading proficiency and academic achievement.

 In the assessment of children’s social competencies, the use of parent and teacher

ratings provides data on children’s behavior skills in different situations and provides

a comprehensive picture of their behavior. Equally important, both parent and teacher 

ratings significantly contribute to the prediction of social skills at the end of 

kindergarten. The parent and teacher ratings also significantly predict reading skills

and general knowledge at the end of kindergarten. Ratings of problem behaviors were 

negatively correlated with kindergarten Reading and General Knowledge scale scores,

suggesting that behaviors that may impede learning are associated with lower reading 

skills in kindergarten. High ratings of behaviors that enhance learning, positive

approaches to learning and cooperative classroom behavior were positively correlated

with kindergarten outcomes. 

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FACES 2000 Technical Report E-9 March 06 
INTRODUCTION 

HEAD START FACES 2000 TECHNICAL REPORT 

In 1997, as part of the Head Start Program Performance Measures Initiative, the Head Start

Bureau launched the Family and Child Experiences Survey (FACES), a study with a nationally

representative sample of 3,200 children and their families, to describe the characteristics, experiences, and

outcomes for children and families served by Head Start. FACES also observed the relationship among 

family and program characteristics and outcomes. In the Fall of 2000, Head Start began data collection on

a new national cohort of FACES, called FACES 2000. The FACES 2000 sample included 2,800 children 

and their families in 43 different Head Start programs across the nation. 

FACES complements other Head Start data in many ways. It provides Head Start with the

capacity to report on important aspects of outcomes and quality and practices beyond aggregated

administrative data. FACES provides the ability for Head Start to examine all facets of key outcomes and 

children’s school readiness on an ongoing basis. Prior to FACES, Head Start had no national data on child 

or family outcomes. 

This introductory chapter provides a brief review of the research literature on early

intervention programs and the link between program quality and children’s outcomes. In addition, it

discusses the history, conceptual framework, and terminology of the Head Start Program Performance

Measures Initiative, of which FACES is an integral component. The chapter also describes the research 

design of FACES, and closes with an overview of the report. 

Research Context: Brief Review of the Effectiveness and Quality of Early Intervention 

Programs 

A broad base of research exists demonstrating the effectiveness of high-quality, intensive 

early childhood education programs for improving children's cognitive and social outcomes. For example, 

the most influential studies demonstrating the positive effects of early childhood education for children 

living in poverty comprised the Consortium for Longitudinal Studies, including Ira Gordon's Parent 

Education Program, Francis Palmer's Harlem Training Project, and the High/Scope Perry Preschool

Project, among others (Consortium for Longitudinal Studies, 1983; Lazar and Darlington, 1982). Across 

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FACES 2000 Technical Report 1 March 06 
these studies, the children showed large positive immediate benefits from the programs and even years 

later, children who had attended preschool were less likely to have failed a grade in school or to have

been assigned to special education classes. 

Other program evaluations also indicate that high quality early interventions enhance

children’s cognitive and language development. For example, children participating in the Abecedarian

Project had significantly better outcomes in reading achievement and grade retention rates than children

in control groups (Seitz, 1990). Children participating in the Infant Health and Development Project also 

had enhanced cognitive and language development (IHDP, 1990). Recently, a national evaluation of the 

Early Head Start program (Administration for Children and Families, 2002) showed a consistent pattern 

of modest yet significant favorable impacts across a range of child and parent outcomes when children 

were 2- and 3-years-old, with larger impacts in several subgroups. Specifically, positive effects were 

found in the areas of children’s cognitive, language, and social-emotional development. 

Other early intervention research highlights that attaining positive outcomes for children can 

be elusive, particularly for programs that do not directly focus services on children. For example, an

evaluation of the Comprehensive Child Development Program (CCDP), a program designed to help lowincome families with children from birth to age 5 attain self-sufficiency and enhance child outcomes,

showed that CCDP did not produce any important positive effects on families (St. Pierre, Layzer, 

Goodson, and Bernstein, 1997). Similarly, an evaluation of the New Chance Demonstration, a twogeneration program designed to assist low-income young mothers achieve self-sufficiency and enhance 

the development of their children, found that the children’s preschool readiness scores did not improve 

(Quint, Bos, and Polit, 1997). 

Research on the Effectiveness of Head Start 

While these evaluated programs share many common features with Head Start, such as the

population served, goals, and program strategies, little large-scale research on Head Start’s quality or

outcomes of participating children and families has been conducted. However, numerous smaller scale 

studies have examined questions of Head Start’s efficacy. In 1985, the Administration on Children, Youth 

and Families published the final report of the Head Start Evaluation, Synthesis and Utilization Project 

(McKey, Condelli, Ganson, Barrett, McConkey, and Plantz, 1985). This synthesis provides the most

comprehensive assessment of Head Start’s effectiveness, reporting the results of a meta-analysis of over 

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FACES 2000 Technical Report 2 March 06 
75 Head Start research studies. Overall, the analysis showed that Head Start produced immediate, 

meaningful gains in all areas of cognitive development, as well as in social behavior, achievement

motivation, and health status. However, the cognitive and socio-emotional gains of Head Start children

appeared to fade over time. 

In addition, a study using data from the National Longitudinal Survey of Youth (NLSY) 

from 1979 through 1992 compared the outcomes of Head Start children to those of siblings who did not 

attend Head Start but either attended another type of preschool or did not attend preschool. The study 

found large and significant gains in receptive vocabulary for both the White and African American

children attending Head Start over their siblings, as well as gains for Hispanic children (Currie and 

Thomas, 1995; Currie and Thomas, 1999). However, the gains of African American children faded by

age 8. For White children, the effects of Head Start were greater than the effects of other preschool

programs. Children who attended Head Start also had better health outcomes as measured by 

immunization status and height-for-age (Currie and Thomas, 1995). A second study using a subsample of

children from the National Educational Longitudinal Survey who had attended Head Start explored 

possible reasons that the gains of African American children faded more quickly than those of White 

children. The results indicated that African American eighth grade students who had attended Head Start 

were enrolled in schools of significantly lower quality than African American students who did not attend 

Head Start. However, little difference was found in the quality of schools between White children who 

did and did not attend Head Start (Currie and Thomas, 1998). 

Unfortunately, the data used in these studies is dated. To provide current information on 

Head Start’s quality and effectiveness, the Administration for Children and Families (ACF) has 

undertaken the national Head Start Impact Study, a longitudinal study that involves approximately 5,000

3- and 4-year-old preschool children across an estimated 75 nationally representative grantee/delegate 

agencies in communities where there were more eligible children and families than could be served by the 

program. Data collection for this randomized study began in Fall 2002. The study’s goals were to answer 

two important questions: How does Head Start affect the school readiness of children participating in the 

program as compared to children not enrolled in Head Start? Secondly, under which conditions does Head

Start work best and for which children? More information about the Head Start Impact Study can be 

found at http://www.acf.hhs.gov/programs/opre/hs/impact_study/index.html. 

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FACES 2000 Technical Report 3 March 06 
The Link Between Program Quality and Outcomes for Children and Families 

Research in the early childhood education field has pointed to the necessity of high-quality

programming to achieve both short- and long-term positive results (Lazar and Darlington, 1982; Weikart 

and Schweinhart, 1991). While the success of programs such as the Perry Preschool Project and the

Abecedarian Project is impressive, the intensity and duration of such programs are difficult and expensive

to implement on a wide scale. Indeed, a review of the research found that “the general level of child care 

quality available to millions of young children is one that many experts consider to be inadequate,

mediocre, and perhaps even detrimental to children’s well-being. Furthermore, children from low 

socioeconomic status families under stress are more likely to receive lower-quality out-of-home care”

(Love, Schochet, and Meckstroth, 1996, p. 12). 

In light of such findings, researchers have continued to study the aspects of high-quality 

programs that lead to positive outcomes in a cost-effective manner. For example, Bryant, Burchinal, Lau,

and Sparling (1994) found that Head Start classroom ratings on the Early Childhood Environment Rating 

Scale (ECERS) significantly predicted children's cognitive skills and school readiness. In addition, 

analyses from the NICHD Study of Early Child Care indicated that the overall quality of child care, and 

language stimulation in particular, were consistently, but modestly related to cognitive and language 

outcomes at ages 15, 24, and 36 months (NICHD Early Child Care Research Network, 2000).

Furthermore, in the Cost, Quality, and Child Outcomes in Child Care Centers study, researchers from 

Colorado, California, North Carolina, and Connecticut found that children in higher quality classrooms

had more advanced pre-mathematical skills than those in lower-rated classrooms (Cost, Quality and Child 

Outcomes Study Team, 1995). This study also found that staff:child ratios were the most significant 

determinant of center quality and that children at risk of not doing well in school were more sensitive to

the negative effects of poor quality child care and received more benefits from high quality child care. 

Center quality also increased as the percentage of center staff with a high level of education increased,

and with an increase in the center administrator's prior experience.

Another study, using a measure of classroom quality based on the National Association for 

the Education of Young Children's (NAEYC) Guidelines for Developmentally Appropriate Practice and 

the High/Scope curriculum, reported that children from classrooms with high quality scores scored 

significantly higher on a battery of cognitive skills in first grade (Frede, Austin, and Lindauer, 1993). 

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FACES 2000 Technical Report 4 March 06 
Howes, Phillips, and Whitebook (1992) reported that children in classrooms with better

teacher: child ratios were more likely than children in classrooms with worse ratios to experience both 

appropriate caregiving and developmentally appropriate classroom activities. Children in classrooms 

rated higher on "appropriate caregiving" were more likely to be classified as secure, according to the

Waters and Deane Attachment Q-Set. Similarly, children who attended preschool classrooms with 18 or 

fewer children were more likely than children in classrooms not meeting these standards to experience

developmentally appropriate activities. These findings support earlier results by Ruopp, Travers, Glantz,

and Coelen (1979), who demonstrated that smaller group sizes were consistently associated with better

care and more socially active children. Additionally, children in classrooms where caregivers exhibited 

high levels of social interaction made greater gains in receptive language abilities. 

The existing research base documenting the potential benefits of high-quality early

intervention programs for low-income preschoolers, coupled with the dearth of recent national research

on Head Start, made it critical for the Head Start Bureau to conduct a study of the program’s quality and 

outcomes, particularly as the program underwent rapid expansion and entered an era of increased program

accountability. 

The Head Start Program Performance Measures Initiative 

FACES was launched as a key component of the Head Start Program Performance Measures 

Initiative. In 1995, Head Start embarked on an initiative to design and implement an outcome-oriented

accountability system. This initiative combines the best attributes of scientific research with programlevel reporting and monitoring and is based on a consensus-driven set of criteria for program 

accountability. 

The Head Start Program Performance Measures Initiative is a response to a specific 

legislative mandate, strategic planning for Head Start, and broader public emphasis on accountability and 

the general movement toward results-oriented evaluation. Specifically, the Program Performance

Measures were developed in accordance with the recommendations of the Advisory Committee on Head 

Start Quality and Expansion, the mandate of Section 641A (b) of the Head Start Act (42 USC 9831 et 

seq.) as reauthorized in 1994, and the Government Performance and Results Act (GPRA)(Public Law 

103-62). 

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FACES 2000 Technical Report 5 March 06 
The Head Start Act defines Program Performance Measures as “methods and procedures for 

measuring, annually and over longer periods, the quality and effectiveness of programs operated by Head

Start agencies” that will be used to identify strengths and weaknesses in the Head Start program—both

nationally and by region—and pinpoint areas requiring additional training and technical assistance. 

In 1995, Head Start undertook a consensus-building process to develop the Head Start 

Program Performance Measures that drew on the opinions of Head Start program staff and parents; early

childhood organization representatives; researchers; experts in the education, child development, and 

early intervention fields; and Head Start Bureau officials (Administration on Children, Youth and 

Families, 1995). In 1996 it began the FACES study, with data collection commencing in 1997. In 2000, 

Head Start collected data on the second cohort of FACES (FACES 2000). 

 Conceptual Framework 

The conceptual framework for the Program Performance Measures Initiative unifies and

organizes the Measures to display the linkages between process and outcome measures for Head Start

children and families.1

 (See Figure 1 for the graphical representation of the framework.) The framework 

is based on the ultimate goal of Head Start, which is to promote the school readiness of children. 

Head Start has adopted the “whole child” view of school readiness that was recommended 

by the Goal One Technical Planning Group of the National Education Goals Panel (Goal One Technical 

Planning Group, 1991, 1993). This view sees school readiness as a multifaceted phenomenon comprising

five developmental domains that are important to the child’s readiness for school: physical well-being and 

motor development, social and emotional development, approaches to learning, language usage and

emerging literacy, and cognition and general knowledge. Each of these domains is represented in the 

1 See Head Start FACES: Longitudinal findings on program performance. Third progress report (ACYF, 2001) for a list of the 24 Program

Performance Measures. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6 March 06 
Figure 1. Head Start program performance measures conceptual framework 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7 March 06 
battery of measures being used in FACES to assess how well Head Start programs are performing. It

takes into account the interrelatedness of cognitive, emotional, and social development; physical and 

mental health; and nutritional needs. School readiness is depicted at the top of the pyramid, with five 

objectives supporting it: 

 Objective 1. Enhance children’s healthy growth and development; 

 Objective 2. Strengthen families as the primary nurturers of their children; 

 Objective 3. Provide children with educational, health, and nutritional services;

 Objective 4. Link children and families to needed community services; and 

 Objective 5. Ensure well-managed programs that involve parents in decision-making. 

Each of these objectives is critical to helping children of low-income families attain their full 

potential. They also represent the cornerstones of the Head Start program. Objectives 1 and 2 represent

outcomes or results that the program is designed to produce. Achieving both of these objectives is critical

to the ultimate success of Head Start. As parent involvement and family support are key tenets of Head

Start, both child and family-oriented outcome measures are included here. Objectives 3, 4, and 5 comprise

the lower tiers of the pyramid and contain the process measures that are the basis for the attainment of

Objectives 1 and 2 and the ultimate goal of enhancing children’s social competence. An important aspect

of the pyramid is the strong empirical connection between the provision of quality services (process 

measures) and improvements in child development (outcome measures). 

The Head Start Family and Child Experiences Survey 

The Head Start Family and Child Experiences Survey (FACES) is a central part of Head

Start’s Program Performance Measures Initiative. FACES is gathering comprehensive data on the 

cognitive, social, emotional, and physical development of Head Start children; the characteristics, wellbeing, and accomplishments of families; the quality of Head Start classrooms; and the characteristics, 

needs, and opinions of Head Start teachers and other program staff.

Each cohort of FACES employs a nationally representative sample of Head Start programs,

centers, classrooms, children, and parents. The sample is stratified by three variables: region of the

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8 March 06 
country (northeast, midwest, south, or west); urbanicity (urban vs. rural); and percentage of minority 

families in the program (50 percent or more vs. less than 50 percent). 

The first cohort of FACES had six phases of data collection: 

 Phase One involved a Spring 1997 field test in which approximately 2,400 children

and parents were studied in a nationally stratified random sample of 40 Head Start 

programs. The field test was an opportunity to assess the feasibility of interviewing 

parents and assessing children on a large scale using the selected instruments.

Although it was a field test, it provided valuable information on the status of Head 

Start programs, children, and families; 

 Phases Two and Three of FACES occurred in Fall 1997 and Spring 1998 when data

were collected on a sample of 3,200 children and families in the same 40 Head Start 

programs. Spring 1998 data collection included assessments of both Head Start 

children completing the program and Head Start graduates completing kindergarten

(kindergarten field test), as well as interviews with their parents and ratings by their 

kindergarten teachers; 

 Phase Four occurred in Spring 1999 with data collection in the 40 Head Start

programs, plus a kindergarten followup for former Head Start children; 

 Phase Five, in Spring 2000, completed the kindergarten followup for the children 

completing Head Start in Spring 1999 and first grade followup for children who 

completed Head Start in Spring 1998; and 

 Phase Six, in Spring 2001, completed the first grade followup for the children who 

completed Head Start in Spring 1999. 

These phases allow for pre-post comparisons, examining children and parents before their 

exposure to Head Start and determining their status at the end of the program and in the early school 

years. 

Because Head Start is committed to regular, longitudinal, ongoing accountability 

measurements and program improvement, a new national cohort of FACES was launched in 2000. 

FACES 2000 sampled 2,800 children and their families from a new sample of 43 Head Start programs 

across the nation. This cohort features four phases of data collection and followed 3- and 4-year-old Head 

Start children from program entry through the Spring of their kindergarten year. Figure 2 presents the 

FACES 2000 study design.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9 March 06 
FACE

 

Figure 2. FACES 2000 stu

d

y design 

___________________________________________________________________________________________________________________________________

S 2000 Technical Report 10 March 06 
Survey Measures and Instruments 

The FACES 2000 battery has four main components: the child assessment, parent interview,

teacher and staff interviews, and classroom observations. The child outcomes include the major

components of school readiness, and are collected through direct child assessments and rating scales 

completed by parents and teachers. Parent interviews are conducted with the primary caregiver of the 

Head Start child, and tap parenting behaviors, the socioeconomic characteristics of the family, and 

parental health and well-being. Interviews are administered to classroom teachers, center directors, 

program directors, and component coordinators to collect data on staff experience, education, and

training, as well as knowledge and beliefs about child development and educational activities with

children and parents. Classroom observations collect data on both the structure of the classroom and 

classroom processes, such as teacher-child interactions. This battery has remained largely the same since 

1997, with some minor revisions based on field experiences and newly released versions of instruments.2

FACES Response Rates

Through the full cooperation of the Head Start programs studied, FACES has been able to 

achieve high instrument completion rates, over 85 percent return on all survey measures. A detailed list of 

response rates by study phase and respondent is available in the appendix. 

The FACES Embedded Case Study 

An additional feature of the 1997 cohort of FACES was the embedded case study of a 

longitudinal sample of 120 randomly selected families from the larger FACES sample (Vaden-Kiernan, 

D’Elio, and Sprague, 1999). The goal of the case study was to provide a more complete profile of Head 

Start families and children, their neighborhoods, and the nature of their interactions with Head Start. The 

FACES case study provides in-depth cross-sectional and longitudinal descriptive data, both qualitative

and quantitative, over a two-year period. Findings from the case study are described in previous FACES

reports, including A Descriptive Study of Head Start Families: FACES Technical Report I,

2

 See the appendix for details on data collection instruments. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 11 March 06 
(Administration on Children, Youth and Families, 2002), which integrates extensive data from the case 

studies with parent and staff interviews from the FACES national sample. 

Dissemination of Study Findings 

The FACES team strives to disseminate study findings in a timely fashion to the Head Start

community as well as the general public. Several reports have been published detailing the development 

of Head Start’s Program Performance Measures and findings from FACES from the Spring 1997 field test 

and the 1997 and 2000 cohorts. The following reports can be accessed at the website 

www.acf.hhs.gov/programs/opre/ongoing_research/faces/faces_pubs_reports.html: 

 Head Start FACES (2000): A Whole Child Perspective on Program Performance - 

Fourth Progress Report (June 2003); 

 A Descriptive Study of Head Start Families: FACES Technical Report I (January 

2002);

 Head Start FACES: Reaching Out to Families: Head Start Recruitment and 

Enrollment Practices (January 2001); 

 Head Start FACES (1997): Longitudinal Findings on Program Performance–Third 

Progress Report (January 2001); 

 FACES Findings: New Research on Head Start Program Quality and Outcomes 

(June 2000); and 

 Head Start FACES (Pilot): Program Performance Measures–Second Progress Report 

(June 1998). 

The website also houses numerous papers presented at national conferences as well as details

about the FACES study design and data collection instruments. 

 Overview of Report 

This current document is the final report for FACES 2000. Subsequent chapters describe: 

 Cognitive gains of Head Start children and their achievement in kindergarten; 

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FACES 2000 Technical Report 12 March 06 
 Changes in social skills and problem behavior in Head Start; 

 Relationship between curricula and family, program, and classroom characteristics; 

 Quality in Head Start programs and the factors that help explain variations in quality 

across Head Start classrooms; 

 The relationship of program, classroom, and child characteristics and cognitive gains; 

 The relationship of program, classroom, child, and family characteristics and social

behavior in Head Start; 

 The social-emotional and cognitive development of children with disabilities; 

 Longitudinal changes in family structure and other household characteristics of Head

Start children; 

 Family risk factors, parental involvement, and Head Start’s protective role; and

 Predictive validity of the FACES 2000 battery. 

The technical appendix details the FACES study design, field test, data collection and 

processing, sample weights and analysis considerations, survey measures and derived variables, and data 

tables. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 13 March 06 
CHAPTER 1. 

DEMOGRAPHIC CHARACTERISTICS OF HEAD START CHILDREN AND THEIR 

FAMILIES 

In Fall 2000, slightly more than one-third (35 percent) of Head Start children were White, 

non-Hispanic followed by African American, non-Hispanic (32 percent) and Hispanic/Latino (28 percent) 

(see Table 1-1). Equal percentages of children were male and female (50 percent). The majority of 

children (62 percent) were 4 and 5 years of age and 38 percent of the children were 3 years of age. 

Parents of Head Start children had a high school diploma or GED (41 percent), had

vocational/technical diploma or Associate’s degree (30 percent), or a Bachelor’s degree or higher (6

percent). Parents reported working on a full-time basis (39 percent) or on a part-time basis (14 percent), 

and 34 percent of the parents were not in the labor force. 

Twenty percent of the Head Start families reported family monthly incomes of $2,000 or 

more (see Table 1-1). However, the majority of Head Start families reported family monthly incomes of

either $500 to $999 (27 percent) or $1,000 to $1,499 (25 percent). Nearly one-half (48 percent) of the

children resided in dual-parent families whereas more than one-half (52 percent) of children resided in

other family arrangements. One-half (50 percent) of the Head Start families were comprised of 4 to 5 

persons. Slightly more than two-fifths (41 percent) of the families were located in the southern region of

the country and the vast majority of the families (70 percent) lived in urban/suburban areas. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 1-1 March 06 
Table 1-1. Demographic characteristics of Head Start children and families – Fall 2000 

Category Percent 

Child’s Race/Ethnicity: 

White, non-Hispanic 35 

African American, non-Hispanic 32 

Hispanic/Latino 28 

Asian or Pacific Islander 1 

Multiracial/Biracial 3 

Other Race 1 

Gender: 

Male 50 

Female 50 

Child’s Age:

3 Years Old 38 

4 Years Old 52 

5 Years Old or Older 10 

Parents’ Highest Education Level:*

Less than High School 23 

High School Diploma or GED 41 

Voc/Tech Diploma, Some College, or AA 30 

Bachelor’s Degree or Higher 6 

Parent’s Employment Status:**

Working Full-Time 39 

Working Part-Time 14 

Looking for Work 7 

Not in Labor Force 34 

No Mother or Father in Household 6 

Family Monthly Income: 

Less than $500 13 

$500 to $999 27 

$1,000 to $1,499 25 

$1,500 to $1,999 15 

$2,000 or More 20 

Family Structure: 

Mother and Father 48 

Mother Only 45 

Father Only 2 

Neither Mother nor Father 5 

Family Size: 

2 or 3 26 

4 or 5 50 

6 or More 24 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 1-2 March 06 
Table 1-1. Demographic characteristics of Head Start children and families – Fall 2000 (continued) 

Category Percent 

Region: 

Northeast 14 

South 41 

Midwest 25 

West 20 

Urbanicity: 

Urban 70 

Rural 30 

Note: Column categories sum to 100 percent.

*

The highest level of education for either the mother or father is reported here. If no education information is collected for either the mother or

father and the respondent is someone else other than the mother or father, then the education level for the respondent is reported here.

**The employment level of either the mother respondent or father respondent is reported here. If there is no mother or father in the household, i.e., 

someone else is the respondent, then this is reported as no mother or father in the household.

The demographic characteristics were similar for children and their families who enrolled in 

Head Start for 1 year versus those who enrolled in Head Start for 2 years (see Table 1-2). However, some

noteworthy differences pertain to characteristics such as race/ethnicity. White, non-Hispanic children 

represented 37 percent of children who enrolled in Head Start for one year; while 39 percent of children 

who enrolled in Head Start for 2 years were African American, non-Hispanic children. Twenty-five

percent of parents whose children attended Head Start for 1 year did not have a high school diploma or 

GED as compared to 20 percent of parents whose children attended Head start for 2 years did not. Not 

surprisingly, 65 percent of children who had been in Head Start for 1 year were 4 years of age in the Fall

of 2000 as compared to 68 percent of children who had been in Head Start for 2 years were 3 years of age

in the Fall of 2000. 

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FACES 2000 Technical Report 1-3 March 06 
Table 1-2. Demographic characteristics of Head Start children and families by years of enrollment in 

Head Start program – Fall 2000 

Percent 

Category

Enrolled in Head 

Start for one year 

Enrolled in Head 

Start for two years 

Child’s Race/Ethnicity: 

White, non-Hispanic 37 31 

African American, non-Hispanic 27 39 

Hispanic/Latino 31 25 

Asian or Pacific Islander 1 1 

Multiracial/Biracial 3 3 

Other Race 1 1 

Gender: 

Male 50 51 

Female 50 49 

Child’s Age:

3 Years Old 19 68 

4 Years Old 65 32 

5 Years Old or Older 16 NA 

Parents’ Highest Education Level:*

Less than High School 25 20 

High School Diploma or GED 40 43 

Voc/Tech Diploma, Some College, or AA 29 31 

Bachelor’s Degree or Higher 6 6 

Parent’s Employment Status:**

Working Full-Time 39 40 

Working Part-Time 14 15 

Looking for Work 7 6 

Not in Labor Force 34 33 

No Mother or Father in Household 6 6 

Family Monthly Income: 

Less than $500 12 14 

$500 to $999 26 28 

$1,000 to $1,499 24 26 

$1,500 to $1,999 16 15 

$2,000 or More 22 17 

Family Structure: 

Mother and Father 50 47 

Mother Only 43 47 

Father Only 2 2 

Neither Mother nor Father 5 4 

Family Size: 

2 or 3 25 26 

4 or 5 50 49 

6 or More 25 25 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 1-4 March 06 
Table 1-2. Demographic characteristics of Head Start children and families by years of enrollment in 

Head Start program – Fall 2000 (continued) 

Percent 

Category

Enrolled in Head 

Start for one year 

Enrolled in Head 

Start for two years 

Region: 

Northeast 14 12 

South 36 51 

Midwest 26 22 

West 24 15 

Urbanicity: 

Urban 69 71 

Rural 31 29 

Note: Column categories sum to 100 percent.

Note: Number of years of attendance in Head Start is determined using parent interview, child assessment, and teacher-child report data through 

Spring 2002 though all reported percentages are based on Fall 2000 parent interview data.

*The highest level of education for either the mother or father is reported here. If no education information is collected for either the mother or 

father and the respondent is someone else other than the mother or father, then the education level for the respondent is reported. 

**The employment level of either the mother respondent or father respondent is reported here. If there is no mother or father in the household,

i.e., someone else is the respondent, then this is reported as no mother or father in the household.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 1-5 March 06 
CHAPTER 2. 

COGNITIVE GAINS MADE BY HEAD START CHILDREN AND THEIR ACHIEVEMENT IN 

KINDERGARTEN 

The Head Start Family and Child Experiences Survey (FACES) provides information about

the knowledge and skills that children who attend Head Start have when they enter the program and the 

gains they make during the Head Start year and the first year of elementary school. The information is 

helpful in assessing how well the Head Start program is performing, and what changes and reforms may

be needed to improve program performance. This information is gained through direct, one-on-one 

assessments of nationally representative samples of Head Start students in the Fall and Spring of the 

program and at the end of their kindergarten year. Although there is no non-Head Start comparison group

in FACES, the use of assessment measures with national norms permits comparisons between the skills of 

children in the sample and children of the same ages in the norming samples. Analyses are also presented 

using criterion-referenced measures without national norms. 

2.1 Research Questions 

Assessment data from FACES 2000 were used to address the following research questions

with respect to children’s cognitive development: 

1. What skills and knowledge do children have when they enter Head Start programs? 

2. Do children make significant gains in knowledge and skills during the Head Start year? 

During the kindergarten year? 

3. How do these gains vary across skill areas and among children who enter the program 

with lower or higher knowledge levels? and 

4. Are there differences in the gains in knowledge and skills between children who attend

Head Start for one year and those who attend for two years?

In making these comparisons, this chapter focuses on children who were assessed in English 

in both the Fall and Spring of the Head Start year. Information is also presented about the skills and 

knowledge of children who were initially assessed in Spanish because they came from Spanish-speaking 

homes and their knowledge of English was insufficient for testing in English in the Fall. 

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FACES 2000 Technical Report 2-1 March 06 
2.1.1 Composition of the Child Assessment 

The child outcomes instruments are a series of tasks designed to appraise the children’s

cognitive and perceptual-motor development in areas such as word knowledge, letter recognition, early

math, and early writing. These tasks have been shown to be predictive of later school achievement, 

especially of later reading proficiency and general knowledge (ACF, 2003). Instruments included: 

 Peabody Picture Vocabulary Test, Third Edition (PPVT-III), (Dunn and Dunn, 1997), 

a nationally-normed test that measures children’s word knowledge through asking

children to show the meaning of spoken words by pointing to one of four pictures that 

best illustrates the meaning of the word;

 Letter-Word Identification, Applied Problems, and Dictation tasks of the WoodcockJohnson Psycho-Educational Battery-Revised (WJ-R), (Woodcock and Mather, 1989).

These nationally-normed scales ask children to identify letters and words, solve

simple addition and subtraction problems, and trace letters and write their own name;

and 

 McCarthy Draw-A-Design from the McCarthy Scales of Children’s Abilities 

(McCarthy, 1972), a test with national norms in which children copy simple designs, 

such as a circle, a right angle, and a star. 

The children were also asked to tell their own names, ages, and birthdays; recognize colors 

by name; count objects in one-to-one correspondence; and show familiarity with story books, 

understanding of print conventions, and comprehension of a simple story. Spanish-speaking children in 

the FACES sample were assessed in Spanish unless their teachers reported they had sufficient command 

of English to be assessed in that language. By Spring 2001, language-minority children in most Head

Start programs were assessed in English. All child assessors were trained and monitored periodically by 

research staff. The assessment required 30 to 40 minutes per child.1

Cognitive measures with national norms available for comparison with the Head Start results

included tests in vocabulary, early writing, letter identification, and early math. Raw scores are available

for tests in book knowledge, design copying, one-to-one counting, color naming, and social awareness. In

all analyses, statistical tests were carried out on weighted data using the WesVar analytic procedure. This 

allows for interpretation of the results for the population of Head Start children as a whole. To assist in

interpreting the weighted results, the Technical Appendix contains supporting information on the 

weighting procedures. 

1

 Please refer to the Technical Appendix for a complete listing of the instruments, their psychometric properties, and procedures used in FACES.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-2 March 06 
2.2 Findings 

2.2.1 Emergent Literacy and Mathematics Skills of Head Start Children Compared with 

those of the General Population of Preschoolers 

These analyses were conducted on children who were assessed in English at both Fall and 

Spring of the 2000-2001 Head Start program year. 

2.2.1.1 Majority Entered Head Start with Academic Skills Below National Norms 

A primary focus of FACES was to measure the knowledge and skills children brought with 

them when they entered the Head Start program, and how this varied across academic skill areas. The 

majority of children who entered Head Start in Fall 2000 came into the program with early literacy and 

numeracy skills that were less developed than those of most children of the same age (Table 2-1). FACES

found that Head Start entrants had a mean standard score of 85.3 on the PPVT-III. They had mean

standard scores of 92.4 on the Letter-Word Identification (LWI) pre-reading task, 85.1 on the dictation 

(early writing) task, and 87.9 on the Applied Problems (early math) task of the WJ-R achievement 

battery. Standard scores are constructed to have an overall mean of 100 and a standard deviation of 15,

and are based on a sample of children of a given age, across all income levels. Thus, the literacy and 

numeracy skills that the average Head Start child brought to the program were from half a standard

deviation to a full standard deviation below national averages. 

On the criterion-referenced tasks, children scored in the middle range of the One-to-One 

Counting task (2.5 out of a possible 5), indicating that they could count fairly well, with few mistakes. 

They also scored in the middle range on the Color Naming and Social Awareness tasks. However, they

scored in the low range on Book Knowledge (1.6 out of a possible 5) and on the Draw-A-Design task (2.9 

out of a possible 19). 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-3 March 06 
Table 2-1. Fall 2000 mean scores (SD) for FACES assessment measures on entry into Head Start 

Mean (SD) 

Skill area Sample size Overall Bottom quartile Top quartile 

Norm referenced measures

Vocabulary 1,801 85.3 (14.6) 67.0 (8.3) 102.8 (7.1) 

Letter-word identification* 833 92.4 (9.6) 82.9 (4.4) 104.0 (8.8) 

Early writing 799 85.1 (13.6) 70.8 (12.0) 100.5 (8.4) 

Early math 859 87.9 (15.2) 69.0 (11.6) 104.7 (7.3) 

Criterion referenced measures 

One-to-one counting 1,848 2.5 (1.2) 1.68 (.5) 3.8 (.9) 

Color naming 1,893 11.3 (7.3) 1.73 (1.4) 19.7 (.5) 

Social awareness 1,893 3.4 (1.7) 1.26 (.8) 5.6 (.5) 

Book knowledge 1,876 1.6 (1.3) .53 (.5) 3.4 (.6) 

Draw-a-design 1,914 2.9 (1.3) 1.51 (.6) 4.5 (1.3) 

* Sample sizes for the Letter-Word Identification, Early Writing (Dictation), and Early Math (Applied Problems) tasks of the Woodcock-Johnson

Revised achievement battery are smaller than those of the other FACES measures because it was only administered to children who were

4-years old or older. Please see the Technical Appendix for details.

2.2.1.2 Diversity in Skills at Program Entry 

Though most children had below-average literacy skills, FACES 2000 found considerable 

diversity in the Head Start population (Table 2-1). For example, mean standard scores for the highest 

quarter of children entering Head Start were at national averages: 102.8 in vocabulary, 104.0 in letter 

recognition, 104.7 in early math, and 101.1 in early writing skills. Thus, these students would rank above 

the 50th percentile when compared to all U.S. preschoolers. On the other hand, mean standard scores for 

the lowest quarter of Head Start children were two standard deviations or more below national averages:

(e.g., 67.0 in vocabulary and 70.8 in early writing skills). These scores would rank the bottom quarter of

Head Start students in the lowest 2 percent of all U.S. preschoolers. 

2.2.2 Change in Knowledge and Skills Over the Head Start Year 

A primary focus of FACES was to measure the extent of change in children’s knowledge 

and skills from the Fall to the Spring of the Head Start year, especially in comparison to national averages 

for all children of the same ages. These changes were meant to serve as key indicators of the extent to

which programs were enhancing children’s school readiness. To determine the children’s gains during 

their Head Start year, differences between the Fall and Spring mean scores were calculated for the norm-

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-4 March 06 
referenced word vocabulary, letter-word identification, early writing, early math measures; as well as the 

criterion-referenced book knowledge, one-to-one counting, social awareness, color naming, design

copying, and color naming measures. That is, the gain scores were comprised of subtracting the Spring 

score from the Fall score, for each child in the study.

2

 Fall-to-Spring gain scores were tested for 

significance using dependent samples t-tests. Effect sizes are provided to estimate how meaningful these

gains are. In studies of large samples, it is often the case that differences may be statistically significant,

but the size of the effect may be too small to be meaningful from an educational programming

perspective. In this case, researchers use the effect size for determining the meaningfulness of statistical 

results.3

 When sample sizes are small, effect sizes need to be large in order to detect significant

differences, but when sample sizes are large, as they are in this study, a very small effect size can be

statistically significant but not meaningful from a policy or program perspective (see Cohen, 1988 or 

Rosenthal and Rosnow, 1984 for details on effect size). 

Table 2-2 displays the Fall, Spring, and gain scores from Fall to Spring for the FACES

sample, and provides the relevant effect sizes for these differences.

2.2.2.1 Gains in Vocabulary Knowledge and Writing Skills 

Children in Head Start showed significant expansion of their vocabularies between the 

beginning and end of the program year. By the Spring of the Head Start year, mean standard scores were

89.1 for the PPVT-III and 87.1 on the WJ-R Dictation writing task. The mean standard score on the 

vocabulary test went up by 3.8 points (p < .001), or more than one quarter of a standard deviation. The 

2

 Much has been written about the unreliability of difference scores derived from subtracting the Time 2 score from the Time 1 score when trying

to estimate individual differences in growth. However, according to Willett (1988), the reliability in the difference score can actually be quite 

high under some conditions, particularly those favored by large-scale population-based survey methods. Difference scores for measuring

change over two data points are not intrinsically as unreliable as the psychometric literature has argued and the difference score can be "an 

appealing and unbiased measure" of individual growth (Willett, 1988). 

3

 The effect size is defined as an estimate of the magnitude of the relationship or difference between two or more variables. In this study, effect

sizes were calculated as “Cohen’s d,” which was defined as the mean difference divided by the standard deviation for the underlying

distribution, and is expressed in standard score units. Effect sizes of approximately .20 are considered “small,” such as the difference in mean

IQ between twins and non-twins (see Cohen, 1988 for details). Moderate effect sizes typically approximate .50 and are conceived as those

differences large enough to be clearly visible in behavior or attitudes. Large effect sizes are those above .80, and are represented, for example,

by the mean IQ difference between holders of the Ph.D. degree and typical college freshman. However, the delineation of thresholds for 

considering an effect size to be small, moderate, or large may vary depending on the research question being asked, and the methodological

rigor of the study (Cohen, 1988). In this study, the weighted means and standard deviations were used, so that they are already adjusted for the

underlying FACES population, reflecting the probability sample that was drawn. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-5 March 06 
mean standard score on the writing task increased by 2.0 points (p < .05), or .13 of a standard deviation

(Table 2-1).4

Table 2-2. Mean scores (SD) for FACES measures from Fall 2000, Spring 2001, and Fall-Spring 

difference 

Mean (SD) 

Skill area 

Sample 

size Fall 2000 Spring 2001 

Fall-Spring 

difference Effect size

Vocabulary 1,801 85.3 (14.6) 89.1 (14.3) 3.8 .26 

Letter-word identification 833 92.4 (9.6) 92.9 (12.0) .5 (ns) .05 

Early writing 799 85.1 (13.6) 87.1 (14.3) 2.0* .13 

Early math 859 87.9 (15.2) 89.0 (17.1) 1.2* .08 

Book knowledge 1,876 1.6 (1.3) 2.5 (1.3) 0.9 .67 

Color naming 1,893 11.3 (7.3) 15.7 (5.9) 4.4 .60 

Draw-A-Design 1,914 2.9 (1.3) 3.6 (1.7) 0.6 .47 

One-to-one counting 1,848 2.5 (1.2) 3.3 (1.4) 0.7 .59 

Social awareness 1,893 3.4 (1.7) 4.1 (1.5) 0.6 .38 

Note: All Fall-Spring difference scores are significant at p<.0001 except where indicated. *p < .05.

While the gains shown by children in the FACES 2000 sample from Fall to Spring were 

relatively modest, they fell within the range that has been deemed “educationally meaningful” (Rosenthal

and Rosnow, 1984). “Educationally meaningful” results are those that explain a sufficiently large amount 

of the variation in scores to have meaningful programmatic or policy implications. They were in line with

earlier findings on the immediate effects of Head Start on children’s intellectual performance (Haskins,

1989, p. 277; McKey et al., 1985). On the other hand, the vocabulary gains found in this sample were 

about half the size of standard-score gains in IQ and achievement that have been obtained in some earlier 

studies of more intensive interventions with children from disadvantaged families (Barnett, 1998, 

pp. 13-14). Most children left Head Start with vocabulary knowledge and early writing skills that were 

still below national averages. 

4

 The Fall and Spring mean scores and gains are those for children who were assessed in English in both Fall and Spring. For information about

the mean scores and gains of Spanish-speaking children from language-minority families, see below. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-6 March 06 
In recent years, the national Head Start program has been stressing the importance of early 

literacy skills like letter recognition. In Fall 2000, the typical child was found to enter the program 

knowing about four letters (3.9) of the alphabet and to leave knowing about nine (8.9).5

 However, the 

Fall-to-Spring gain in LWI standard scores was not statistically significant. 

Children in FACES 2000 showed very slight gains in early math skills with respect to

national averages. Their mean standard scores on the WJ-R Applied Problems task went from 87.9 in the

Fall to 89.0 in the Spring. While the gain of 1.2 standard score points was statistically significant 

(p< .05), it amounted to only .08 of a standard deviation. 

2.2.2.2 Gains in Book Knowledge, Color Naming, Design Copying, One-to-One Counting, and 

Social Awareness 

Head Start children made significant Fall-to-Spring gains in the criterion-referenced tasks

which cover areas of basic knowledge, verbal, mathematical, and perceptual-motor skills that children 

typically learn in the preschool years (Table 2-1). Effect sizes ranged from .6 of a standard deviation (for 

color naming) to .38 of a standard deviation (for social awareness).

2.2.2.3 Greater Gains for those Who Entered with Lower Skills 

FACES 2000 found that children who came to Head Start with lower early literacy and math

skills made greater gains in the program than those who came with average skills (Table 2-3). For

example, whereas the average gain in vocabulary standard scores was 3.8 points, the mean gain for those

in the lowest quarter of the distribution on this measure was 8.4 points. This amounted to more than half 

of a standard deviation. By contrast, children who were in the highest quarter of the distribution in the

Fall showed no gain (-0.5) in standard scores by Spring. (Differences between mean gain in lowest 

quartile and overall mean gain, in highest quartile and overall mean gain, and between mean gains in

lowest and highest quartiles were all statistically significant, p < .001.) This suggests that the greater 

5

 The mean number of letters known out of the entire English alphabet are estimates based on the mean scores children received on the WJ-R

Letter-Word Identification (LWI) task. Estimates were derived using a known relationship between scores on the WJ-R LWI and a Letter 

Naming task in which children are shown all the letters of the alphabet. There are no national norms on the number of letters of the alphabet the

typical 4-year-old can name. For further details, see the Technical Appendix.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-7 March 06 
gains by children with lower skills is less likely to be a statistical artifact, such as regression to the mean, 

and more likely to be a meaningful contrast in relative growth in skills. 

Table 2-3. Fall 2000 – Spring 2001 mean gain scores (SD) for FACES assessment measures 

Mean gain score (SD) 

Skill area Sample size Overall Bottom quartile Top quartile 

Vocabulary 1,801 3.8 (10.5) 8.4 (11.5) -.5 (9.2) 

Letter-word identification 833 .5 (9.2) 1.3 (10.6) -.6 (8.1) 

Early writing 799 2.0 (13.3) 7.0 (15.6) -2.5 (11.9) 

Early math 859 1.2 (13.9) 5.9 (17.8) -3.2 (11.7) 

Book knowledge 1,876 0.9 (1.4) 1.5 (1.2) -.2 (1.1) 

Color naming 1,893 4.4 (5.5) 7.8 (6.4) -.4 (1.6) 

Draw-a-design 1,914 0.6 (1.6) 1.3 (1.2) .1 (2.0) 

One-to-one counting 1,848 0.7 (1.4) 1.2 (1.3) .1 (1.4) 

Social awareness 1,893 0.6 (10.5) 1.9 (1.6) -.4 (1.1) 

FACES 2000 found a similar picture with respect to changes in early writing and math skills. 

With respect to letter-word identification, there was evidence of a slight but significant increase in

standard scores (1.3, or .08 of a standard deviation) for children in the lowest quartile in the Fall. 

Despite the greater gains shown by children who entered in the lowest quarter of the Head

Start population, these children ended the year with skills that were still well below average. 

2.2.3 Emergent Literacy Gains of Language-Minority Children 

In FACES 2000, children whose English-language skills were not sufficient to enable them

to be assessed fully in English, and whose parents spoke Spanish at home, were given a Spanish-language

version of the FACES battery in the Fall. In the Spring, these children received the full assessment battery 

in English. However, these English-language learners also received two additional tests that enabled the

research team to track their language development and pre-reading skills in both English and Spanish. In

the Fall, they received two components of the battery—vocabulary and letter identification—in English as

well as Spanish. In the Spring, they received the same two components in Spanish as well as English.

Thus, the levels of proficiency achieved and the gains made in vocabulary and letter identification could 

be determined in both languages.6

6

 English-language learners whose home language was something other than Spanish were not given any direct assessment in their native

languages. They received only the full assessment battery in English in the Spring. For further details, see the Technical Appendix.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-8 March 06 
The dual assessment procedure made it possible to investigate the following research

questions: 

1. How do the literacy levels and gains of language-minority children in Head Start 

compare with those of language-majority children? and 

2. How do the literacy levels and gains of these children vary across the two languages? 

Of course, in comparing children to test norms, a different set of norms has to be used for 

test performance in Spanish. The Spanish-language knowledge of Head Start children from Spanishspeaking homes was compared to norms based on samples of children drawn in Mexico and Puerto Rico 

combined (Dunn, Padilla, Lugo, and Dunn 1986). 

2.2.3.1 Knowing the Meaning of English Words 

Spanish-speaking children in Head Start entered with English vocabulary skills considerably

behind those of children who came from households where English was the primary language spoken in

the home. They made greater gains over the course of the Head Start year. But their English vocabulary

knowledge remained behind that of other children at the end of the year. The mean standard score on the 

PPVT-III for Spanish-speaking children in Fall 2000 was 59.7, more than two standard deviations below 

the national norm. By the Spring, their mean score had risen to 66.6, a gain of 7 points. But this was still

more than 20 points (or one and a third standard deviations) lower than the mean score in vocabulary for 

language-majority children in Head Start (Table 2-4). 

Table 2-4. Fall 2000, Spring 2001, and Fall-to-Spring gain vocabulary scores for language-minority, 

language-majority, and combined groups of children 

Vocabulary mean score (SD) 

Language-minority

(N = 306) 

Language-majority

(N = 1,801) 

Language-minority and 

majority combined 

Fall 2000 59.7 (13.3) 85.3 (14.6) 81.4 (17.1) 

Spring 2001 66.7 (14.1) 89.1 (14.3) 85.7 (16.4) 

Fall-Spring difference 7.0 3.8 4.3 

All mean differences significant at p < .0001 level.

When the vocabulary scores of language-minority and language-majority children were

added together, the combined Head Start student population began the year with a mean standard score of 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-9 March 06 
81.4, and ended the year with a mean standard score of 85.7. This represented a gain of 4.3 standard score

points. 

2.2.3.2 Identifying Letters in English 

Spanish-speaking children in Head Start entered with English letter identification skills that 

were only slightly behind those of language-majority children. However, like the English-speaking

children, they did not make gains in these skills over the course of the year, at least not in comparison to 

national averages. The mean standard score of Spanish-speaking children tested in English on the WJ-R

LWI test for Spanish-speaking children in Fall 2000 was 89.5, about two thirds of a standard deviation 

below the national norm. By the Spring, their mean score was 87.5, which was not significantly different

from the Fall score (Table 2-5). 

Table 2-5. Fall 2000, Spring 2001, and Fall-to-Spring gain letter-word identification scores for 

language-minority, language-majority, and combined groups of children 

Letter-word identification mean score (SD) 

Language-minority

(N = 178) 

Language-majority

(N =833 ) 

Language-minority and 

majority combined 

Fall 2000 89.5 (6.1) 92.4 (9.6) 91.9 (9.2) 

Spring 2001 87.5 (7.9) 92.9 (12.0) 91.9 (11.6) 

Fall-Spring difference -2.0 .5 0.0 

*p < .01.

When the letter identification scores of language-minority and language-majority children 

were added together, the combined Head Start student population began and ended the Head Start year

with a mean standard score of 91.9. 

2.2.3.3 Changes in English Language Skills Versus Changes in Spanish Skills 

The Spanish vocabulary knowledge of Spanish-speaking Head Start children was quite 

comparable, in standard score terms, to the knowledge levels of English-speaking Head Start children in

English. While the Spanish children made gains in English vocabulary knowledge during the year, they

did not lose ground in Spanish vocabulary knowledge. The mean standard score for Spanish vocabulary 

knowledge was 84.9 in the Fall and 84.4 in the Spring (Table 2-6). 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-10 March 06 
Table 2-6. Vocabulary skills in English and Spanish of Head Start children from Spanish-speaking 

language-minority families 

Mean score (SD) 

English vocabulary task 

(N = 306) 

Spanish vocabulary task 

(N = 300) 

Fall 2000 59.7 (13.3) 84.9 (11.4) 

Spring 2001 66.7 (14.1) 84.4 (12.8) 

Fall-Spring difference 7.0* -.6 

*p < .0001.

The ability of Spanish-speaking Head Start children to identify letters of the alphabet in

Spanish was comparable, in standard score terms, to the ability of English-speaking Head Start children to 

identify letters in English. It was also comparable to their own ability to identify letters in English. 

However, the Spanish-speaking children showed no gains against norms in their ability to identify letters 

in either language. The mean standard score for Spanish letter identification was 89.6 in the Fall and 86.2

in the Spring (Table 2-7). 

Table 2-7. Letter-word identification skills in English and Spanish of Head Start children from Spanishspeaking language-minority families 

Mean score (SD) 

English letter-word ID task 

(N = 178) 

Spanish letter-word ID task 

(N = 300) 

Fall 2000 89.5 (6.1) 89.6 (5.6) 

Spring 2001 87.5 (7.9) 86.2 (6.7) 

Fall-Spring difference -2.0 -3.4** 

*p < .01; **p < .0001.

2.2.4 Growth of Knowledge and Skills in Kindergarten 

From assessments in the kindergarten followup, Head Start children continue to make

advances against national norms during their first year in elementary school. For example, vocabulary 

standard scores went from 90.6 at the end of Head Start to 94.5 at the end of kindergarten. This was an

increase of 3.9 points, or .37 of a standard deviation. Similarly, early math scores went from a mean 

standard score of 88.8 at the end of Head Start to a mean of 94.6 at the end of kindergarten. This was a

gain of 5.8 points, or .34 of a standard deviation. Early writing scores showed a gain in kindergarten of 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-11 March 06 
.80 of a standard deviation. They went from 85.9 at the end of Head Start to 98.0 at the end of

kindergarten, an increase of 12.1 points (Table 2-8). 

Table 2-8. Norm-referenced scores at end of Head Start and end of kindergarten and Head Start-tokindergarten gain scores 

Mean (SD) 

Sample size 

End of Head 

Start 

End of 

kindergarten 

Head Start to 

kindergarten 

gain score 

Effect size of 

gain score 

Vocabulary 1,433 90.6 (14.2) 94.5 (12.3) 3.9 .37 

Early math 1,387 88.8 (17.3) 94.6 (18.1) 5.8 .34 

Early writing 1,340 85.9 (14.8) 98.0 (13.9) 12.1 .80 

Note: All Head Start to kindergarten gain scores significant at p < .0001.

2.2.5 Differences in Gains in Knowledge and Skills Between Children Who Attend One Year 

of Head Start Versus those Who Attend for Two Years 

These analyses were conducted on children who were assessed in English at both Fall and 

Spring of their respective Head Start program years. All children entered Head Start for the first time in

Fall 2000 and either graduated in Spring 2001 (i.e., one-year graduates) or in Spring 2002 (i.e., two-year 

graduates). 

2.2.5.1 Children Who Attend Head Start for Two Years Show Greater Entry to Graduation

Gains than those Who Attend for One Year 

Analyses were conducted comparing the child assessment scores of children who attended 

Head Start for 2 years with those who attended Head Start for only 1 year. Three-way Analyses of

Covariance (ANCOVA) were conducted with length of Head Start attendance (one year vs. two years) 

predicting gains in child assessment scores from “entry in” to “graduation from” Head Start, while

controlling for child’s age and assessment score in Fall 2000 (i.e., at baseline).7

7

 Because the Woodcock-Johnson-Revised subtests (Letter Word Identification, Applied Problems, and Dictation) are only administered to

children 4-years-old or older, very few children who attended Head Start for two years have baseline data from Fall 2000. As a result, gain 

scores were not calculated for these subtests. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-12 March 06 
From Table 2-9, results show that children who attended Head Start for 2 years showed 

greater progress than their peers who attended for 1 year in all measures for which gain scores were

calculated. On the PPVT-III, two-year Head Start graduates showed greater gains towards national norms 

in vocabulary than one-year graduates. Children who attended Head Start for only 1 year increased their

vocabulary skills from a baseline score of 87.4 to 90.8 when they graduated from Head Start in Spring 

2001. This represents a statistically significant gain of 3.4 points. In contrast, children who attended for 2 

years increased their vocabulary skills from a baseline score of 82.9 to 90.6 when they graduated from 

Head Start in Spring 2002. This represents a statistically significant gain of 7.7 points, which was 

significantly greater than the gains in vocabulary scores for those who attended Head Start for only 1 

year. It is important to note that while children who participate for 2 years have higher cognitive gains

than those who participate for only 1 year, they achieve similar levels of performance at the end of Head

Start (90.8 for one-year graduates; 90.6 for two-year graduates). However, the children who attend for 2 

years start at a lower level, which accounts for their greater gain scores. 

Table 2-9. Child assessment “entry-graduation” means (SD) for Fall, Spring and Fall-Spring gain 

scores for one-year Head Start graduates and two-year Head Start graduates 

One-year 

graduate

Two-year 

graduate

Fall Spring F-S gain Fall Spring F-S gain F-value 

Vocabulary 87.4 

(14.7) 

90.8 

(13.9) 

3.4 

(9.6) 

82.9 

(13.9) 

90.6 

(14.4) 

7.7 

(12.1) 

F (1, 1388)

= 12.4* 

Book

knowledge 

1.9 (1.3) 2.8 (1.3) .8 (1.4) 1.3 (1.1) 2.9 (1.4) 1.6 (1.5) F (1, 1450)

= 68.4**

Color naming 13.0 (7.0) 16.9 (5.1) 3.9 (5.3) 9.1 (7.0) 18.5 (3.1) 9.4 (6.6) F (1, 1463)

= 202.9**

Draw-A-Design 3.2 (1.5) 4.0 (2.0) .8 (1.8) 2.5 (1.1) 4.4 (1.8) 1.9 (1.8) F (1, 1474)

= 128.9**

One-to-one 

counting 2.8 (1.3) 3.6 (1.4) .8 (1.5) 2.1 (1.3) 3.8 (1.3) 1.7 (1.4) F (1, 1425)= 92.5**

Social 

awareness 

3.7 (1.6) 4.3 (1.4) .6 (1.5) 3.1 (1.7) 4.8 (1.2) 1.7 (1.7) F (1, 1450)

= 134.7**

*p < .001; **p < .0001.

Children who attended Head Start for 2 years also showed greater “entry to graduation”

gains than their peers who attended for only 1 year in each of the criterion-referenced measures, for which 

only raw scores are available. Gains demonstrated by two-year graduates ranged from approximately two

times greater (e.g., Book Knowledge, One-to-One Counting) to approximately three times greater (e.g.,

Social Awareness, Draw-A-Design) than the gains demonstrated by one-year graduates. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-13 March 06 
2.3 Conclusions 

Cognitive assessment data from FACES 2000 showed that most children entered Head Start

with early literacy and math skills well below national averages. However, there was considerable 

diversity in skill levels among Head Start children. At Head Start entry, the highest quarter of Head Start 

children were at or above the national average (50th percentile) in early language and number skills, while

the lowest quarter of children ranked in the lowest 2 percent of all U.S. preschoolers in these areas. 

Children made gains toward national averages during the Head Start year, especially with respect 

to vocabulary knowledge and early writing skills. Children who entered the program with lower levels of 

knowledge and skill showed larger gains during the program year, yet still lagged considerably behind 

national averages. Children who started with higher assessment scores in the Fall wound up with higher 

scores in the Spring, but did not show the same level of gains as did those with lower baseline scores.

Language-minority children in Head Start showed significant gains in English vocabulary skills without 

declines in their Spanish vocabulary skills. They did not gain in letter recognition skills. Children who 

graduated after 2 years of Head Start made greater gains from entry to graduation than those who spent 

only 1 year in Head Start. Typically, children who graduate Head Start after 2 years enter with lower 

skills than one-year graduates. However, by the time both groups leave Head Start, they achieve similar 

levels of performance. 

Head Start graduates also showed further progress toward national averages during 

kindergarten. Gains of between a quarter to more than three quarters a standard deviation were observed

in vocabulary, early math, and early writing skills during kindergarten. Most Head Start graduates could 

identify the letters of the alphabet by the end of kindergarten and more than half could recognize 

beginning sounds of words. Further, Head Start graduates achieved early writing scores near the national

norm by the end of kindergarten. Nevertheless, Head Start graduates remained behind their more

advantaged peers in vocabulary and early math. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 2-14 March 06 
CHAPTER 3. 

CHANGES IN SOCIAL COMPETENCE THROUGH THE HEAD START YEARS 

FACES 2000 provides information about desirable and undesirable social behaviors that 

children who attend Head Start display when they enter the program and at the end of the program year. 

Examining social competence of preschool children is important because of evidence that children's 

academic achievement and adjustment once they go to school depend not only on their intellectual

capabilities, but also on their acquisition of social skills and positive approaches to learning, and on the 

improvement of negative behavior patterns (Pianta and McCoy, 1997; Zill and West, 2001).

In a previous cohort (FACES 1997), significant positive changes were found in participants’ 

social behaviors from the beginning to the end of Head Start. It was also found that social behaviors of 

Head Start children could predict social adjustment to elementary school, and, to a lesser extent, could 

predict academic performance in elementary school. Improvements in social behavior were particularly

strong for children who entered Head Start with the lowest levels of social skills and those who entered 

Head Start with the highest levels of problem behaviors. In this chapter, we wanted to examine whether

the significant positive changes in social behaviors found in 1997 are replicated in FACES 2000. The

examination of the predictive power of the social behavior ratings in relation to kindergarten outcomes 

can be found in chapter 10 of this report. Information regarding children’s social behavior in Head Start 

and beyond was obtained through behavior ratings provided by parents, Head Start teachers, and

kindergarten teachers. 

3.1 Research Questions 

1. Do children show significant gains in social skills and significant declines in problem 

behavior during the Head Start year? 

2. Do children graduating from Head Start programs after 2 years demonstrate more social

skills and less problem behavior than children who had 1 year of Head Start? and 

3. How do gains vary across behavior areas among children who enter the program with

different levels of social skills and problem behavior? 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 3-1 March 06 
3.2 Measures 

3.2.1 Teacher Report 

3.2.1.1 Cooperative Classroom Behavior of Head Start Children 

Lead teachers in the FACES 2000 national sample of Head Start classes (as well as

kindergarten teachers) were asked to rate the cooperative classroom behavior of children in their classes.

These ratings were obtained early in the program year (October-November) and toward the end of the 

Head Start year (April-June 2001 and 2002), with followup in kindergarten (April-June 2002 or 2003).

The scale was partly composed of items dealing with helpful and compliant behavior like, “Follows the

teacher’s directions,” “Joins an activity or group without being told to do so,” and “Helps in putting work 

materials or center property away.” Other items dealt with the child’s maturity and skill in interacting 

with other children. Examples include, “Invites others to join in activities,” “Waits her or his turn in 

games or other activities,” and “Accepts classmates’ ideas for sharing and playing.” For each item, the

teacher was asked to judge whether the child behaved in the indicated way, “never,” “sometimes,” or 

“very often.” There were 12 rating items in all, and the scale score could range from zero (all items

marked “never”) to 24 (all items marked “very often”). For a complete description of this measure, see 

the Technical Appendix of this report. 

3.2.1.2 Problem Behavior of Head Start Children 

Lead teachers in the FACES 2000 national sample of Head Start classes (as well as

kindergarten teachers) were also asked to rate the undesirable or problem behavior of children in their 

classes. Three scales were composed from this measure: the Aggressive Behavior scale was partly

composed of items such as, “Hits or fights with others,” “Disrupts ongoing activities,” and “Has temper 

tantrums or hot temper.” The Hyperactive Behavior scale was composed of items such as “Can’t 

concentrate, can’t pay attention for long,” and “Is very restless, fidgets all the time, can’t sit still.” The 

Withdrawn Behavior scale was composed of items such as “Keeps to herself or himself, tends to 

withdraw,” “Lacks confidence in learning new things or trying new activities,” and “Often seems

unhappy, sad, or depressed.” For each item, the teacher was asked to judge whether the behavioral

description was “not true,” “somewhat or sometimes true,” or “very true or often true” of the child. The 

Aggressive Behavior scale contained four items and could range in value from zero to eight. The

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FACES 2000 Technical Report 3-2 March 06 
Hyperactive Behavior scale was composed of three items and could range in value from zero to six. The

Withdrawn Behavior scale contained seven items and could range in value from zero to 14. For a 

complete description of the measures see the Technical Appendix of this report.

3.2.2 Parent Report 

3.2.2.1 Social Skills and Approaches to Learning 

Parents in the FACES 2000 national sample of Head Start classes were asked to rate the 

social skills and approaches to learning of their children. These ratings were obtained early in the program 

year (October-November) and toward the end of the Head Start year (April-June 2001 and 2002), with a

followup in kindergarten (April-June 2002 or 2003). Social skills items rated by parents were similar to

those presented to teachers (e.g., “Makes friends easily,” “Comforts or helps others,” and “Accepts

friends’ ideas in sharing and playing”). Examples of the approaches to learning items included, "Enjoys

learning,” “Likes to try new things,” and “Shows imagination in work and play.” There were seven items

in this scale, and scores could range from zero (meaning all the items were rated “not true” of the child) to

14 (meaning all the items were rated “very true or often true” of the child). The kindergarten scale was

composed of different items and yielded slightly different scores. For a complete description of this

measure, see the Technical Appendix of this report. 

3.2.2.2 Behavior Problems

Parents were also asked to rate their children on negative behaviors that are relatively 

common among preschool children and that are associated with adjustment problems in elementary

school. Parents were asked to rate their children’s problem behavior on three scales: the Aggressive

Behavior scale (example item: “has temper tantrums or hot temper”), the Hyperactive Behavior scale 

(example item: “Can’t concentrate, Can’t pay attention for long”), and the Withdrawn Behavior scale

(example item: “Feels worthless or inferior”). The Aggressive Behavior scale contained four items and 

could range in value from zero to eight. The Hyperactive Behavior scale was composed of three items and

could range in value from zero to six. The Withdrawn Behavior scale contained five items and could 

range in value from zero to 10. The kindergarten scales were composed of different items and yielded

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 3-3 March 06 
slightly different scores. For a complete description of the problem behavior measures, see the Technical

Appendix of this report. 

3.3 Findings 

3.3.1 Do Children Show Significant Gains in Cooperative Classroom Behavior and Social 

Skills and Significant Declines in Problem Behavior During the Head Start Years? 

Table 3-1 presents the results of a repeated measure ANOVA for each of the eight 

(4 teacher-rated and 4 parent-rated) social competency variables after controlling for the child’s age and 

the amount of time spent in Head Start between entry and graduation (one year vs. two years). There were 

major differences between the teachers’ and the parents’ reports of change in social behaviors: Teachers

reported significant improvements in three out of the four social behaviors scales (cooperative classroom 

behavior, hyperactive behavior, and withdrawn behavior). On the other hand, no significant 

improvements in children’s social behaviors from the beginning to end of Head Start were reported by

parents. 

Table 3-1. Means and standard deviations of social competence scores at Head Start entry and 

graduation 

Data collection point 

Social behavior Entry Graduation d F 

Teacher report 

Cooperative behavior 14.77 (4.79) 17.80 (5.78) .57 42.10*** 

Aggressive behavior 1.73 (1.99) 1.60 (1.38) .94 

Hyperactive behavior 1.37 (1.53) 1.06 (1.18) .22 10.46** 

Withdrawn behavior 2.45 (2.63) 2.10 (2.10) .14 15.71*** 

Parent report 

Social skills 12.18 (1.70) 12.32 (2.12) .07 3.60† 

Aggressive behavior 3.18 (1.74) 2.75 (2.38) 1.24 

Hyperactive behavior 1.89 (1.54) 1.59 (1.62) .03 

Withdrawn behavior .61 (.96) .66 (1.33) 1.07 

Note: Standard deviations are given in parenthesis. F values are based on a repeated measure ANOVA controlling for child’s age and length of 

exposure to Head Start. Effect sizes (d) are given only for significant differences. Sample sizes for teacher reported behaviors ranged from n = 

2,057 (for aggressive behavior) to n = 2,169 (for cooperative classroom behavior). Sample sizes for parent reported behaviors ranged from n = 

2,102 (for withdrawn behavior) to n = 2,135 (for social skills). 

† p < .1; ** p < .01; *** p < .001.

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FACES 2000 Technical Report 3-4 March 06 
3.3.2 Do Children Graduating from Head Start Programs After Two Years Show More 

Cooperative Classroom Behavior and Social Skills and Less Problem Behavior Than 

Children Who had One Year of Head Start? 

Table 3-2 presents the results of a two-way ANOVA comparing the group of children who 

spent only 1 year in Head Start to the group of children who spent 2 years in Head Start on the eight

social behavior variables (after controlling for age). The results indicate that children who spent more

time in Head Start were reported to display higher levels of cooperative classroom behavior and social 

skills and less hyperactive behavior at the end of Head Start even after controlling for age. Moreover, the 

differences between one- and two-year graduates were consistent across reporters: both teachers and 

parents reported significantly more social skills and significantly less hyperactive behavior for the 

children who spent 2 years in Head Start compared to children who spent 1 year in Head Start. No 

significant differences were reported in aggressive and withdrawn behaviors. 

Table 3-2. Means and standard deviations of social competence scores at Head Start graduation as a 

function of length of Head Start participation (1 vs. 2 years) 

Length of Head Start participation 

Social behavior One year Two years d F 

Teacher report 

Cooperative behavior 17.44 (4.52) 18.26 (4.20) .19 17.81*** 

Aggressive behavior 1.62 (2.03) 1.58 (1.58) .27 

Hyperactive behavior 1.12 (1.45) .98 (1.43) .10 4.78* 

Withdrawn behavior 2.11 (2.46) 2.09 (2.44) .04 

Parent report 

Social skills 12.17 (1.73) 12.53 (1.67) .21 21.17*** 

Aggressive behavior 2.80 (1.72) 2.67 (1.81) .07 2.99† 

Hyperactive behavior 1.66 (1.50) 1.50 (1.50) .11 5.95* 

Withdrawn behavior .68 (.94) .64 (1.00) .67 

Note: Standard deviations are given in parenthesis. F values are based on a three-way ANOVA controlling for child’s age and baseline behavior

ratings. Effect sizes (d) are given only for significant differences. Sample sizes for one-year graduates ranged from n = 612 (for teacherreported withdrawn behavior) to n = 820 (for all parent-reported behaviors). Sample sizes for one-year graduates ranged from n = 889 (for

parent-reported withdrawn behavior) to n = 954 (for teacher-reported cooperative classroom behavior). 

† p < .1; * p < .05; *** p < .001.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 3-5 March 06 
3.3.3 How do Gains Vary Across Behavior Areas Among Children Who Enter the Program

with Different Levels of Cooperative Classroom Behavior, Social Skills, and Problem 

Behavior? 

Table 3-3 presents the mean scores of children in the most and least desirable quartiles on 

measures of social competence at the beginning and end of Head Start participation. Table 3-4 presents 

the comparisons between the positive gains in social behaviors made during the Head Start years for 

children at the most versus the least socially desirable behavior quartiles of each of the eight (4 teacherrated and 4 parent-rated) social behaviors ratings.1

 As can be seen in Table 3-4, the differences between 

the most and least desirable groups in terms of social behavior gains achieved in Head Start were highly 

significant. Children who entered Head Start with high social skills and minimal problem behavior did

not seem to improve their already high social performance (in fact, their behavior seemed to slightly

decline during the Head Start years). In contrast, children who entered Head Start with the lowest levels

of social skills and children who had the highest levels of problem behavior made significant

improvements in all reported social behaviors, even after controlling for age and amount of time (1 or 2

years) spent in Head Start. Note that although children who started with the least desirable levels of social

competency closed some of the gap between them and children in the most desirable quartiles, their

scores in all the rating scales remained considerably lower (see Table 3-3). 

Table 3-3. Mean scores of children in quartiles representing most and least desirable social competence 

scores at the beginning and end of Head Start participation 

Most desirable Least desirable 

Social behavior Entry Graduation Entry Graduation 

Teacher report 

Cooperative behavior 20.47 20.00 8.72 15.40

Aggressive behavior 0 .66 4.33 3.02 

Hyperactive behavior 0 .43 2.99 1.75 

Withdrawn behavior 0 1.07 5.93 3.46 

Parent report 

Social skills 13.52 12.89 10.05 11.47 

Aggressive behavior 1.33 1.84 4.89 3.59 

Hyperactive behavior .50 .93 3.79 2.52 

Withdrawn behavior 0 .43 1.64 1.05 

Note: Children who scored highest on the measures of cooperative behavior and social skills, or lowest on measures of aggressive, hyperactive, or

withdrawn behaviors comprise the “most desirable” quartiles. Children who scored lowest on measures of cooperative behavior and social

skills, or highest on measures of aggressive, hyperactive, or withdrawn behaviors comprise the “least desirable” quartiles. Comparisons

between the different most and least desirable groups were independent from each other. Thus, children who belonged to one of the extreme 

quartiles on one behavior rating were not necessarily part of the extreme quartiles of any other behavioral ratings. 

1

 Comparisons between the different most and least desirable groups were independent from each other. Thus, children who belonged to one of 

the extreme quartiles in one behavior rating were not necessarily part of the extreme quartiles of any other behavioral ratings. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 3-6 March 06 
Table 3-4. Means and standard deviations of social competence gain scores (from entry to graduation) 

of children scoring in the most and least desirable quartiles 

Social behavior Most desirable Least desirable d F 

Teacher report 

Cooperative behavior -.47 (3.71) 6.68 (4.91) 1.64 659.49*** 

Aggressive behavior .66 (1.27) -.31 (2.42) .50 306.45*** 

Hyperactive behavior .43 (.81) -1.24 (1.75) 1.22 498.41*** 

Withdrawn behavior 1.07 (1.78) -2.47 (3.14) 1.39 451.67*** 

Parent report 

Social skills -.64 (1.33) 1.42 (2.06) 1.19 503.57*** 

Aggressive behavior .51 (1.47) -1.30 (1.83) 1.09 369.77*** 

Hyperactive behavior .43 (1.18) -1.27 (1.53) 1.24 495.34*** 

Withdrawn behavior .43 (.81) -.59 (1.29) .95 394.49*** 

Note: Numbers in table represent mean gain scores (Δ). Standard deviations are given in parenthesis. F values are based on a repeated measure

ANOVA controlling for child’s age and length of exposure to Head Start. Sample sizes for the bottom quartile ranged from n = 433 (teacherreported cooperative classroom behavior) to n = 1,016 (parent-reported withdrawn behavior). Sample sizes for the top quartile ranged from n = 

433 (teacher-reported aggressive and withdrawn behavior) to n = 826 (parent-reported social skills). 

*** p < .001.

3.4 Conclusions 

This chapter examined whether social behaviors, as reported by Head Start parents and

teachers, change during the Head Start years. The findings indicate that teachers in particular report 

significant positive changes on measures of social competence from Head Start entry to graduation. The 

findings also indicate that children who spent 2 years in Head Start were reported to display higher levels 

of cooperative classroom behavior and social skills and less hyperactive behavior at the end of Head Start

compared to children who spent only 1 year in Head Start. Children entering Head Start with the lowest 

levels of social skills, and those who entered Head Start with the highest levels of problem behaviors,

gained the most from participation in Head Start. Although these children did not close the gap between

themselves and other children, they did narrow it significantly. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 3-7 March 06 
CHAPTER 4. 

CURRICULUM, FAMILY, PROGRAM, AND CLASSROOM CHARACTERISTICS 

There is a lack of substantial evidence about the relative efficacy of various types of 

standardized curricula available to preschool programs and their relationship to children's school 

readiness. Accordingly, the Head Start Program Performance Standards require that programs have a

curriculum, and delineate the areas that must be covered by it, but do not prescribe one. Programs may

use curricula from a variety of sources, develop one of their own, or use a combination of curricula. In the 

2001-2002 program year, the Head Start Program Information Report (PIR) queried local programs about 

the curricula they use. In descending order of frequency, center-based programs indicated that they used 

the Creative Curriculum, High/Scope curriculum, and locally designed curriculum. This chapter examines 

the curricula Head Start programs in the FACES sample are using; the training and ongoing support

teachers receive in the use of their curricula; teacher satisfaction with their curricula; and the relationships

between the type of curricula used and family, program, and classroom characteristics. 

4.1 Research Questions 

This chapter addresses the following research questions: 

1. What percentage of Head Start programs use a curriculum?

2. What types of curricula are used in Head Start programs?

3. Do Head Start teachers receive training and ongoing support in the use of their

curriculum and from whom?

4. What percentage of Head Start teachers have access to a copy of their curriculum?

5. What aspects of the curricula do Head Start teachers like?

6. What is the relationship between the type of curricula used and the characteristics of 

children and families served?

7. Are there regional and rural-urban differences in the type of curricula used by Head Start

programs? and 

8. What is the relationship between the type of curricula used and classroom quality? 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-1 March 06 
4.2 Methods 

The sample for this chapter includes 231 center-based Head Start teachers from 43 Head

Start programs in the FACES 2000 study. Data reported in this chapter are from teacher interviews

conducted by field staff in Fall 2000. The monthly family income data and child ethnicity data come from 

parent interviews conducted in Fall 2000. These parent interview numbers are less than the total number 

of parents interviewed in Fall 2000 because of non-response or missing data on monthly family income or 

child ethnicity variables. 

Weighted percentages, correlations, independent-sample t-tests and multivariate analyses of

variance were used to answer the research questions. Data presented in this chapter are weighted to 

represent Head Start programs nationally.1

4.3 Findings 

4.3.1 Head Start Teachers Report Using a Specific Curriculum, Receiving Training, and 

Having Access to their Curriculum 

4.3.1.1 Types of Curricula 

Head Start teachers were asked if they used a single specific curriculum, a combination of 

curricula, or no curriculum. About 70 percent of the teachers used a single curriculum, 21 percent used a 

combination of curricula, and 9 percent did not use a curriculum. Teachers who reported using a single 

curriculum or a combination of curricula were asked to name their principal curriculum. The majority

(59.1 percent) said that they used either Creative Curriculum or High/Scope curriculum (see Table 4-1). 

Almost 41 percent used a curriculum other than Creative Curriculum or High/Scope curriculum, which

will be referred to as other curricula. Other curricula mentioned by teachers were High Reach, Scholastic,

Los Cantos Los Ninos, R.E.A.L, Newport, Global Curriculum, Creating Child Centered Classrooms –

Step by Step, Building Bridges, Northern Kentucky Curriculum, Montessori, Teacher Planning Wellbook, 

Therapeutic Intervention Program, and Kid College Curriculum. Some others include the “Head Start”

curriculum or “theme units” although there is no “official” Head Start curriculum.

1

 FACES 2000 employs a nationally representative sample of 43 Head Start programs. It does not include migrant or American Indian/Alaskan

Native programs, Early Head Start programs or programs in Puerto Rico and the other territories. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-2 March 06 
Table 4-1. The majority of teachers used either Creative Curriculum or High/Scope curriculum

Curricula Percent of teachers 

Creative Curriculum 39.1%

High/Scope curriculum 20.0%

Other 40.9%

4.3.1.2 Curricular Training and Support 

Teachers were asked if they received training in their curriculum and who provided this

training (teachers could respond with only one source). Ninety-three percent reported receiving training in

their curricula. Of those that received training, most had received it from their own program staff

(58.5 percent), followed by curricula developers (14 percent), a Head Start Quality Improvement Center

or HSQIC (10.3 percent), another Head Start program (5 percent), a university school of education 

(4.4 percent), or another source (7.9 percent). 

Almost 92 percent of the teachers received ongoing support such as consultation or 

mentoring in the use of their curriculum and this support could come from several sources. Of those who 

received support, it most often came from their supervisor or the education coordinator (70.3 percent), 

other teachers (23.9 percent), the HSQIC (20 percent), curriculum developers (19.3 percent), or a

mentor/master teacher (14 percent). Support also came from other Head Start programs (10.8 percent), 

schools of education (6.6 percent), the Disability Services Quality Improvement Center or DSQIC 

(4.1 percent), and other sources (8.6 percent). 

4.3.1.3 Teacher Access to Curricula 

Of teachers who used a curriculum, 97 percent responded that teachers and assistant teachers 

in their program had access to a copy of their curriculum.

4.3.1.4 Teacher Satisfaction with Curricula 

The vast majority of the teachers (92.3 percent) said that they liked their curriculum.

Table 4-2 indicates that an overwhelming majority of the teachers said they liked their curriculum 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-3 March 06 
because it addressed multiple domains of learning (99.1 percent), was easy to use and adapt 

(98.3 percent), involved parents (96.6 percent), had room for teacher creativity (96.4 percent), and had

adequate learning materials, resources, and examples of activities (92.1 percent). 

Table 4-2. Teachers liked their respective curricula for a variety of reasons 

Reasons Percent of teachers 

Multiple domains addressed 99.1% 

Easy to use/adapt 98.3% 

Involves parents 96.6%

Room for teacher creativity 96.4%

Adequate learning materials 92.1%

4.3.2 Relationship Between Curricula and Family, Program, and Classroom Characteristics 

4.3.2.1 Relationship Between Curricula and Family Characteristics 

In the context of the study’s conceptual framework, the relationship between the use of 

particular curricula and the characteristics of the families served by the programs were examined. The

mean monthly family income of families from classrooms using the High/Scope curriculum was

$1,641.18, from classrooms using Creative Curriculum was $1,559.60, and from classrooms using other 

curricula was $1,319.43. This indicates that classrooms using other curricula served the poorest families 

compared to classrooms using Creative Curriculum or High/Scope curriculum. The percentage of 

minority children served by teachers using other curricula was 75.8 percent, for teachers using 

High/Scope curriculum it was 69.6 percent, and for teachers using Creative Curriculum it was 48.8 

percent. Thus, teachers using other curricula served the highest percentage of minority children. 

4.3.2.2 Relationship Between Curricula and Program Characteristics 

Table 4-3 shows that more teachers from the Northeast (78.7 percent), Midwest 

(59.4 percent), and West (69.4 percent) used Creative Curriculum or High/Scope curriculum than other 

curricula, while the majority of teachers from the South (54.4 percent) used other curricula. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-4 March 06 
Table 4-3. Most teachers from the northeast, midwest, and west used Creative Curriculum or 

High/Scope curriculum, while majority of teachers from the south used other curricula 

Percent of teachers 

Curricula Northeast Midwest South West 

Creative Curriculum 61.4% 42.7% 24.5% 44.5%

High/Scope 17.3% 16.7% 21.1% 24.9%

Other 21.3% 40.6% 54.4% 30.5%

A greater percentage of rural teachers (77.5 percent) used either Creative Curriculum or 

High/Scope curriculum than urban teachers (51.4 percent). As shown in Table 4-4, although urban and 

rural teachers were equally likely to use the High/Scope curriculum (20 percent), urban teachers were

more likely than rural teachers to use other curricula (48.6 percent vs. 22.4 percent). 

Table 4-4. The majority of urban teachers used either Creative Curriculum or High/Scope curriculum

while the majority of rural teachers used Creative Curriculum

Creative Curriculum High/Scope Other 

Urban 31.4% 20% 48.6%

Rural 57.5% 20% 22.4%

4.3.2.3 Relationship Between Curricula and Classroom Quality 

The relationship between curricula and classroom quality was examined using independent 

samples t-tests on three different scores (weighted means) of classroom quality–ECERS-R Total score, 

ECERS-R Language subscale score, and a Quality Composite score. 

The ECERS-R Total score is derived from the ECERS-R, which provides a global rating of 

classroom quality based on structural features of the classroom. Scores can range from 1 (inadequate) to 

7 (excellent). As displayed in Table 4-5, the average ECERS-R Total scores for classrooms using

Creative Curriculum (5.02, t =3.70) and High/Scope curriculum (5.04, t =3.83) were significantly higher 

(p < .05.), than those for classrooms using other curricula (4.55). However, the average ECERS-R Total 

scores for High/Scope curriculum and Creative Curriculum were not significantly different from each

other. 

The ECERS-R Language subscale score is a subscale of the ECERS-R and assesses 

classroom quality as it pertains to encouraging language-reasoning experiences (Table 4-5). Scores can 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-5 March 06 
range from 1 (inadequate) to 7 (excellent). Classrooms of teachers who used Creative Curriculum and 

High/Scope curriculum had significantly higher average ECERS-R Language subscale scores (5.03, t = 

3.18 and 5.12, t = 3.64 respectively; p < .05) than classrooms of teachers using other curricula (4.58).

However, the average ECERS-R Language subscale scores of classrooms that used Creative Curriculum 

(5.03) and High/Scope curriculum (5.12) were not significantly different from one another. 

Table 4-5. The classrooms of teachers who used Creative Curriculum or High/Scope curriculum had 

significantly higher average ECERS-R total scores and ECERS-R Language subscale scores 

than classrooms of teachers who used other curricula 

Average ECERS-R total and Language subscale scores 

Curricula Average ECERS-R total score Average ECERS-R Language subscale scores 

Creative Curriculum 5.02 5.03 

High/Scope 5.04 5.12 

Other 4.55 4.58 

The Quality Composite score is derived from a principal components factor analysis of the 

ECERS-R Language subscale score, Assessment Profile Scheduling raw score, and Assessment Profile 

Learning Environment raw score. The standardized factor scores were calculated, so that the scores are in

standard deviation units, with a mean of 0 and a standard deviation of 1 (see Appendix for further 

description of the Quality Composite Score). As displayed in Table 4-6, the classrooms of teachers who 

used Creative Curriculum and High/Scope curriculum had significantly higher Quality Composite scores 

(0.27, t = 3.63 and 0.26, t = 3.26 respectively; p < .05) than classrooms of teachers using other curricula (-

0.18). The Quality Composite scores of classrooms that used Creative Curriculum (0.27) and High/Scope

curriculum (0.26) did not differ significantly from one another. 

Table 4-6. The classrooms of teachers who used Creative Curriculum or High/Scope curriculum had 

significantly higher quality composite scores than classrooms using other curricula 

Curricula Average quality composite score 

Creative Curriculum 0.27 

High/Scope 0.26 

Other -0.18 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-6 March 06 
4.3.2.4 Other Curricula and Classroom Quality 

In order to determine the relationship of curricula within the other category to classroom 

quality, other curricula have been further categorized as Widely Available Curricula and All Other 

Curricula. Widely Available Curricula include High Reach, Scholastic Curriculum, Newport Curriculum,

and Montessori. These curricula appear to be established (for example High Reach has been 

commercially available for about 17 years, Scholastic for more than 82 years, and Montessori for 96 

years), have information about the curricular goals and practices, printed materials, and in some cases 

have research available on their efficacy. All Other Curricula includes curricula not specified by teachers,

as well as curricula termed “Head Start,” Los Cantos Los Ninos, Theme Units, R.E.A.L, Global

Curriculum, Creating Child Centered Classrooms—Step by Step, Building Bridges, Early Childhood 

Lesson Plan, Curriculum Workbook, Northern Kentucky Curriculum, Teacher Planning Wellbook, 

Therapeutic Intervention Program, and Kid College Curriculum. This group of curricula appears to be 

designed by programs locally or from sources not widely available. 

The classroom quality scores for Widely Available Curricula, All Other Curricula, Creative

Curriculum, and High/Scope curriculum are presented in Table 4-7. The average ECERS-R Total scores

and average ECERS-R Language subscale scores for Creative Curriculum, High/Scope curriculum, and

Widely Available Curricula are similar although the Quality Composite score for Widely Available 

Curricula is lower. 

Table 4-7. Type of curricula and classroom quality scores 

Type of curricula used 

Weighted 

percentage 

of Head 

Start 

teachers 

Average 

total 

ECERS-R 

score SD 

Average 

ECERS-R 

language 

subscale 

score SD 

Quality

composite 

score SD 

Creative Curriculum 39.1 5.02 .92 5.03 1.32 0.27 .96 

High/Scope Curriculum 20.0 5.04 .73 5.12 1.01 0.26 .84 

Widely Available Curricula 9.8 4.82 .63 5.15 .96 0.07 .95 

All Other Curricula 31.1 4.47 .86 4.4 1.19 -0.27 .95 

Note: 

 Widely Available Curricula includes: High Reach, Scholastic Curriculum, Newport Curriculum, and Montessori; and 

 All Other Curricula includes: curriculum not specified, Head Start curriculum, Los Cantos Los Ninos, Theme Units, R.E.A.L, Global

Curriculum, Creating Child Centered Classrooms—Step by Step, Building Bridges, Early Childhood Lesson Plan, Curriculum Workbook, 

Northern Kentucky Curriculum, Teacher Planning Wellbook, Therapeutic Intervention Program, and Kid College Curriculum.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-7 March 06 
Multivariate analyses of variance were used to examine if the classroom quality scores were 

significantly different between classrooms using Creative Curriculum versus High/Scope curriculum, 

Creative Curriculum versus Widely Available Curricula, Creative Curriculum versus All Other Curricula,

High/Scope curriculum versus Widely Available Curricula, High/Scope curriculum versus All Other 

Curricula, and Widely Available Curricula versus All Other Curricula. Significant differences (p < .05) 

were found between classrooms using Creative Curriculum versus All Other Curricula on all three

classroom quality scores, as well as between classrooms using High/Scope curriculum versus All Other

Curricula on all three classroom quality scores. Classroom quality scores between classrooms using 

Widely Available Curricula versus All Other Curricula were not significantly different. 

 Classrooms using the Creative Curriculum when compared to classrooms using All 

Other Curricula had significantly higher average ECERS-R Total scores (5.02 versus

4.47), average ECERS-R Language subscale scores (5.03 versus 4.4), and Quality

Composite scores (0.27 versus - 0.27); 

 Classrooms using the High/Scope curriculum when compared to classrooms using All 

Other Curricula had significantly higher average ECERS-R Total scores (5.04 versus

4.47), average ECERS-R Language subscale scores (5.12 versus 4.4), and Quality

Composite scores (0.26 versus - 0.27); and 

 Classrooms using Widely Available Curricula were not significantly different from

classrooms using All Other Curricula. Classrooms using Widely Available Curricula

were also not significantly different from those using Creative Curriculum or those

using High/Scope curriculum. In addition, classrooms using Creative Curriculum were

not significantly different from those using High/Scope curriculum.

Overall, these findings suggest that classrooms using curricula such as Creative Curriculum 

and High/Scope curriculum have relatively higher classroom quality than Head Start classrooms using

other curricula. 

4.4 Summary of Findings 

Findings from FACES 2000 indicate that the great majority of Head Start programs use a 

curriculum, with the goal of providing a planned, developmentally appropriate early childhood program

for children. Most teachers reported using a single curriculum. The most frequently used curricula are the 

Creative Curriculum (39.1 percent) and High/Scope curriculum (20 percent). Further, 93 percent of

teachers reported receiving training in their curriculum, and 92 percent reported receiving ongoing 

support. Nearly all teachers (92.3 percent) reported liking their curriculum. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-8 March 06 
Data from FACES 2000 also indicate a relationship between program characteristics and the 

type of curriculum used. Specifically, classrooms using a curriculum other than the Creative Curriculum 

or High/Scope curriculum served the poorest Head Start families and the highest percentage of non-White 

children. There was also regional variation in curricula used by classrooms. More teachers from the

Northeast (78.7 percent), Midwest (59.4 percent), and West (69.4 percent) used either the Creative

Curriculum or High/Scope curriculum compared to any other type of curricula, while the majority of 

teachers from the South (54.4 percent) used a curriculum other than the Creative Curriculum or 

High/Scope curriculum. In addition, the majority of urban teachers (51.4 percent) used either the Creative

Curriculum or High/Scope curriculum, while the majority of rural teachers (57.5 percent) used Creative

Curriculum. 

Finally, findings demonstrate a relationship between type of curricula and classroom quality. 

Classrooms using Creative Curriculum and High/Scope curriculum had significantly higher ECERS-R

Total scores, ECERS-R Language subscale scores, and Quality Composite scores than classrooms using 

Other Curricula. However, the scores on these three measures for classrooms that used High/Scope

curriculum and Creative Curriculum were not significantly different from each other. Analyses were also

conducted separating the Other curricula category into Widely Available Curricula and All Other

Curricula. The average ECERS-R Total scores and average ECERS-R Language subscale scores for

Creative Curriculum, High/Scope curriculum, and Widely Available Curricula are similar although the

Quality Composite score for Widely Available Curricula is lower. Multivariate analyses showed

significant differences between classrooms using Creative Curriculum versus All Other Curricula on all 

three classroom quality scores, as well as between classrooms using High/Scope curriculum versus All 

Other Curricula on all three classroom quality scores. Classroom quality scores between classrooms using 

Widely Available Curricula versus All Other Curricula were not significantly different. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 4-9 March 06 
CHAPTER 5. 

QUALITY IN HEAD START CLASSROOMS 

This chapter examines the quality of Head Start classrooms in the FACES 2000 sample, in 

order to build a model that “unpacks” the critical ingredients of quality in Head Start by accounting for

explainable variation at the levels of the classroom and the Head Start center. The nature of quality in 

Head Start programs will be described and key factors will be identified that help explain variations in 

quality across Head Start classrooms. The results of these analyses should provide information for 

improving quality in Head Start classrooms and general program improvement. Findings about the 

relationship between classroom quality and child outcomes are described in Chapters 6 and 7. 

5.1 Conceptual Framework and Research Questions 

The conceptual framework for this chapter is based on a multi-level, multi-causal model of 

the factors that explain variations in classroom quality. The model is presented in Figure 5-1 and 

describes a multi-level perspective on understanding or “unpacking” quality in Head Start classrooms. 

There are a variety of indicators of quality in early childhood educational settings cited in the 

research literature (Phillips, Mekos, Scarr, McCartney and Abbott-Shim, 2000). In addition to “structural” 

indices, such as child:staff ratio (Cost, Quality and Outcome Studies Team, 1995; Howes, Phillips, and 

Whitebook, 1992) and group size (Ruopp, Travers, Glantz and Coelen, 1979), the backgrounds and

experiences of early childhood teachers are important (Cost, Quality and Outcome Studies Team, 1995).

Additionally, a variety of “process” aspects of the classroom environment have been considered

important, including teacher-child interactions, child-child interactions, as well as curriculum, the

schedule of activities and materials (Bredekamp, 1986; Hayes, Palmer and Zaslow, 1990; Phillips and 

Howes, 1987; Scarr and Eisenberg, 1993). 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-1 March 06 
FACE

 

Head Start Program -Characteristics of Families Served: 

-Percent Non-minority-Percent La

nguage Minority

-Percent Parents with some College E

xperience 

 -Percent Parents Ear

ning $1500/month or higher

-Average Annual Teacher Salary (Program) 

Teacher Attitudes andKnowled

ge

-9-Item Attitu

des and

 Knowledge Scale 

Classroom Process Quality -ECERS-R Total Score 

-Quality Co

mposite 

-Assessment Profile Learni

n

g Environ

-Assessment Profile Schedulin

g

-Assessment Profile In

dividualizin

g

Teacher E

ducati

on and

Experience -Years Teaching Overall 

 (Head Start and other) -B

A, AA Only 

-Teacher Salary  (Derivation from 

Program Mean) Classr

o

om Structural Q

ual

-Child:Ad

ult Ratio

Teacher-Child Interactions-Arnett Caregiver Interaction 

Primary Curriculum (Majorit

y

of 

-High/Scope C

urricul

u

m

-Creative C

urriculum

-Other/No C

urriculum

PROGRAM LEVEL

CLASSROOM LEVEL

Teacher B

ackgrounds 

-Ethnicity

(African-American, Hispa

nic)

Quality of L

angu

age/

Literacy E

n

-EC

E

RS-R Language Score 

Figure 5-1. A conceptual model of program- and classroo

m-level factors explaining qualit

y i

n Head S

___________________________________________________________________________________________________________________________________

S 2000 Technical Report 5-2 March 06 
However, the search for understanding the mechanisms by which process, structural and 

teacher indicators influence quality has been relatively sparse and based more on logical assumptions than

empirical evidence. For example, lower child:staff ratios (e.g., more staff per child) are assumed to create

the conditions that support developmentally beneficial teacher-child interactions (Phillips, Mekos, Scarr,

McCartney and Abbott-Shim, 2000). Although the empirical literature supports this connection (Phillips, 

Howes and Whitebook, 1992), only modest amounts of variance can be explained (Scarr, Eisenberg and 

Deater-Deckard, 1994). Little is known about how different indicators of quality in varying levels

contribute to overall classroom quality. For example, the possible compensatory effect of more optimal 

levels on one indicator, such as child:staff ratios, on less favorable levels of other indicators, such as staff 

training is not known (Phillips, Mekos, Scarr, McCartney and Abbott-Shim, 2000). 

Furthermore, factors “beyond the classroom door” may have potentially powerful influences 

on children’s experiences of quality care in early childhood classrooms. Some of the factors suggested 

consist of the additional resources available to early childhood settings and the broader context within

which these programs are situated (Blau, 1997; Hofferth and Chaplin, 1998 cited in Phillips, Mekos, 

Scarr, McCartney and Abbott-Shim, 2000). Program management styles, resources, and the demographics

of the community may influence decisions about quality made by center directors (e.g., the quality of

teachers that can be recruited) and, indirectly, by teachers in individual classrooms. 

Although factors that exist beyond the classroom are typically difficult to measure in early 

childhood settings, the organizational structure of Head Start in which classrooms are located within

centers, which in turn are located within a grantee or program, lends itself to the examination of this kind 

of factor. Head Start programs consist of the grantee and delegate agencies that administer the centers and

classrooms within their purview. A program comprises the administrative entity primarily responsible for

determining budgets, staffing, and the allocation of resources across centers and classrooms, as well as for

choosing curricula for its classrooms and providing training and resources to support the curricula. 

Programs also define the geographic areas they serve and identify the needs of low-income families and

children living there. 

The FACES Third Performance Measures Report used FACES 1997 data to describe how 

classroom quality varies across classrooms and across programs suggesting that factors at the level of the 

Head Start program, in addition to those at the classroom level, may help to explain variations in quality 

(Administration for Children and Families, 2001). Thus, in developing a comprehensive model for 

understanding the many sources of influence on classroom quality, it is important to look at factors at 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-3 March 06 
both the classroom and the program levels. While some of the program-level factors were identified in 

earlier rounds of FACES, it was only with the FACES 2000 data that additional factors at the level of 

program were collected. 

FACES 2000 employed similar measures as those used in the earlier cohort in order to make 

some comparisons in quality, but several key measures were added. Quality was considered to include not

only the number of children and adults in each classroom, but process factors such as the availability of 

learning materials, the types of classroom activities, the scheduling and the variety of learning 

opportunities provided to all children. Many of the newer factors were collected through the lead teacher

interview,1

 including teacher background information (experience and qualifications) as well as more

detailed information about their curriculum, classroom activities, and attitudes and knowledge about early

childhood education practices. The classroom quality measures are fully described in the Appendix. 

The following research questions guided the analyses in this chapter: 

 What is the quality of Head Start classrooms in 2000-2001, and how does it compare 

to quality reported in 1997-1998? 

 What are the backgrounds, qualifications and experiences of Head Start teachers in 

2000-2001 and were there any changes from the earlier cohort (1997-1998)? 

 How are teaching qualifications and experience related to attitudes and knowledge of 

early childhood education and how are these factors linked to quality in Head Start 

classrooms? and 

 Do factors beyond the classroom such as the types of curricula Head Start programs 

provide, the average teacher salaries, and characteristics of families served by the

Head Start program explain variations in the quality of Head Start classrooms?

5.2 Analytic Methods 

This chapter used a number of classroom quality measures, described more fully in the

Appendix. The variables derived from these measures that were used in the analyses of classroom quality

are as follows: 

1

 The results of teacher data presented in this chapter were based on interviews and ratings of the lead or senior teacher in each classroom.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-4 March 06 
 ECERS-R Total Score. The mean of the 37 ECERS-R items2

 coded on a 7-point

scale with a score of 1 representing “inadequate”, a score of 3 representing “minimal 

quality,” a score of 5 representing “good quality,” and a score of 7 representing 

“excellent quality.” The internal consistency of the ECERS-R mean score for all 37 

items was .92 for both Fall 2000 and Spring 2001, and .89 for Spring 2002 (Head 

Start). A high score on the total ECERS-R indicates higher classroom quality, in terms 

of equipment, space and play materials, as well as the range of learning activities,

supervision, and staff-child interactions; 

 ECERS-R Language Subscale Score. The mean of 4 ECERS-R items related to

language quality in classrooms, including informal use of language, books and

pictures, encouraging children to communicate, and using language to develop

reasoning skills. Scores range from 1 to 7, with high scores indicating a classroom 

with a rich language environment; 

 Assessment Profile Scheduling Scale Score. The score consists of the sum of the 14 

observation items, each with yes/no response formats. Raw scores used in these 

analyses ranged from 3 to 14. A high score is indicative of a teacher’s “planfulness”

and strategy for providing varied learning activities in whole groups, small groups,

and one-on-one. The reliability of the Scheduling subscale was reported as .89 for Fall

2000, .87 for Spring 2001, and .82 for Spring 2002; 

 Assessment Profile Learning Environment Scale Score. This score consists of the 

sum of the 18 observation items in this scale, with each item scored yes or no. Raw

scores used in these analyses ranged from 4 to 18. A high score on this scale is

indicative of a greater variety of materials accessible, that stimulate growth in a 

variety developmental domains in a “learning rich” environment. The reliability of the 

Learning Environment subscale was reported as .68 for Fall 2000, .77 for Spring 

2001, and .65 for Spring 2002; 

 Assessment Profile Individualizing Scale Score. This score is comprised of the sum 

of five observational items with raw scores ranging from 0 through 5. A high score 

indicates that teachers are able to adjust classroom activities to meet the learning

needs of individual children. The reliability of the Individualizing subscale was 

reported as .50 for Fall 2000, .54 for Spring 2001, and .44 for Spring 2002; 

 Arnett Caregiver Interaction Scale for the Lead Teacher. This score is the sum of

30 items each with four-point responses asking observers to rate the teacher according 

to a fixed descriptor either “not at all,” “somewhat,” “quite a bit,” or “very much.”

Although there are five subscales measuring the teacher's sensitivity, punitiveness,

detachment, permissiveness, and encouragement of child independence and self-help 

skills, in the foregoing analyses we primarily focus on the total score (since all 

subscales are highly correlated with this score). Scores ranged from 20 to 89 on this

measure. A high score indicates greater teacher sensitivity, responsiveness and

encouragement of children’s independence and self-help skills, and lower levels of 

2

 FACES did not use 6 items that comprise the Parents and Staff subscale. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-5 March 06 
punitiveness and detachment. The Cronbach Coefficient Alphas for all of the items 

were .94 for both Fall 2000 and Spring 2001, and .93 for Spring 2002; 

 Quality Composite. Using a principal components factors analysis, scores from the 

ECERS-R Language subscale, and the Assessment Profile Scheduling and Learning 

Environment scales were combined to form a single quality factor score. The quality 

factor score was standardized with a mean of 0 and a standard deviation of 1, and 

scores ranged from -3.57 to 1.90. A higher score indicates higher levels of quality; 

 Child:Adult/Child:Staff Ratio. This is a number obtained by dividing the number of 

children present in the class by the number of adult teachers, aides, or volunteers who

were actively interacting with the children. Observers counted children and adults at 

two different times during their observation session and ratios were averaged over all 

classes visited in a given center. In addition, the observers took counts of the number 

of children present in the class and the number of adult teachers, aides, or volunteers

who were actively engaged with the children. A higher ratio is indicative of lower 

quality, since this indicates there are more children with fewer adults; 

 Teacher Backgrounds and Qualifications. A set of variables were derived from the 

teacher interview that assessed the teachers’ backgrounds, qualifications and teaching 

experience. Continuous variables included: annual salary, years teaching Head Start, 

total years of teaching experience, and teacher age. A variety of variables were also

binary coded 0 or 1 to allow for comparisons of proportions across time and between

groups. Based on information in the teacher interview, variables were coded 1 for 

teachers who had: 

- CDA or state-awarded certificate; 

- AA degree or higher; 

- BA or AA degree; 

- BA degree or higher; 

- Teaching certificate or license; 

- Field of study in their highest degree obtained included Early Childhood

Education; 

- Member of an Early Childhood Education association; 

- Teaches in Spanish; 

- Teaches in a language other than English or Spanish;

- African American, Latino or Asian (three separate variables); 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-6 March 06 
- Currently enrolled in teacher related training; or 

- Primary curriculum is High/Scope curriculum or Creative Curriculum (two

separate variables). 

 Teacher Attitudes and Knowledge Score. This score was derived from a single 

factor consisting of 9 items from the 24-item Teacher Beliefs Scale that explained 

most of the variation in scores for the entire scale. Each item used a five-point Likert

scale from 1 (strongly disagree) to 5 (strongly agree) with negatively-worded items 

reverse scored. The 9 individual items were then combined to form the composite 

score with a minimum value of 1 and a maximum value of 10. A high score indicates 

higher positive attitudes and knowledge about early childhood education practices. 

To answer the first three research questions, a number of descriptive and correlational 

analyses were conducted. To answer questions about change in quality and teacher backgrounds, 

qualifications or experiences from the first to the second cohorts, and to determine change in quality from

Fall to Spring of the Head Start year, t-tests using the continuous (e.g., ECERS-R score, years of 

teaching) and the binary coded teacher variables (e.g., whether teacher had a BA or AA degree) were

employed. Specifically, analyses of the binary coded variables used t-tests on independent samples to

compare the proportions of “1” responses for each variable across the two time periods in question. To

assess differences over time in categorical data, chi-square tests were used. However, since a significant 

chi-square statistic only indicates there was significant change over time but not where those changes 

occurred, that is, which of the categories was the source of the change, significant chi-square analyses

were supplemented by binomial tests of the differences between proportions across time periods using 

unweighted data. This latter test allows for a comparison across time in the proportions for a specific 

response category.

Most descriptive statistics were derived from the weighted data wherever possible, with the 

exception of the Fall 1997–Spring 1998 data (first cohort) and Spring 2002 data,

3

 where unweighted data

were used. Analyses involving the first cohort data were all done using unweighted data because

classroom weights were not developed for this cohort. Comparisons of Spring 2002 data with the earlier 

waves were done using only the unweighted data. 

3

 The Spring 2002 data were based on a much smaller number of classrooms, because most of the children in the sample had graduated to

kindergarten. The Spring 2002 classrooms consisted only of those in which FACES study children were still attending in their second year of 

Head Start. The Fall 2000 weights and the longitudinal weights were not considered appropriate for this small subsample and thus the

unweighted data were analyzed. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-7 March 06 
To answer research question #4, a multi-level approach with two levels of factors: program 

and classroom4

 was used. This approach determines the joint influence of both program- and classroomlevel factors in predicting classroom quality, by testing models for explaining quality in Head Start 

(see Figure 5-1). The first level of the model, the classroom (N=258), included the following predictors:

Teacher having a Bachelor’s or Associate’s degree, teacher attitudes and knowledge, years of teaching

experience, ethnicity and the teacher’s salary as a deviation from the national average teacher salary of 

the Head Start program. The second level of the model, the program (N=43), included several variables 

describing the characteristics of families served by the Head Start program, the primary curriculum used

by the program for all its classrooms (High/Scope curriculum, Creative Curriculum, or other/none), and 

the average of teacher salaries. Characteristics of the families enrolled in the program included: the 

percentage of parents with some college, the percentage of parents earning $1500/month or more, the 

percentage of non-minority children attending the program, and the percentage of language-minority 

children attending the program. The dependent variables consisted of the Fall 2000 quality scores, 

summarized earlier. Separate multi-level models were performed for each of these dependent variables. 

During the Fall 2000 data collection period, which operated from September 2000 to

December 2000, classroom quality and teacher data were obtained from 225 Head Start centers in 43

programs around the country. In Fall 2000, 278 classrooms were observed, from a possible 286

classrooms, for a completion rate of 97 percent.5

 In Spring 2001, 275 classrooms were observed out of 

284 in the sample for a completion rate of 97 percent.6

 Finally, in Spring 2002, 204 classrooms were 

observed with sample children who were enrolled in Head Start for a second year (those who were three 

years of age in Fall 2000). 

On the quality measures, agreement between two independent observers in a sample of 

classrooms during Fall 2000 averaged 93.5 percent for the Assessment Profile Scheduling Scale, 

87.9 percent for the Assessment Profile Learning Environment Scale, and 86.7 percent for the Assessment

Profile Individualizing Scale. Percent agreement across all ECERS scales (which includes direct hits and

being off by one on a seven-point scale) averaged 79.5 percent, agreement on the ECERS-R Language 

subscale averaged 85.7 percent, and agreement on the Caregiver Interaction Scale averaged 93.9 percent. 

4

 The PROC MIXED statistical procedure in SAS, as outlined by Singer (1998), was used. 

5

 Due to some missing data among one or more of the quality indicators, the analytic sample was comprised of 258 classrooms. 

6

 Due to missing data, the analytic sample was comprised of 256 classrooms.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-8 March 06 
5.3 Findings 

5.3.1 What is the Quality of Head Start Classrooms in 2000-2001, and How Does it Compare 

to Quality Reported in 1997-1998? 

In FACES 2000, quality in Head Start classrooms continues to be good and above that found 

among other center-based preschools. Figure 5-2 compares the two FACES cohorts with other studies 

using the overall ECERS or ECERS-R score as the measure of quality. Not only is the average score

higher, but the variation is less than that found in many other preschool settings.7

The Early Childhood Environment Rating Scale (ECERS-R). In FACES 2000, the

overall average ECERS-R score for the 258 classrooms observed in Fall 2000 was 4.84 (with a standard

deviation of .87). This compares with an overall average ECERS (the original scale) score of 4.93 (with a 

standard deviation of 0.63) for the 518 classrooms in the first FACES cohort (Fall 1997). While the

FACES 2000 average score is comparable to that found earlier, the variability in the scores was higher, 

and approached that reported by the test developers for the revised measure. Since this comparison

involved scores on the original ECERS and the revised ECERS, it is also hard to interpret any changes, 

because little is known of how the two measures are calibrated. In Spring 2001, the average ECERS-R 

total score remained virtually the same at 4.83 (standard deviation of 1.0). Thus, while the means 

remained the same from Fall to Spring, the variation in the quality scores increased, with a Spring 2001 

standard deviation of 1.00 (from 0.84 in Fall 2000). In Spring 2002, with the reduced sample of

classrooms, the ECERS-R total score averaged 4.84 with a standard deviation of 0.86, almost identical to 

the scores found for the total sample in Fall 2000. Overall, the average scores are consistent and indicate 

that Head Start classrooms continue to show good quality. 

Table 5-1 compares the FACES 1997 and FACES 2000 cohorts on the ECERS/ECERS-R 

total score, with 1 indicating “inadequate” quality and 7 indicating “excellent” quality. The chi-square test

for differences between the proportions of classrooms in the two cohorts was statistically significant

(chi-square = 26.8234, df = 5, p < .0001) indicating significant differences from 1997 to 2000 in the

proportion of classrooms rated from inadequate to excellent in quality. In FACES 1997, no classrooms 

were scored in the “inadequate” range (1 or 2) and only 4 of 518 classrooms were scored in the “minimal”

7

 It should be noted that, with the exception of the New Jersey study, all other studies used the original ECERS, and at this writing there are no 

published reports attesting to the appropriateness of comparing scores on the two versions.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-9 March 06 
FACE

 

___________________________________________________________________________________________________________________________________

S 2000 Technical Report 5-10 March 06 4

4.20 4.50 4.50 4.62 4.84 4.90 4.93 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Head Start FACES Fall 1997

(518 classroo

ms)

ECERS

39 Head Start

classroo

ms

(Layzer et al,

1993) E

C

E

RS

Head Start

FACES Fall 2000

(258 classroo

ms)

ECERSR

246 New Jersey

Abbott

Community-

/School-based

Centers (2001)

ECERSR

38 School-based

Centers (Layzer

et al, 1993)

ECERS

50 Non-profit

Child-care

Centers (

Cost,

Quality and

Outco

mes Study,

1995) E

C

E

RS

42 Child-care

Centers (Layzer

et al, 1993)

ECERS

120 Presch

Centers (Sc

al, 1992) E

C

Mean ECERS Score 

Minimal Qualit

y

Variability defined as +/- 1.5 SD's. It should be noted that studies published after 2001 used ECERS-R whereas all others used the original ECERS.

Figure 5-2. Classroo

m quality in Head Start co

mpared with other preschool and child care settings 
range (score of 3). In FACES 2000, using the revised version of the ECERS which more strictly

differentiated the highest and lowest ends of the scale, in Fall 2000, five classrooms (1.9 percent) were

scored in the “inadequate” range and 15 of the 258 classrooms (5.7 percent) scored in the “minimal”

range. A comparison of the proportions of classrooms that were rated “inadequate” from Fall 1997 and 

Fall 2000 reveals a non-significant difference (z = -000003), and the increase in classrooms rated 

“minimal” (from 0.8 percent to 5.7 percent) also did not reach statistical significance (z = -1.50). 

However, when combined, the number of classrooms rated “minimal” or lower (ECERS/ECERS-R scores

of 3 or lower) increased significantly from 0.8 percent to 7.6 percent (z = -2.12, p < .05). Thus, compared

to the earlier cohort, in FACES 2000 significantly more classrooms were rated lower in quality, but lowscoring classrooms still represented only 20 of 258 classrooms overall. On the other hand, the number of

classrooms rated “excellent” (ECERS/ECERS-R scores of 6 or higher) increased significantly from

FACES 1997 to FACES 2000 (z = -3.31, p<.01). In FACES 1997, there were 97 out of 518 (18.7 percent) 

classrooms rated “excellent” while in FACES 2000, 56 out of 258 classrooms (21.6 percent) were rated

“excellent.” 

Table 5-1. Comparison of ECERS/ECERS-R categorical scores, Fall 1997, Fall 2000 and Spring 2001, 

percent of classrooms

ECERS Score category

Fall 1997* 

(N=518) 

Fall 2000 

(N=258) 

Spring 2001 

(N=264) 

Spring 2002 

(N=202) 

1 “Inadequate” 0.0 0.0 0.0 0.0 

2 0.0 1.9 2.3 1.5 

3 “Minimal” 0.8 5.7 10.1 4.5 

4 26.8 22.8 21.4 23.8 

5 “Good” 53.7 48.1 36.7 50.5 

6 18.1 20.9 28.0 18.3 

7 “Excellent” 0.6 0.7 1.7 1.5 

Total percentage 100 100 100 100 

*Fall 1997 used the ECERS, whereas the ECERS-R was used in all other time periods.

A further comparison was done of the classrooms in the FACES 2000 sample, looking at any

shifts in classroom quality from Fall to Spring (Table 5-1). The chi-square test for differences between the 

proportions of classrooms from Fall to Spring was statistically significant (chi-square = 11.27, df = 5, 

p < .05) indicating significant differences in proportion of classrooms rated from inadequate to excellent

in quality from Fall to Spring of the same Head Start year. The proportion of classrooms in the lowest 

category (ECERS-R score of 2) increased slightly, from 1.9 percent in Fall 2000 and 2.3 percent in Spring

2001, but the differences did not reach statistical significance levels. However, there was a statistically 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-11 March 06 
significant increase in the proportion of classrooms rated a score of 3 for minimal quality, from 

5.7 percent in Fall 2000 to 10.1 percent in Spring 2001 (z = -2.15, p < .05). When looking at the

proportion of classrooms rated minimal or lower (ECERS-R scores of 3 or lower), there was a statistically

significant increase from Fall to Spring, from 7.6 percent to 12.4 percent (z = -2.66, p < .01). There were 

also significantly fewer classrooms receiving a rating of 5 indicating good quality, from 48.0 percent in 

Fall 2000 to 36.4 percent in Spring 2001 (z = 13.49, p < .001). The Fall-to-Spring increases in the 

proportion of classrooms at the lower end of the quality scale were also mirrored by increases in the 

proportion of classes rated 6 or 7 for “excellent” quality. There was a statistically significant increase in

the proportion of classrooms rated 6, from 20.9 percent in Fall to 28.4 percent in the Spring (z = -6.66, 

p < .001), although the increase in the percentage of classrooms rated 7 for “excellent” from 0.7 percent 

in the Fall to 1.7 percent in the Spring was not statistically significant. Overall, the proportion of

classrooms rated “excellent” (ECERS-R scores of 6 or higher) increased significantly from 21.6 percent

in Fall 2000 to 30.1 percent in Spring 2001 (z = -7.70, p < .001). Overall, it would appear that the slight 

shifts in categories reflects a movement towards both ends of the distribution in classroom quality, since 

the mean ECERS-R score remained almost the same from Fall to Spring. 

Assessment Profile Scheduling, Learning Environment and Individualizing Scales. On

the Scheduling scale, the raw scores were virtually identical from FACES 1997 to FACES 2000 (average 

raw scores of 11.17 in Fall 1997 and 11.12 in Fall 2000). In Spring 2001, the mean Scheduling score was 

10.99, and in Spring 2002, with the reduced sample of classrooms, the mean Scheduling score was 11.39. 

The differences from Fall 2000 to Spring 2001 and Spring 2002 were not statistically significant. On the 

Learning Environment scale, the raw scores over the two cohorts were not significantly different (13.46 in

Fall 1997 vs. 14.44 in Fall 2000). In Spring 2001, the Learning Environment mean score was 14.14 and in

Spring 2002 the Learning Environment mean score was 14.63. The difference between the Fall 2000 and

Spring 2001 Learning Environment scores was not statistically significant. However, the difference 

between the Spring 2001 and Spring 2002 scores was statistically significant, indicating an increase in the 

quality of learning materials in Head Start classrooms in the second year (t=3.41, p < .001). As well, from 

Fall 2000 to Spring 2002, Learning Environment raw scores increased significantly (t=2.07, p=.04).

Finally, on the Individualizing Scale, a new measure in FACES 2000, the average raw score was 3.58 (out 

of a maximum raw score of 5), with a standard deviation of 1.2, indicating that overall Head Start

classrooms provide an environment that takes into account the learning needs of individual students, but 

there is room for improvement. In particular, in Fall 2000 on the Individualizing Scale, 60 percent of 

classrooms maintained portfolios on individual children but only 37 percent of classrooms provided 

opportunities for children to evaluate their work, or to decide which products are included in their 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-12 March 06 
portfolios. However, with regard to the inclusion of children with disabilities, and making

accommodations to allow these children to be included in classroom activities, 94 percent of classrooms 

were rated as having full inclusion and 90 percent of classrooms had provisions for accommodating

children with special needs. In Spring 2001, the Individualizing raw score averaged 3.47, which was a 

statistically significant decrease from Fall 2000 (t=-2.22, p=.03). The Spring 2002 raw score averaged

3.52, which was not a statistically significant difference from either the Fall 2000 score or the 

Spring 2001 score. 

Arnett Caregiver Interaction Scale. On this scale, measuring the sensitivity and 

responsiveness of teachers in Head Start classrooms, the average score for Fall 2000 was 71.5, almost

identical to the score of 71.3 in FACES 1997. In Spring 2001, the average score was 72.24 and in

Spring 2002, for the subsample of 201 classrooms, the average score was 73.65. Again, although the

scores appear to increase from Fall 2000 to Spring 2001, the differences did not reach levels of statistical

significance according to t-tests on the weighted means. Further, the differences between the Fall 2000 

and the Spring 2002 means were also not statistically significant. 

Summary of Changes in Process Quality Indicators Over Time. Comparisons across the

two cohorts, FACES 1997 and 2000, revealed that, for all measures of classroom quality – the ECERS, 

the Assessment Profile scales and the Arnett Caregiver Interaction Scale – scores were consistent. Thus, it 

could be concluded that, in general, quality in Head Start classrooms was consistent over the two cohorts 

of classrooms, from 1997 to 2000. 

When looking at changes in quality from Fall to Spring of FACES 2000 across a variety of 

indicators, very few of the differences reached levels of statistical significance. There was a statistically

significant decrease in the Assessment Profile Individualizing raw score from Fall 2000 to Spring 2001, 

indicating a decrease in the focus on monitoring children’s performance and adjusting the program to 

meet individual needs of each child. For the subset of classrooms observed in the second year of 

FACES 2000 (Spring 2002), most scores did not change significantly from the prior year. The only

noteworthy difference was in the quality of the learning materials and literacy environment in the 

classroom, according to the Assessment Profile Learning Environment scale, in which the scores 

increased, indicating increased quality, from Spring 2001 to Spring 2002 and from Fall 2000 to 

Spring 2002.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-13 March 06 
Child:Adult Ratio. The average child:adult ratio for the FACES 2000 Head Start 

classrooms was 5.4 children per adult in Fall 2000, 5.7 in Spring 2001, and 6.1 in Spring 2002. These 

ratios compared with 6.3 children per adult at the Fall 1997 observation and 6.2 children per adult during 

the Spring 1998 observation.8

 Looking only at paid staff, the FACES 2000 cohort classrooms averaged

6.5 in Fall 2000, 6.4 in Spring 2001 and 6.8 in Spring 2002. Using weighted t-tests comparing the Fall 

2000 and Spring 2001 means, the average child:staff ratios were not significantly different. However, the 

average child:adult ratio increased significantly from Fall 2000 to Spring 2001, indicating a decrease in 

quality (t=2.66, p=.008). The differences between Spring 2001 and Spring 2002 were not statistically

significant and neither were the differences from Fall 2000 to Spring 2002 (likely due to the use of

unweighted data in these comparisons with higher standard errors). The child:adult ratios were also lower

than those found for Fall and Spring of the FACES 1997 cohort. The difference in these ratios suggests 

the important influence of volunteers on improving child:adult ratios in Head Start classrooms (lower

ratios indicate higher quality). Despite a decline from Fall to Spring in FACES 2000, these ratios are far 

better than the NAEYC accreditation standard of eight or fewer three-year-olds or 10 or fewer four-yearolds for each adult and exceed the Head Start Program Performance Standards of 7.5 to 8.5 or fewer

three-year-olds or 10 or fewer four-year-olds per adult. 

Curricula. Teachers were asked at each interview what types of curricula they use and 

which curriculum is their primary curriculum. In Fall 2000, 91 percent of teachers reporting using a 

primary curriculum, with 23.5 percent of all teachers using the High/Scope curriculum and 41.3 percent

using the Creative Curriculum. In Spring 2001, 93 percent of teachers reported that they used some type 

of curriculum, which represents a statistically significant increase from Fall 2000 in the use of any 

curriculum (z = -3.48, p < .01). In Spring 2001, 45.2 percent reported using the Creative Curriculum and

19.5 percent reporting the High/Scope curriculum. Compared to Fall 2000, in Spring 2001 more teachers 

reported using the Creative Curriculum (z = -4.55, p < .001) while fewer reported using the High/Scope 

curriculum (z = 3.24, p < .01). 

8

 In Fall 1997, only the total number of adults in the classroom was measured, so that the discrepancy between 1997 and 2000 could be due to the

slightly different measurement methods. In the remaining analyses in this chapter, the child-adult ratio rather than the child-staff ratio will be 

used, to remain consistent with the earlier cohort. In fact, the two measures are so highly correlated that results of statistical analyses using each 

will be almost identical. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-14 March 06 
In Spring 2002, 97.5 percent of teachers reported using a curriculum, significantly more than 

the 93 percent in Spring 2001 (z = -5.88, p < .001). In Spring 2002, 48.7 percent of teachers reported

using the Creative Curriculum and 15.5 percent reported using the High/Scope curriculum. Using 

binomial tests comparing these proportions with those from Spring 2001, there was a significant decrease 

in the proportion of teachers reporting use of the High/Scope curriculum (z = 4.66. p < .001) and a

significant increase in the proportion of teachers reporting use of the Creative Curriculum (z = -7.29, p < 

.001). 

In general, from Fall to Spring of the same Head Start year there is an increase in the

proportion of teachers reporting the use of one of the two most widely used integrated curriculum –

Creative Curriculum and High/Scope curriculum – and the increase continues into the Spring of the

following year when as many as 97.5 percent of teachers reported using one of the two most widely used 

integrated curriculum – Creative Curriculum and High/Scope curriculum. At the same time, when

teachers were asked whether they use two of the most popular curricula, there was a steady decline in the 

proportion who reported using the High/Scope curriculum along with a steady increase in the proportion 

who reported using the Creative Curriculum, from Fall 2000 through to Spring 2001. 

5.3.2 What are the Backgrounds, Qualifications and Experiences of Head Start Teachers in

2000-2001 and were there any Changes from the Earlier Cohort (1997-1998)? 

In FACES 2000, Head Start teachers overall are experienced and qualified (see Tables 5-2 

and 5-3) and these findings are consistent with the prior cohort. In Fall 2000, teachers in Head Start 

classrooms have been teaching in Head Start for an average of 7.9 years and they have been teaching for 

an average of 11.8 years in all educational settings. These data are almost identical to those reported for 

the earlier cohort, Fall 1997 (7.5 years teaching Head Start and 11.7 total years teaching, reported in the 

Third Progress Report, Administration for Children and Families, 2001). 

In later waves of FACES 2000 (Spring 2001 and Spring 2002), the average years teaching

were consistent (Table 5-3). In Spring 2001, the average number of years teaching Head Start was 7.95 

and 11.7 total years teaching, whereas, one year later, teachers averaged 8.5 years of teaching Head Start

and 12.1 total years teaching. Again, these differences did not reach levels of statistical significance. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-15 March 06 
Table 5-2. Comparison of lead teacher backgrounds, FACES Fall 1997 through Spring 2002 

Fall 1997 

(N=437) 

Fall 2000 

(N=257) 

Spring 2001 

(N=264) 

Spring 2002 

(N=202)* 

Years Teaching Head Start 

 1-2 Years 14.2 21.1 23.4 19.8 

 3-4 Years 22.7 23.5 18.7 16.8 

 5-9 Years 34.1 27.6 29.3 33.5 

 10+ Years 29.0 27.8 28.6 30.0 

 Total 100.0 100.0 100.0 100.0 

Highest Level of Education 

High School or Equivalent 10.8 10.4 12.1 11.5 

 Some College 31.4 32.2 32.5 31.5 

 Associate’s Diploma 29.8 18.6 17.3 21.0 

Bachelor’s Degree or equivalent 24.9 27.8 28.1 29.0 

Graduate or Professional Degree 3.2 10.9 10.0 7.0 

 Total 100 100 100 100.00 

Teacher Age Category

 18-29 14.7 14.9 12.5 14.2 

 30-39 33.3 33.4 34.8 33.0 

 40-49 31.8 28.3 26.6 34.5 

 50-59 15.9 16.3 18.4 12.7 

60 or Older 4.3 7.1 7.8 5.6 

 Total 100 100 100 100 

Member in Early Childhood Education 

Association 

 No 47.1 38.0 38.7 49.0 

 Yes 52.9 62.0 61.3 51.0 

 Total 100 100 100 100 

Child Development Associates (DCA) 

Certificate or Equivalent 

 No 23.9 26.0 28.4 34.0 

 Yes 76.1 74.0 71.6 66.0 

 Total 100 100 100 100 

Teacher Ethnicity

 White, non-Hispanic 41.1 48.1 47.8 51.5 

African American, non-Hispanic 34.2 33.7 33.7 28.5 

 Hispanic** 22.4 15.4 14.9 16.5 

 Asian 2.3 1.2 1.2 2.0 

 Multiple Race/Other NA 1.7 2.4 1.5 

 Total 100 100 100 100 

*Spring 2002 data are unweighted. No longitudinal weights for these classrooms were derived because they constitute only those classrooms

where sampled children were three years of age in Fall 2000 and were attending a second year of Head Start.

**Puerto Rico was represented in FACES 1997, but not in the FACES 2000 sample, explaining the lower percentage of Hispanic teachers in this

later cohort (2000).

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-16 March 06 
Table 5-3. Comparison of teacher experiences and qualifications, Fall 2000 through Spring 2002 

Means or proportions (weighted) 

Fall 2000 

(N=257) 

Spring 2001 

(N=264) 

Spring 2002 

(N=202)* 

Total Annual Salary (Mean Dollars) 20,750 20,823 21,727 

Age in Years (Mean) 41.4 41.9 41.0 

Total Years Teaching (Mean) 11.8 11.7 12.1 

Years Teaching in Head Start (Mean) 7.9 8.0 8.5 

Has a CDA (%) 58.0 55.8 58.3 

Has a CDA or State-Awarded Certificate (%) 74.0 71.6 66.0 

Has AA Degree or Higher (%) 57.0 54.9 57.0 

Has BA or AA Degree (%) 41.0 39.2 43.0 

Has BA Degree or Higher (%) 39.0 38.1 36.0 

Has Teaching Certificate or License (%) 34.0 34.1 35.4 

Field of Study Includes Early Childhood Education (%) 86.0 86.6 87.7 

Currently enrolled in Teacher Related Training (%) 45.0 46.5 28.2 

*Spring 2002 data are unweighted. No longitudinal weights for these classrooms were derived because they constitute only those classrooms

where sampled children were three years of age in Fall 2000 and were attending a second year of Head Start.

The average amount of time teachers have spent in Head Start relative to their total years in 

teaching reflects that teachers spent most of their teaching careers in Head Start classrooms. However,

there was a relatively wide range of experience in teaching Head Start that the average scores obscure. In

Fall 2000, approximately 21 percent of the Head Start teachers were relatively new, having been teaching

in Head Start for less than two years, and 28 percent had taught in Head Start for 10 years or more. The 

Spring 2001 and Spring 2002 data for the same cohort are not substantially different and reflect slight 

effect of the cohort as its members age across time, that is, fewer teachers were “new” in the following 

year and more teachers entered the older experienced group. 

When teacher backgrounds in FACES 2000 were compared with the backgrounds of

teachers in the earlier Fall 1997 cohort, several statistically significant differences emerged.9

 There was a 

statistically significant different in the number of years teaching in Head Start in Fall 2000 compared with

Fall 1997 (chi-square = 8.38, df = 3, p < .05). Looking at the proportions in the two cohorts, there was an

increase in the proportion of teachers who had taught for less than 2 years from 14 percent in Fall 1997 to 

21 percent in Fall 2000 (z = -8.26, p < .001) and a decline in the percentage of teachers who taught from 

five to nine years from 34 percent in Fall 1997 to 28 percent in Fall 2000 (z = 9.15, p < .001). 

9

 The chi-square statistic was calculated for these comparisons, using unweighted data on the independent samples because no classroom weights

were created for the Fall 1997 sample.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-17 March 06 
Approximately the same number of teachers in both cohorts had been teaching in Head Start for 10 years 

or more (28 percent in Fall 2000 and 29 percent in Fall 1997). 

Most Head Start teachers have good teaching qualifications, but lower than those of teachers 

in public elementary schools. In a survey of pre-kindergarten classrooms in the U. S. public schools in

2000-2001, 86 percent of pre-kindergarten teachers had a Bachelor’s or higher degree (Smith, Kleiner, 

Parsad and Farris, 2002). Overall in Fall 2000, 46.4 percent of Head Start teachers had either a Bachelor’s 

or an Associate’s degree with 38.7 percent having a Bachelor’s degree or higher and 57 percent having an

Associate’s degree or higher. In the Spring of that year (Spring 2001), 38 percent reported having a 

Bachelor’s degree or higher and 55 percent reported having an Associate’s degree or higher. In the 

following year, Spring 2002, these percentages remained very similar, 36 percent and 57 percent

respectively.

Looking at the specific types of educational qualifications, in Fall 2000, 27.8 percent had a 

Bachelor’s degree, 18.6 percent had an Associate’s degree, and another 32.2 percent had some college but 

no degree in Fall 2000. In Spring 2001 and Spring 2002, the percentage of teachers reporting a Bachelor’s 

degree was 28.1 percent and 29 percent respectively, and the percentage of teachers reporting an 

Associate’s degree was 17.3 percent and 21 percent for Spring 2001 and Spring 2002. Thus, over the 

course of two years, the percentage of teachers with Bachelor’s degree increased slightly from 27.8 

percent to 29 percent while the proportion of teachers with Associate’s degree increased from 18.6 

percent in Fall 2000 to 21 percent in Spring 2002. However, caution must be exercised in interpreting 

these changes because the Spring 2002 sample consisted of only those classrooms with children in their 

second year of Head Start, and did not include all classrooms in the FACES sample (necessitating the use

of unweighted data). 

In Fall 2000, 74 percent of all teachers reported having the Child Development Associate 

(CDA) credential or a state-awarded preschool certificate, with 58 percent having the CDA only. In

Spring 2001, teachers in the same cohort of classrooms reported similar percentages; 71.6 percent

reported having a CDA or state-awarded certificate and 55 percent reported having a CDA diploma only. 

In Spring 2002, 66 percent reported having a CDA or state certificate, and 58 percent reported having just 

a CDA. 

When looking at the change across cohorts, from Fall 1997 to Fall 2000, the proportion of

teachers with a Bachelor’s degree or higher increased significantly from 28.1 percent in Fall 1997 to 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-18 March 06 
38.7 percent in Fall 2000, primarily due to an increase in the proportion of teachers with graduate level 

degrees, defined as a Master’s degree, its equivalent or higher. In Fall 2000, 10.9 percent of teachers

reported having a Master’s degree or higher compared with only 3.2 percent in Fall 1997, with another 

16 percent having received some graduate level training in Fall 2000.10 The increase in the proportion of

teachers with graduate level degrees was significantly correlated with the increase in the proportion of

teachers with two years or less of teaching experience in Head Start, from 14 percent to 21 percent over

the same time period. In Fall 2000, 32.9 percent of teachers with graduate level education or higher were 

new teachers, compared with only 13.3 percent in Fall 1997.11 These results suggest that an increased 

number of new teachers with advanced degrees entered Head Start from 1997 to 2000. 

In Spring 2001 the proportion of teachers with a Bachelor’s degree or higher remained at the

high level shown in the Fall, with 38 percent of teachers having these qualifications. In Spring 2002, 

36 percent of teachers reported having a Bachelor’s degree or higher, which is not a statistically

significant change from the year earlier (especially given the reduced sample of teachers at this time

period). In Spring 2001, the proportion of teachers with graduate level degrees also remained similar to

the Fall 2000, with 10 percent of teachers, and in the following Spring (2002) the proportion dropped 

slightly (but not to a statistically significant degree) to 7 percent of teachers (with graduate level

qualifications). 

In addition to an increase from the prior FACES cohort in the proportion of teachers with

advanced degrees, more teachers in FACES 2000 are reporting having studied Early Childhood Education

or Child Development as part of their highest degree, whether for an Associate’s, Bachelor’s, or higher 

degree. In Fall 2000, 78 percent indicated that their field of study included Early Childhood Education or

Child Development, compared with approximately 62 percent in Fall 1997. However, the proportion of 

teachers having a CDA or state preschool certificate has stayed approximately the same (74 percent in 

Fall 2000 compared with 76 percent in Fall 1997). In the same cohort of FACES 2000, from Fall 2000 to

Spring 2001 and Spring 2002, the percentage of teachers who studied Early Childhood Education or

Child Development in their degree work increased from 78 percent in Fall 2000 to 86.7 percent in

Spring 2001 and 87.7 percent in Spring 2002, but these differences were not statistically significant.

However, the percentage of teachers enrolled in teacher-related training was 45 percent in Fall 2000, 

10 The chi-square comparison using unweighted data on the independent samples was statistically significant at p<.01 (chi-square = 12.5371,

1 df).

11 In Fall 2000 the chi-square test using weighted data was statistically significant at p<.001 (chi-square = 344.9624, 1 df). Further, a comparison

of the two proportions from Fall 1997 to Fall 2000 using unweighted data also revealed a statistically significant increase at p<.01 (z = 4.441).

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-19 March 06 
46.6 percent in Spring 2001 and declined to 28.2 percent in Spring 2002. The decrease in Spring 2002 

was significant compared with both Fall 2000 (t=-2.01, p=.05) and Spring 2001 (t=-2.11, p=.04) and

indicates that fewer teachers in Spring 2002 were engaged in continuing education activities. 

In Spring 2001, the proportion of teachers reporting a CDA or state preschool certificate

remained similar to that reported in the Fall, with 72 percent of teachers (compared with 74% in Fall 

2000) having this qualification. In the following year (Spring 2001), the proportion of teachers having a 

CDA or state preschool certificate dropped slightly to 66 percent, which was not a statistically significant

decrease. 

Head Start teachers were, on average, 41.4 years old with a range from 23 to 73 years of age

(standard deviation of 11.1 years). One-third of teachers belonged to the 30 to 39 year age group and 

another 28 percent were between the ages of 40 and 49 years. There were no differences in the 

proportions of teachers in each of the ten-year age groupings between the earlier cohort (Fall 1997) and 

this cohort (Fall 2000), with the exception that this cohort reflects an aging of teachers at the upper end of 

the distribution. Whereas only 4 percent of teachers were 60 years of age or older in Fall 1997, in this 

newest cohort (Fall 2000), 7 percent of teachers were 60 years of age or older. 

There was also an increase in the membership of teachers in a national professional 

association for early childhood educators (e.g., NAEYC, NHSA, and NEA), from 53 percent in Fall 1997 

to 62 percent in Fall 2000 but this increase did not reach levels of statistical significance. In Spring 2001,

the proportion of teachers with membership in a national professional early childhood education 

association remained similar, with 61 percent of teachers reporting membership. In the following year 

(Spring 2002), the proportion dropped from 61 percent to 51 percent but this was not a statistically

significant decline (likely due to the use of unweighted data for the comparisons). 

In terms of racial and ethnic background, in Fall 2000, 33.7 percent of the teachers were

African American, 15 percent were Hispanic, 1 percent were Asian and 48 percent were White. 

Compared with the Fall 1997 data, teachers in Fall 2000 were slightly less likely to be African American

(the percentage of African American teachers declined to 33.7 percent from 34.2 percent in Fall 1997). 

Although it may appear that there was a strong decline in the percentage of Hispanic teachers, this decline 

is due entirely to the fact that Puerto Rico was included in the Fall 1997 but excluded from the Fall 2000 

cohort. In FACES 2000, the proportion of teachers who were White increased slightly from 41 percent in 

Fall 1997 to 48 percent in Fall 2000 but this was not statistically significant and from Fall to Spring of

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-20 March 06 
FACES 2000, the proportion of teachers remained very similar (see Table 5-2). In the following 

Spring (2002), the differences in the proportions of White (52 percent compared with 49 percent in Spring 

2001) and African American teachers (29 percent compared with 34 percent in Spring 2001) over these 

two years were not statistically significant. The proportion of Hispanic teachers remained approximately

the same in Spring 2002 (17 percent compared with 15 percent in Spring 2001).

In general, the data reveal that Head Start teachers are experienced and qualified to teach 

early childhood education. Compared with the first FACES cohort, Head Start teachers in FACES 2000 

are more qualified. They are more likely to be White, younger, new to teaching Head Start and have 

higher educational levels including graduate degrees. They are also more likely to be trained in Early

Childhood Education and to be members of a professional organization. There were few significant

changes in the characteristics of the teachers across time periods within the FACES 2000 cohort, which 

likely reflects similarities in the teacher samples across each of the data collection periods. 

Teacher Attitudes and Knowledge. In Fall 2000, on average, Head Start teachers showed

generally positive attitudes and knowledge about instructional practice in early childhood education, with

a mean score for all teachers of 7.9 out of a maximum score of 10 on the 9 items from the Teacher Beliefs

Scale (see earlier description as well as Appendix). For example, they tended to agree with statements

indicating positive attitudes and knowledge about early childhood education practices such as: “Head

Start classroom activities should be responsive to individual differences in development” and “Children 

should be allowed to select many of their own activities from a variety of learning areas that the teacher

has prepared (writing, science center, etc.).” Head Start teachers tended to disagree with statements

indicating negative attitudes and a lack of knowledge about early childhood education practices such as:

“Each curriculum area should be taught as a separate subject at separate times” and “Students should 

work silently and alone on seatwork.” In Spring 2001, the average score was 7.9, indicating stable scores 

for this measure from Fall to Spring in the FACES 2000 cohort. In Spring 2002, the average score 

dropped to 7.2, which represents a statistically significant decline from Spring 2001 (t = -3.27, p < .001) 

and from Fall 2000 (t = -3.73, p < .0003) in teachers’ knowledge and attitudes about early childhood 

education practices. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-21 March 06 
5.3.3 How are Teaching Qualifications and Experience Related to Attitudes and Knowledge

of Early Childhood Education and How are these Factors Linked to Quality in Head 

Start Classrooms? 

Teacher Background and Qualifications Correlated with Attitudes and Knowledge.

The following analyses were comprised of bivariate correlations using either Spearman Rank-Order

Correlations (for ordinal variables) or Pearson Product-Moment Correlations (for interval and binarycoded variables). The correlations show that teachers who had higher levels of knowledge about early

childhood education practices tended to be more experienced and better educated (Table 5-4). Higher 

scores for teacher attitudes and knowledge of early childhood education practices were significantly

correlated with higher levels of educational attainment (r=.16), some graduate school education or higher 

(r=0.13), more total years teaching (r=0.13), membership in an early childhood education association

(r=0.19), teaching in a language other than Spanish or English (r=0.14), and teachers with White,

Hispanic, or Asian racial backgrounds (r=-0.17). Teacher’s attitudes and knowledge were not

significantly correlated with teacher salary, years teaching Head Start, having a teaching certificate,

having a CDA certificate, or having a course of study in Early Childhood Education. 

Table 5-4. Teacher attitudes and knowledge correlated with teacher backgrounds and qualifications, 

Fall 2000 (N=257) 

Teacher backgrounds and qualifications Correlation coefficient Significance (p level) 

ECE Association Membership 0.19 0.01 

Highest Level of Education 0.16 0.01 

Teach in a language other than English or Spanish 0.14 0.01 

Total Years Teaching 0.13 0.05 

Some graduate school education or higher 0.13 0.05 

Current Gross Annual Salary 0.09 Ns 

Years Teaching Head Start 0.09 Ns 

Field of Study includes ECE 0.09 Ns 

Teaching Certificate 0.07 Ns 

CDA Credential 0.06 Ns 

Enrolled in teacher-related training 0.03 Ns 

Hispanic Teacher 0.02 Ns 

Teach in Spanish 0.00 Ns 

Teach in English -0.06 Ns 

Teacher's Age -0.06 Ns 

African American Teacher -0.17 0.01 

*See Appendix for description of the variables. Highest level of education was ordinally-scaled. The rest were either interval or binary-coded.

This relationship between teacher backgrounds and qualifications and teacher’s attitudes and 

knowledge about early childhood education practices is supported by findings from other studies. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-22 March 06 
Abbott-Shim, Lambert, and McCarty (2000) reported that teachers with higher levels of education also 

showed more positive attitudes and knowledge about early childhood education practices. 

These results suggest that teachers who have higher levels of educational attainment

especially at the graduate school level, more years of teaching experience overall, and who enroll in a 

related professional association are more likely to have knowledge and positive attitudes about early

childhood education practices. These attitudes and knowledge should be expected to influence classroom 

quality, particularly since teacher credentials were related to classroom quality. In the next step toward 

building a model explaining the connection between teacher backgrounds, qualifications and experience 

and classroom quality, the relationship between teacher attitudes and knowledge and classroom quality is 

tested. 

Teacher Backgrounds, Qualifications and Experience Correlated with Classroom

Quality. In Fall 2000, teachers with more experience and higher levels of education tended to be in 

classrooms rated higher in classroom quality (Table 5-5). Specifically teachers with higher levels of

education tend to be in classrooms rated higher on a number of quality indicators, including the ECERS-R

Language subscale (r = 0.21), the Caregiver Interaction Scale (r=0.19), the ECERS-R total score (r=0.13), 

the quality factor score (r=0.15), and the classrooms had lower child:adult ratios, indicative of higher

quality (r=-0.20). It is noteworthy that the correlation between education levels and the ECERS-R 

Language subscale was stronger than that for the total ECERS-R score. 

Teachers with a BA or AA degree were in classrooms with lower child:adult ratios (r=-0.12), 

indicating higher quality, but also in classrooms rated lower on the ECERS-R Language subscale (r=-

0.12), indicative of lower quality of language activities and materials. Teachers with a CDA tended to be 

in classrooms with higher ratios (r=0.16), indicative of lower quality, but were also in classrooms with

higher Individualizing scores (r=0.19), indicating more individualized planning and attention. Teachers

who had more years teaching overall (not just in Head Start) were rated higher in their sensitivity and 

responsiveness, as measured by the Caregiver Interaction Scale (r=0.17) and had higher ECERS-R

Language subscale scores (r=0.13). Teachers with more years teaching Head Start were in classrooms 

rated higher on the Quality Composite score (r=.12). Teachers who were members of an early childhood 

education professional association were rated higher in their sensitivity and responsiveness, as measured

by the Caregiver Interaction Scale (r=0.15), and were in classrooms rated higher on ECERS-R Language 

(r=0.16), the Assessment Profile Individualizing Scale (r=0.17), with higher Quality Composite scores 

(r=0.15). Teachers with at least some graduate school education (versus no graduate school education) 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-23 March 06 
were also in classrooms rated higher in quality as measured by the ECERS-R total score (r=0.16). Finally,

teachers who had a teaching certificate (versus no certificate) were in classrooms rated higher on the

overall ECERS-R (r=0.12) and the ECERS Language subscale (r=0.14), with lower child:adult ratios,

indicative of higher quality (r=-0.19). Interestingly, teachers’ total annual salaries were not significantly

correlated with any of the quality indicators. 

Table 5-5. Correlation of teacher backgrounds, qualifications and experience with classroom quality, 

Fall 2000 (N=257). 

ECERS-R 

Total 

ECERS-R 

Language 

Assessment 

profile 

individualizing 

Caregiver 

interaction 

scale 

(Arnett) 

Child-adult 

ratio 

Quality

factor score 

Correlation 

coefficient 

Correlation 

coefficient 

Correlation 

coefficient 

Correlation 

coefficient 

Correlation 

coefficient 

Correlation 

coefficient 

Highest Level of 

Education* 

0.13* 0.21*** -0.06 0.19*** -0.20*** 0.15** 

Teacher has AA 

or BA 

-0.07 -0.12* -0.06 0.00 -0.12* -0.10 

Total Years 

Teaching 

0.09 0.13* 0.05 0.17** 0.03 0.06 

Years Teaching 

Head Start 

0.05 0.07 0.04 0.08 0.05 0.12* 

ECE Association 

Membership 

0.10 0.16** 0.17** 0.15** 0.10 0.15** 

CDA Credential -0.10 -0.02 0.19*** -0.09 0.16** 0.05 

Some Graduate 

School Education 

or higher 

0.16** 0.21*** -0.03 0.14** -0.11 0.10 

Teaching 

certificate 

0.12* 0.14** -0.09 0.10 -0.19** 0.08 

*Highest level of education was ordinally-scaled and the correlation coefficients were obtained from Spearman Rank-Order Correlations.

‡Significance levels as follows: *** indicates p < .001; ** indicates p < .01; * indicates p < .05. With the exception of highest level of education,

all variables were either interval or binary-coded and coefficients were obtained from Pearson Product Moment Correlations.

These results indicate that teacher backgrounds and qualifications are related to higher levels 

of quality in Head Start classrooms. However, the above results are based only on simple correlations,

and do not take into account the complex interplay between the various teacher-related factors. To 

understand the links between these factors, the relationships between teacher backgrounds and experience 

and teacher attitudes and knowledge about early childhood education practices were tested. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-24 March 06 
Teacher Attitudes and Knowledge Correlated with Classroom Quality. Teachers with

more positive attitudes and knowledge about early childhood education practices tend to be in classrooms 

rated higher in quality (Table 5-6). This relationship was found for a wide variety of quality indicators,

including the ECERS-R total score (r=0.32), the ECERS-R Language subscale (r=0.29), the Arnett 

Caregiver Interaction Scale (r=0.28), the Quality Composite score (r=0.27), and the Assessment Profile

Individualizing subscale (r=0.15). It is noteworthy that the size of these correlations greatly exceed those

found for the relationships between teacher attitudes and knowledge and teacher backgrounds, and they 

also exceed those found for the relationship between teacher backgrounds and classroom quality. Only

child:adult ratio was not significantly related to teacher’s attitudes and knowledge of early childhood 

education practices. 

Table 5-6. Teacher attitudes and knowledge correlated with classroom quality indicators, Fall 2000 

(N=257) 

Classroom quality indicators Correlation coefficient Significance (p level) 

ECERS-R Total Score 0.32 0.001 

ECERS-R Language Subscale 0.29 0.001 

Arnett Lead Teacher Total 0.28 0.001 

Quality Factor Score 0.27 0.001 

AP Individualizing Observed 0.15 0.01 

Child:Adult Ratio -0.06 Ns 

Teachers holding more positive attitudes and knowledge of early childhood education 

practices were more sensitive and responsive to children, as measured by the Arnett Caregiver Interaction

Scale. They were also more likely to adjust activities to meet the varying needs of individual children, as 

indicated by the Assessment Profile Individualizing scale. Teachers holding more positive attitudes and

knowledge of practices in early childhood education were also in classrooms rated higher in overall 

quality on the ECERS-R and in classrooms with higher quality language activities, as rated by the 

ECERS-R Language subscale. 

The above findings suggest that teacher backgrounds, experience and qualifications, notably

their level of education, are significantly related to both teacher’s attitudes and knowledge about early

childhood education practice, and classroom quality. Teacher attitudes and knowledge alone was also

significantly correlated with classroom quality. Thus, in variations in quality in Head Start classrooms, it

would appear that teacher qualifications as well as their attitudes and knowledge about early childhood 

education practices are important. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-25 March 06 
These results are limited because they cannot specify, based on the simple correlations 

presented above, the complexities of the relationships between both teacher backgrounds and experiences 

and teacher attitudes and knowledge in explaining or predicting classroom quality. The relationships with 

classroom quality may be independent, suggesting that teacher education, for example, and teacher

attitudes and knowledge contribute separately and uniquely to variations in quality, or there may be a 

more complicated, mediated pattern, in which teacher attitudes and knowledge may mediate the 

relationship between teacher backgrounds and experiences and classroom quality. 

5.3.4 Do Factors Beyond the Classroom, Such as the Types of Curricula Head Start

Programs Provide, the Average Teacher Salaries, and Characteristics of Families 

Served by the Head Start Program Explain Variations in the Quality of Head Start 

Classrooms?

As described earlier, a series of multi-level models were tested using the SAS PROC 

MIXED computer program (Singer, 1998; Bryk and Raudenbush, 1993). This method predicts average 

quality scores of a sample of classes, schools, or other educational units (in the present case, Head Start 

centers) from a set of characteristics of those units, such as measures of center demographics and 

program-level factors. Simultaneously, the models identify how the quality of Head Start in each center 

relate to a set of classroom-level teacher characteristics, such as teacher educational qualifications, 

experience, and attitudes and knowledge of early childhood education practice. The method provides a 

numerical estimate of how sizable the center-to-center variation in average quality scores is, relative to

the class-to-class variation in scores within centers. In this approach, each level of the model is tested 

separately, with the results approximating those obtained from simple linear regression analyses, but then 

the final test involves both levels of the model entered simultaneously. This approach is possible only

because of the hierarchical nature of the data, in which classrooms are nested within centers. 

To determine how much Head Start programs differed in average quality, the total variability

in classroom quality scores was divided into two components, the variation between programs in the 

average quality scores of the classrooms, and the variation among classrooms within the same program. If

classrooms with differing levels of quality were randomly distributed across Head Start programs, one

would expect that 90 percent or more of the variation in quality would Fall into the within-programs 

component, and only a small proportion would Fall into the between-programs component. On the other

hand, if programs differed substantially in classroom quality, then, based on previous research, one might

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-26 March 06 
expect a significant amount of the variation to Fall into the between-program component (Bryk and 

Raudenbush, 1992). Such an approach was used effectively to study characteristics of school organization

on teachers’ sense of efficacy (Bryk and Driscoll, 1988, cited in Bryk and Raudenbush, 1992) and the 

effects of school characteristics on individual children’s achievement (Lee and Bryk, 1989, cited in Bryk

and Raudenbush, 1992). 

In order to assess the contribution of the program- and classroom-level variables to the 

modeling of classroom quality, a sequence of regression models was run for each dependent variable 

(these are the indicators of quality listed earlier in the chapter, such as the ECERS-R total score). The first

model, which Singer refers to as the “unconditional means model,” a random effect parameter for the

between-classroom variability in quality was added to the fixed effect for the overall mean (for all 

classrooms in the sample). This model had one fixed effect (the overall mean) and two variance

components, one representing the variation between classroom means and the other representing the 

variation within classrooms. The second model added the classroom level teacher factors, including 

teacher education, years of teaching Head Start, membership in EC associations, teacher ethnicity, and 

teacher beliefs about developmentally appropriate practices to the unconditional model.12 The third model 

tested the effect of the program-level factors including the effects of the proportion of families with 

incomes at the higher end of the poverty range, the proportion of non-minority students, the proportion of 

families with at least some college education, the use of Creative or High/Scope curriculum, and the 

center average teacher salaries to the unconditional model (independent of the classroom-level

predictors). The fourth model added the classroom-level teacher factors to the program-level model and

was the final model for predicting classroom quality scores. 

As each successive model was run, the contribution of the additional variables was assessed 

by calculating the difference in the residual log likelihood statistic between the current model and the 

prior model in the sequence. This statistic multiplied by -2 is distributed approximately as chi-square, 

with the degrees of freedom equal to the difference between the degrees of freedom for the current model

(with its additional parameters) and the prior model. Also examined was the extent to which the current 

model reduced the between-programs variance, the among-programs variance, and the total variance, 

relative to the sizes of these variances in the unconditional means model (Bryk and Raudenbush, 1992,

p. 65; Singer, 1998, p. 332). 

12 The teacher variables were either interval level or binary-coded, allowing for their use and interpretation in these models as predictors. Teacher

education was entered as a binary-coded variable coded 1 for teachers having an Associate’s or a Bachelor’s degree and 0 for teachers without 

these qualifications. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-27 March 06 
The results of the multi-level models are presented separately for each of the six key

indicators of quality (ECERS-R total scores, ECERS-R Language subscale, Arnett Caregiver Interaction 

Scale, Assessment Profile Individualizing subscale, Child:Adult Ratio, and Quality Composite score), in 

Tables 5-7 through 5-12.

13 A summary of the final two-level models for all indicators of quality is

presented in Table 5-13. 

Predicting ECERS-R Total Score. Looking first at only the initial classroom-level model

in which between-classroom variability in quality was added to the fixed effect for the overall ECERS-R 

total score, there were significant effects of teacher ethnicity and teacher knowledge and attitudes towards 

early childhood education. However, these classroom-level factors explained only 1.5 percent of the 

between-program variation and less than 1 percent of the variation overall. The second, program-level

model revealed that programs with a higher proportion of non-minority students and with a higher 

proportion of language-minority students, tended to be rated higher in quality. In combining these two

factors, one interpretation of these findings is that higher quality was found among programs serving

white children and among programs serving children where English is not their primary language, such as 

Spanish-speaking children (representing the largest group of language-minority students). Program-level 

only effects accounted for 7.9 percent of overall variation in ECERS-R total scores and 32.2 percent of

the between-program variation. However, in the final two-level model, when program- and classroomlevel factors are combined, the initial effects of teacher ethnicity disappear and only teacher knowledge

and attitudes at the classroom level remains a significant predictor. At the program-level the percentage of 

non-minority students and the percentage of language-minority students remained as significant 

predictors of quality. Overall, the two-level model accounted for 5.5 percent of the total variation and 

28.3 percent of the between-program variation in ECERS-R total scores. These findings suggest that high 

quality classrooms are likely to be those where programs have a higher percentage of non-minority

students, a higher percentage of language-minority students (e.g., Spanish speakers), and teachers who

have greater knowledge about early childhood education practices (Table 5-7). 

13 The Assessment Profile Learning Environment and Scheduling subscales were not used in separate models because they were included in the 

Quality Composite. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-28 March 06 
Table 5-7. Multi-level model predicting ECERS-R mean score from teacher factors, controlling for 

program-level effects (n=265), Fall 2000 

Independent variables 

Program-level 

effects 

Class-level 

effects 

Program + class 

effects 

(INTERCEPT = 4.8) Estimate Signif‡ Estimate Signif Estimate Signif 

Program-Level Factors

Percent parents with some college or 

higher 0.46 0.55 

Percent parents earning $1500/month 

or more 

0.28 0.44 

Percent non-minority students 1.13 *** 0.82 ** 

Percent language-minority students 1.04 * 1.04 * 

High/Scope Curriculum 0.35 0.30 

Creative Curriculum 0.32 0.33 

Average Annual Teacher Salary 0.14 0.10 

Classroom-Level Teacher Factors

Teacher having BA or AA -0.05 -0.09 

Teacher Attitudes and Knowledge 0.12 *** 0.11 *** 

Years Teaching Experience 0.01 0.01 

African-American Teacher -0.33 ** -0.14 

Hispanic Teacher -0.23 -0.18 

Teacher Salary

(deviation from program mean) 0.02 0.03 

‡Significance levels as follows: *** indicates p < .001; ** indicates p < .01; * indicates p < .05.

Predicting ECERS-R Language Subscale. The initial classroom-level model revealed 

significant effects of teacher knowledge and attitudes and teacher ethnicity. These classroom-level factors 

predicted 55 percent of the between-program variation and 18.9 percent of the total variation in ECERS-R 

Language subscale scores. The second, program-level model revealed that programs with a higher

proportion of non-minority students and with a higher proportion of language-minority students tended to

be rated higher in quality. There was also a non-significant trend towards families whose parents had

some college education or higher being in programs rated higher on ECERS-R Language subscale but this 

was only at p < .10. Program-level only effects accounted for 15.6 percent of overall variation in ECERSR Language subscale scores and 56.2 percent of the between-program variation. However, in the final

two-level model, when program- and classroom-level factors are combined, the initial effects of teacher

ethnicity disappear and only teacher knowledge and attitudes at the classroom level remains a significant 

predictor. There was a non-statistically significant trend towards teacher education having an effect as 

well. At the program-level, none of the factors reached levels of statistical significance although 

percentage of non-minority and language-minority students in the program reached trend levels (p < .06

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-29 March 06 
and .10 respectively). Overall, the two-level model accounted for 25.3 percent of the total variation and

73.4 percent of the between-program variation in ECERS-R total scores. These findings suggest that

classrooms with higher quality of language activities and materials were likely to be those whose teachers 

had higher scores for attitudes and knowledge about early childhood education practice. Having a teacher

with a BA or AA, or having a higher percentage of non-minority students or a higher percentage of 

language-minority students were associated with higher quality at the trend level, but did not reach

statistical significance (Table 5-8). 

Table 5-8. Multi-level model predicting ECERS-R language subscale scores from teacher factors, 

controlling for program-level effects (N=265), Fall 2000 

Independent variables 

Program-level 

effects 

Class-level 

effects 

Program + class 

effects 

INTERCEPT = 4.80 Estimate Signif‡ Estimate Signif Estimate Signif 

Program-Level Factors

Percent parents with some college or 

higher 0.53 † 0.46 

Percent parents earning $1500/month 

or more 

0.24 0.36 

Percent non-minority students 1.17 *** 0.68 † 

Percent language-minority students 0.91 † 0.84 † 

High/Scope Curriculum 0.29 0.24 

Creative Curriculum 0.25 0.27 

Average Annual Teacher Salary 0.11 0.08 

Classroom-Level Teacher Factors

Teacher having BA or AA -0.17 -0.23 † 

Teacher Attitudes and Knowledge 0.17 *** 0.16 *** 

Years Teaching Experience 0.01 0.01 

African-American Teacher -0.50 *** -0.22 

Hispanic Teacher -0.53 * -0.34 

Teacher Salary

(deviation from program mean) 0.11 0.11 

‡Significance levels as follows: *** indicates p < .001; ** indicates p < .01; * indicates p < .05, † indicates a non-significant trend at p < .10.

Predicting Assessment Profile Individualizing Score. The initial classroom-level model 

revealed no significant effects and classroom-level factors predicted only 1.5 percent of the betweenprogram variation and 1.1 percent of the total variation in the Assessment Profile Individualizing scores.

The second, program-level model revealed that programs with a higher proportion of parents earning

$1,500 per month or more tended to be rated higher on this quality measure (Individualizing). Programlevel only effects accounted for 3.3 percent of overall variation in Individualizing subscale scores and

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-30 March 06 
8.5 percent of the between-program variation. In the final two-level model, when program- and

classroom-level factors are combined, the initial effects of the program-level factor (parents earning 

$,1500 per month or more) remains a significant predictor. Overall, the two-level model accounted for 

5.4 percent of the total variation and 12 percent of the between-program variation in Individualizing

scores. These findings, while significant, are not as strong as many of the other models indicating that the 

program- and classroom-level factors in the models do not explain a large amount of variation in 

Assessment Profile Individualizing scores. Nevertheless, the significant findings do suggest that 

classrooms with a focus on individualizing the classroom activities for individual students (an indicator of 

greater quality) are likely to be located in Head Start programs with greater numbers of families with 

relatively higher incomes (Table 5-9). 

Table 5-9. Multi-level model predicting assessment profile individualizing scores from teacher factors, 

controlling for program-level effects (n=265), Fall 2000 

Independent variables 

Program-level 

effects 

Class-level 

effects 

Program + class 

effects 

INTERCEPT = 3.5 Estimate Signif‡ Estimate Signif Estimate Signif 

Program-Level Factors

Percent parents with some college or 

higher 0.60 0.52 

Percent parents earning 

$1,500/month or more 

3.67 ** 3.82 ** 

Percent non-minority students 0.15 0.14 

Percent language-minority students 0.26 0.22 

High/Scope Curriculum -0.34 -0.40 

Creative Curriculum -0.38 -0.38 

Average Annual Teacher Salary -0.33 -0.34 † 

Classroom-Level Teacher Factors

Teacher having BA or AA 0.09 0.10 

Teacher Attitudes and Knowledge 0.05 0.04 

Years Teaching Experience 0.01 0.01 

African-American Teacher 0.03 0.06 

Hispanic Teacher -0.02 0.04 

Teacher Salary

(deviation from program mean) 0.11 0.15 

‡Significance levels as follows: *** indicates p < .001; ** indicates p < .01; * indicates p < .05, † indicates a non-significant trend at p < .10.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-31 March 06 
Predicting Teacher Arnett Caregiver Interaction Scale Score. The initial classroom-level 

model in which between-classroom variability in quality was added to the fixed effect for the overall

Arnett Caregiver Interaction Scale (CIS) score (lead teacher), there were significant effects of teacher

ethnicity, teacher knowledge and attitudes towards early childhood education, and years of teaching 

experience. These classroom-level factors explained 13.6 percent of the total variation in Arnett CIS 

scores and 42.7 percent of the between-program variation. The second, program-level model revealed that

programs with a higher proportion of non-minority students and that use the Creative Curriculum tended

to be rated higher in quality. There was a non-significant trend towards programs using the High/Scope 

curriculum also being rated higher in quality, but this did not reach statistical significant levels (p < .08). 

Program-level only effects accounted for 12.6 percent of overall variation in Arnett CIS scores and 44.3

percent of the between-program variation. However, in the final two-level model, when program- and 

classroom-level factors are combined, the initial effects of teacher ethnicity disappear but teacher 

knowledge and attitudes and teacher years of experience remained significant predictors at the classroom 

level. At the program-level the percentage of non-minority students disappeared and only the use of 

Creative Curriculum and, to a much lesser extent, the use of the High/Scope curriculum remained as

significant predictors of quality. Programs that used the High/Scope curriculum (19.5 percent in Spring

2001) had classrooms with somewhat higher scores for teacher sensitivity, although this did not reach

statistically significant levels in the final model. Overall, the two-level model accounted for 20.4 percent 

of the total variation and 59.7 percent of the between-program variation in Arnett CIS scores. These 

findings suggest that curriculum, teacher experience, and teacher attitudes and knowledge were

significant predictors, with the strongest being the teachers’ attitudes and knowledge of early childhood 

education practice, followed by programs that used the Creative Curriculum. Classrooms with sensitive 

and responsive teachers are likely to be those that use the Creative Curriculum (45.2 percent in Spring 

2001), where the teachers have more years of teaching experience and where the teachers hold more

positive attitudes and knowledge about practices in early childhood education (Table 5-10). 

Teacher education level, indicated by whether teachers had an Associate’s or Bachelor’s

degree or not, was not significantly related to teacher sensitivity, even though it was related in earlier

analyses without program level factors included. These results further suggest that the relationship 

between teacher education and classroom quality is not direct, but rather is mediated by their knowledge 

and attitudes towards early childhood education practice as well as by the type of curriculum used and the

teacher’s level of experience. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-32 March 06 
Table 5-10. Multi-level model predicting Arnett caregiver interaction scale scores from teacher factors, 

controlling for program-level effects (n=265), Fall 2000 

Independent variables 

Program-level 

effects 

Class-level 

effects 

Program + class 

effects 

INTERCEPT = 70.96 Estimate Signif‡ Estimate Signif Estimate Signif 

Program-Level Factors

Percent parents with some college or 

higher 9.60 10.59 

Percent parents earning $1500/month 

or more 

-0.18 2.83 

Percent non-minority students 7.93 * 3.24 

Percent language-minority students -3.28 -1.98 

High/Scope Curriculum 6.21 † 5.33 † 

Creative Curriculum 6.22 * 6.41 * 

Average Annual Teacher Salary 2.47 1.62 

Classroom-Level Teacher Factors

Teacher having BA or AA -0.15 -1.09 

Teacher Attitudes and Knowledge 1.62 *** 1.55 *** 

Years Teaching Experience 0.17 * 0.17 * 

African-American Teacher -3.81 * -1.75 

Hispanic Teacher -6.67 *** -3.91 

Teacher Salary

(deviation from program mean) 0.48 1.09 

‡Significance levels as follows: *** indicates p < .001; ** indicates p < .01; * indicates p < .05, † indicates a non-significant trend at p < .10.

Predicting Quality Composite Score. The initial classroom-level model in which betweenclassroom variability in quality was added to the fixed effect for Quality Composite score, there were

significant effects only for teacher knowledge and attitudes towards early childhood education. This 

classroom-level factor explained 11.62 percent of the total variation in Arnett CIS scores and 28 percent 

of the between-program variation. The second, program-level model revealed that programs with a higher 

proportion of non-minority students and language-minority students tended to be rated higher in quality.

There was a non-significant trend towards programs with a higher percentage of with at least some 

college level education being rated higher in quality, but this did not reach statistically significant levels

(p < .06). Program-level only effects accounted for 12.2 percent of overall variation in Quality Composite 

scores and 52.4 percent of the between-program variation. In the final two-level model, when programand classroom-level factors are combined, teacher knowledge and attitudes remained a significant

predictor at the classroom level. At the program-level, the percentage of language-minority students 

remained as a significant predictor (p < .01) whereas the percentage of non-minority students was no

longer statistically significant (p < .06) and the percentage of parents with some college education or

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-33 March 06 
higher remained as a non-significant trend (p < .06). Overall, the final two-level model accounted for 

19.2 percent of the total variation and 55.9 percent of the between-program variation in Quality 

Composite scores. These findings suggest that classrooms with higher scores for quality on this indicator 

(comprising the ECERS-R Language subscale, and the Assessment Profile Scheduling and Learning

Environment Scales) were likely to be those from Head Start programs with a higher percentage of 

language-minority students, and whose teachers had more positive attitudes and knowledge of early

childhood education practice (Table 5-11). 

Table 5-11. Multi-level model predicting quality factor score from teacher factors, controlling for 

program-level effects (n=265), Fall 2000 

Independent variables 

Program-level 

effects 

Class-level 

effects 

Program + class 

effects 

INTERCEPT = 0.003066 Estimate Signif‡ Estimate Signif Estimate Signif 

Program-Level Factors

Percent parents with some college or 

higher 0.48 † 0.46 † 

Percent parents earning $1500/month 

or more 

0.15 0.19 

Percent non-minority students 0.67 ** 0.43 † 

Percent language-minority students 1.20 ** 1.27 ** 

High/Scope Curriculum 0.25 0.22 

Creative Curriculum 0.26 0.26 

Average Annual Teacher Salary -0.07 -0.11 

Classroom-Level Teacher Factors

Teacher having BA or AA -0.06 -0.09 

Teacher Attitudes and Knowledge 0.15 *** 0.14 *** 

Years Teaching Experience 0.01 0.01 

African-American Teacher -0.23 -0.04 

Hispanic Teacher -0.20 -0.21 

Teacher Salary

(deviation from program mean) -0.02 -0.03 

‡Significance levels as follows: *** indicates p < .001; ** indicates p < .01; * indicates p < .05, † indicates a non-significant trend at p < .10.

Predicting Child:Adult Ratio. The initial classroom-level model revealed no significant 

effects and classroom-level factors predicted only 1.5 percent of the between-program variation and less

than 1 percent of the total variation in the child:adult ratio. The second, program-level model revealed that 

programs with higher average annual teacher salaries had lower child:adult ratios, indicative of higher

quality. Program-level effects accounted for 7.9 percent of overall variation in child:adult ratios and 32.2

percent of the between-program variation in these ratios. In the final two-level model, when program- and

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-34 March 06 
classroom-level factors are combined, the initial effects of the program-level factor (average annual

teacher salary) remained a significant predictor. Overall, the two-level model accounted for 5.5 percent of

the total variation and 28.3 percent of the between-program variation in child:adult ratios. These findings, 

while significant, are not as strong as many of the other models indicating that the program- and

classroom-level factors in the models do not explain a large amount of variation in child:adult ratios. 

Nevertheless, the significant findings do suggest that classrooms with lower child:adult ratios, indicating

higher quality, are likely to be those where teachers are paid more (Table 5-12). 

Table 5-12. Multi-level model predicting child-adult ratio from teacher factors, controlling for programlevel effects (N=265), Fall 2000 

Independent variables 

Program-level 

effects 

Class-level 

effects 

Program + class 

effects 

(INTERCEPT = 5.4) Estimate Signif‡ Estimate Signif Estimate Signif 

Program-Level Factors

Percent parents with some college 

or higher 

-2.64 -2.57 

Percent parents earning 

$1500/month or more 

0.49 0.50 

Percent non-minority students -0.96 -0.87 

Percent language-minority students -1.23 -1.31 

High/Scope Curriculum -0.88 -0.88 

Creative Curriculum -0.58 -0.56 

Average Annual Teacher Salary -0.84 *** -0.81 ** 

Classroom-Level Teacher Factors

Teacher having BA or AA -0.16 -0.04 

Teacher Attitudes and Knowledge 0.03 0.04 

Years Teaching Experience 0.00 0.00 

African-American Teacher 0.35 0.14 

Hispanic Teacher 0.31 0.21 

Teacher Salary

(deviation from program mean) 0.08 0.04 

‡Significance levels as follows: *** indicates p < .001; ** indicates p < .01; * indicates p < .05, † indicates a non-significant trend at p < .10.

Taken together, the results of these multi-level analytic models enhance our understanding of 

factors that explain quality in Head Start by “unpacking” some of the key elements that lead to higher 

quality (Table 5-13). The factors included in the model do a good job of explaining the more 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-35 March 06 
FACE

 

Table 5-13. Summary of program- and classroo

m-level factors predicting classroom quality, Fall 2000 

Predicting 

ECERS-R total 

Predicting AP 

individualizing 

Predicting 

caregiver 

interaction scale 

Predicting childadult ratio 

(Intercept=4.8) (Intercept=3.5) (Intercept = 70.96) (Intercept= 5.4) (In

Esti

mate Signif‡ Esti

mate Signif Esti

mate Signif Estimate Signif Es

Program-Level FactorsPercent parents with some college or hig

her 0.55 0.52 10.59 -2.58 0

Percent parents earning $1500/month or m

ore 

0.44 3.82 *** 2.83 0.50 0

Percent non-minorit

y students 0.82 ** 0.14 3.24 -0.87 0

Percent language-minority students 1.05 * 0.22 -1.98 -1.31 0High/Scope Curriculum 0.30 -0.40 5.33 † -0.88 0Creative Curriculum 0.32 -0.38 6.41 * -0.56 0Average Annual Teacher Salary 0.10 -0.34 † 1.62 -0.81 ** 0Classroo

m-Level Teacher Factors

Teacher having BA or AA -0.09 0.10 -1.09 -0.04 -0Teacher Attitudes and Knowledge 0.11 *** 0.04 1.55 *** 0.04 0Years Teaching Experience 0.01 0.01 0.17 * 0.00 0African-American Teacher -0.14 0.06 -1.75 0.14 -0Hispanic Teacher -0.18 0.04 -3.91 0.21 -0Teacher Salary(deviation fro

m program mean) 0.03 0.16 1.09 0.04 0

‡Significance levels as follows: *** indicates p < .001; ** indicates p < .01; * indicates p < .05, † indicates a non-significant trend at p < .10.

___________________________________________________________________________________________________________________________________

S 2000 Technical Report 5-36 March 06 
“process-oriented” aspects of quality, such as learning materials, quality of language activities and 

teacher-child interactions, but they do less well at predicting the more structural aspects of quality, such

as child:adult ratios. 

5.4 Summary and Conclusions 

Head Start classrooms continue to show good levels of quality, based on the indicators of

quality measured in FACES 2000 in the Fall (2000), Spring (2001) and the following Spring (2002). 

These levels of quality are consistent from the first cohort, and the consistency is evident across a wide 

variety of the indicators. Head Start teachers are qualified and experienced (although as a group they do

not have the same level of credentials as public school teachers), and there appear to be substantially more

teachers with higher educational attainment in this cohort compared with the first FACES cohort, in 1997. 

Head Start teachers in 2000 are younger, compared with those in 1997-1998, and more of them have been 

teaching in Head Start for two years or less. These newer teachers are also the ones most likely to have a

graduate school degree. These results appeared to hold for the Spring 2001 classrooms (which consisted 

of many of the same teachers) and for the Spring 2002 classrooms (despite limitations of this sample). 

The role of teacher attitudes and knowledge, experience and education has been illuminated

by these analyses. Classrooms with higher levels of quality are likely to be those whose teachers have

higher levels of education, experience, and knowledge and attitudes of early childhood education 

practices. However, the relationship between teacher education and classroom quality is explained by 

teacher’s attitudes and knowledge of early childhood education practices, so that teachers who are more

educated have more positive attitudes and knowledge, which translates into higher levels of classroom 

quality. 

In general, when all three factors are included, the direct relationships occur most 

consistently and strongly for attitudes and knowledge about early childhood education practice, and to a 

lesser extent teacher experience, rather than with teacher education. When these other factors were not 

included there was a significant relationship between teacher education and classroom quality, suggesting 

that the role of teacher education in influencing classroom quality is an indirect one. Teachers with higher 

levels of education have more positive attitudes and knowledge about early childhood education practice, 

and they are more likely to be in classrooms rated higher in quality. Thus, teacher attitudes and 

knowledge mediates the role of teacher education in explaining classroom quality. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-37 March 06 
Interestingly, programs using one of the two most widely used integrated curriculum –

High/Scope curriculum and Creative Curriculum – also have teachers with positive attitudes and 

knowledge about early childhood education practice. Both of these factors appear to have the strongest

effect on teacher sensitivity and responsiveness compared with other indicators of quality.

The multi-level results suggest that variations in the quality of Head Start classrooms may be 

explained by characteristics of the families and children they serve, by the curriculum used in the

program, and by teacher attitudes and knowledge about early childhood education practice. The results 

suggest that Head Start classroom quality may be affected by factors beyond the classroom door, that are 

characteristics of the program and the families who participate. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 5-38 March 06 
CHAPTER 6. 

RELATIONSHIP OF PROGRAM, CLASSROOM, AND CHILD AND FAMILY 

CHARACTERISTICS TO CHILDREN'S COGNITIVE GAINS IN HEAD START 

This chapter explores variations in child achievement and behavior across local Head Start 

programs and classes. It uses multilevel modeling to test hypotheses about early education program and

classroom characteristics and child and family educational activities that many child development

scholars believe to be associated with enhanced cognitive growth in preschool children (Phillips, Mekos, 

Scarr, McCartney, and Abbott-Shim, 2000; Whitebook, Howes, and Phillips, 1989). The characteristics 

that are thought to make a difference for program effectiveness include the following: 

 Using an integrated and comprehensive preschool curriculum; 

 Having more ample program resources; 

 Providing classrooms that are of higher quality as early learning environments; 

 Employing a better prepared teaching staff; 

 Providing preschool services for a longer period each day; 

 Conducting educational activities in smaller groups with more personal adult attention 

to the needs and preferences of individual children; 

 Having parents who engage in more educational activities with their children at home;

and 

 Having children who attend Head Start for more than one year. 

This chapter examines relationships between these characteristics and several measures of 

children’s cognitive development while accounting for the influence of other variables. Dependent

variables consisted primarily of direct assessment measures of children’s letter recognition and prereading skills, vocabulary knowledge, early writing and early math skills, book knowledge, and 

knowledge of color names.1

 Covariates included measures of the socioeconomic and ethnic composition 

1

 Analyses with norm-referenced measures (i.e., PPVT-III and the Letter-Word Identification, Applied Problems, and Dictation subtests from

WJ-R), used W ability scores, or IRT scale scores based on item response theory. Analyses with criterion-referenced measures (e.g., book 

knowledge, color names) used raw scores. For description of the measures and their respective scores, please refer to the Appendix.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-1 March 06 
of the families and children participating in each program and classroom, characteristics of the child like 

age, sex, and disability status, and measures of parents’ literacy skills.2

The multilevel analyses of FACES 2000 data did indeed show that some of the

aforementioned characteristics listed above were significantly related to variations in the size of the gains 

children made in Head Start. This chapter enumerates the program, classroom, and child and family 

characteristics that seemed to make a difference, describes the nature and size of the relationships 

involved, and also lists factors that were not significantly related to gains in achievement or behavior and 

discusses possible reasons why hypothesized relationships failed to materialize.

6.1 Conceptual Framework 

The conceptual framework that guided our analyses was a multi-level, multi-causal model of the 

influences that shape children’s cognitive development and the factors that help determine the nature of

the experience children have in Head Start. (See Figure 6-1.) This view posits that children’s development 

in the early years is primarily a function of the experiences they have in their families. Children from lowincome families, whose parents tend to have lower educational attainments than other parents, often do

not experience the same extent or quality of intellectual stimulation at home as children from middle-class 

families (Phillips et al., 1998). Furthermore, their parents are less able to purchase high-quality

supplementary or substitute care in the marketplace. In some cases, children from low-income families 

may also not receive as much emotional support from parents as they need for optimal development. A 

center-based early childhood learning environment such as Head Start may help provide experiences that 

would be beneficial for the development of all children, but especially for those from higher-risk family

environments (NICHD Early Child Care Research Network, 2000). Also, parents’ involvement in their 

children’s educational experiences may be an important factor, and one that programs can foster. 

2

 FACES 2000 included a wider range of program and classroom characteristics that could be related to differences in achievement than did 

FACES 1997. FACES 2000 added interview questions and observational procedures that looked more systematically at areas like the

curriculum used in each center and classroom, training and support for that curriculum, teacher salary levels, teacher knowledge and beliefs,

and the use of child portfolios and other procedures aimed at individualizing instruction. In addition, the sample design was modified to yield a

larger number of sample children in each sample classroom. This produced more stable estimates of class means and more variation in child 

characteristics in each classroom subsample. The modified design made it possible to carry out multilevel regression analysis at three levels: the

program, classroom, and child level. In FACES 1997, multilevel regression analyses could be carried out at only the center and child levels. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-2 March 06 
Teacher Characteristics

 Experience and training

 - education, years teaching

 Attitudes and knowledge about

 ECE instructional practices

 Demographics (age, ethnicity)

 Salary level (as deviation from

 program mean)

Program Characteristics

 Characteristics of families

 - mean family income level

 - mean parent education level

 Primary curriculum

 Teacher salaries

Children's level of achievement

and Fall-Spring gains in cognitive 

skills

Classroom Quality

 ECERS-R language

 Teacher sensitivity

 Teacher individualizing

 Child-staff ratio

Full-day versus 

Part-day class

Child and Family Characteristics

 Child characteristics 

 Parent education, family income, welfare status,

 family structure

 Parent literacy level

 Books in home 

 Educational activities at home

 Child attending Head Start for one versus two years

Child-Level

Classroom-Level

Program-Level

Figure 6-1. Analytical model of multi-level factors predicting classroom quality and children’s 

achievement and gains in the Head Start year 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-3 March 06 
The nature of the learning environment that a given child experiences in Head Start depends 

on the training and teaching experience of teachers in the program, and the resources available to them in

terms of facilities, materials and teaching assistants. Programs with more resources are likely to be better 

able to provide adequate facilities and materials and recruit and retain talented and well-prepared teachers 

(Whitebook, Howes, and Phillips, 1989). 

The character of the classroom environment that a given Head Start program is able to 

provide for a child is not just a question of program resources. It also depends on the educational 

philosophy to which the program adheres, and the kind of curriculum teachers use. Other things equal, 

children would be expected to do better in programs that employ well-thought-out curricula that are

comprehensive and integrated in terms of educational activities and assessment methods. This is 

especially the case if the program is able to provide teachers with adequate training and support in the 

curriculum. At the same time, children’s progress in a given cognitive or social-emotional area depends 

on whether the program’s basic philosophy and curriculum of choice are supportive of efforts to bolster

that area of child development. 

6.2 Research Questions 

The analyses reported in this chapter used multilevel regression models to address the 

following research questions: 

1. Do Head Start programs and classes differ in the cognitive gains that children have 

attained when they leave the program?

2. Do children in Head Start programs that employ one of the two most widely used 

integrated early childhood curricula–Creative Curriculum or High/Scope curriculum–

show larger cognitive gains than children in Head Start programs that employ other 

curricula?

3. Do children in Head Start programs that pay higher salaries to their lead teachers show

larger cognitive gains than children in Head Start programs that have less ample 

resources?

4. Do children in Head Start classes that are of higher quality, as indicated by their 

receiving higher scores on the Language subscale of the Early Childhood Environment

Ratings Scale–Revised (ECERS-R) or the Caregiver Interaction Scale (CIS), show larger

cognitive gains than children in classes that are of lower quality on these measures? 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-4 March 06 
5. Do children in Head Start classes led by better prepared teachers show larger cognitive

gains than children in classes led by teachers who are less well prepared? Indicators of

teacher preparation that were examined included whether the teacher had a Bachelor’s

degree or Associate’s degree or higher, her years of teaching experience, her annual 

salary as a deviation from the program mean salary, and her score on a scale that

measured positive attitudes and knowledge about early childhood educational practices. 

6. Do children who participate in Head Start classes for a longer period each day–who 

attend “full-day” classes–show larger cognitive gains than children who participate for a 

shorter period of time–who attend “part-day” classes?

7. Do children in Head Start classes with lower child:staff ratios, and that provide more 

attention to the needs and preferences of individual children, as indicated by a higher 

score on the Assessment Profile Individualizing scale, show larger cognitive gains than 

children who are in classes with higher child:staff ratios or lower individualizing scores? 

8. Do children whose parents engage in more educational activities at home with their 

children show larger cognitive gains than children whose parents engage in fewer 

educational activities? The presented analyses examined whether children whose parents

read to them on a daily basis at home showed greater gains than children whose parents

read to them less often. Frequency of reading was reported by the parents themselves in

parent interviews in the Fall of 2003; and 

9. Do children who attend Head Start for 2 years show larger cognitive gains than children

who attend for only 1 year? 

6.3 Analysis Method 

The analysis method used to examine associations between Head Start program and class

characteristics, as well as children’s educational activities in the home and the number of years in Head

Start, and children's cognitive development was multilevel linear regression modeling, using the SAS 

PROC MIXED computer program (Singer, 1998; Bryk and Raudenbush, 1992). Multilevel modeling 

shows how the average achievement scores of a sample of classes, schools, or other educational units (in 

the present case, Head Start programs and classes) relate to a set of characteristics of those units, such as 

measures of program demographics and classroom quality. Simultaneously, this type of modeling can 

examine how the achievement scores of individual children in each program and class relate to a set of

child-level characteristics, such as child demographics and home literacy activities. This method provides 

a numerical estimate of how sizable the program-to-program and class-to-class variation in average scores

is, relative to the child-to-child variation in scores within classes. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-5 March 06 
The primary dependent variables were the cognitive assessment scores at graduation from 

Head Start and the gains each child made between entry and graduation. Models were also constructed of 

assessment scores3

 attained by Head Start children in the FACES national sample in the Fall of 2000 and

the Spring of their final Head Start year.4

 Each analytic model had three levels. The first level involved

variation in average assessment scores or average gain scores across the 43 programs in the FACES

national sample, expressed as deviations of the program means from the overall mean score for the entire 

sample. The second level involved variations of class means from the overall program means. And the 

third level involved variation in individual children's scores or gain scores around the class means. 

There were three levels of independent variables used to model or predict the assessment

scores and gain scores. At the program level, the independent variables consisted of measures

representing the curriculum employed by the program, average teacher salary levels in the program, and 

average demographic and socioeconomic characteristics of the children who attended each program and

their families. At the classroom level, independent variables consisted of measures of teacher preparation, 

teacher background characteristics, whether the class was of full-day or part-day duration, and indicators 

of classroom quality such as the ECERS-R Language subscale and Caregiver Interaction Scale. Classlevel variables also included measures of the demographic composition of the class, expressed as

deviations from the average demographic characteristics of the program. At the child level, the 

independent variables were measures that represented demographic characteristics of the child, 

socioeconomic, cultural, and structural characteristics of the family, parent literacy levels, disability status

of the child, the frequency of parental reading to the child, and whether the child attended Head Start for 

one year or two years. 

Statistical tests were conducted to assess whether a given set of independent variables 

(program-level, class-level, and child-level) improved the model's fit to the data, over and above simpler

models that did not include that set. Tests were also done as to whether the regression coefficient for a 

given independent variable was reliably greater than zero. Details about variable definitions, means and

3 In the multilevel regression models, assessment scores for the norm-referenced measures were converted to “W-ability scores,” based on IRT

scaling of item difficulties carried out by the test developers. These scale scores are purported to have equal-interval properties that are

desirable in regression modeling, particularly of gain scores. In other analyses, standard score versions of the assessment scores were used.

These scores show how Head Start children performed compared to national norms. But they do not have as strong equal-interval properties as 

the W-ability scores. Analyses with criterion-referenced measures used raw scores. For more information on the measures and scores used in 

FACES 2000, please refer to the Appendix.

4

 Children participating in FACES 2000 who entered Head Start in Fall 2000 were all new to Head Start. However, some children graduated after

that first year of Head Start (Spring 2001) while others graduated after 2 years (Spring 2002). The entire sample of one- and two-year graduates 

are included in these analyses. The number of years of participation in Head Start was included in the models in the form of a dummy variable

indicating if the child was a one-year graduate (being a two-year graduate is the reference group).

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-6 March 06 
ranges, reliability of measures, and statistical tests used to ascertain the reliability of findings are 

described in the Appendix of the report. 

6.4 Findings 

Multilevel regression analyses of the assessment measures showed that the addition of the 

program- and classroom-level variables provided unique and significant contributions above and beyond

the child-level variables to the prediction of children’s assessment scores at Head Start entry and 

graduation, as well as gains from entry to graduation (see Table 6-1). The addition of the program- and

classroom-level variables significantly contributed to the prediction of all nine assessment scores at entry 

into Head Start, increasing the variance accounted for by the model by approximately 1 to 7 percent. The 

addition of the program- and classroom-level variables significantly contributed to the prediction of eight 

of the nine graduation scores, increasing the variance accounted for in these models by approximately 2 to 

10 percent. Finally, the addition of the program- and classroom-level variables significantly contributed to 

the prediction of five of the nine gain scores, increasing the variance accounted for in these models by

approximately 2 to 4 percent. 

The multilevel regression analyses showed that there were significant relationships between 

some of the program and class characteristics identified above and variations in children’s cognitive 

gains. Tables 6-2 through 6-10 contain the details of the results from the multilevel regression analyses. 

The following factors seemed to make a difference for children’s progress: 

1. Programs using the High/Scope curriculum; 

2. Programs having higher teacher salaries;

3. Teachers having Bachelor’s or Associate’s degrees or higher; 

4. Children attending full-day rather than part-day classes; 

5. Parents reporting that they read to their children more frequently; and 

6. Children attending Head Start for 2 years. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-7 March 06 
_______________________________________________________________________________________________________________________________

FACE

 

Table 6-1. Percentage of variance accounted for b

y the child-level 

model and the combined model with program-, classro

factors, and the difference in the proportions 

Proportion of variance in dependent variable accounted for 

Entry Graduation 

Childlevel 

model 

Co

mbined 

model 

Additional 

variance 

(change in R2

)

Childlevel 

model 

Co

mbined 

model 

Additional 

variance 

(change in R2) 

Childlevel 

model 

Co

m

PPVT-III 51.2 54.1 2.9*** 47.7 51.0 3.3*** 35.5 WJR Letter-Word ID 10.0 17.4 7.4*** 15.2 24.0 8.8*** 15.4 WJR Applied Problems 26.1 31.7 5.6*** 20.2 28.0 7.8*** 15.8 WJR Dictation 20.3 26.3 6.0*** 14.9 24.4 9.5*** 10.1 Book Knowledge 19.6 21.9 2.3*** 15.4 20.9 5.5*** 7.4 Color Naming 29.0 31.4 2.4*** 15.7 18.0 2.3*** 25.9 Design Cop

ying 20.9 22.1 1.2** 13.3 15.0 1.7 11.1 

One-to-One Counting 19.1 21.5 2.4*** 12.7 15.4 2.7*** 8.4 Social Awareness 18.3 20.8 2.5*** 25.2 27.6 2.4*** 13.6 Note: The test of model significance was a 

Χ2 (df = 17) test. *p < .05; **p < .01; ***p < .001.

____

S 2000 Technical Report 6-8 March 06 
Table 6-2. Three-level regression models of PPVT-III Vocabulary scale scores of Head Start children 

upon Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

PPVT-III score 

upon Head 

Start entry

PPVT-III score 

upon Head 

Start graduation 

Gains in PPVT-III 

score from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 2.57* 3.20** 0.66 

Program Mean Family Income Level 1.47 -1.49 -2.99* 

High/Scope Curriculum 0.49 1.91† 1.43 

Creative Curriculum 1.22 1.21 0.00 

Mean Teacher Salary Level 0.54 0.75 0.23 

Proportion Language-Minority Children -0.41 3.35 3.68† 

Proportion Non-Minority Children 5.22** 6.76*** 1.49 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score 0.24 -0.19 -0.47† 

Average Child-Adult Ratio 0.25 0.30 0.06 

AP Individualizing Score -0.17 -0.01 0.20 

Teacher BA or AA or higher 0.42 -0.27 -0.67 

Years Teaching Experience 0.00 -0.04 -0.05 

African American Teacher -0.38 0.43 0.69 

Hispanic Teacher -0.39 0.76 1.21 

Teacher Salary Deviation Score 0.02 0.45 0.46 

Teacher DAP Beliefs Score 0.06 0.01 -0.05 

Average Lead Teacher Arnett Score -0.01 0.03 0.04 

Class Parent Education Level (deviation) 1.16† 0.94† -0.23 

Class Family Income Level (deviation) -1.06 -0.60 0.41 

Proportion Language-Minority (deviation) 0.11 -1.84 -2.26 

Class Proportion Non-minority (deviation) 6.68*** 4.50** -2.19 

Full -Day Class -0.78 -0.34 0.48 

Child-Level Predictor Variables 

Parent Education Level (deviation) 0.50* 0.56** 0.08 

Family Income Level (deviation) 0.13 0.27 0.13 

Welfare Status -0.48 -0.61 -0.14 

Age of Child in Months 0.91*** 0.70*** -0.21*** 

Sex of Child 0.08 -0.12 -0.18 

Disability Status -3.03*** -2.24*** 0.86 

African American Child -2.57** -3.61*** -1.00 

Hispanic Child -1.47 -2.18** -0.70 

Language-Minority Family -8.82*** -6.58*** 2.29* 

Mother-Father Family -0.79 -0.41 0.37 

Neither Birth Parent In Home 1.83 -0.55 -2.33* 

Parent Literacy Standard Score (KFAST) 0.14*** 0.12*** -0.02 

Books In Home 1.47* 1.24* -0.21 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-9 March 06 
Table 6-2. Three-level regression models of PPVT-III Vocabulary scale scores of Head Start children 

upon Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

(continued) 

PPVT-III score 

upon Head 

Start entry

PPVT-III score 

upon Head 

Start graduation 

Gains in PPVT-III 

score from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not at all -0.75 -0.26 0.52 

One or twice -1.45* -1.55** -0.11 

Every day 1.04† 1.28* 0.27 

One-year Head Start graduate -0.64 -10.73*** -10.11*** 

Intercept -8.40 21.13*** 29.29*** 

Proportion of Variance Accounted For 

Between-Programs Variance 100 83 64 

Between-Classes Variance 13 5 16 

Within-Classes Variance 1 1 0 

Total Variance 6 6 2 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001

** p < .01.

* p < .05.

† p < .10.

N = 1,600.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-10 March 06 
Table 6-3. Three-level regression models of WJR Letter-Word ID scale scores of Head Start children 

upon Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

WJR LW ID 

score upon 

Head Start 

entry

WJR LW ID 

score upon 

Head Start 

graduation 

Gains in WJR LW 

ID score from

entry to graduation 

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 4.16* 4.90* 0.61 

Program Mean Family Income Level 2.54 0.01 -2.30 

High/Scope Curriculum -1.17 3.85† 4.62* 

Creative Curriculum -1.35 0.94 1.97 

Mean Teacher Salary Level 1.52 3.88** 2.03† 

Proportion Language-Minority Children 5.34 2.94 -2.46 

Proportion Non-Minority Children -2.03 1.83 3.44 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score -0.63 -0.90 -0.11 

Average Child-Adult Ratio 0.62* 1.15*** 0.46 

AP Individualizing Score 0.37 -0.17 -0.50 

Teacher BA or AA or higher 2.30* 1.70 -0.54 

Years Teaching Experience 0.00 0.00 0.00 

African American Teacher -3.10* -0.59 2.43 

Hispanic Teacher -0.57 -0.13 0.53 

Teacher Salary Deviation Score -1.47 -1.46 -0.11 

Teacher DAP Beliefs Score -0.16 -0.88* -0.77† 

Average Lead Teacher Arnett Score 0.06 0.03 -0.03 

Class Parent Education Level (deviation) 1.67† 3.23* 1.56 

Class Family Income Level (deviation) -0.10 0.39 0.57 

Proportion Language-Minority (deviation) -6.23 0.52 7.25 

Class Proportion Non-minority (deviation) 1.59 4.18 2.73 

Full -Day Class 0.42 2.26 1.67 

Child-Level Predictor Variables 

Parent Education Level (deviation) 1.24** 1.99*** 0.75† 

Family Income Level (deviation) 0.95† 1.03 0.13 

Welfare Status -0.93 -2.94 -2.07† 

Age of Child in Months 0.51*** 0.64*** 0.15 

Sex of Child 0.50 1.54 1.14 

Disability Status -1.54 -4.03* -2.40† 

African American Child 0.95 3.00 2.22 

Hispanic Child -1.60 -0.61 1.23 

Language-Minority Family 2.99 -0.89 -3.92† 

Mother-Father Family -1.12 -1.22 0.02 

Neither Birth Parent In Home 4.02† -0.71 -4.87* 

Parent Literacy Standard Score (KFAST) 0.11** 0.06 -0.04 

Books In Home 0.62 -0.10 -0.75 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-11 March 06 
Table 6-3. Three-level regression models of WJR Letter-Word ID scale scores of Head Start children 

upon Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

(continued) 

WJR LW ID 

score upon 

Head Start 

entry

WJR LW ID 

score upon 

Head Start 

graduation 

Gains in WJR LW 

ID score from

entry to graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not at all -1.39 -2.86 -1.73 

One or twice -1.10 -3.63* -2.78* 

Every day 0.10 -1.25 -1.53 

One-year Head Start graduate -0.46 -14.80*** -14.05*** 

Intercept 291.38*** 315.15*** 22.84† 

Proportion of Variance Accounted For 

Between-Programs Variance 75 96 100 

Between-Classes Variance 100 58 34 

Within-Classes Variance 3 -- 0 

Total Variance 8 10 5 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001 

** p < .01 

* p < .05 

† p < .10 

N = 797 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-12 March 06 
Table 6-4. Three-level regression models of WJR Applied Problems scale scores of Head Start children 

upon Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

WJR AP score

upon Head 

Start entry

WJR AP score

upon Head Start 

graduation 

Gains in WJR AP 

score from entry 

to graduation

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 9.35** 7.70* -1.82 

Program Mean Family Income Level -3.44 -2.91 1.08 

High/Scope Curriculum 7.74* 5.43† -2.54 

Creative Curriculum 1.22 3.22 1.57 

Mean Teacher Salary Level 2.28 2.99† 0.79 

Proportion Language-Minority Children -2.84 -17.46* -15.26* 

Proportion Non-Minority Children 13.95* 8.30 -5.22 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score 0.12 -1.11 -1.32 

Average Child-Adult Ratio 1.93*** 1.40** -0.54 

AP Individualizing Score -0.03 0.53 0.61 

Teacher BA or AA or higher 2.27 1.04 -1.27 

Years Teaching Experience 0.05 0.01 -0.04 

African American Teacher 1.30 -0.83 -2.01 

Hispanic Teacher 2.32 5.53 3.01 

Teacher Salary Deviation Score -2.26 0.41 2.81 

Teacher DAP Beliefs Score 0.00 -1.09† -1.10† 

Average Lead Teacher Arnett Score 0.01 0.12 0.13 

Class Parent Education Level (deviation) 0.60 -0.31 -1.08 

Class Family Income Level (deviation) 0.94 2.13 1.53 

Proportion Language-Minority (deviation) -7.14 1.29 7.36 

Class Proportion Non-minority (deviation) 11.54* 8.20† -2.92 

Full -Day Class 1.08 0.52 -0.64 

Child-Level Predictor Variables 

Parent Education Level (deviation) 1.43† 1.82** 0.44 

Family Income Level (deviation) 2.06* 1.29 -0.68 

Welfare Status -0.16 1.79 1.75 

Age of Child in Months 1.86 1.27*** -0.57** 

Sex of Child 0.64 0.41 -0.20 

Disability Status -12.29*** -9.68*** 2.74 

African American Child -7.09* -8.94** -1.65 

Hispanic Child 1.70 -1.93 -3.08 

Language-Minority Family -8.17 -4.26 5.20 

Mother-Father Family -3.91* -2.72† 1.17 

Neither Birth Parent In Home -0.15 -1.75 -1.12 

Parent Literacy Standard Score (KFAST) 0.19** 0.19** 0.00 

Books In Home 5.49* 1.30 -4.40* 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-13 March 06 
Table 6-4. Three-level regression models of WJR Applied Problems scale scores of Head Start children 

upon Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

(continued) 

WJR Applied 

problems score 

upon Head 

Start entry

WJR Applied 

problems score 

upon Head 

Start graduation 

Gains in WJR 

Applied problems

score from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not at all 2.24 0.80 -1.90 

One or twice -1.67 -1.92 -0.30 

Every day 0.83 -1.15 -1.98 

One-year Head Start graduate 0.37 -16.60*** -16.98*** 

Intercept 224.43*** 308.95*** 82.52*** 

Proportion of Variance Accounted For 

Between-Programs Variance 100 100 100 

Between-Classes Variance 61 48 100 

Within-Classes Variance -- -- 3 

Total Variance 8 10 3 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001 

** p < .01 

* p < .05 

† p < .10 

N = 674 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-14 March 06 
Table 6-5. Three-level regression models of WJR Dictation scale scores of Head Start children upon 

Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

WJR Dictation 

score upon 

Head Start 

entry

WJR Dictation 

score upon 

Head Start 

graduation 

Gains in WJR 

Dictation score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 8.82* 13.75** 4.85 

Program Mean Family Income Level 0.93 1.13 -0.24 

High/Scope Curriculum 4.63 8.90† 4.40 

Creative Curriculum 0.53 1.43 1.12 

Mean Teacher Salary Level 7.32** 6.07* -1.40 

Proportion Language-Minority Children 11.81 1.11 -11.05 

Proportion Non-Minority Children 16.06* 4.91 -11.32 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score -2.01 -4.32** -2.22 

Average Child-Adult Ratio 1.31† 1.92** 0.57 

AP Individualizing Score 1.48 0.82 -0.66 

Teacher BA or AA or higher 5.22† 6.94* 1.70 

Years Teaching Experience 0.16 0.15 -0.01 

African American Teacher 2.55 -4.45 -6.81† 

Hispanic Teacher -0.70 2.11 3.04 

Teacher Salary Deviation Score -2.68 -1.76 0.92 

Teacher DAP Beliefs Score -1.00 0.31 1.25 

Average Lead Teacher Arnett Score 0.19 0.27† 0.08 

Class Parent Education Level (deviation) 0.81 6.93* 6.13* 

Class Family Income Level (deviation) -4.47 -5.26 -0.69 

Proportion Language-Minority (deviation) -17.78 -10.13 8.31 

Class Proportion Non-minority (deviation) 3.79 7.97 4.62 

Full -Day Class 5.62† 8.36** 2.55 

Child-Level Predictor Variables 

Parent Education Level (deviation) 4.44*** 4.52*** 0.08 

Family Income Level (deviation) 2.35† 1.06 -1.24 

Welfare Status -2.49 -5.53† -2.96 

Age of Child in Months 2.60*** 2.18*** -0.43 

Sex of Child 8.38*** 7.03** -1.40 

Disability Status -9.73** -12.83*** -3.09 

African American Child -1.52 2.93 4.19 

Hispanic Child 4.87 5.91 0.98 

Language-Minority Family 0.37 12.94† 12.47† 

Mother-Father Family -3.98 -1.76 2.23 

Neither Birth Parent In Home -6.14 1.34 7.74 

Parent Literacy Standard Score (KFAST) 0.19† 0.17 -0.02 

Books In Home 3.06 3.29 0.05 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-15 March 06 
Table 6-5. Three-level regression models of WJR Dictation scale scores of Head Start children upon 

Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

(continued) 

WJR Dictation 

score upon 

Head Start 

entry

WJR Dictation 

score upon 

Head Start 

graduation 

Gains in WJR 

Dictation score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not at all 0.87 3.78 2.78 

One or twice -3.68 -8.63* -4.91 

Every day -2.19 -2.29 -0.20 

One-year Head Start graduate -1.41 -24.87*** -23.27*** 

Intercept 111.25*** 162.75*** 53.79† 

Proportion of Variance Accounted For 

Between-Programs Variance 100 100 100 

Between-Classes Variance 100 100 71 

Within-Classes Variance 0 -- 0 

Total Variance 8 11 4 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001 

** p < .01 

* p < .05 

† p < .10 

N = 674 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-16 March 06 
Table 6-6. Three-level regression models of Book Knowledge scores of Head Start children upon Head 

Start entry, Head Start graduation, and scale score gains from entry to graduation 

Book 

Knowledge 

score upon 

Head Start 

entry

Book 

Knowledge 

score upon 

Head Start 

graduation 

Gains in Book 

Knowledge score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 0.16 0.57*** 0.42* 

Program Mean Family Income Level 0.12 -0.13 -0.26 

High/Scope Curriculum 0.20 0.25† 0.05 

Creative Curriculum 0.04 0.10 0.06 

Mean Teacher Salary Level 0.06 0.16† 0.09 

Proportion Language-Minority Children 0.12 -0.17 -0.21 

Proportion Non-Minority Children 0.17 0.07 -0.09 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score -0.01 0.00 0.00 

Average Child-Adult Ratio 0.03† 0.04† 0.01 

AP Individualizing Score -0.03 0.00 0.04 

Teacher BA or AA or higher 0.00 -0.02 -0.01 

Years Teaching Experience 0.00 0.00 0.01 

African American Teacher -0.06** -0.03 0.00 

Hispanic Teacher -0.11 0.03 0.06 

Teacher Salary Deviation Score -0.03 0.21* 0.22* 

Teacher DAP Beliefs Score 0.06 -0.02 -0.08* 

Average Lead Teacher Arnett Score 0.00 0.00 0.01 

Class Parent Education Level (deviation) 0.09 0.01 -0.07 

Class Family Income Level (deviation) 0.08 0.13 0.05 

Proportion Language-Minority (deviation) 0.21 -0.30 -0.42 

Class Proportion Non-minority (deviation) 0.49* -0.15 -0.63* 

Full -Day Class 0.03 0.25* 0.24* 

Child-Level Predictor Variables 

Parent Education Level (deviation) 0.07** 0.06* 0.00 

Family Income Level (deviation) 0.00 0.06† 0.06 

Welfare Status -0.07 0.08 0.15† 

Age of Child in Months 0.07*** 0.06*** 0.00 

Sex of Child 0.11 0.24*** 0.11† 

Disability Status -0.14† -0.28** -0.14 

African American Child -0.11 -0.35** -0.24† 

Hispanic Child 0.05 -0.06 -0.09 

Language-Minority Family -0.12 -0.07 0.07 

Mother-Father Family -0.10 0.00 0.10 

Neither Birth Parent In Home -0.06 -0.14 -0.08 

Parent Literacy Standard Score (KFAST) 0.01* 0.01** 0.00 

Books In Home 0.06 0.03 -0.02 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-17 March 06 
Table 6-6. Three-level regression models of Book Knowledge scores of Head Start children upon Head 

Start entry, Head Start graduation, and scale score gains from entry to graduation (continued) 

Book 

Knowledge 

score upon 

Head Start 

entry

Book 

Knowledge 

score upon 

Head Start 

graduation 

Gains in Book 

Knowledge score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not at all -0.07 0.09 0.17 

One or twice -0.26*** -0.14† 0.13 

Every day 0.00 0.20** 0.20* 

One-year Head Start graduate 0.01 -0.74*** -0.74*** 

Intercept -3.45*** -3.52*** -0.20 

Proportion of Variance Accounted For 

Between-Programs Variance 46 73 100 

Between-Classes Variance 40 22 25 

Within-Classes Variance 0 0 0 

Total Variance 3 6 4 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001 

** p < .01 

* p < .05 

† p < .10 

N = 674 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-18 March 06 
Table 6-7. Three-level regression models of Color Naming scores of Head Start children upon Head 

Start entry, Head Start graduation, and scale score gains from entry to graduation 

Color Naming 

score upon 

Head Start 

entry

Color Naming 

score upon 

Head Start 

graduation 

Gains in Color 

Naming score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 1.26† 0.80† -0.49 

Program Mean Family Income Level 0.96 0.67 -0.32 

High/Scope Curriculum -0.98 -0.36 0.62 

Creative Curriculum -1.11† -0.32 0.78 

Mean Teacher Salary Level 0.36 0.16 -0.21 

Proportion Language-Minority Children 2.35 0.41 -1.96 

Proportion Non-Minority Children 2.78* 0.22 -2.53* 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score 0.10 -0.09 -0.18 

Average Child-Adult Ratio 0.26* 0.16* -0.10 

AP Individualizing Score 0.04 -0.06 -0.09 

Teacher BA or AA or higher -0.50 0.12 0.59 

Years Teaching Experience -0.02 0.00 0.02 

African American Teacher -0.23 -0.77* -0.56 

Hispanic Teacher 0.52 -0.31 -0.83 

Teacher Salary Deviation Score 0.04 0.24 0.22 

Teacher DAP Beliefs Score 0.06 -0.05 -0.12 

Average Lead Teacher Arnett Score -0.01 0.01 0.02 

Class Parent Education Level (deviation) 0.60 0.68** 0.09 

Class Family Income Level (deviation) 0.13 -1.17** -1.29** 

Proportion Language-Minority (deviation) -0.22 0.38 0.56 

Class Proportion Non-minority (deviation) 2.32* 0.18 -2.08* 

Full -Day Class -0.56 0.35 0.90* 

Child-Level Predictor Variables 

Parent Education Level (deviation) 0.52*** 0.22* -0.30* 

Family Income Level (deviation) 0.22 -0.12 -0.34* 

Welfare Status -0.70† -0.74** 0.00 

Age of Child in Months 0.42*** 0.19*** -0.23*** 

Sex of Child 1.39*** 1.10*** -0.30 

Disability Status -1.95*** -0.67* 1.28** 

African American Child -0.84 -0.45 0.41 

Hispanic Child 0.14 -0.28 -0.47 

Language-Minority Family -0.76 -0.23 0.56 

Mother-Father Family -0.19 -0.07 0.12 

Neither Birth Parent In Home 2.03** 0.92† -1.09 

Parent Literacy Standard Score (KFAST) 0.07*** 0.03*** -0.04** 

Books In Home 0.50 0.17 -0.33 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-19 March 06 
Table 6-7. Three-level regression models of Color Naming scores of Head Start children upon Head 

Start entry, Head Start graduation, and scale score gains from entry to graduation (continued) 

Color Naming 

score upon 

Head Start 

entry

Color Naming 

score upon 

Head Start 

graduation 

Gains in Color 

Naming score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not at all 0.69 -0.08 -0.75 

One or twice -0.76† -0.13 0.62† 

Every day 0.60 0.06 -0.52 

One-year Head Start graduate -0.28 -3.55*** -3.28*** 

Intercept -24.49*** 2.15 26.95*** 

Proportion of Variance Accounted For 

Between-Programs Variance 74 39 68 

Between-Classes Variance -- 35 22 

Within-Classes Variance 1 0 0 

Total Variance 3 3 3 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001 

** p < .01 

* p < .05 

† p < .10 

N = 1,710 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-20 March 06 
Table 6-8. Three-level regression models of Design Copying scores of Head Start children upon Head 

Start entry, Head Start graduation, and scale score gains from entry to graduation 

Design 

Copying score 

upon Head 

Start entry

Design Copying 

score upon 

Head Start 

graduation 

Gains in Design 

Copying score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 0.14 0.20 0.06 

Program Mean Family Income Level 0.26 0.03 -0.25 

High/Scope Curriculum -0.10 0.09 0.20 

Creative Curriculum -0.24* -0.13 0.10 

Mean Teacher Salary Level -0.03 0.14 0.16† 

Proportion -Minority Children 0.51† -0.02 -0.49 

Proportion Non-Minority Children 0.10 -0.18 -0.28 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score -0.06 0.02 0.08 

Average Child-Adult Ratio 0.01 0.01 0.01 

AP Individualizing Score -0.02 0.00 0.03 

Teacher BA or AA or higher 0.12 0.16 0.06 

Years Teaching Experience 0.00 0.01 0.00 

African American Teacher 0.01 0.10 0.07 

Hispanic Teacher -0.04 0.16 0.18 

Teacher Salary Deviation Score -0.01 -0.02 -0.02 

Teacher DAP Beliefs Score 0.02 -0.07* -0.09** 

Average Lead Teacher Arnett Score 0.00 0.00 0.00 

Class Parent Education Level (deviation) -0.02 0.00 0.00 

Class Family Income Level (deviation) 0.01 0.02 0.01 

Proportion Language-Minority (deviation) -0.01 -0.56 -0.58 

Class Proportion Non-minority (deviation) 0.28 -0.35 -0.59* 

Full -Day Class 0.03 0.10 0.06 

Child-Level Predictor Variables 

Parent Education Level (deviation) 0.03 0.09* 0.06 

Family Income Level (deviation) -0.03 0.01 0.04 

Welfare Status -0.09 -0.16 -0.09 

Age of Child in Months 0.09*** 0.11*** 0.02** 

Sex of Child 0.34*** 0.26** -0.08 

Disability Status -0.25** -0.54*** -0.28* 

African American Child 0.05 -0.53** -0.57** 

Hispanic Child 0.22† 0.00 -0.21 

Language-Minority Family 0.38** 0.25 -0.13 

Mother-Father Family -0.01 0.12 0.13 

Neither Birth Parent In Home -0.33* -0.10 0.25 

Parent Literacy Standard Score (KFAST) 0.00 0.00 0.00 

Books In Home 0.24** 0.15 -0.08 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-21 March 06 
Table 6-8. Three-level regression models of Design Copying scores of Head Start children upon Head 

Start entry, Head Start graduation, and scale score gains from entry to graduation (continued) 

Design 

Copying score 

upon Head 

Start entry

Design 

Copying score 

upon Head 

Start graduation 

Gains in Design 

Copying score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not at all -0.10 0.20 0.32 

One or twice -0.04 -0.23† -0.19 

Every day -0.02 -0.16 -0.14 

One-year Head Start graduate 0.00 -1.42*** -1.42*** 

Intercept -2.84*** -1.21 1.54 

Proportion of Variance Accounted For 

Between-Programs Variance 100 100 54 

Between-Classes Variance 20 23 26 

Within-Classes Variance 0 0 0 

Total Variance 2 2 2 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001 

** p < .01 

* p < .05 

† p < .10 

N = 1,729 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-22 March 06 
Table 6-9. Three-level regression models of One-to-One Counting scores of Head Start children upon 

Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

One-One 

Counting score 

upon Head 

Start entry

One-One 

Counting score 

upon Head Start 

graduation 

Gains in One-One 

Counting score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 0.22† 0.31* 0.09 

Program Mean Family Income Level 0.07 0.13 0.03 

High/Scope Curriculum 0.05 0.00 -0.05 

Creative Curriculum 0.06 -0.12 -0.19 

Mean Teacher Salary Level 0.03 -0.07 -0.09 

Proportion Language-Minority Children 0.35 0.40 0.05 

Proportion Non-Minority Children 0.08 -0.24 -0.33 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score 0.03 -0.02 -0.05 

Average Child-Adult Ratio 0.03† 0.02 -0.01 

AP Individualizing Score -0.04 -0.04 0.00 

Teacher BA or AA or higher -0.03 0.03 0.04 

Years Teaching Experience 0.01 0.00 0.00 

African American Teacher 0.11 -0.06 -0.19 

Hispanic Teacher 0.02 0.01 -0.01 

Teacher Salary Deviation Score -0.06 0.18* 0.24* 

Teacher DAP Beliefs Score 0.01 -0.03 -0.05 

Average Lead Teacher Arnett Score 0.00 0.00 0.00 

Class Parent Education Level (deviation) 0.14* 0.17* 0.03 

Class Family Income Level (deviation) 0.07 -0.08 -0.14 

Proportion Language-Minority (deviation) -0.19 -0.25 -0.06 

Class Proportion Non-minority (deviation) 0.37† -0.04 -0.39 

Full -Day Class 0.15† 0.05 -0.10 

Child-Level Predictor Variables 

Parent Education Level (deviation) 0.06** 0.08** 0.02 

Family Income Level (deviation) 0.05 0.07† 0.02 

Welfare Status -0.03 -0.05 -0.02 

Age of Child in Months 0.07*** 0.07*** 0.01 

Sex of Child 0.24*** 0.28*** 0.04 

Disability Status -0.18* -0.37*** -0.20† 

African American Child -0.05 -0.32** -0.27† 

Hispanic Child -0.05 -0.14 -0.10 

Language Minority Family 0.04 0.06 0.02 

Mother-Father Family -0.08 0.03 0.11 

Neither Birth Parent In Home 0.26† 0.01 -0.23 

Parent Literacy Standard Score (KFAST) 0.01** 0.00† 0.00 

Books In Home 0.08 0.07 -0.01 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-23 March 06 
Table 6-9. Three-level regression models of One-to-One Counting scores of Head Start children upon 

Head Start entry, Head Start graduation, and scale score gains from entry to graduation 

(continued) 

One-One 

Counting score 

upon Head 

Start entry

One-One 

Counting score 

upon Head 

Start graduation 

Gains in One-One 

Counting score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not at all -0.04 -0.06 -0.03 

One or twice -0.09 -0.11 -0.02 

Every day 0.05 0.04 0.00 

One-year Head Start graduate 0.08 -0.84*** -0.92***

Intercept -3.31*** -0.81 2.48**

Proportion of Variance Accounted For 

Between-Programs Variance 20 100 -- 

Between-Classes Variance 39 47 31 

Within-Classes Variance 0 0 -- 

Total Variance 3 3 2 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001 

** p < .01 

* p < .05 

† p < .10 

N = 1,671 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-24 March 06 
Table 6-10. Three-level regression models of Social Awareness scores of Head Start children upon Head 

Start entry, Head Start graduation, and scale score gains from entry to graduation 

Social 

Awareness 

score upon 

Head Start 

entry

Social 

Awareness 

score upon 

Head Start 

graduation 

Gains in Social 

Awareness score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Program Mean Parent Education Level 0.20 0.20 0.01 

Program Mean Family Income Level 0.43* -0.23 -0.67** 

High/Scope Curriculum -0.09 0.25† 0.35* 

Creative Curriculum 0.01 0.20† 0.19 

Mean Teacher Salary Level -0.07 0.11 0.19* 

Proportion Language-Minority Children -0.73* -0.54† 0.26 

Proportion Non-Minority Children -0.56* -0.24 0.37 

Class-Level Predictor Variables 

Average ECERS Language Subscale Score -0.04 -0.02 0.01 

Average Child-Adult Ratio 0.02 0.01 -0.01 

AP Individualizing Score 0.00 0.01 0.01 

Teacher BA or AA or higher -0.12 0.03 0.15 

Years Teaching Experience -0.01† -0.01 0.00 

African American Teacher 0.04 -0.15* -0.19 

Hispanic Teacher -0.15 -0.04 0.08 

Teacher Salary Deviation Score -0.01 0.15 0.16† 

Teacher DAP Beliefs Score -0.03 -0.04 -0.02 

Average Lead Teacher Arnett Score 0.01 0.00 0.00 

Class Parent Education Level (deviation) 0.08 0.17* 0.09 

Class Family Income Level (deviation) 0.09 -0.06 -0.16 

Proportion Language-Minority (deviation) -0.02 0.04 0.09 

Class Proportion Non-minority (deviation) -0.28 -0.31 -0.03 

Full -Day Class -0.20* -0.03 0.18† 

Child-Level Predictor Variables 

Parent Education Level (deviation) 0.06† 0.08** 0.02 

Family Income Level (deviation) 0.03 0.04 0.00 

Welfare Status -0.16† -0.10 0.05 

Age of Child in Months 0.07*** 0.06*** -0.01† 

Sex of Child 0.26*** 0.22*** -0.03 

Disability Status -0.61*** -0.18† 0.44*** 

African American Child 0.29* 0.44*** 0.19 

Hispanic Child 0.21 -0.05 -0.29† 

Language-Minority Family -0.18 -0.48*** -0.30† 

Mother-Father Family -0.25** -0.09 0.17† 

Neither Birth Parent In Home 0.02 0.31† 0.28 

Parent Literacy Standard Score (KFAST) 0.01*** 0.01*** 0.00 

Books In Home 0.16† 0.04 -0.11 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-25 March 06 
Table 6-10. Three-level regression models of Social Awareness scores of Head Start children upon Head 

Start entry, Head Start graduation, and scale score gains from entry to graduation (continued) 

Social 

Awareness 

score upon 

Head Start 

entry

Social 

Awareness 

score upon 

Head Start 

graduation 

Gains in Social 

Awareness score 

from entry to 

graduation 

Program-level predictor variables Unstandardized regression coefficients 

Frequency of Reading to Child 

Not At All 0.24 -0.33* -0.57** 

One or twice 0.02 -0.09 -0.11 

Every day 0.10 0.03 -0.07 

One-year Head Start graduate 0.05 -0.97*** -1.02*** 

Intercept -2.10** 0.63 2.73** 

Proportion of Variance Accounted For 

Between-Programs Variance 100 56 100 

Between-Classes Variance 29 51 41 

Within-Classes Variance 0 0 0 

Total Variance 3 3 3 

Note: Estimates of proportion of variance accounted for represent the proportion of explainable variance, based on the child-level model that is

explained by the combined model.

*** p < .001 

** p < .01 

* p < .05 

† p < .10 

N = 1,707 

Of these factors, only number of years of Head Start attendance was related to increased 

gains or Head Start graduation scores in all cognitive indices examined. But most were related to gains 

and/or Head Start graduation scores on two or more outcome measures, and the relationships were in the 

hypothesized direction. The following sections describe the nature and size of these relationships. 

6.4.1 Use of an Integrated Curriculum

The High/Scope curriculum is a comprehensive, integrated preschool curriculum that has a

long history of research and development. In the present analyses, children in programs that employed the

High/Scope curriculum were found to have made significantly greater gains while at Head Start than

children in programs that employed other curricula. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-26 March 06 
Children in programs that employed the High/Scope curriculum made small but significantly 

greater gains in letter recognition skills than children in programs that employed other curricula (see

Table 6-3). In W ability-score terms, the average Head Start child made a gain on the WoodcockJohnson-Revised Letter-Word Identification (WJ-R LWI) task of 11.4 W ability scale points from entry to

graduation from Head Start. Children in programs employing the High/Scope curriculum showed an 

average gain of 14.1 scale points on the WJ-R LWI from entry to graduation (p < .001), whereas children 

in programs employing other curricula made gains of about 9.4 scale points (p < .001). The regression 

coefficient for the High/Scope curriculum in the three-level regression analysis, which is an estimate of 

the difference in average gains between it and other curricula adjusted for the influence of related

variables, was 4.6 (p < .05). 

Children in programs using the High/Scope curriculum were found to make significantly

greater gains on a criterion-referenced measure of oral communication skills as well (see Table 6-10). The 

“Social Awareness” measure assessed children’s ability to tell an adult basic information about

themselves such as their age, and month and year of birth. The average Head Start child made a gain on

the Social Awareness measure of 0.94 points. Children in programs employing the High/Scope 

curriculum showed an average gain of 1.14 points, whereas children in programs employing other 

curricula made gains of about 0.79 points. The regression coefficient for the High/Scope curriculum 

showed a gain of 0.35 points greater than that for other curricula (p < .05). 

6.4.2 Higher Teacher Salary Levels 

The three-level regression analyses also explored whether children attending Head Start

programs with higher average teacher salary levels would make greater progress in their cognitive and 

social-emotional development. The multivariate analyses showed this to be the case with respect to 

children’s pre-reading and oral communication skills. 

Average Annual Salary for Lead Teachers was associated with higher graduation scores in

the letter recognition task (see Table 6-3). The regression coefficient for Mean Teacher Salary Level in 

the three-level regression analysis of scores at Head Start graduation, which is an estimate of the

difference in LWI scale scores associated with each $10,000 increment in average teacher salaries, 

adjusted for the influence of related variables, was 3.88 (p < .01). 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-27 March 06 
Children in programs with higher average teacher salaries also had higher graduation scores

in the dictation task than those in programs with lower average teacher salaries (see Table 6-5). The 

regression coefficient in the three-level regression model was 6.07 (p < .05). 

Children in programs with higher average teacher salaries made greater gains as well on the 

criterion-referenced “Social Awareness” measure (see Table 6-10). The regression coefficient for the 

Mean Teacher Salary Level showed an increased gain of 0.19 points for every $10,000 increment in mean

salary (p < .05). 

6.4.3 Teachers with Bachelor’s or Associate’s Degrees or Higher 

The possession of a four-year college degree or an Associate’s degree in education or a

closely-related field is among the most widely accepted indicators of teacher preparation. One of the 

current performance goals of the national Head Start program is to have all local programs staffed by

teachers of whom a majority have Bachelor’s degrees or Associate’s degrees. These analyses explored 

whether the lead teacher having at least a BA or AA degree made a difference in children's progress on

the FACES cognitive measures. 

Children in Head Start classes taught by lead teachers with at least a Bachelor’s degree or

Associate’s degree showed greater graduation scores in the dictation task than children in programs with

teachers who did not have such a degree (see Table 6-5). The multilevel regression coefficient showed 

that children whose teachers had at least a Bachelor’s or Associate’s degree had average scores 6.94 W 

ability scale points higher than those whose teachers did not have a degree (p < .05). 

6.4.4 Full-Day Versus Part-Day Classes 

As of the 2000-2001 school year, the majority of children who attended Head Start 

participated in part-day classes that were conducted in morning or afternoon sessions only. These 

analyses explored whether children benefited more from the program in terms of academic achievement if

they attended full-day classes. Children in FACES 2000 who did attend full-day Head Start programs 

made greater gains in several areas than children who attended part-day. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-28 March 06 
In the three-level analysis of Dictation scores at graduation from Head Start (see Table 6-5), 

children in full-day classes had a significant regression coefficient of 8.36 W ability scale points (p < .01).

This meant that children in full-day classes had a mean score upon graduation from Head Start that was

much higher than the mean for children in part-day classes, with related factors controlled. However, in

the multilevel analysis of gains on the Dictation task, the regression coefficient for full-day classes (2.55) 

was not significant. 

In the three-level analysis of book knowledge scores at graduation from Head Start 

(see Table 6-6), children in full-day classes had a significant regression coefficient of 0.25 points

(p < .05), indicating that children in full-day classes had a mean book knowledge score upon graduation

from Head Start that much higher than the mean for children in part-day classes, with related factors

controlled. Further, in the multilevel analysis of gains on the book knowledge task, the regression 

coefficient for full-day classes (0.24) was also significant (p < .05). Children in full-day classes also made

greater gains from Head Start entry to graduation in their knowledge of the parts of a book. 

Children in full-day Head Start classes also made larger gains in color naming skills than 

children in part-day classes (see Table 6-7). The regression coefficient for full-day classes in the threelevel regression analysis was 0.90 (p < .05). 

6.4.5 More Frequent Parental Reading to Children 

Analyses with FACES 2000 data suggest that Head Start programs would contribute to the 

school readiness of its children by encouraging parents to engage in more frequent and more effective 

educational activities at home with their children. Children are in preschool programs for only a limited 

time, both in terms of hours of each day and months out of the child’s life. However, preschool programs 

may extend their influence by encouraging parents to participate in educational activities such as reading 

at home with their children. The national Head Start program recognized the importance of this function 

by stating, in its performance measures framework, that one of the major objectives of the program is, to

“strengthen parents as the primary nurturers of their children.”5

5

 See Head Start FACES: Longitudinal findings on program performance. Third progress report (ACYF, 2001) for a list of the 24 Program

Performance Measures.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-29 March 06 
The three-level regression analyses with FACES 2000 data showed that more frequent 

parental reading in the Fall was associated not only with higher initial achievement for children as they

entered the program, but also with larger gains during the program year. Larger gains were observed for 

children whose parents read to them every day. Smaller gains were observed for children who were read

to only once or twice a week or not at all. 

Parents were asked whether they read to their children, “not at all,” “once or twice,” “three

to six times,” or “every day” during the previous week. Parental responses to the question were entered

into the three-level regression analysis as a set of dichotomous variables, with the most frequent response, 

“three to six times,” as the omitted reference category. The reading responses were entered as child-level

independent variables. 

In the regression analysis of graduation vocabulary test scores, children whose parents

reported reading to their children only “once or twice” had significantly lower mean scores than children 

whose parents reported reading “three to six” times (see Table 6-2). The mean score for children whose

parents said they read “every day” was significantly larger than that of the “three to six times” group. In 

terms of W ability scores on the Peabody Picture Vocabulary Test, Third Edition, the mean for the “once

or twice” group was 1.55 points lower (p < .01); in contrast, the mean for the “every day” group was 1.28 

points higher (p < .05), than the mean for the “three to six times” reference group. 

In the regression analysis of the graduation letter-word identification scores (see Table 6-3), 

the “once or twice” groups again had mean scores that were significantly lower (by 3.63 scale points,

p < .05) than that for the “three to six times” reference group. In the regression analysis of letter-word 

identification gains from entry to graduation, the “once or twice” group had a significantly smaller gain

than the reference group (by 2.78 scale points, p < .05). 

For the graduation book knowledge scores (see Table 6-6), the “every day” groups had mean

scores that were significantly higher than that for the “three to six times” reference group. Children whose

parents reported reading to them “every day” in the past week had scores .20 scale points higher than

those whose parents read to them “three to six times.” (p < .01) In the regression analysis of book 

knowledge gains from entry to graduation, the children whose parents reported reading to them “every

day” had significantly larger gains than the reference group (by .20 scale points, p < .05). 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-30 March 06 
For the graduation social awareness scores (see Table 6-10), children whose parents reported 

not reading to their children at all had mean scores that were significantly lower than that for the “three to 

six times” reference group (b = -.33; p < .05). In the regression analysis of social awareness gains from

entry to graduation, the children whose parents reported not reading to them at all in the past week had

gain scores that were .57 scale points lower than those whose parents read to them “three to six times”

(p < .01). 

In the regression analysis of the graduation dictation scores (see Table 6-5), the “once or

twice” group again had mean scores that were significantly lower (by 8.63 scale points, p < .05) than that 

for the “three to six times” reference group. However, parents’ reported frequency of reading to their

children in the past week were not significantly associated with the entry-to-graduation gain scores for

this cognitive outcome. 

These differences related to frequency of parental reading were obtained even after 

controlling for parent education level, the mother’s score on a measure of adult literacy (the K-FAST), 

and an indicator of the presence of books in the home. While these analyses do not address whether Head

Start programs have an impact on parental reading to children in the home, they do support the notion that 

programs that are able to effectively encourage parents to engage in such activities show greater cognitive

gains among their children. 

6.4.6 Attending Head Start for More than One Year 

Analyses of the FACES 2000 data also suggest that children who benefit from 2 years of 

Head Start show greater cognitive gains across their years in Head Start compared with their peers who

attend for 1 year. The three-level regression analyses with FACES 2000 data showed that, for every 

measure, graduating from Head Start after 2 years as opposed to only 1 year was associated not only with 

higher achievement for children when they graduated from the program, but also with larger gains during

their program years. 

In the regression analysis of graduation vocabulary test scores (see Table 6-2), children who 

graduated from Head Start after 1 year had a significant regression coefficient of -10.73 W ability scale 

points (p < .001). This meant that children who graduated after 2 years had a mean score at graduation

from Head Start that much higher than the mean for children who graduated after 1 year, with related 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-31 March 06 
factors controlled. Further, in the multilevel analysis of gains in vocabulary test scores from entry to

graduation, the regression coefficient for one-year graduates (-10.11) was also significant (p < .001). 

Children who graduated after 2 years in Head Start also made greater gains from Head Start entry to 

graduation in their vocabulary size than those who graduated after 1 year. 

In the regression analysis of the graduation letter-word identification scores (see Table 6-3), 

one-year graduates had a significant regression coefficient of -14.80 W ability scale points (p < .001). 

This meant that two-year graduates had a mean score at graduation from Head Start that much higher than

that of one-year graduates. In the regression analysis of letter-word identification gains from entry to 

graduation, the one-year graduates had a significant regression coefficient of -14.05 (p < .001), indicating

that two-year graduates showed greater improvement in their ability to identify letters and words. 

For the graduation early math scores (see Table 6-4), the regression coefficient for one-year 

graduates was a significant -16.60 (p < .001), indicating that two-year graduates had a mean score at

graduation from Head Start that much higher than their peers who graduated after 1 year. In the analysis

of the early math gain scores, the regression coefficient was also significant (b = -16.98, p < .001). This 

meant that entry-to-graduation gains in early math W ability scores for two-year graduates were that

much higher than those for one-year graduates. 

For the graduation dictation scores (see Table 6-5), children who attended 1 year of Head 

Start had a significant regression coefficient of -24.87 (p < .001), indicating that the mean scores for twoyear graduates was that much greater than that of one-year graduates. Likewise, analysis of the mean

dictation gain scores shows that the one-year graduates had a significant regression coefficient 

(b = -23.27, p < .001). This meant that the entry-to-graduation mean gain in dictation scores was that

much greater for the two-year graduates compared to the one-year graduates. 

Similar patterns of results were found in each of the three-level regression analyses with the 

criterion-referenced variables (see Tables 6-6 through 6-10). The regression coefficients for the one-year

Head Start graduates were significant and negative for the mean graduation scores in book knowledge,

color naming, design copying, one-to-one counting, and social awareness. This meant that the mean

graduation scores for the two-year graduates were significantly greater than those of the one-year 

graduates in each of these measures. Further, the regression coefficients for the one-year Head Start

graduates were significant and negative for the mean entry-to-graduation gain scores in these measures.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-32 March 06 
This meant that the average gain scores for the two-year graduates were also significantly greater than 

those of the one-year graduates in each of these measures. 

6.5 Child:Staff Ratio, More Individual Attention, and Teacher’s Positive Attitudes and

Knowledge About Early Childhood Educational Practices 

The program and class characteristics described earlier in this chapter showed significant 

relationships with children’s gains in Head Start, but there were some sets of characteristics that did not 

show the relationships with children’s gains that were hypothesized. These were the indicators of

child:staff ratio and the indicators of individualized attention to the needs of each child, and the teacher’s

positive attitudes and knowledge about early childhood educational practices. 

6.6 Child:Staff Ratio and More Individual Attention 

It was hypothesized that lower child:staff ratios in Head Start classroom activities, and more

attention to the needs and preferences of individual children, would result in greater gains for children. 

These hypotheses were not confirmed by the data. Indeed, on some outcome measures, children actually

showed higher scores at graduation from classrooms with more children per staff member. 

Child:Staff Ratios. The mean child:staff ratio was a figure derived from counting the 

number of children in the Head Start classroom and dividing that number by the number of teachers or

other adult staff members actively interacting with children. These counts were taken at two separate 

occasions on the day that the classroom was observed, and the two resulting ratios were averaged. When 

the mean child:staff ratio was entered into the three-level regression analyses of children’s cognitive gains 

as a class-level variable, it was not significantly associated with gains in any of the cognitive outcomes 

measures. 

In the analyses of children’s scores at graduation, results were opposite to what was 

predicted. Children in classes with higher child:staff ratios had significantly higher scores at graduation in 

letter recognition skills, early math, early writing, and color naming than those in classes with lower 

ratios. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-33 March 06 
In the three-level regression analyses of letter-word identification scores at Head Start 

graduation (see Table 6-3), the value of the regression coefficient for the mean child:staff ratio was 1.15 

(p < .001). This may be interpreted as the change in LWI W ability scores at Head Start graduation that 

would be expected for every unit increase in the child:staff ratio, net of the effects of other related

variables. If the original hypothesis had been confirmed, this coefficient would be negative. Instead, it 

was significantly greater than zero in the positive direction. Significant positive regression coefficients 

were also found in the regressions predicting graduation scores for the applied problems task (b = 1.40,

p < .01); (see Table 6-4) the dictation task (b = 1.92, p < .01; (see Table 6-5)), and the color naming task 

(b = .16, p < .05; (see Table 6-7)). 

Assessment Profile Individualizing Scale. The Individualizing scale of the Assessment

Profile instrument uses both observational and interview methods to assess the degree to which preschool 

teachers track the accomplishments of children in their classes and provide activities suited to the 

capabilities and interests of individual pupils. Class-level scores on this instrument did not relate to gains 

in any of the cognitive development areas. Nor did they show associations with graduation scores. 

Caregiver Interaction Scale (CIS). The sensitivity and emotional tone of teacher-child

interaction was assessed with the Caregiver Interaction Scale (CIS), an observation-based rating scale. 

CIS scores for the classroom teacher were not associated with gains for any of the cognitive development

areas. Nor did they show associations with graduation scores. 

ECERS-R Language Subscale. The other indicator of classroom quality, the ECERS-R 

Language subscale, was not associated with higher graduation scores or greater entry-to-graduation gain 

scores on any of the cognitive outcome measures. On the contrary, scores on the ECERS-R Language 

subscale had counterintuitive associations with early writing skills at graduation from Head Start. In the 

three-level regression analyses predicting Dictation scores at graduation (see Table 6-5), the regression

coefficient for the ECERS-R Language subscale signified a Dictation score that was 4.32 W ability scale 

points lower for each unit increase in the classroom’s ECERS-R Language subscale score (p < .01). The

ECERS-R Language subscale score was not associated with any other cognitive outcomes. 

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FACES 2000 Technical Report 6-34 March 06 
6.7 Teacher’s Positive Attitudes and Knowledge About Early Childhood Educational 

Practices 

Teachers’ knowledge about early childhood educational (ECE) practices was assessed by 

asking teachers their level of endorsement of various statements representing beliefs about how children 

in Head Start should be taught or managed. Examples of these statements are “Children should work 

silently and alone on seatwork” or “Head Start activities should be responsive to individual differences in

development.” Items were coded with respect to their conformity with developmentally appropriate ECE 

practices. High scores on this scale indicate strong knowledge of ECE practices. It was expected that

children taught by teachers with stronger knowledge of ECE practices would display higher graduation 

scores and greater gains in the cognitive outcomes. 

However, in the three-level analyses of graduation scores for letter recognition (see Table 6-

3), children taught by teachers with stronger knowledge of ECE practices showed lower scores at

graduation from Head Start. The value of the regression coefficient for the mean ECE practices score was

-.88 (p < .05). This may be interpreted as the change in LWI W ability gain scores that would be expected 

for every unit increase in the teachers score on the ECE practices measure, net of the effects of other 

related variables. If the original hypothesis had been confirmed, this coefficient would be positive. 

Instead, it was significantly less than zero in the negative direction. Counterintuitive findings were also 

found for graduation scores in the design copying task (see Table 6-8). The value of the regression 

coefficient for the mean ECE practices score was -.07 (p < .05). 

In the analyses of children’s gain scores from Head Start entry to graduation, results were 

also opposite to what was predicted. Children taught by teachers with higher scores on the ECE practices 

measure had significantly smaller gain scores in book knowledge (b = -.08, p < .05; (see Table 6-6), and 

design copying (b = -.09, p < .01; (see Table 6-8) than those taught by teachers with lower scores. 

6.8 Summary and Discussion

This chapter explored variations in child achievement across local Head Start programs and

classes. It used multilevel modeling to test hypotheses about early education program, class, and family

characteristics that many child development scholars believe to be associated with enhanced cognitive 

growth in preschool children. The conceptual framework posited that the gains a child makes in Head

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FACES 2000 Technical Report 6-35 March 06 
Start depends on the nature of the learning environment that he or she experiences in the local program 

and the learning activities in the home. The nature of the learning environment depends in turn on the

training and experience of teachers in the program and the resources available to them in terms of

facilities, materials, and teaching assistants. Programs with more resources are likely to be better able to

provide adequate facilities and materials and recruit and retain well-prepared teachers. Another 

hypothesis was that children would make larger gains in programs employing curricula that are

comprehensive and integrated in terms of educational activities and assessment methods. Other

expectations were that children would make more sizable gains in higher quality classrooms, in full-day

as opposed to part-day classes, in classes with better child:staff ratios and more individualized attention to 

pupils, in families where parents engaged in more educational activities with their children, and had the 

benefit of Head Start for more than one year. 

The addition of the program- and classroom-level variables provided unique and significant 

contributions to the prediction of children’s assessment scores at Head Start entry and graduation, as well 

as gains from entry to graduation. Analysis of longitudinal data from FACES 2000 showed that children’s 

gains in Head Start were significantly related to several of the hypothesized characteristics of programs 

and classes. Specifically, use of the High/Scope curriculum, higher teacher salaries, teachers' educational 

credentials (Bachelor’s degrees or Associate’s degrees or higher), and provision of preschool services for

a longer period each day all serve as a pathway to greater cognitive gains. 

Analyses of child-level data show that Head Start children whose parents read to them more

often show greater gains and graduation scores on some measures. These analyses suggest that Head Start

programs who implement efforts to encourage parents to engage in more educational activities with their 

children at home may contribute to the school readiness of children. 

Analyses of FACES 2000 data also suggest that children’s readiness for elementary school is 

enhanced by an extra year of Head Start. For each measure, children who attended Head Start for 2 years 

showed greater graduation scores and greater entry-to-graduation gains compared to their peers who 

attended Head Start for only 1 year. 

However, other analytic results were not in line with expectations. In particular, within the 

narrow range of child:staff ratios in Head Start, higher child:staff ratios were associated with greater 

entry-graduation achievement gains in some of the cognitive outcomes. Further, teachers’ scores on a 

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FACES 2000 Technical Report 6-36 March 06 
scale assessing their knowledge of ECE practices were negatively linked with children’s cognitive 

outcomes. 

Some provisos about the results should be noted. Differences in cognitive gains, while 

statistically significant, were relatively modest in magnitude. By itself, each of the differences was not 

large enough to close the gap between where Head Start children typically end up at the end of the 

program year and the average achievement levels of American children at the start of elementary school.

However, if several of the positive characteristics could be implemented simultaneously in a program,

they might jointly make a more sizable difference. 

The failure to find significant links between children’s cognitive gains in Head Start and 

class-level scores on the ECERS-R Language subscale may have to do with the generally good quality of 

Head Start classrooms and the limited range of variation in classroom quality that FACES found in its 

national samples of programs and classes (Peisner-Feinberg, Burchinal, Clifford, Culkin, Howes, Kagan 

and Yazejian, 2001). Studies encompassing broader ranges of quality of childcare and early education 

facilities have shown greater variations in classroom quality measures and significant relationships

between quality measures and children’s gains (Peisner-Feinberg and Burchinal, 1997; Bryant, Burchinal, 

Lau, and Sparling, 1994; NICHD Early Child Care Research Network, 2000; Phillips, McCartney, and 

Scarr, 1987; Whitebook, Howes and Phillips, 1989; but for another failure to find a relationship, see 

Kontos and Fiene, 1987). 

At the same time, the FACES results should make us wary of claims that Head Start could 

produce dramatically larger achievement gains in children from low-income families simply by raising 

ECERS scores or other indicators of classroom quality. It may be that good classroom quality is a 

necessary but not sufficient condition for practically significant gains in specific cognitive or behavioral

areas. It may be that further progress depends on discovering and applying instructional approaches that

can bolster gains in specific areas. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 6-37 March 06 
CHAPTER 7. 

RELATIONSHIP OF PROGRAM, CLASSROOM, AND CHILD AND FAMILY 

CHARACTERISTICS TO CHILDREN'S SOCIAL BEHAVIOR IN HEAD START 

This chapter explores variations in children’s social behavior at the beginning and at the end

of Head Start participation as a function of different program, classroom, and child- and family-level 

predictors. It uses hierarchical linear models to test hypotheses about the links between various predictors

in each of these levels and social behavior in Head Start as reported by Head Start teachers and parents.

Program characteristics that may influence social behaviors include the kind of curriculum used by the 

program, the mean teacher salary level, and different types of family characteristics as a function of the 

program mean. Head Start classroom and center characteristics that may influence children’s social

behavior include the child:adult ratio in the classrooms, the teacher’s behavior in the classroom, and the

teacher’s educational level. Child and family characteristics that may influence social behaviors include 

the child’s gender, race, disability status, the parent’s educational level, and the family income level.

These and other child and family, classroom, and program characteristics are generally believed to be

associated with enhanced social skills in preschool children (Phillips, Mekos, Scarr, McCartney, and 

Abbott-Shim, 2000; Whitebook, Howes, and Phillips, 1989). 

7.1 Conceptual Framework and Research Questions 

The conceptual framework that guided the analyses presented in this chapter was a multilevel, multi-causal model of the influences that shape children’s social-emotional development and the 

factors that help determine the nature of the experience children have in Head Start. This view posits that 

children’s social development in the early years is primarily a function of the experiences they have in 

their families. In some cases, children from low-income families may not receive as much emotional 

support from parents as they need for optimal social development. A center-based early childhood 

learning environment such as Head Start may help provide experiences that would be beneficial for the

socio-emotional development of all children, but especially for those from higher-risk family

environments (NICHD Early Child Care Research Network, 2000).

The nature of the environment that a given child experiences in Head Start depends on the 

training and experience of teachers in the program and the resources available to them in terms of

facilities, materials, and teaching assistants. Programs with more resources are likely to be better able to

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FACES 2000 Technical Report 7-1 March 06 
provide adequate facilities and materials and recruit and retain talented and well-prepared teachers 

(Whitebook et al., 1989). According to these assumptions, the following research questions are examined

in this chapter: 

1. Are Head Start program characteristics predictive of children’s social behaviors? 

2. Are Head Start classroom characteristics predictive of children’s social behaviors?

3. Are child and family characteristics predictive of children’s social behaviors? and 

4. Do Head Start program and classroom characteristics explain children’s social 

development over and above child and family characteristics?

7.2 Analysis Method 

The analytic model used here examines all four research questions simultaneously. It is a 

multilevel linear regression modeling, using the SAS PROC MIXED computer program (Bryk and 

Raudenbush, 1992; Singer, 1998) which was designed for the simultaneous examination of the effects of

different sets of characteristics which are not independent (i.e., one set of characteristics is nested within 

the other) on children’s social behavior outcomes. It provides an estimate of the amount of variance 

accounted for by each set of variables separately, as well as an estimate of the amount of additional

explanatory power of one or more sets of characteristics (e.g., program and classroom characteristics)

over and above another set of characteristics (e.g., child and family characteristics). 

The primary dependent variable sets were: 

 Head Start entry year (Fall 2000) social behavior scores; 

 Head Start graduation year (Spring 2001/2002) social behavior scores; and 

 The gains each child made between the Fall of their entry year and the Spring of their

final year in Head Start in their behavior ratings scale scores (for the social skills

variables, gains refer to an increase in scale scores; for the problem behavior

variables—(i.e., aggressive, hyperactive, and withdrawn behaviors)—gains refer to a 

decrease in scale scores). 

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FACES 2000 Technical Report 7-2 March 06 
Each analytic model had three levels. The first level involved variation in average

assessment scores or average gain scores across the programs in the FACES national sample, expressed as

deviations of the programs means from the overall mean score for the entire sample. The second level

involved variation in average assessment scores or average gain scores across the classrooms in the 

FACES national sample, expressed as deviations of the classrooms means from the overall mean score for 

the entire sample. The third level involved variation in individual children's scores or gain scores. The

sets of independent and dependent variables used in the analyses are presented in Table 7-1. 

7.3 Findings 

Twenty-four separate multilevel linear regression modeling analyses were conducted. Sixteen

analyses were used to predict social behavior at entry and graduation. Eight analyses were used to predict 

gains from entry to graduation. In each analysis, the three sets of independent variables were used to

predict 1 of the 24 social behavior outcomes or gains from entry to graduation (i.e., eight parent and 

teacher social behaviors ratings multiplied by three types of scores: entry, graduation, and gain from entry

to graduation). The results are presented in four different sections corresponding to the four research

questions. 

7.3.1 Are Head Start Program Characteristics Predictive of Children’s Social Behaviors? 

There were significant relationships between some of the program characteristics and

variations in children’s social behaviors. All of these links were in the expected directions (i.e., better

scores in the program-level characteristics predicted better social behaviors). The data related to the

specific links between program characteristics and social behavior outcomes or gains in social behavior

are detailed in the upper portions of Tables 7-2 (each table represents the links with 1 of the 8 social

behavior outcomes). As can be seen in these tables, the program factors that seemed to influence

children’s social behaviors were: 

 The salary level of teachers in the programs, which was related to 6 of the 8 social

behavior variables (All the teacher-reported scales, and parent-reported social skills 

and withdrawn behavior); 

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FACES 2000 Technical Report 7-3 March 06 
_______________________________________________________________________________________________________________________________

FACE

 

Table 7-1. Independent and dependent variables used in the analyses 

Independent variables list 

Dependent variables Program level Classroo

m level Child/

Teacher report: 

1 Social skills 2. Aggressive behavior 3. Hyperactive behavior 4. Withdrawn 

behavior 

Parent report: 

1. Social skills 2. Aggressive behavior 3. Hyperactive behavior 4. Withdrawn 

behavior 

1. Curriculum (High/Scope 

curriculum or Creative Curriculum)

2. Average teacher salary in 

the program

3. Proportion of non-minority 

children 

4. Program mean parent 

education level 

5. Program mean family

income level

6. Proportion of languageminorit

y children 

1. Full-da

y class 

2. Proportion of non-minority 

children (deviation fromprogram) 

3. Average child:adult ratio in 

classroo

m

4. Average ECERS-R 

Language subscale 

5. Average Arnett score 6. Assessment Profile score 7. Teacher education 8. Teacher experience 9. Teacher D

A

P beliefs score

10. African A

merican teacher 

11. Hispanic teacher 12. Teacher salar

y deviation 

score 

13. Parent education level 

(deviation) 

14. Family income level 

(deviation) 

15. Proportion languageminorit

y (deviation) 

1. Parent lite2. Parental e3. Family inc4. Welfare st5. Books at h6. Frequency 

1. Not 2. Onc3. Ever

7. Child’s ag8. Child’s ge9. Child’s Af

racial orig

10. Child’s Hi11. Child from 

minorit

y h

12. Disability 13. Two-paren

household 

14. No biolo

g

15. Years in H

Note: For a detailed description of these variables, see Technical Appendix.

____

S 2000 Technical Report 7-4 March 06 
 The use of the High/Scope curriculum, which was also related to 6 of the 8 social

behavior variables (all the teacher-reported scales and parent-reported aggressive and 

hyperactive behavior); and

 The mean parent education level in the program, which was related to 4 of the 8 social 

behavior variables (All of the teacher-reported scales). 

The social behavior variable that seemed to be most affected by program characteristics was

teacher-reported social skills. It was linked to 4 of the 7 program characteristics: the mean family income 

in the program, the use of High/Scope curriculum, the use of Creative Curriculum, and the mean teacher

salary in the program (see Tables 7-2). The program-level models explained only 0.4 to 5.2 percent of the

variance in social behavior variables. In fact, the explanatory power of the program-level models was 

rarely higher than 2 percent (see Table 7-3). A notable exception was found in the case of parent-reported

hyperactive behavior, for which the program-level model explained 5.2 percent of the variance at entry

and 5 percent of variance at graduation. Links between program-level characteristics and social behaviors

were most evident in the graduation period of data collection (21 of the 34 significant links in the program 

level were in this period). 

7.3.2 Are Head Start Classroom Characteristics Predictive of Children’s Social Behaviors? 

Data related to specific links between classroom characteristics and children’s social 

behavior are detailed in the middle portions of Tables 7-2. In general, only a few significant relationships 

emerged between the classroom characteristics and children’s social behavior outcomes, but all were in

the expected direction. The only classroom-level characteristic related to more than two social behavior 

outcomes was the teachers’ education level (the proportion of teachers with an AA degree or higher). This

variable was significantly related to four social behavior variables: teacher-reported aggressive, 

hyperactive, and withdrawn behaviors, and parent-reported withdrawn behavior. The classroom level 

models explained only 0.8 to 3.4 percent of the variance in social behavior variables. Again, the 

explanatory power of the classroom-level models was rarely higher than 2 percent (see Table 7-3). Links 

between classroom-level characteristics and social behaviors were most evident at graduation from Head

Start (8 of the 17 significant links in the classroom level were in this period). 

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FACES 2000 Technical Report 7-5 March 06 
Table 7-2. Three-level regression models of Parent-reported Withdrawn Behavior scores in Head Start 

entry, graduation, and entry-graduation gains 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Program mean parent education level -0.01 0.01 0.02 

Program mean family income level 0.10 0.00 -0.11 

High/Scope curriculum -0.06 -0.10 -0.02 

Creative Curriculum -0.08 -0.10 0.00 

Mean teacher salary level -0.12* 0.00 0.12* 

Proportion language-minority children -0.13 0.10 0.25 

Proportion non-minority children 0.19 0.11 -0.06 

Class-level predictor variables 

Average ECERS-R language score 0.00 0.05† 0.05 

Average child:adult ratio 0.00 -0.01 -0.01 

AP individualizing score 0.03 0.00 -0.02 

Teacher BA or AA or higher -0.07 0.11† 0.16* 

Years teaching experience 0.01* 0.00 -0.01** 

African American teacher -0.04 -0.05 0.02 

Hispanic teacher -0.04 0.09 0.13 

Teacher salary deviation score 0.04 0.04 0.00 

Teacher DAP beliefs score -0.01 -0.02 -0.01 

Average lead teacher Arnett score 0.00 0.00 0.00 

Class parent education level (deviation) 0.15** -0.01 -0.16* 

Class family income level (deviation) 0.03 0.09 0.05 

Class proportion non-minority (deviation) 0.14 -0.09 -0.22 

Proportion language-minority (deviation) 0.11 0.06 -0.04 

Full-day class -0.08 0.07 0.14† 

Child-level predictor variables 

Parent education level (deviation) -0.01 -0.02 -0.01 

Family income level (deviation) 0.02 0.01 -0.01 

Welfare status 0.17** 0.12* -0.05 

Age of child in months 0.01* 0.01 0.00 

Sex of child 0.06 0.01 -0.05 

Disability status 0.19* 0.19* 0.00 

African American child -0.01 -0.05 -0.05 

Hispanic child 0.21* -0.03 -0.23* 

Language-minority family 0.09 0.13 0.04 

Mother-father family -0.16** -0.13* 0.03 

Neither birth parent in home 0.23* 0.28* 0.04 

Parent literacy standard score (KFAST) 0.00* 0.00 0.01* 

Books in home -0.09 -0.21** -0.12† 

 Frequency of reading to child 

 Not at all 0.11 0.25* 0.14 

 Once or twice -0.12* -0.09 0.04 

 Every day -0.08 -0.05 0.03 

One year in Head Start 0.14* -0.04 -0.19* 

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FACES 2000 Technical Report 7-6 March 06 
Table 7-2. Three-level regression models of Parent-reported Withdrawn Behavior scores in Head Start 

entry, graduation, and entry-graduation gains (continued) 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Intercept 0.48 0.27 -0.22 

Proportion of variance accounted for 64% 100% 100%

Between-programs variance 66% 65% 43%

Between-classes variance 4% 3% 2% 

Within-classes variance 

Total variance 8% 5% 5%

Note: Deviation scores in child/family level represent deviations from classroom level mean. Deviation scores in classroom level represent

deviations from program mean.

† p < .1; * p < .05; ** p < .01; *** p < .001.

N = 1,684.

Table 7-3. Three-level regression models of Teacher-reported Social Skills scores in Head Start entry,

graduation, and entry-graduation gains 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Program mean parent education level 0.33 -0.32 -0.68 

Program mean family income level -1.33 -2.80*** -1.38 

High/Scope curriculum -0.10 2.14*** 2.18** 

Creative Curriculum -0.59 0.85* 1.40* 

Mean teacher salary level -0.49 0.84*** 1.33*** 

Proportion language-minority children 0.87 -0.20 -0.99 

Proportion non-minority children -0.57 0.05 0.62 

Class-level predictor variables 

Average ECERS-R language subscale 

score -0.02 0.03 0.01 

Average child:adult ratio 0.05 0.07 0.02 

AP individualizing score 0.03 -0.06 -0.08 

Teacher BA or AA or higher -0.63 -0.58† 0.08 

Years teaching experience -0.04 -0.01 0.02 

African American teacher -0.85 -0.73 0.08 

Hispanic teacher -0.19 -0.38 -0.22 

Teacher salary deviation score 0.36 0.22 -0.15 

Teacher DAP beliefs score -0.04 0.04 0.09 

Average lead teacher Arnett score 0.03 0.00 -0.02 

Class parent education level (deviation) -0.43 -0.11 0.33 

Class family income level (deviation) 0.39 -0.03 -0.36 

Class proportion non-minority (deviation) 0.54 -0.44 -0.94 

Proportion language-minority (deviation) 1.12 1.46† 0.31 

Full-day class -0.42 0.14 0.57 

See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-7 March 06 
Table 7-3. Three-level regression models of Teacher-reported Social Skills scores in Head Start entry,

graduation, and entry-graduation gains (continued) 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Child-level predictor variables 

Parent education level (deviation) 0.03 0.07 0.04 

Family income level (deviation) 0.21 0.03 -0.18 

Welfare status -0.35 -0.50 -0.13 

Age of child in months 0.22*** 0.13*** -0.09*** 

Sex of child 1.49*** 1.53*** 0.04 

Disability status -1.40*** -1.15*** 0.21 

African American child 0.23 -0.18 -0.40 

Hispanic child 0.09 -0.04 -0.18 

Language-minority family 0.19 0.19 0.00 

Mother-father family -0.04 0.51* 0.55* 

Neither birth parent in home -0.70 -0.63 0.04 

Parent literacy standard score (KFAST) 0.00 0.01 0.01 

Books in home 0.67** 0.38 -0.33 

 Frequency of reading to child 

 Not at all 0.22 0.53 0.34 

 Once or twice 0.02 -0.16 -0.17 

 Every day 0.57* 0.36 -0.14 

 One year in Head Start 0.11 -2.31*** -2.36*** 

Intercept 3.42 12.78*** 9.28** 

Proportion of variance accounted for 100% 100% 100%

Between-programs variance 14% 24% 16%

Between-classes variance 15% 11% 10% 

Within-classes variance 

Total variance 17% 14% 14%

Note: Deviation scores in child/family level represent deviations from classroom level mean. Deviation scores in classroom level represent

deviations from program mean.

† p < .1; * p < .05; ** p < .01; *** p < .001.

N = 1,678.

7.3.3 Are Child and Family Characteristics Predictive of Children’s Social Behavior? 

Data related to specific links between child and family characteristics and social behavior 

scores are detailed in the lower portions of Tables 7-2. As expected, the child- and family-level 

characteristics yielded the most significant links with children’s social outcomes. The child characteristics

that were most predictive of the child’s social development were the child’s disability status (8 of 8–

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-8 March 06 
children with disabilities reported to have the less desirable behaviors), the number of years the child

spent in Head Start (8 of 8–children with two years of Head Start reported to have the more desirable 

behaviors), gender (significant links in 7 of the 8 social behavior variables with girls reported to have the

more desirable behaviors), and age (7 of 8–older children reported to have the more desirable behaviors). 

Family characteristics most predictive of child’s social development included the presence of both 

biological/adoptive parents in the household (6 of 8–children with both parents reported to have the more 

desirable behavior) and the existence of books in the home (5 of 8–children with books at home reported

to have the more desirable behaviors). All other child and family characteristics were related to at least

one of the social outcomes and most (15 of 17) were related to at least 2 of the 8 social behavior 

outcomes. The social behaviors most affected from variables in this level were the teacher- and parentreported withdrawn behavior (each were related to 12 of the 17 child and family characteristics). Even the 

least affected social behavior variables (teacher-reported social skills and aggressive behavior) had 

significant links with 7 of the 17 characteristics. The child- and family-level models explained 1.4 to

14.5 percent of the variance in social behavior variables, but most explained more than 5 percent of the 

variance (see Tables 7-3 through 7-10). Links between child- and family-level characteristics and social

behaviors were evident in both entry and graduation periods (45 and 48 significant links, respectively),

but were also fairly evident in terms of gains from entry to graduation (20 significant links). 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-9 March 06 
Table 7-4. Three-level regression models of Teacher-reported Aggressive Behavior scores in Head Start 

entry, graduation, and entry-graduation gains 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Program mean parent education level 0.22 -0.12 -0.31 

Program mean family income level 0.35 0.76* 0.40 

High/Scope curriculum 0.14 -0.49 -0.62** 

Creative Curriculum -0.06 -0.31 -0.25 

Mean teacher salary level -0.06 -0.46*** -0.39** 

Proportion language-minority children 0.64 0.75 0.15 

Proportion non-minority children -0.05 -0.08 -0.05 

Class-level predictor variables 

Average ECERS-R language subscale 

score -0.01 -0.01 -0.01 

Average child:adult ratio 0.02 -0.03 -0.05 

AP individualizing score 0.07 0.05 -0.02 

Teacher BA or AA or higher -0.01 0.30* 0.31† 

Years teaching experience 0.01 0.01 0.00 

African American teacher 0.09 -0.05 -0.15 

Hispanic teacher 0.03 0.21 0.19 

Teacher salary deviation score 0.01 -0.10 -0.10 

Teacher DAP beliefs score -0.03 0.00 0.03 

Average lead teacher Arnett score -0.01 0.00 0.01 

Class parent education level (deviation) 0.26† 0.26 0.01 

Class family income level (deviation) 0.09 0.17 0.07 

Class proportion non-minority (deviation) 1.30* 0.42 -0.87 

Proportion language-minority (deviation) -0.44 -0.31 0.12 

Full-day class 0.18 0.12 -0.06 

Child-level predictor variables 

Parent education level (deviation) -0.05 -0.06 -0.01 

Family income level (deviation) -0.08 0.05 0.13* 

Welfare status 0.16 0.24* 0.08 

Age of child in months -0.05*** -0.04*** 0.01 

Sex of child -0.80*** -0.93*** -0.14 

Disability status 0.43** 0.44** 0.00 

African American child 0.02 0.30 0.28 

Hispanic child -0.13 0.02 0.11 

Language-minority family 0.02 -0.18 -0.21 

Mother-father family -0.30*** -0.41** -0.11 

Neither birth parent in home 0.06 0.17 0.08 

Parent literacy standard score (KFAST) 0.01 0.00 -0.01 

Books in home -0.18 -0.04 0.12 

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FACES 2000 Technical Report 7-10 March 06 
 Frequency of reading to child 

 Not at all 0.07 -0.16 -0.22 

 Once or twice 0.06 0.22† 0.16 

 Every day -0.15 -0.10 0.03 

One year in Head Start 0.03 0.53*** 0.50*** 

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FACES 2000 Technical Report 7-11 March 06 
Table 7-4. Three-level regression models of Teacher-reported Aggressive Behavior scores in Head Start 

entry, graduation, and entry-graduation gains (continued) 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Intercept 3.07** 3.59** 0.46 

Proportion of variance accounted for 99% 93% 98%

Between-programs variance 19% 2% 5%

Between-classes variance 9% 11% 3% 

Within-classes variance 

Total variance 11% 13% 6%

Note: Deviation scores in child/family level represent deviations from classroom level mean. Deviation scores in classroom level represent

deviations from program mean.

† p < .1; * p < .05; ** p < .01; *** p < .001.

N = 1,591.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-12 March 06 
Table 7-5. Three-level regression models of Teacher-reported Hyperactive Behavior scores in Head 

Start entry, graduation, and entry-graduation gains 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Program mean parent education level 0.13 -0.33* -0.45* 

Program mean family income level 0.12 0.68** 0.52† 

High/Scope curriculum 0.06 -0.38* -0.41* 

Creative Curriculum 0.12 -0.13 -0.23 

Mean teacher salary level -0.02 -0.24** -0.21* 

Proportion language-minority children 0.14 0.29 0.13 

Proportion non-minority children -0.34 -0.14 0.23 

Class-level predictor variables 

Average ECERS-R language subscale 

score -0.02 0.02 0.04 

Average child:adult ratio -0.04 -0.07** -0.03 

AP individualizing score 0.07 0.00 -0.07 

Teacher BA or AA or higher -0.04 0.22* 0.26* 

Years teaching experience 0.01 0.00 0.00 

African American teacher -0.28† -0.13 0.15 

Hispanic teacher -0.12 0.07 0.21 

Teacher salary deviation score 0.03 0.04 0.00 

Teacher DAP beliefs score -0.01 -0.01 0.01 

Average lead teacher Arnett score 0.00 0.00 0.01 

Class parent education level (deviation) 0.17 0.19* 0.01 

Class family income level (deviation) -0.06 -0.10 -0.04 

Class proportion non-minority (deviation) 0.49 0.28 -0.25 

Proportion language-minority (deviation) -0.31 -0.22 0.12 

Full-day class 0.15 0.10 -0.05 

Child-level predictor variables 

Parent education level (deviation) -0.03 -0.03 0.01 

Family income level (deviation) -0.05 0.03 0.09* 

Welfare status -0.01 0.08 0.10 

Age of child in months -0.05*** -0.03*** 0.02** 

Sex of child -0.42*** -0.49*** -0.06 

Disability status 0.60*** 0.61*** 0.01 

African American child 0.02 0.10 0.08 

Hispanic child -0.02 0.09 0.13 

Language-minority family -0.07 -0.32* -0.24 

Mother-father family -0.13 -0.27*** -0.15† 

Neither birth parent in home -0.04 0.41* 0.45* 

Parent literacy standard score (KFAST) 0.00 0.00 0.00 

Books in home -0.21* -0.11 0.11 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-13 March 06 
 Frequency of reading to child 

 Not at all -0.20 0.00 0.23 

 Once or twice -0.05 0.13 0.18† 

 Every day -0.15 -0.12 0.02 

 One year in Head Start 0.06 0.46*** 0.39*** 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-14 March 06 
Table 7-5. Three-level regression models of Teacher-reported Hyperactive Behavior scores in Head 

Start entry, graduation, and entry-graduation gains (continued) 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Intercept 4.58*** 3.38*** -1.22 

Proportion of variance accounted for 100% 87% 100%

Between-programs variance 17% 14% 16%

Between-classes variance 10% 10% 5% 

Within-classes variance 

Total variance 11% 13% 8%

Note: Deviation scores in child/family level represent deviations from classroom level mean. Deviation scores in classroom level represent

deviations from program mean.

† p < .1; * p < .05; ** p < .01; *** p < .001.

N = 1,611.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-15 March 06 
Table 7-6. Three-level regression models of Teacher-reported Withdrawn Behavior scores in Head Start 

entry, graduation, and entry-graduation gains 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Program mean parent education level 0.04 -0.37 -0.40 

Program mean family income level 0.76 1.33* 0.42 

High/Scope curriculum -0.23 -0.97* -0.46 

Creative Curriculum -0.21 -0.26 0.09 

Mean teacher salary level -0.36† -0.47* 0.04 

Proportion language-minority children -0.20 0.03 -0.56 

Proportion non-minority children -0.07 0.15 -0.05 

Class-level predictor variables 

Average ECERS-R language score 0.11 0.10 -0.05 

Average child:adult ratio -0.09† -0.12* 0.02 

AP individualizing score -0.09 -0.02 0.08 

Teacher BA or AA or higher 0.24 0.73*** 0.36 

Years teaching experience 0.02† 0.01 -0.02 

African American teacher -0.47 -0.18 0.08 

Hispanic teacher -0.34 0.05 0.19 

Teacher salary deviation score 0.24 0.09 0.00 

Teacher DAP beliefs score -0.02 -0.07 -0.02 

Average lead teacher Arnett score -0.01 0.00 0.01 

Class parent education level (deviation) 0.14 0.24 0.02 

Class family income level (deviation) -0.18 -0.36 -0.27 

Class proportion non-minority (deviation) 1.40 1.14† -1.07 

Proportion language-minority (deviation) -0.12† 0.15 0.08 

Full-day class -0.23 -0.22 0.03 

Child-level predictor variables 

Parent education level (deviation) 0.00 -0.07 -0.06 

Family income level (deviation) -0.11 -0.03 0.09 

Welfare status 0.02 0.33* 0.33† 

Age of child in months -0.07*** -0.03* 0.04** 

Sex of child -0.21† -0.40*** -0.19 

Disability status 1.18*** 1.42*** 0.23 

African American child 0.31 0.55* 0.12 

Hispanic child 0.42† 0.54* 0.13 

Language-minority family -0.13 -0.82*** -0.64* 

Mother-father family 0.28* -0.01 -0.28 

Neither birth parent in home 0.16 0.13 -0.04 

Parent literacy standard score (KFAST) -0.01 -0.02** -0.01 

Books in home -0.30* -0.12 0.16 

 Frequency of reading to child 

 Not at all 0.13 -0.07 -0.18 

 Once or twice -0.18 0.16 0.38* 

 Every day -0.21 -0.17 0.05 

 One year in Head Start 0.08 0.40** 0.31† 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-16 March 06 
Table 7-6. Three-level regression models of Teacher-reported Withdrawn Behavior scores in Head Start 

entry, graduation, and entry-graduation gains (continued) 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Intercept 7.45*** 5.38** -2.17 

Proportion of variance accounted for 

Between-programs variance 55% 43% 25%

Between-classes variance 13% 22% 12% 

Within-classes variance 8% 10% 4% 

Total variance 10% 14% 6%

Note: Deviation scores in child/family level represent deviations from classroom level mean. Deviation scores in classroom level represent

deviations from program mean.

† p < .1; * p < .05; ** p < .01; *** p < .001.

N = 1,591.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-17 March 06 
Table 7-7. Three-level regression models of Parent-reported Social Skills scores in Head Start entry,

graduation, and entry-graduation gains 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Program mean parent education level 0.04 0.50** 0.45* 

Program mean family income level -0.51† -0.17 0.33 

High/Scope curriculum 0.17 0.21 0.05 

Creative Curriculum 0.24† 0.08 -0.16 

Mean teacher salary level 0.27** 0.25* -0.02 

Proportion language-minority children 0.16 0.29 0.13 

Proportion non-minority children 0.45 0.13 -0.29 

Class-level predictor variables 

Average ECERS-R language score -0.01 -0.05 -0.03 

Average child:adult ratio 0.02 0.00 -0.01 

AP individualizing score 0.09† 0.01 -0.08 

Teacher BA or AA or higher -0.16 -0.17 -0.01 

Years teaching experience 0.00 0.00** 0.00 

African American teacher 0.05 0.03 -0.02 

Hispanic teacher 0.22 0.20 -0.03 

Teacher salary deviation score -0.07 -0.10 -0.03 

Teacher DAP beliefs score -0.06† 0.00 0.06 

Average lead teacher Arnett score 0.00 0.00 0.00 

Class parent education level (deviation) -0.07 0.09 0.16 

Class family income level (deviation) -0.30† -0.03 0.32* 

Class proportion non-minority (deviation) 0.60 -0.09 -0.41 

Proportion language-minority (deviation) 0.45 -0.22 -0.61† 

Full-day class 0.02 -0.05** -0.03 

Child-level predictor variables 

Parent education level (deviation) 0.06 0.06† 0.00 

Family income level (deviation) 0.01 0.00 -0.01 

Welfare status 0.25* 0.12 -0.13 

Age of child in months 0.03** 0.02* -0.01 

Sex of child 0.16* 0.03 -0.15 

Disability status -0.62*** -0.75*** -0.14 

African American child 0.27† 0.09 -0.17 

Hispanic child -0.15 -0.21 -0.06 

Language-minority family 0.03 -0.32† -0.33 

Mother-father family -0.08 0.09 0.17† 

Neither birth parent in home -0.25 0.00 0.27 

Parent literacy standard score (KFAST) 0.00 -0.01 -0.01* 

Books in home 0.23* 0.02 -0.20† 

 Frequency of reading to child 

 Not at all -0.34† -0.18 0.17 

 Once or twice -0.20† -0.28* -0.08 

 Every day 0.32** 0.26* -0.06 

One year in Head Start -0.01 -0.50 -0.48*** 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-18 March 06 
Table 7-7. Three-level regression models of Parent-reported Social Skills scores in Head Start entry,

graduation, and entry-graduation gains (continued) 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Intercept 9.73*** 10.23*** 0.59 

Proportion of variance accounted for 

Between-programs variance 100% 100% 63%

Between-classes variance 15% 27% 36% 

Within-classes variance 7% 6% 3% 

Total variance 9% 8% 6%

Note: Deviation scores in child/family level represent deviations from classroom level mean. Deviation scores in classroom level represent

deviations from program mean.

† p < .1; * p < .05; ** p < .01; *** p < .001.

N = 1,709.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-19 March 06 
Table 7-8. Three-level regression models of Parent-reported Aggressive Behavior scores in Head Start 

entry, graduation, and entry-graduation gains 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Program mean parent education level -0.37† -0.55** -0.15 

Program mean family income level -0.05 0.20 0.28† 

High/Scope curriculum -0.02 -0.33* -0.28 

Creative Curriculum -0.25 -0.27* 0.00 

Mean teacher salary level -0.14 -0.05 0.09 

Proportion language-minority children -0.10 0.01 0.09 

Proportion non-minority children 0.07 -0.03 -0.05 

Class-level predictor variables 

Average ECERS-R language score 0.05 0.00 -0.07 

Average child:adult ratio -0.03 -0.05† -0.01 

AP individualizing score -0.04 -0.05 -0.01 

Teacher BA or AA or higher -0.04 -0.02 0.02 

Years teaching experience 0.00 -0.01† 0.00 

African American teacher 0.07 0.18 0.17 

Hispanic teacher 0.02 0.16 0.22 

Teacher salary deviation score -0.10 -0.06 0.05 

Teacher DAP beliefs score 0.04 -0.02 -0.07* 

Average lead teacher Arnett score 0.00 0.00 0.00 

Class parent education level (deviation) -0.06 -0.06 0.00 

Class family income level (deviation) 0.26† 0.11 -0.16 

Class proportion non-minority (deviation) 0.74† 0.37 -0.37 

Proportion language-minority (deviation) -0.19 -0.23 -0.03 

Full-day class -0.02 0.02 0.07 

Child-level predictor variables 

Parent education level (deviation) -0.09* -0.02 0.07† 

Family income level (deviation) -0.05 -0.08 -0.03 

Welfare status 0.02 0.00 -0.03 

Age of child in months -0.02* -0.01 0.00 

Sex of child -0.20* -0.35*** -0.15† 

Disability status 0.54*** 0.45*** -0.10 

African American child -0.25 -0.46*** -0.23 

Hispanic child -0.10 -0.18 -0.06 

Language-minority family 0.08 -0.10 -0.19 

Mother-father family -0.05 -0.17† -0.11 

Neither birth parent in home 0.07 -0.06 -0.13 

Parent literacy standard score (KFAST) 0.00 0.00 0.00 

Books in home -0.11 0.00 0.12 

 Frequency of reading to child 

 Not at all 0.32 0.40† 0.07 

 Once or twice 0.25* 0.06 -0.19† 

 Every day -0.14 -0.19† -0.06 

One year in Head Start -0.08 0.26* 0.36** 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-20 March 06 
Table 7-8. Three-level regression models of Parent-reported Aggressive Behavior scores in Head Start 

entry, graduation, and entry-graduation gains (continued) 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Intercept 5.67*** 5.91*** 0.20 

Proportion of variance accounted for 

Between-programs variance 64% 100% 100%

Between-classes variance 29% 54% 18% 

Within-classes variance 4% 4% 2% 

Total variance 8% 7% 5%

Note: Deviation scores in child/family level represent deviations from classroom level mean. Deviation scores in classroom level represent

deviations from program mean.

† p < .1; * p < .05; ** p < .01; *** p < .001.

N = 1,694.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-21 March 06 
Table 7-9. Three-level regression models of Parent-reported Hyperactive Behavior scores in Head Start 

entry, graduation, and entry-graduation gains 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Program mean parent education level -0.53** -0.41** 0.13 

Program mean family income level 0.01 0.17 0.19 

High/Scope curriculum -0.10 -0.29* -0.19 

Creative Curriculum -0.19 -0.24* -0.04 

Mean teacher salary level -0.07 -0.06 0.00 

Proportion language-minority children -0.22 -0.04 0.18 

Proportion non-minority children 0.21 -0.09 -0.30 

Class-level predictor variables 

Average ECERS-R language score 0.08† 0.03 -0.05 

Average child:adult ratio -0.02 -0.01 0.00 

AP individualizing score 0.00 0.04 0.03 

Teacher BA or AA or higher 0.16† 0.10 -0.04 

Years teaching experience -0.01 -0.01† 0.00 

African American teacher 0.19 0.05 -0.15 

Hispanic teacher 0.17 0.13 -0.03 

Teacher salary deviation score -0.15† 0.02 0.18† 

Teacher DAP beliefs score 0.00 -0.04 -0.04 

Average lead teacher Arnett score 0.00 0.00 0.00 

Class parent education level (deviation) -0.01 -0.05 -0.05 

Class family income level (deviation) 0.11 0.03 -0.07 

Class proportion non-minority (deviation) -0.02 0.15 0.15 

Proportion language-minority (deviation) 0.16 -0.01 -0.20 

Full-day class -0.01 0.02 0.04 

Child-level predictor variables 

Parent education level (deviation) -0.09** -0.04 0.05 

Family income level (deviation) -0.07† -0.04 0.03 

Welfare status -0.01 0.11 0.12 

Age of child in months 0.00 0.00 0.00 

Sex of child -0.13† -0.24*** -0.11 

Disability status 0.81*** 0.77*** -0.03 

African American child -0.10 -0.28** -0.17 

Hispanic child -0.06 -0.08 -0.02 

Language-minority family 0.52*** 0.36* -0.15 

Mother-father family -0.08 -0.12 -0.05 

Neither birth parent in home 0.41* 0.72*** 0.30 

Parent literacy standard score (KFAST) -0.01*** -0.01* 0.01* 

Books in home -0.01 -0.15 -0.14 

 Frequency of reading to child 

 Not at all 0.65*** 0.57*** -0.06 

 Once or twice 0.33*** 0.09 -0.23* 

 Every day 0.07 -0.02 -0.08 

One year in Head Start 0.06 0.18† 0.13 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-22 March 06 
Table 7-9. Three-level regression models of Parent-reported Hyperactive Behavior scores in Head Start 

entry, graduation, and entry-graduation gains (continued) 

Unstandardized regression coeffficents (β) 

Program-level predictor variables Entry Graduation Gains 

Intercept 4.34*** 3.95*** -0.37 

Proportion of variance accounted for 

Between-programs variance 90% 100% 100%

Between-classes variance 76% 55% 7% 

Within-classes variance 10% 9% 3% 

Total variance 17% 15% 3%

Note: Deviation scores in child/family level represent deviations from classroom level mean. Deviation scores in classroom level represent

deviations from program mean.

† p < .1; * p < .05; ** p < .01; *** p < .001.

N = 1,696.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-23 March 06 
Table 7-10. Variance accounted by program-, classroom-, and child- and family-level models in social 

behavior outcomes 

Program-level models 

Percentage of variance accounted for in:

Social behavior Entry Graduation Entry to end gain 

Teacher report: 

Social skills 

Aggressive behavior 

Hyperactive behavior 

Withdrawn behavior 

Parent report: 

Social skills 

Aggressive behavior 

Hyperactive behavior 

Withdrawn behavior 

1.2 

0.9 

0.4 

0.6 

1.3 

1.6 

5.2*** 

1.8* 

2.6** 

1.9 

1.7 

1.8 

1.9** 

2.4*** 

5.0*** 

0.8 

2.9* 

1.3 

1.6 

0.7 

0.5 

0.7 

0.5 

0.8 

Classroom-level models 

Percentage of variance accounted for in:

Social behavior Entry Graduation Entry to end gain 

Teacher report: 

Social skills 

Aggressive behavior 

Hyperactive behavior 

Withdrawn behavior 

Parent report: 

Social skills 

Aggressive behavior 

Hyperactive behavior 

Withdrawn behavior 

2.1 

2.0 

1.8 

3.1† 

1.2 

1.9 

2.7* 

1.9 

1.5 

1.4 

1.7 

2.1 

1.0 

1.8 

3.4** 

1.3 

1.4 

0.8 

1.2 

1.1 

1.4 

1.6 

0.9 

1.6 

Child and family-level models 

Percentage of variance accounted for in:

Social behavior Entry Graduation Entry to end gain 

Teacher report: 

Social skills 

Aggressive behavior 

Hyperactive behavior 

Withdrawn behavior 

Parent report: 

Social skills 

Aggressive behavior 

Hyperactive behavior 

Withdrawn behavior 

14.4*** 

8.7*** 

9.5*** 

6.7*** 

7.1*** 

5.7*** 

14.5*** 

5.6*** 

9.1*** 

8.8*** 

8.7*** 

7.5*** 

5.8*** 

4.7*** 

12.5*** 

4.0*** 

8.7*** 

2.3*** 

4.7*** 

3.5*** 

3.5*** 

2.4** 

1.9** 

1.4† 

Note: Numbers represent percentage of variance accounted for by each model. 

Tests of model significance–χ2

. 

† p < .1; * p < .05; ** p < .01; *** p < .001.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-24 March 06 
7.3.4 Do Head Start Program and Classroom Characteristics Explain Children’s Social 

Development Over and Above Child and Family Characteristics? 

The variance accounted for by the combined program- and classroom-level models in social 

behavior scores is presented in Table 7-3. As can be seen in the table, the combined model typically

explained 3 to 5 percent of the variance in the social behavior scores. The only two cases where the

combined model explained more than 6 percent of the variance were in relation to the parent-reported 

hyperactive behavior at entry and graduation (6.8 percent and 6.4 percent, respectively). Nine of the 24 

combined models were significant and three more were close to significance (see Table 7-3). Next, it was

examined whether the inclusion of the program- and classroom-level sets of independent variables in the

analyses improved models’ fit to the data over and above models which included only the child- and

family-level set of independent variables. In Tables 7-11 and 7-12, the comparison between the childlevel models and the combined model (of all three levels) is presented. As can be seen in the table, these 

levels did add a considerable amount of explained variance to the combined models. Eleven of the 24

additions were significant, and 3 others were close to significance, but all of the combined models

accounted for more variance in social behavior outcomes than the child and family models by themselves, 

typically adding 2 to 4 percent to the models’ fit to the data. 

Table 7-11. Variance accounted by the combined program- and classroom-level model in social behavior 

outcomes 

Program- and classroom-level models 

Percentage of variance accounted for in:

Social behavior Entry Graduation Entry to end gain 

Teacher report: 

Social skills 

Aggressive behavior 

Hyperactive behavior 

Withdrawn behavior 

Parent report: 

Social skills 

Aggressive behavior 

Hyperactive behavior 

Withdrawn behavior 

4.1 

2.5 

2.2 

3.9† 

2.6† 

3.6 

6.8* 

3.0** 

4.4*** 

3.1 

3.8 

5.4*** 

2.6* 

3.7 

6.4* 

1.9 

4.0** 

2.7 

3.1 

1.9 

1.9† 

3.5** 

1.3 

2.8*** 

Note: Numbers represent percentage of variance accounted for by the model.

Tests of model significance–χ2. 

† p < .1; * p < .05; ** p < .01; *** p < .001.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-25 March 06 
Table 7-12. Variance accounted by child- and family-level models and the addition program- and classlevel models to the combined models 

Percentage of variance accounted for: 

Social behavior Child-level models Combined models Addition 

Teacher report: 

Social skills: 

Entry

Graduation 

Gain 

Aggressive behavior: 

Entry

Graduation 

Gain 

Hyperactive behavior: 

Entry

Graduation 

Gain 

Withdrawn behavior: 

Entry

Graduation 

Gain 

Parent report: 

Social skills: 

Entry

Graduation 

Gain 

Aggressive behavior: 

Entry

Graduation 

Gain 

Hyperactive behavior: 

Entry

Graduation 

Gain 

Withdrawn behavior: 

Entry

Graduation 

Gain 

14.4*** 

9.1*** 

8.7*** 

8.7*** 

8.8*** 

2.3*** 

9.5*** 

8.7*** 

4.7*** 

6.7*** 

7.5*** 

3.5*** 

7.1*** 

5.8*** 

3.5*** 

5.7*** 

4.7*** 

2.4** 

14.5*** 

12.5*** 

1.9** 

5.6*** 

4.0*** 

1.4† 

17.2*** 

14.1*** 

13.7*** 

11.2*** 

12.7*** 

5.7*** 

11.3*** 

13.1*** 

8.0*** 

9.9*** 

13.6*** 

5.6*** 

9.1*** 

7.9*** 

5.7*** 

7.9*** 

7.4*** 

4.8*** 

16.7*** 

14.6*** 

3.2** 

8.4*** 

5.0*** 

4.2** 

2.8 

5** 

5† 

2.5 

3.9 

3.4 

1.8 

4.4* 

3.5† 

3.2* 

6.1* 

2.1 

2.0† 

2.1* 

2.2 

2.2** 

2.7*** 

2.4 

2.2*** 

2.1*** 

1.3 

2.8* 

1.0 

2.8* 

Note: Numbers represent percentage of variance accounted for by each model. 

Tests of model significance–χ2

. 

† p < .1; * p < .05; ** p < .01; *** p < .001.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-26 March 06 
7.4 Summary and Conclusions 

The strongest predictors of children’s social behaviors were predictors at the child and 

family level, mainly the child’s age, gender, disability status, and number of years spent in Head Start, as 

well as the presence of both biological/adoptive parents in the house and the existence of books in the

home. Most child and family characteristics have shown stronger links with the social behavior variables 

than characteristics in the program and classroom levels. 

The program- and especially the classroom-level characteristics showed relatively low 

predictive power over children’s social behaviors. Nonetheless, the addition of the program and

classroom levels to the child and family level set of characteristics did result in higher explanatory power 

of the combined model over and above the explanatory power of the child- and family-level model by 

itself. This addition was significantly higher in almost half of the cases examined (see Table 7-4). Thus, 

the inclusion of program and classroom level sets of variables in the combined models increased the

models’ overall fit to the data. This finding supports our initial expectations that (at least in some cases) 

the Head Start experience may serve to compensate for disadvantages in the child- and family-levels. 

The FACES 2000 data are not completely comparable to data from the FACES 1997 cohort

because only two levels were examined in the 1997 modeling: child and family level and center level. 

Nonetheless, the similarities between the two cohorts are still noticeable. In both cohorts, the same child

and family characteristics mentioned above had the strongest links to social behaviors and in both cohorts 

the Head Start-related levels added a significant amount of explained variance to increase the models’ fit

to the data. It should be noted, however, that these results do not supports claims that Head Start could 

produce dramatic social gains in children with disadvantaging circumstances. In particular, important 

program and classroom characteristics such as the kind of curriculum used, classroom quality variables

(e.g., ECERS-R and Arnett scores), and child:adult ratio were not as strong predictors of children’s social 

outcomes as expected. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 7-27 March 06 
CHAPTER 8. 

HEAD START CHILDREN WITH DISABILITIES: SOCIAL-EMOTIONAL AND COGNITIVE 

DEVELOPMENTAL OUTCOMES

8.1 Introduction 

This chapter examines two hypotheses regarding children with disabilities and their nondisabled counterparts. The first hypothesis is that Head Start children with disabilities exhibit lower

social-emotional and cognitive developmental outcomes than their counterparts without disabilities upon 

entrance into Head Start programs. This hypothesis is consistent with expectations regarding the apparent 

linkages between types and severity of disabilities and negative outcomes for children with these 

disabilities. The second hypothesis is that children with disabilities will not progress as well as their nondisabled counterparts over the course of a Head Start year in most social-emotional and cognitive 

developmental outcomes even after controlling for differences in baseline starting points for these 

outcomes and socio-demographic characteristics. This hypothesis will be verified as correct if it can be

shown that children with disabilities exhibited statistically significantly different gains, either in a positive 

direction or a negative direction, from their non-disabled counterparts, favoring the later group of 

children, in most social-emotional and cognitive developmental outcomes. 

8.2 Methodology 

This chapter of the report describes the socio-demographic and other family characteristics

of Head Start children1

 with disabilities and those without disabilities and compares these two groups of

children on their social-emotional and cognitive developmental outcomes. 

Numerous social-emotional and cognitive developmental outcome measures were utilized

for the analyses in this chapter. The social-emotional outcomes as reported by each child’s primary 

caregiver (parent) and teacher include aggression, hyperactivity, withdrawn behavior, total problem

behaviors (a compilation of previous three), positive approaches to learning (parent only), and

cooperative classroom behavior (teacher only). The cognitive developmental outcomes as derived from 

1

 There were 2,429 sampled cases with both completed parent interviews and child assessments in the Fall 2000 sample. Only 2,337 of these 

children and their families were utilized in the analyses for this chapter based on the availability of parent-reported and child assessment data

for both the Fall 2000 and Spring 2001 data collection periods, and specifically, the parental reporting of disability status in the Spring 2001

parent interviews. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8-1 March 06 
direct child assessments include receptive vocabulary knowledge, as measured by the Peabody Picture 

Vocabulary Test-III (PPVT-III); letter and word knowledge, early mathematical skills, and early writing 

skills, as measured by the Woodcock Johnson–Revised (WJ-R) subtests Letter Word Identification, 

Applied Problems, and Dictation; perceptual-motor skills, assessed by the McCarthy Draw-a-Design; and 

book knowledge. Detailed information about the measures is included in the Appendix. 

Head Start requires 10 percent of enrolled children to meet the definition of disability

(45 CFR - Part 1308.4). For these analyses, disability status was determined by the Spring 2001 parent

interview. Children were categorized as disabled only if (a) the parent reported that the child possessed a

disability as reported by a doctor or other health or education professional at some point prior to or during 

enrollment in Head Start, and (b) the parent reported that the child had an Individualized Education Plan 

(IEP) or an Individualized Family Service Plan (IFSP). Children’s disability status as reported in the 

Spring of 2001 was used in lieu of their disability status as reported in the Fall of 2000. This was done to

reflect the diagnoses of disabilities over the course of the Head Start year so as not to underreport the 

numbers of children with verifiable disabilities. Some of the children categorized as non-disabled may

have actually had disabilities that had not yet been diagnosed as of Spring 2001. For these analyses, these 

children will be categorized as non-disabled. 

The analyses conducted for this section of the report entailed the generation of results at the 

beginning of the Head Start year (Fall 2000) to delineate baseline results and across the Head Start year 

(Fall 2000 to Spring 2001) for both children with disabilities and children without disabilities. Data from 

the Fall 2000 and Spring 2001 parent interviews, teacher-child reports, and child assessments were

utilized for these analyses. For measures of children’s knowledge and cognitive skills, the sample size 

was limited to children who completed assessments in English during both interview periods. The sample 

size was limited in this way because it would have been impossible to gauge change over time with

assessments that had been administered in different languages using non-comparable assessment tools. 

Progress in the social-emotional and cognitive developmental domains over the course of the 

Head Start year was demonstrated by taking the difference between Spring 2001 scores and Fall 2000

scores. For example, a difference of 5.0 on the PPVT standard score (standardized with regard to the age 

of the child) represented a 5-point gain from Fall to Spring, and a score of -5.0 on the PPVT standard

score represented a 5-point loss. Generally, positive difference scores indicated progress in that domain. 

The exception to this is with ratings of problem behaviors, where higher scores for these social-emotional 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8-2 March 06 
variables indicated more problematic behaviors. In this case, negative numbers represented reductions in 

problematic behaviors, and thus, progress. 

All of the differences to be discussed with regard to socio-demographic and other family 

characteristics, and all of the differences to be discussed with regard to children's social-emotional and

cognitive developmental outcomes, were determined to be statistically significant through statistical tests 

and regression modeling. For the results pertaining to the social-emotional and cognitive developmental

outcome measures, significance tests were run in SAS utilizing the GLM procedure with a least squares 

means option to control for the large disparities in sample sizes (unbalanced design) between the disabled

subgroup and the non-disabled subgroup. This procedure essentially equates the sample sizes between 

subgroups, thus controlling for large disparities in sample sizes between subgroups in statistical tests to

determine if averages are significantly different. 

8.3 Findings 

As reported by parents, 6 percent of the Head Start children had a disability (see Table 8-1). 

The majority of the children with disabilities had either speech or language impairments or cognitive 

impairments. 

Table 8-1. Disability categories for children with disabilities (Spring 2001) 

Disability categorizations Weighted percentages diagnosed 

Percent of Head Start Children with Disabilities 6% 

Cognitive impairment* 23%

Speech or language impairment** 82%

Behavioral impairment*** 20%

Physical impairment† 17%

Sensory impairment‡ 13%

*

Cognitive impairment includes the following: Specific learning disability, mental retardation, autism, and non-categorical/developmental delay. 

**Speech or language impairment includes speech impairment and language impairment. 

***Behavioral impairment includes emotional/behavioral disorder. 

†

Physical impairment includes the following: orthopedic impairment, health impairment lasting six months or more, and traumatic brain injury.

‡

Sensory impairment includes the following: deafness, other hearing impairment, blindness, and other visual impairment.

Note: Individuals can have more than one impairment type within any impairment category and/or can have more than one impairment type

across the impairment categories. Eleven cases could not be incorporated into any of the five disability categorization types, referenced above,

and thus were excluded from this analysis.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8-3 March 06 
White children were three times more likely than African American children (9 percent vs. 3 

percent) to have disabilities (see Table 8-2). Boys were nearly three times more likely than girls to have 

disabilities (8 percent vs. 3 percent). Children of parents with more than a high school education were two

times more likely than children of parents with a high school education or less to have disabilities (8

percent vs. 4 percent). Finally, the parents of children with disabilities were older, on average, than the

parents of children without disabilities (31.19 vs. 29.59) (see Table 8-3). There were no significant

differences between children with disabilities and those without disabilities on any of the other sociodemographic measures referenced in Tables 8-2 and 8-3. 

Table 8-2. Characteristics of children with disabilities and their families 

Demographic/socioeconomic variables – categorical Weighted percentages 

Percent of Head Start children with disabilities 6% 

African American 3%*** 

White 9%*** 

Hispanic 5% 

Other Race/Ethnicities 7%

Male 8%*** 

Female 3% 

Child's age – 3 years of age 5% 

Child's age – 4, 5, or 6 years of age 6%

Parent with high school education or less 4%** 

Parent with more than high school education 8%

Married 6% 

Not married 5% 

Parent working 5%

Parent not working 6%

Urban 5%

Non-urban 6%

Welfare receipt status – Yes 4% 

Welfare receipt status – No 6% 

Food stamps receipt status – Yes 5% 

Food stamps receipt status – No 6% 

Language-minority household 4%

Non-language-minority household 6%

Difference of Means T-Tests were run in Excel using standard errors generated in WesVar v4.1. 

*** p<.001; ** p<.01.

For race/ethnicity, the only significant difference is between African American children and White children. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8-4 March 06 
Table 8-3. Characteristics of the families of children with disabilities and the families of children 

without disabilities (Fall 2000) 

Weighted average 

Demographic/socioeconomic variables – continuous Disabled Nondisabled 

Percents of Head Start children with and without

disabilities 

6% 94%

Parent's age 31.19** 

(7.26) 

29.59 

(7.76) 

Monthly family income $1,668.13

($1,157.98) 

$1,482.68 

($1,082.60) 

Family size 4.74 

(1.77) 

4.66 

(1.80) 

Standard deviations are in parentheses.

Difference of Means T-Tests were run in Excel using standard errors generated in WesVar v4.1. 

** p<.01.

The results generated with disability status predicting to all beginning of the Head Start year 

social-emotional and cognitive developmental outcomes indicated that, on average, children with 

disabilities did not perform as well as other children on any of these measures with the exception of two 

(see Tables 8-4 and 8-5). The two exceptions were for receptive vocabulary knowledge and book 

knowledge, for which no significant differences were observed. 

Table 8-4. Parent- and teacher-reported social-emotional outcomes for both children with disabilities 

and children without disabilities (Fall 2000) [bivariate results]

Social-emotional measures Weighted averages 

Outcome variables – continuous Disabled Nondisabled 

Percents of Head Start children with and without disabilities 6% 94% 

Aggression scale (parent-reported) 3.59** 3.14 

Hyperactivity scale (parent-reported) 2.46*** 1.84 

Withdrawn Behavior scale (parent-reported) 0.95*** 0.59 

Total Problem Behaviors scale (parent-reported) 8.01*** 6.08 

Positive Approaches to Learning scale (parent-reported) 11.38*** 12.17 

Aggression scale (teacher-reported) 3.02*** 1.66 

Hyperactivity scale (teacher-reported) 2.34*** 1.28 

Withdrawn Behavior scale (teacher-reported) 4.58*** 2.35 

Total Problem Behaviors scale (teacher-reported) 9.93*** 5.30 

Cooperative Classroom Behavior scale (teacher-reported) 12.26*** 14.79 

Significant differences were determined using the GLM Procedure (Least Squares Means option) in SAS v8.0.

A regression model was run for each dependent variable outcome with disability status as the independent variable in each model. 

*** p<.001; ** p<.01.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8-5 March 06 
Table 8-5. Cognitive developmental outcomes for both children with disabilities and children without 

disabilities (Fall 2000) [bivariate results] 

Cognitive developmental measures Weighted averages 

Outcome variables – continuous – E1E2 Disabled Nondisabled 

Percents of Head Start children with and without disabilities 6% 94% 

Receptive vocabulary knowledge – PPVT standardized score 83.48 85.23 

Letter/word knowledge – WJ-R letter/word identification 

standardized score 

89.57* 92.73 

Early mathematical skills – WJ-R applied problems 

standardized score 

82.09** 88.27 

Early writing skills – WJ-R dictation standardized score 79.03*** 85.58 

Perceptual – motor skills – McCarthy draw-a-design score 2.47*** 2.96 

Book knowledge – book knowledge score 1.64 1.61 

E1E2 – Assessment administered in English in both Fall 2000 and Spring 2001.

Significant differences were determined using the GLM Procedure (Least Squares Means option) in SAS v8.0.

A regression model was run for each dependent variable outcome with disability status as the independent variable in each model. 

*** p<.001; ** p<.01; * p<.05.

The results generated with disability status predicting beginning of the Head Start year 

social-emotional and cognitive developmental outcomes, controlling for numerous socio-demographic 

characteristics of the sampled children and their families, indicated that, on average, children with 

disabilities did not perform as well as other children on any of these outcomes with the exception of one 

(see Table 8-6 and 8-7). The one exception was for book knowledge, for which no significant difference 

was observed. The covariates included in the models were child’s race/ethnicity, gender, and age; parent’s

(respondent’s) age; highest education level of parent(s); monthly family income; parental marital status; 

parent’s (respondent’s) employment status; family size; urbanicity of school; household languageminority status; and parental reading to child on a daily basis. 

The results generated with disability status predicting children’s progress over the course of 

the Head Start year with regard to all social-emotional and cognitive developmental outcomes, controlling 

for numerous socio-demographic characteristics of the sampled children and their families, indicated that, 

on average, children with disabilities did not progress as well as other children on parent- and teacherreported hyperactivity, withdrawn behavior, and total problem behaviors (see Table 8-8 and 8-9). The 

covariates included in the models were Fall 2000 baseline score (for each individual scale), child’s

race/ethnicity, gender, and age; parent’s (respondent’s) age; highest education level of parent(s); monthly 

family income; parental marital status; parent’s (respondent’s) employment status; family size; urbanicity 

of school; household language-minority status; and parental reading to child on a daily basis. On average,

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8-6 March 06 
children with disabilities progressed similarly to children without disabilities on all remaining socialemotional outcomes. With regard to the cognitive developmental outcomes, children with disabilities did

not progress as well as other children, on average, on early math skills, perceptual-motor skills, and book

knowledge. No other significant differences were observed. 

Table 8-6. Parent- and teacher-reported social-emotional outcomes for both children with disabilities 

and children without disabilities (Fall 2000) [multivariate results]

Social-emotional measures Weighted averages 

Outcome variables – continuous Disabled Nondisabled 

Percents of Head Start children with and without disabilities 6% 94% 

Aggression scale (parent-reported) 3.59** 3.13 

Hyperactivity scale (parent-reported) 2.40*** 1.81 

Withdrawn Behavior scale (parent-reported) 0.96*** 0.57 

Total Problem Behaviors scale (parent-reported) 7.85*** 5.99 

Positive Approaches to Learning scale (parent-reported) 11.54*** 12.18 

Aggression scale (teacher-reported) 2.91*** 1.68 

Hyperactivity scale (teacher-reported) 2.26*** 1.28 

Withdrawn Behavior scale (teacher-reported) 4.46*** 2.36 

Total Problem Behaviors scale (teacher-reported) 9.63*** 5.32 

Cooperative Classroom Behavior scale (teacher-reported) 12.60*** 14.86 

Significant differences were determined using the GLM Procedure (Least Squares Means option) in SAS v8.0.

A regression model was run for each dependent variable outcome with disability status and other covariates as the independent variables in each

model.

*** p<.001; ** p<.01.

Table 8-7. Cognitive developmental outcomes for both children with disabilities and children without 

disabilities (Fall 2000) [multivariate results]

Cognitive developmental measures Weighted averages 

Outcome variables – continuous – E1E2 Disabled Nondisabled 

Percents of Head Start children with and without disabilities 6% 94% 

Receptive vocabulary knowledge – PPVT standardized score 79.50*** 85.67 

Letter/word knowledge – WJ-R Letter/Word Identification 

standardized score 

89.54* 92.52 

Early mathematical skills – WJ-R Applied Problems 

standardized score 

81.51*** 88.54 

Early writing skills – WJ-R Dictation standardized score 79.41** 85.53 

Perceptual – motor skills – McCarthy Draw-a-Design score 2.40*** 2.95 

Book knowledge – Book Knowledge score 1.51 1.63 

E1E2 – Assessment administered in English in both Fall 2000 and Spring 2001.

Significant differences were determined using the GLM Procedure (Least Squares Means option) in SAS v8.0.

A regression model was run for each dependent variable outcome with disability status and other covariates as the independent variables in each

model.

*** p<.001; ** p<.01; * p<.05.

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FACES 2000 Technical Report 8-7 March 06 
Table 8-8. Parent- and teacher-reported social-emotional outcomes for both children with disabilities 

and children without disabilities (Fall 2000 – Spring 2001) [multivariate results] 

Social-emotional measures Weighted averages 

Outcome variables – continuous Disabled Nondisabled 

Percents of Head Start children with and without disabilities 6% 94% 

Aggression scale (parent-reported) -0.07 -0.29 

Hyperactivity scale (parent-reported) 0.12** -0.23 

Withdrawn Behavior scale (parent-reported) 0.17* -0.00 

Total Problem Behaviors scale (parent-reported) 0.18* -0.53 

Positive Approaches to Learning scale (parent-reported) -0.10 0.05 

Aggression scale (teacher-reported) 0.11 -0.08 

Hyperactivity scale (teacher-reported) 0.17** -0.18 

Withdrawn Behavior scale (teacher-reported) 0.43** -0.25 

Total Problem Behaviors scale (teacher-reported) 0.63** -0.51 

Cooperative Classroom Behavior scale (teacher-reported) 1.36 2.01 

Significant differences were determined using the GLM Procedure (Least Squares Means option) in SAS v8.0.

A regression model was run for each dependent variable outcome with disability status and other covariates as the independent variables in each

model.

** p<.01; * p<.05.

Table 8-9. Cognitive developmental outcomes for both children with disabilities and children without 

disabilities (Fall 2000 – Spring 2001) [multivariate results]

Cognitive developmental measures Weighted averages 

Outcome variables – continuous – E1E2 Disabled Nondisabled 

Percents of Head Start children with and without disabilities 6% 94% 

Receptive vocabulary knowledge – PPVT standardized score 4.76 4.10 

Letter/word knowledge – WJ-R Letter/Word Identification 

standardized score 

-0.54 0.76 

Early mathematical skills – WJ-R Applied Problems 

standardized score 

-4.62*** 1.79 

Early writing skills – WJ-R Dictation standardized score -0.34 2.34 

Perceptual – motor skills – McCarthy Draw-a-Design score 0.31* 0.63 

Book knowledge – Book Knowledge score 0.48** 0.85 

E1E2 - Assessment administered in English in both Fall 2000 and Spring 2001.

Significant differences were determined using the GLM Procedure (Least Squares Means option) in SAS v8.0.

A regression model was run for each dependent variable outcome with disability status and other covariates as the independent variables in each

model.

*** p<.001; ** p<.01; * p<.05.

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FACES 2000 Technical Report 8-8 March 06 
8.4 Conclusion 

In summary, at the beginning of the Head Start year children’s disability status was highly 

associated with both social-emotional and cognitive developmental outcomes. Results generated without

covariates indicated that, on average, children with disabilities did not perform as well as other children 

on all baseline social-emotional and cognitive developmental outcomes with the exception of receptive 

vocabulary knowledge and book knowledge. Results generated with covariates indicated that, on average, 

children with disabilities did not perform as well as other children on all baseline social-emotional and 

cognitive developmental outcomes with the exception of book knowledge. 

Results generated pertaining to children’s progress over the course of the Head Start year

with regard to both social-emotional and cognitive developmental outcomes, controlling for baseline 

outcomes and child and family socio-demographic characteristics, indicated that, on average, children 

with disabilities did not progress as well as other children on 9 out of 16 social-emotional and cognitive 

developmental outcomes. The ones for which they did not progress as well as their non-disabled 

counterparts included the following: parent- and teacher-reported hyperactivity, withdrawn behavior, total

problem behaviors, early math skills, perceptual-motor skills, and book knowledge. The remaining seven 

outcomes were not statistically significantly different for the two groups. 

8.5 Discussion 

As noted earlier, White children were more likely than African American children to be

disabled. Male children were more likely than female children to be disabled. These findings are 

consistent with findings from other studies indicating the greater prevalence of identifications of

disabilities for White children as compared to others and male children as compared to female children 

(Coiro, Zill, & Bloom, 1994; Bloom & Tonthat, 2002; Child Trends Data Bank, 2002). Because young 

boys are more likely than young girls to have speech or language problems (Dale, Price, Bishop, & 

Plomin, 2003) that are classified as disabilities, it is not surprising that more male children than female 

children in the Head Start sample were classified as disabled. This is particularly the case given the fact 

that speech and language impairments constituted the largest category within the disabilities 

categorization. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8-9 March 06 
As delineated earlier, children with disabilities exhibited more problematic behaviors (i.e., 

had higher scores on negative behavior measures and lower scores on positive behavior measures) than 

other children for all social-emotional outcomes in the Fall of 2000 as consistent with expectations 

regarding the apparent linkages between the types and severity of the disabilities and negative outcomes 

for children with these disabilities. Over the course of a Head Start year, children with disabilities were 

not able to achieve similar gains to their non-disabled counterparts in 6 out of 10 social-emotional 

outcomes, controlling for baseline starting point outcomes and other child and family socio-demographic 

characteristics. Interestingly enough, for these six outcomes, children with disabilities actually

experienced deterioration in both parent- and teacher-reported behaviors while their counterparts

experienced improvements in these behaviors. There were no significant differences in gains between

children with disabilities and their non-disabled counterparts for any of the other social-emotional 

outcomes. 

The results obtained for the cognitive developmental outcomes were quite similar to those 

obtained for the social-emotional outcomes in the Fall of 2000. Children with disabilities had lower 

baseline outcomes for most of the cognitive developmental outcomes. Over the course of a Head Start

year, children with disabilities were not able to achieve similar gains to their non-disabled counterparts in

three out of six cognitive developmental outcomes, controlling for baseline starting point outcomes and

other child and family socio-demographic characteristics. For two of the outcomes, children with 

disabilities experienced significantly smaller gains than their non-disabled counterparts. Interestingly

enough, for one of the outcomes (early math skills), the former group of children experienced a 

significantly large decline while the latter group experienced a sizable increase in this skill area. There 

were no significant differences in gains between children with disabilities and their non-disabled 

counterparts for any of the other cognitive developmental outcomes. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 8-10 March 06 
CHAPTER 9. 

FAMILY STRUCTURE AND FAMILY CHANGES 

9.1 Introduction 

Past research shows that the nature of the family and other household socioeconomic 

characteristics has important implications for children’s well being (Amato, 2000; Duncan and BrooksGunn, 1997). Attempts have also been made to better understand the mechanisms through which this 

relationship operates. Some argue that family dissolution resulting in single parenthood has a negative 

effect on children because of a decline in emotional support from the single parent (Astone and 

McLanahan, 1991) or that deterioration in child outcomes is a result of a possible decline in familial 

economic resources following marital dissolution (Duncan and Brooks-Gunn, 1997; Duncan, BrooksGunn, Yeung, and Smith 1998; White and Rogers, 2000 for example). Other research shows that parents’

mental health and wellbeing could also affect child outcomes (Simons, Beaman, Cogner, and Chao,

1993). More recent research using longitudinal data on young children distinguishes between the effects

of various household and family characteristics based on the type of child outcomes discussed. Ram and

Hou (2003) argue that while household poverty mediates the relationship between family structure and 

cognitive outcomes, a deterioration of familial resources including mothers’ marital dissolution has a 

negative impact on emotional and behavioral outcomes of children.

This chapter uses four waves of data from the FACES 2000 data collection effort to gain a 

better understanding of the parental and other household characteristics of children who enroll in the

Head Start program. The main interest in this chapter lies in examining these household characteristics 

both at the time of initial enrollment into the Head Start program as well as observing annual changes as

the children move from Head Start to kindergarten. The differences in these characteristics are observed

between children who spend additional years in the Head Start program and those who move on to

kindergarten by Spring 2002. This chapter also examines changes in family structure and composition 

including mothers’ presence in the home and marital status, her education and employment, as well as her 

health and well-being as children move through the Head Start program. The relationships among

mothers’ marital status, family structure and selected children’s cognitive outcomes are also examined 

after controlling for mothers’ race and other household socioeconomic characteristics such as parents’

education, household poverty status, and mothers’ health and well-being. Chapter 10 of this report further

examines the extent of risk factors that are experienced by Head Start families and their relationship to 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-1 March 06 
children’s outcomes after taking into account parent involvement, and Head Start’s protective role for 

children. 

9.2 The FACES 2000-2003 Longitudinal Sample 

The FACES 2000 longitudinal data come from interviews of parents of Head Start children 

at four points of data collection (the base year, Fall 2000, and follow up surveys in Spring 2001, Spring 

2002, and Spring 2003). Children between the ages of 3 and 5 years with no previous Head Start 

experience who enrolled into the program were selected for this study in Fall 2000 and were subsequently

followed through Spring 2003.1

 The analysis presented in this chapter is based on information for the

longitudinal sample of 1,645 Head Start children interviewed in Fall 2000 for whom data from all three 

time points, Fall 2000, Spring 2001 and Spring 2002 were available. All these children continued in the 

Head Start program in Spring 2001. However, while 678 children remained in Head Start in Spring 2002,

967 children had moved on to kindergarten. In Spring 2003, the 678 children who were in Head Start in 

Spring 2002 had also moved on to kindergarten.2

 Therefore, the results presented in this chapter are not 

representative of the entire Fall 2000 sample as they exclude households which had dropped out of the 

sample over time or for whom insufficient information was available at later time points. Furthermore,

while Table 9-1 reports information obtained on mothers of all Head Start children, the results presented

in Tables 9-2 to 9-5 are restricted to households where the mother was the primary caregiver.3

1

 The results presented later in this chapter are based on the use of appropriate weights. The Spring 2003 longitudinal weight is used for

longitudinal analysis of the data following Head Start children from Fall 2000 through Spring 2003.

2

 A small number of kindergarten children interviewed in Spring 2003 were those repeating kindergarten. The numbers presented in all tables do

not include information on these “repeater” kindergarten children.

3

 As Table 9-1 shows, slightly less than 7 percent of the mothers do not reside in the households of their children and approximately 11 percent 

are not primary caregivers. However, the data show that the characteristics of the respondent of the parent interview (i.e., the primary

caregiver) on the topics of interest to the study are very similar to that of the mother. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-2 March 06 
Table 9-1. Changes in mother’s and other family characteristics of children in the Head Start program

at various time points: FACES 2000-2003

Fall 

2000 

Spring 

2001 Spring 2002 

Spring 

2003 

HS HS HS and KG KG 

Mother's Characteristics 

Mother's education 

 Some high school or lower 34.3 - - - 

 High school graduate/GED 36.1 - - - 

 High school plus voc/tech 5.6 - - - 

 Some college/Associate’s degree 21.5 - - - 

 Bachelor's degree or more 2.5 - - - 

Mother's education in last 12 months 

 No classes 61.0 87.6 - - 

 High school diploma - 0.9 - - 

 Classes but not towards a degree/certificate 14.2 - - - 

 Certificate/license/Associate’s degree etc. 17.2 9.6 - - 

 Bachelor's degree or more 4.1 0.1 - - 

 Other 3.6 1.7 - - 

Mother's employment status

 Working full-time 37.6 40.4 42.9 43.2 

 Working part-time 14.7 12.9 14.4 11.1 

 Looking for work 6.3 7.1 2.6 3.1 

 Not in labor force 34.9 34.5 38.1 40.4 

 No mother in household 6.5 5.1 2.0 2.2 

Mother's marital status 

 Married 44.3 45.7 49.8 43.7 

 Single, never married 37.0 35.1 34.0 38.2 

 Divorced/widowed 11.4 11.9 10.0 9.5 

 Married living separately 7.3 7.3 6.2 8.6 

Family Characteristics 

% With Mother in Household 93.5 94.9 92.2 91.9 

% With Mother as Primary Caregiver 89.2 90.0 88.7 87.8 

Family size 

 2-3 25.5 24.9 23.9 26.3 

 4-5 49.9 51.8 52.2 52.9 

 6 + 24.6 23.3 23.9 20.8 

Family structure 

 Mother-father 48.2 48.6 47.8 43.2 

 Mother only 45.3 46.0 44.4 48.7 

 Father only 2.1 2.1 2.5 2.1 

 Neither mother nor father 4.5 3.4 5.3 5.9 

See note at end of table. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-3 March 06 
Table 9-1. Changes in mother’s and other family characteristics of children in the Head Start program

at various time points: FACES 2000-2003 (continued)

Fall 

2000 

Spring 

2001 

Spring 

2002 

Spring 

2003 

HS HS HS and KG KG 

Household SES 

Monthly Family Income

 Less than $500 11.3 8.0 8.6 7.1 

 $500 to $999 22.4 19.7 16.9 18.6 

 $1000 to $1499 26.3 25.2 24.6 24.6 

 $1500 to $1999 14.6 17.0 17.2 18.1 

 $2000 or more 25.3 30.2 32.7 31.7 

Poverty Status

 % Poor 65.4 59.2 57.3 59.3 

 % Receiving Welfare 22.0 19.6 18.5 17.0 

N 1,645 1,645 1,645 678 

Notes: HS refers to children in the Head Start program, KG refers to children who have moved on to Kindergarten but were interviewed as part of 

FACES:2000-2003. Information on mother's education is available only for Fall 2000. For mothers in Spring 2001, information on recent 

education refers to education since Thanksgiving, therefore comparisons between mother's recent education for Fall 2000 and Spring 2001 

should be made with caution. Information on mother's recent education between data collection points is not presented for Spring 2002 and 

Spring 2003 due to missing information in the data. In Spring 2002, 678 children were enrolled in their second year of Head Start while 967 

children had moved on to Kindergarten.

9.2.1 Mothers’ Characteristics

In order to explore the changes in family characteristics and their implications for child 

outcomes over time, the first step is to get a good picture of the nature of mothers’ and family 

characteristics of Head Start children between Fall 2000 and Spring 2003. Table 9-1 shows that 

65 percent of all mothers had at least completed high school or had obtained a GED at the time their child

entered Head Start. Although about 21 percent of mothers had attended some college or had obtained an

Associate’s degree, only 2.5 percent had a Bachelor’s degree. Much of this education was completed well

before Fall 2000. About 61 percent of mothers did not attend any classes in the last 12 months before the 

Fall 2000 survey was conducted. About 21 percent had attended classes towards a certificate, license, an 

Associate’s degree, or a Bachelor’s degree. Furthermore, as many as 81 percent of mothers in Spring 

2001 did not attend any classes since the last Thanksgiving. 

With regard to employment, 35 percent of mothers were not in the labor force in Fall 2000, 

implying that they were not employed as well as not looking for a job. In later years, this percentage 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-4 March 06 
increased to 38 percent of mothers in Spring 2002 being out of the labor force. This increase is matched

by a corresponding decline in the percentage of mothers looking for work. Most others worked full time 

(38 percent in Fall 2000), again with percentages increasing over time.4

Over 44 percent of all mothers of Head Start children were currently married in Fall 2000.

This percentage increases steadily over the years, and was as high as 50 percent among mothers of

children in Spring 2002. Over the years, the increase in marriage rates is matched by a decline in the 

percentage of mothers who were divorced or widowed or those married but living separately. 

9.2.2 Family and Household Characteristics 

Table 9-1 also shows that approximately half of the children enrolled in Head Start in Fall

2000 and later years lived in families comprised of 4 to 5 members. About a quarter were in larger 

families, and a quarter in smaller families with 2 to 3 members. A majority of the children were also

either the youngest or the only child in the household.

About 94 percent of the families of these children had a mother present in the household. 

Furthermore, about 89 percent of mothers in the household were the primary caregivers for their children. 

In Fall 2000, slightly less than half the families had the mother and father of the children present in the 

household while approximately 45 percent of families had only the mother in the household and a very

marginal number (about 2 percent) had only the father residing in the household. The same general 

patterns persist across the years with some small differences. These results generally fit the pattern of

family structure reported in earlier analysis on Head Start children in the FACES 1997 data (FACES 1997 

Technical Report II, forthcoming). 

Since the Head Start program is targeted towards economically-deprived children, it is not

surprising that household income levels of the Head Start children are low. In Fall 2000, 11 percent of 

households had a monthly income of less than $500, about half the households had incomes ranging 

between $500 and $1,500 a month, and about 25 percent had a monthly income over $2,000. Over the 

years however, there is a slight increase in the economic status of these households. A lower incidence of

4

 Full time work is defined as working 35 or more hours a week.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-5 March 06 
poverty (57 percent) is also evident by Spring 2002 as compared to 65 percent of households in Fall 2000. 

Similarly, a decline in the percentage of households receiving welfare is also evident over the years. 

9.2.3 Mothers’ Health and Well-being 

Research has shown that mothers’ mental and physical health and general well-being is 

especially important in the context of its implications for children’s outcomes. An examination of the 

rates of depression among mothers in Table 9-2 indicates a general betterment in mothers’ mental health

over time. The percentage of mothers who were not depressed increased from 47 percent in Fall 2000 to

close to 60 percent in Spring 2002. This corresponds with the steady decline in the percentage of mothers 

with various levels of depression ranging from mild depression to severe depression. Similarly, on a locus 

of control scale of 0 to 21 that includes information on feelings and behavior, mothers reported an average 

score of 14.8 in Fall 2000 with a marginal but statistically significant increase in the score in subsequent 

years. 

Table 9-2. Changes in health and wellbeing of mother’s of children in the Head Start program at 

various time points: FACES 2000-2003

Fall 

2000 

Spring 

2001 Spring 2002 

Spring 

2003 

HS HS HS and KG KG 

Depression 

 Not depressed 47.1 45.5 59.2 61.2 

 Mildly depressed 26.5 30.0 20.4 18.6 

 Moderately depressed 14.2 13.5 11.1 11.1 

 Severely depressed 12.3 11.0 9.3 9.1 

Locus of Control 14.8 15.3 15.3 15.3 

Health 

 Excellent 22.3 26.4 21.2 20.5 

 Very good 33.0 30.1 33.0 33.0 

 Good 31.0 28.7 32.4 35.0 

 Fair 11.3 12.8 11.3 9.8 

 Poor 2.5 2.0 2.2 1.7 

Mother is primary caregiver 1,461 1,472 1,262 590 

Notes: Analysis is restricted to mothers who were respondents in each of the three time points, Fall 2000, Spring 2001 and Spring 2002. HS 

refers to children in the Head Start program, KG refers to children who have moved on to Kindergarten but were interviewed as part of 

FACES:2000-2003 In Spring 2002, 678 children were enrolled in their second year of Head Start while 967 children had moved on to 

Kindergarten.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-6 March 06 
9.3 Mothers’ Characteristics and Children’s Cognitive Outcomes 

Regression analyses are used to examine the relationship between mothers’ marital status

and family structure of children enrolled in Head Start (their mothers’ marital status, whether both parents 

reside in the household) between Fall 2000 and Spring 2002 and children’s cognitive outcomes assessed

using the standardized scores for the Peabody Picture Vocabulary Test and the Woodcock JohnsonRevised Letter Word Identification and Applied Problem tests in Spring 2002.5

 These analyses are

restricted to those children whose mothers were respondents and had complete information on household

characteristics at all time periods (Fall 2000, Spring 2001, and Spring 2002) as well as cognitive 

assessments in Spring 2002 thus bringing the sample size down to 1,180 children. The regression models

control for mothers’ and household socio-economic characteristics such as mothers’ ethnicity, highest

parental education, and household poverty status in Fall 2000; mothers’ health status between Fall 2000

and Spring 2002; and whether the child was enrolled in the Head Start program or kindergarten in Spring

2002.

6

Table 9-3 presents means of children’s cognitive outcomes in relation to their mothers’

characteristics. The table shows that there are some differences in cognitive scores of children of mothers 

who stayed married between Fall 2000 and Spring 2002 and those who were single and never married.

Children of married mothers performed better than children of never married mothers on the assessment

of math skills. Interestingly, children of mothers who had been married only for some of the time during 

the period Fall 2000-Spring 2002 also performed better than children of single, never married mothers 

with respect to their vocabulary and math skills.7

 However, no differences in cognitive outcomes were 

observed for children based on their co-residence with both parents between Fall 2000 and Spring 2002. 

The table also shows that children of mothers who reported that that they were always in good health 

performed better on two of the measures than children of mothers with changing health status. 

The means presented in Table 9-3 do not control for mothers’ and other household socioeconomic characteristics such as race, parents’ education, poverty and mothers’ health status. Regression

results that take these characteristics into account are presented in Tables 9-4 and 9-5. Table 9-4 presents 

5

 The Woodcock Johnson-Revised tests assess the child’s writing and math skills while the PPVT assesses the child’s vocabulary skills. The WJR LWI test was not administered to children in kindergarten in Spring 2002.

6

 Since the mother could be either the biological or adoptive mother, there is a possibility that the respondent could vary between the survey time

points. However, this variation is expected to be small.

7

 It is important to note that this category of persons includes mothers who were married in Fall 2000 but may have been divorced/separated 

subsequently or others who were divorced or separated in Fall 2000 and got married by Spring 2002.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-7 March 06 
results for the relationship between mothers’ marital status and the three cognitive outcomes while 

Table 9-5 shows results of the relationship between family structure and the three cognitive outcomes. In

each table, for each of the cognitive outcomes, results from two models are presented. The first column

examines the relationship between mothers’ marital status (Table 9-4) and family structure (Table 9-5)

and cognitive outcomes of Head Start children without controlling for any household socio-economic 

characteristics. The second column takes into account the role of additional characteristics such as race,

parents’ education, poverty, and mothers’ health status. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-8 March 06 
FACE

 

Table 9-3. Means and standard deviations of children’s cognitive outcomes in Spring 2002 in relation to selected 

m

ot

(Fall 2000-S

pring 2002) 

Writing skills Math skills Vocabulary 

Marital Status 

Always Single, Never Married 93.5

2 (12.49) 88.51 ab (17.90) 89.7

0 a (14.26) 

Always Married 91.3

6 (12.72) 92.7

4 a (19.60) 90.7

7 (16.33) 

Any Div

orce/Separation/Widowhood 92.28 (12.23) 92.08 b (18.34) 92.43 a (14.86) 

Family Structure 

Both Parents Always in Household 91.3

6 (12.57) 91.9

4 (19.25) 90.1

7 (16.64) 

Someti

mes Less than Two Parents in 

Household 92.9

6 (12.44) 90.88 (18.44) 91.6

7 (14.17) 

Depression 

Never Depressed 91.95 (12.87) 92.0

6 (19.03) 90.8

7 (15.58) 

Always Depressed 93.39 (10.94) 92.94 (17.40) 92.68 (14.15) Sometimes Depressed 92.5

2 (12.31) 89.8

4 (18.66) 90.83 (15.20) 

Health 

Always Good Health 93.08 a (12.60) 91.6

6 (19.11) 91.5

9 a (14.96) 

Always Poor Health 88.9

2 (12.27) 90.68 (16.88) 92.8

6 (14.68) 

Changing Health Status 89.9

6 a (11.89) 90.38 (18.14) 88.5

2 a (16.50) 

Note: Standard deviations are given in parentheses. Analysis is restricted to 

mothers who were respondents at all three time points, Fall 2000, Spring 2001 and Spr

that 

means are significantly different from each other (p<0.05). Differences in 

math skills between children of 

mothers who were always single and always 

marrie

Differences in vocabulary between children of

mothers who were always in good health and those with changing health are significant at p < 0.01. Writing and Ma

the Woodcock Johnson tests, vocabulary skills were assessed using PPVT. Assess

ment of child's writing skills using the WJ Word Test was ad

ministered only 

program in Spring 2002 while other tests were ad

ministered to children in Kindergarten as well. Family structure is defined as "so

meti

mes less than two parents i

the time points between Fall 2000 and Spring 2002, one of the child's parents was not present in the household. A 

mother is reported to have changing health statu

at least one but not all of the time points between Fall 2000 and Spring 2002.

___________________________________________________________________________________________________________________________________

S 2000 Technical Report 9-9 March 06 
Table 9-4. Relationship between longitudinal change in mothers’ marital status and various cognitive 

outcomes in Spring 2002: FACES 2000 (Fall 2000-Spring 2002) 

Writing skills Math skills Vocabulary

Mothers' Marital Status 

(Always Married: reference group) 

Always Single, Never Married 3.35* 1.25 -4.53** -1.24 -1.44 0.62 

Any Divorce/Separation/Widowhood 1.90 1.61 -0.97 -0.62 1.56 1.12 

Enrolled in KG (Spring 2002) - 7.03** 3.23** 

Mothers' Race (White: reference group) 

African American 5.54** -7.70** -10.19** 

Hispanic 1.12 -6.81** -15.78** 

Other race 3.57 -9.74** -15.68** 

Parents' Education 

(Less than High School: reference group) 

High School 5.94** 6.88** 4.84** 

Some College or higher 8.13** 11.35** 8.46** 

Poverty Status -2.36+ -1.89 -1.56+ 

Mothers' Health Status 

(Always Good Health: reference group) 

Always Poor Health -3.02 -0.55 0.91 

Changing Health Status -1.08 -0.55 -0.99 

Constant 90.16** 85.03** 92.70** 87.15** 90.59** 92.72** 

Observations 539 525 1148 1117 1137 1106 

R-squared 0.01 0.11 0.01 0.15 0.01 0.30 

Note: + significant at 10%; * significant at 5%; ** significant at 1%. Analysis is restricted to mothers who were respondents at all three time

points, Fall 2000, Spring 2001 and Spring 2002. Writing and Math skills were assessed using the Woodcock Johnson tests, vocabulary skills 

were assessed using PPVT. Assessment of child's writing skills using the WJ Word Test was administered only to children in Spring 2002 while 

other tests were administered to children in Kindergarten as well. A mother is reported to have changing health status if she was in poor health

in at least one but not all of the time points between Fall 2000 and Spring 2002.

Consistent with results presented in Table 9-3, the regression results in Table 9-4 indicate

that mothers’ marital status bears a statistically significant relationship to children’s cognitive outcomes 

when examined in isolation without controlling for other family characteristics. Surprisingly, children of

single, never married mothers perform better than children of married mothers with regard to children’s 

writing skills. But the opposite is true with regard to math skills. However, this relationship disappears 

after controlling for other family characteristics. Coresidence with both parents is also not related to 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-10 March 06 
children’s cognitive outcomes in Table 9-5 after controlling for other family and background 

characteristics. 

Table 9-5. Relationship between longitudinal change in family structure and various cognitive 

outcomes in Spring 2002: FACES 2000 (Fall 2000-Spring 2002) 

Writing skills Math skills Vocabulary

Family Structure 

(Both parents in household: reference 

group) 

Less than Two Parents in Household 2.01 0.63 -1.86 -0.32 0.98 1.22 

Enrolled in KG (Spring 2002) - 7.02** 3.06** 

Mothers' Race (White: reference group) 

African American 5.71** -7.97** -10.57** 

Hispanic 0.83 -6.79** -15.57** 

Other race 3.39 -9.85** -15.88** 

Parents' Education 

(Less than High School: reference group) 

High School 5.88** 6.84** 4.93** 

Some College or higher 8.21** 11.33** 8.45** 

Poverty Status -2.00 -2.04 -1.73+ 

Mothers' Health Status 

(Always Good Health: reference group) 

Always Poor Health -3.47 -0.56 0.76 

Changing Health Status -0.99 -0.59 -1.13 

Constant 90.56** 85.25** 92.16** 87.03** 90.14** 92.88** 

Observations 544 530 1154 1122 1143 1111 

R-squared 0.01 0.11 0.00 0.15 0.00 0.30 

Note: + significant at 10%; * significant at 5%; ** significant at 1%. Analysis is restricted to mothers who were respondents at all three time

points, Fall 2000, Spring 2001 and Spring 2002. Writing and math skills were assessed using the Woodcock Johnson tests, vocabulary skills

were assessed using PPVT. Assessment of child's writing skills using the WJ Word Test was administered only to children in Spring 2002 while 

other tests were administered to children in Kindergarten as well. A mother is reported to have changing health status if she was in poor health

in at least one but not all of the time points between Fall 2000 and Spring 2002.

Children in kindergarten in Spring 2002 have better cognitive outcomes as compared to

children still enrolled in Head Start (Tables 9-4 and 9-5). With regard to the role of household socioeconomic characteristics, higher education of parents, particularly at the college level, is associated with

better cognitive outcomes while the poverty status of the household is associated with poorer outcomes.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-11 March 06 
Moreover, children of mothers who identified themselves as White also performed better than others. An 

exception is the case of children’s writing skills where children whose mothers were African American

performed better than children with White mothers. 

9.4 Summary and Conclusions 

This chapter uses data from the FACES 2000-2003 longitudinal surveys to present an overall 

picture of the family characteristics of children enrolled in Head Start. In particular, the emphasis is on 

the family structure and characteristics of these families including the marital status and general health 

and well-being of the mother, the predominant primary caregiver in the household, in relation to child 

outcomes. The longitudinal data collection effort of FACES provides the ability to examine changes in

these characteristics and relationships over time. 

Overall, the results indicate that the condition of Head Start children’s families and 

especially their mothers has generally remained the same or marginally improved as children move from

enrollment in Head Start to kindergarten between Fall 2000 and Spring 2002. Although not all mothers 

reside in the household of their children, the percentage remains consistently over 90 percent. It is also

interesting to note that a high percentage of mothers are also single, never married mothers. Over 40

percent of households have only the mother (and no father) residing in the child’s household. The 

longitudinal analysis shows evidence of an improvement in the socioeconomic status of households over 

the years. The data show that a greater percentage of households report higher levels of monthly income

in Spring 2002 and Spring 2003. Moreover, a smaller percentage of households remains in poverty or

depends on welfare as children move through the Head Start program and possibly to kindergarten. 

Examining the role of these mothers’ and household characteristics on children’s cognitive

outcomes using the FACES 2000 data shows that a change in the family situation represented in terms of

a change in mothers’ marital status or coresidence with parents bears little relationship with children’s

cognitive outcomes. Instead, household characteristics such as parents’ education and household poverty

status are more important predictors. While greater parents’ education is related to better cognitive 

outcomes, a poor household economic situation is associated with lower assessment scores. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 9-12 March 06 
CHAPTER 10. 

FAMILY RISK FACTORS, PARENTAL INVOLVEMENT, AND HEAD START’S 

PROTECTIVE ROLE 

Head Start has a strong interest in supporting parents as the primary educators of their 

children. This chapter explores relationships between family and parental characteristics and child 

outcomes (including teacher ratings of social skills and behavior problems, and direct cognitive 

assessments) that may be related to the development of school readiness in the FACES 2000 sample of 

Head Start children. 

These data provide further insight into the development of cognitive and social skills, 

particularly with regard to family challenges and strengths. The family risk factors investigated in this

chapter include parental depression, exposure to violence, domestic violence, involvement in the criminal 

justice system, substance use, and cumulative social and economic risks. The chapter concludes with a

presentation of protective family factors and investigates how experiences in Head Start may help some

families cope with the multiple life challenges they encounter. 

10.1 Research Questions 

The following research questions will be addressed: 

1. How are family and parental characteristics related to children’s cognitive and social

development? 

2. How are family interactions with children related to children’s cognitive and social

development? and 

3. How do parents interact with Head Start and how is their interaction related to children’s

cognitive and social development? 

10.2 Findings 

The findings presented in this chapter are primarily based on partial correlations, tests of

group differences (t-test, ANOVA), and multivariate logistic regression models used to estimate levels of 

risk while controlling for demographic variables. Unless noted in the text, all findings tested significant 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-1 March 06 
(p < .05). Additional information on specific parent interview scales and child assessment measures is

found in the Appendix. Means and standard deviations for scales from the parent interview and from the 

teachers’ reports of children’s behavior are also included in the Appendix. 

10.2.1 Prevalence of Family and Parental Risk Factors and their Relationship to Children’s

Outcomes 

Depression.1

 Because depression is a frequent challenge facing low-income families with 

young children (Hall, Williams and Greenberg, 1985; Liaw and Brooks-Gunn, 1994), depression among 

the Head Start parents was measured using the CES-D Depression Scale (Radloff, 1977). Overall, parents 

had a mean score of 6.8 in the Fall of 2000, which was in the mildly depressed range. As seen in

Figure 10-1, most parents were classified as not depressed (47.7 percent) or only mildly depressed (27.0 

percent), while one-fourth of the parents were classified as moderately depressed (13.6 percent) or 

severely depressed (11.7 percent). From Fall to Spring, there was a small decline in the overall mean

depression scores (Spring 2001 mean score of 6.6), but the difference was not statistically significant. 

Over 40 percent of parents reported moderate or severe depression at two or more time points. 

The level of depression did not vary significantly by race or ethnicity. Similar proportions of

African American parents (27.7 percent), Hispanic parents (27.4 percent), and White parents (25.0 

percent) were classified as moderately or severely depressed. 

Group differences, evaluated using t-tests, were found between parents who were moderately 

or severely depressed and those who were not at all or only mildly depressed (Table 10-1). Parents who 

were moderately or severely depressed reported a lower household income, had a more external locus of

control, had a more authoritarian parenting style (i.e., more directive and harsh), and spanked their 

children more frequently. When asked about activities with the children, parents who were moderately or

severely depressed were more likely to report participating in fewer activities with their children and were 

also less likely to be involved with their children’s Head Start program. A higher proportion of mothers 

living without a father in the home were classified as moderately or severely depressed (30.4 percent) 

than those who had a father present in the home (20.3 percent). 

1

 The literature cited on depression focuses largely on maternal depression. All parent figures who served as primary caregivers, including fathers 

and grandfathers, were included in this analysis. However, 87.9 percent of the FACES primary caregivers were mothers. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-2 March 06 
Figure 10-1. The prevalence of depression among Head Start parents in Fall 2000 

47.7%

27.0%

13.6%

11.7%

Not Depressed

Mildly Depressed

Moderately Depressed

Severely Depressed

Table 10-1. Significant group differences between moderately or severely depressed parents and mildly

or not at all depressed parents on selected family factors 

Family factors 

Moderately or 

severely depressed 

Mildly or not

depressed 

Mean SD Mean SD T 

Household Income 1.54 0.66 1.64 0.50 3.38*** 

Locus of Control 13.0 3.27 15.4 3.06 16.19*** 

Authoritarian Parenting Style 2.22 0.78 2.17 0.67 1.74* 

Spanking 1.59 0.50 1.51 0.50 2.85** 

Involvement at Head Start 21.3 5.86 22.00 7.59 1.96* 

*p< .05; **p < .01, ***p < .001.

Results of partial correlations (Table 10-2) controlling for household income, education,

employment, and child gender, age, and ethnicity also revealed that the overall parental depression scale

score was significantly correlated with parent and teacher reports of the children’s behavior. Parents who

were more depressed reported that children had more problem behavior, including being more aggressive,

hyperactive, and withdrawn. Similarly, teachers also reported more aggressive, hyperactive, and overall 

problem behavior for children of parents who were more depressed. Negative correlations were also 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-3 March 06 
found between parental depression and children’s positive social behavior ratings and emergent literacy, 

indicating that less depressed parents reported having children with better social and academic skills. 

Table 10-2. Significant partial correlations between parental depression and child behavior and cognitive 

outcomes 

Problem

Behavior–Parent Report 

r = .23*** 

Aggressive 

Behavior–Parent 

Report 

r = .18*** 

Withdrawn 

Behavior–Parent 

Report 

r = .20*** 

Hyperactive 

Behavior–Parent Report 

r = .15*** 

Positive Social 

Behavior 

r = -.06** 

Emergent 

Literacy–Parent Report 

r = -.05** 

Problem

Behavior–Teacher 

Report 

r = .08*** 

Aggressive 

Behavior–Teacher 

Report 

r = .06** 

Hyperactive 

Behavior–Teacher 

Report 

r = .05** 

One-to-One Counting 

r = -.07** 

Early Math Skills 

r = -.09** 

Creativity–Teacher 

Report 

r = -.06** 

*p< .05; **p < .01, ***p < .001.

Significant correlations were also found between parental depression and selected child

cognitive outcomes. Children of parents who were depressed did worse on one-to-one counting and early 

math tasks, as well as on the teacher reports of creativity (descriptions of the child outcome measures are

found in the Appendix). 

Additional risks identified in the literature on maternal depression were explored more fully 

through multivariate logistic regression models, controlling for parent’s education and employment; 

household income; and child’s race, age, and gender. Odds ratios and 95 percent confidence intervals for

each model are presented in Table 10-3. These risk estimates indicate that parents who were moderately

or severely depressed, compared to parents who were not at all or only mildly depressed, were 1.45 times

more likely to be single parents, and almost twice as likely to report that they, another household member, 

or a non-household biological parent had been arrested or charged with a crime since the birth of their

Head Start children. In addition, depressed parents were 1.36 times more likely than non-depressed 

parents to drink or live with someone who drank alcohol, and 1.69 times more likely to have been 

exposed to violence in their neighborhoods or homes. The risk for screening positive for domestic 

violence greatly increased for those parents who were moderately or severely depressed. These parents

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-4 March 06 
were almost 3 times more likely to have been victims of domestic violence compared to parents who were 

only mildly depressed or not depressed. 

Table 10-3. Significant adjusted odds ratios and 95 percent confidence intervals for parental depression, 

exposure to violence, domestic violence, alcohol use, and involvement with the criminal 

justice system 

Parental depression 

Risk factors Adjusted odds ratio 95 Percent confidence interval 

Exposure to Violence 1.69 (1.38–2.06) 

Domestic Violence 2.99 (2.33–3.84) 

Alcohol Use 1.36 (1.12–1.65) 

Criminal Justice System Involvement 1.97 (1.57–2.47) 

Single Parent 1.45 (1.17–1.79) 

Exposure to violence 

Risk factors Adjusted odds ratio 95 Percent confidence interval 

Domestic Violence 2.68 (2.09–3.44) 

Criminal Justice System Involvement 1.73 (1.38–2.16) 

Alcohol Use 1.46 (1.21–1.75) 

Single Parent 1.43 (1.18–1.74) 

Domestic violence 

Risk factors Adjusted odds ratio 95 Percent confidence interval 

Criminal Justice System Involvement 3.47 (2.68–4.50) 

Single Parent 2.61 (1.97–3.46) 

Alcohol Use 1.50 (1.18–1.91) 

Alcohol use 

Risk factors Adjusted odds ratio 95 Percent confidence interval 

Criminal Justice System Involvement 1.48 (1.19–1.83) 

Exposure to Violence 1.45 (1.21–1.74) 

Domestic Violence 1.48 (1.17–1.89) 

Criminal justice system involvement 

Risk factors Adjusted odds ratio 95 Percent confidence interval 

Parental Depression 1.97 (1.57–2.47) 

Single Parent 2.64 (2.06–3.39) 

Domestic Violence 3.47 (2.68–4.50) 

Child Witness to Violence 3.23 (2.04–5.12) 

Child Witness to Domestic Violence 3.60 (2.63–2.90) 

Child Victim of Violence 3.06 (1.35–6.97) 

Child Victim of Domestic Violence 3.14 (1.57–6.30) 

Exposure to Violence. Neighborhoods have long been recognized in theory and research as

important contexts for child development (Leventhal and Brooks-Gunn, 2000). Parents were asked about 

the violence they knew to occur in their neighborhoods, and were asked additional questions about their

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-5 March 06 
own personal exposure to violence and domestic violence, as well as their children’s exposure to

violence. 

As depicted in Figure 10-2, more than one-fifth of all parents (22.5 percent) reported seeing 

nonviolent crime such as selling drugs or stealing in their neighborhoods in Fall 2000 (15.3 percent more 

than once), as well as having been a witness to violent crime (22.4 percent; 17.2 percent more than once). 

Approximately 17.0 percent of the parents knew someone who was the victim of a violent crime in their

neighborhood, bringing the reality of violence very close to many of the Head Start families. Five percent 

of parents reported being a victim of violent crime in their neighborhood, and similarly, 5.0 percent of the 

parents reported being victims of violence in their homes. 

Figure 10-2. The frequency of parents’ exposure to crime in their neighborhoods and their homes 

22.5

22.4

17

5

5

0 5 10 15 20 25

Saw Non-violent Crime

Saw Violent Crime

Know Victim of Violent

Crime

Victim of Violent Crime

in Neighborhood

Victim of Violent Crime

in Home

Exposure to violence varied across ethnic groups. Among parents of African American

children, 34.5 percent reported seeing nonviolent crimes in their neighborhoods, a figure that was over

twice the rate reported by parents of White children (15.0 percent) and approximately one-third more than

parents of Hispanic children (24.2 percent). This pattern held for each type of exposure to violent crime. 

Over twice as many parents of African American children (36.3 percent) reported witnessing violent 

crimes in their neighborhoods compared to parents of White children (15.5 percent) and Hispanic children 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-6 March 06 
(17.5 percent). For reports of victimization, parents of African American children were again highest, 

with 7.4 percent indicating they were victims of crime in their neighborhoods, and 6.2 percent reporting

they were victims of violent crime in their homes. These victimization rates were closer to reports for

parents of Hispanic children (5.8 percent in the neighborhoods; 5.4 percent in their homes) than for 

parents of White children (4.4 percent in the neighborhoods; 4.5 percent in their homes). 

As for the Head Start children, 3.8 percent were reported by parents to have witnessed a

violent crime and 8.6 percent were reported to have witnessed domestic violence during the previous 

year. Slightly more than 1 percent of the children were reported by their parents to have been victims of

violent crime (1.1 percent), while almost 2 percent were victims of domestic violence (1.7 percent) during 

the previous year. 

Exposure to violence had direct and indirect associations with child outcomes. Partial 

correlations controlling for household income, education, employment, and child gender, age, and

ethnicity revealed small but significant positive correlations between parents’ reports of exposure to 

violence and parents’ reports of child problem behavior. In these analyses, exposure to violence is 

represented as a summary score of how often each of the five types of exposure to violence (as noted

above) was reported by parents. Scores ranged from 5 (no exposure) to 15 (more than one exposure to

every type). The mean score for the sample was 6.1. Parents who reported greater exposure reported their

children engaged in fewer positive social behaviors and more overall problem behavior; teachers of these 

children also reported they were more aggressive. Exposure to violence did not have a direct relationship 

with child cognitive outcomes. Parents who reported more exposure to violence were significantly more 

depressed, but interestingly, they also were more likely to have an authoritative parenting style (e.g., less

harsh, more use of rationales). 

Controlling for mother’s education and employment; household income; and child’s race,

age, and gender; multivariate logistic regression models were used to further explore the risks associated 

with exposure to violence. Odds ratios and 95 percent confidence intervals for risk factors (alcohol use, 

single parent, domestic violence, and criminal justice system involvement) included in the models are 

presented in Table 10-3. Parents who reported exposure to violence in their neighborhoods or homes,

compared to parents who were not exposed to violence, were 1.45 times more likely to be single parents 

as well as to live in households where either they or someone else drank alcohol. Parents who were 

exposed to violence in their neighborhoods or homes, compared to parents not exposed to violence, were 

also 1.73 times more likely to have reported that they, another household member, or a non-household

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-7 March 06 
biological parent had been arrested or charged with a crime since the birth of their Head Start children, 

and over 2.68 times more likely to have screened positive for domestic violence. 

Domestic Violence. A three-item screening measure for domestic violence was administered

to the parents (Feldhaus, Koziol-McLain and Amsbury, 1997). They were asked if they had ever been hit,

kicked, punched, or otherwise hurt by anyone within the past year; if they felt safe in their current 

relationship; and if they currently felt unsafe because of a partner from a previous relationship. Almost 13 

percent of the parents answered ‘yes’ to one of these questions, thereby screening positively for 

experiencing domestic violence. Differences on family and child outcomes were found between families 

with a parent who screened positively for domestic violence versus those who did not. For example,

parents experiencing domestic violence were significantly more depressed, and reported their children to 

be more aggressive, more hyperactive, more withdrawn, and to have more overall problem behavior. 

Teachers also reported these children to be more withdrawn and have more overall problem behavior than 

children whose parents were not experiencing domestic violence (Table 10-4). However, no direct 

relationship was found between parent-reported domestic violence and child cognitive outcomes. 

Table 10-4. Significant group differences between parents who did and did not screen positive for 

domestic violence on parental depression and child behavior 

Domestic violence No domestic violence 

Mean SD Mean SD T 

Parental Depression 10.8 8.04 6.17 6.26 -12.19*** 

Child Behavior (Parent-Reported) 

Aggressive Behavior 3.59 1.77 3.09 1.73 -4.87*** 

Hyperactive Behavior 2.08 1.58 1.81 1.49 -2.92** 

Withdrawn Behavior 0.85 1.08 0.58 0.90 -4.95*** 

Overall Problem Behavior 7.08 3.87 6.02 3.48 -5.17*** 

Child Behavior (Teacher-Reported) 

Withdrawn Behavior 2.98 2.71 2.53 2.64 -2.76** 

Overall Problem Behavior 6.39 5.16 5.67 5.04 -2.34* 

*p< .05; **p < .01, ***p < .001.

Multivariate logistic regression models, controlling for mother’s education and employment;

household income; and child’s race, age, and gender; estimated that parents who screened positive for

domestic violence, compared to those who did not, were 2.61 times more likely to be single parents, 1.5

times more likely to drink alcohol or live with a drinker, and almost 3.5 times more likely to report that

they, another household member, or a non-household biological parent had been arrested or charged with

a crime since the birth of their Head Start children. (See Table 10-3.) 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-8 March 06 
Substance Use in the Home. The occurrence of substance use in homes, especially cigarette

smoking and alcohol use, is another challenge that faced a number of Head Start families (Figure 10-3). 

Almost one-half of the children (45.1 percent) lived in households with at least one individual who 

smoked cigarettes. Smoking varied by ethnicity. Cigarette smoking was reported less frequently in 

households where African American children lived (38.8 percent) than in households of Hispanic children 

(52.2 percent) or White children (54.3 percent). More than one-fourth of the parents (28.1 percent)

reported drinking alcohol such as beer, wine, or liquor in the past 30 days; 20.0 percent drank less than

once a week, and 7.8 percent reported drinking between 1-2 times per week to every day. Slightly over 40

percent of all households reported having at least one individual who drank alcohol. Among families who 

lived in households where someone drank alcohol, 7.9 percent reported alcohol-related problems with 

family members, 5.9 percent experienced trouble with the police because of alcohol, and 4.2 percent 

missed work or school due to alcohol-related illness. Less than 1 percent of the families reported having 

anyone in the household who used drugs. 

Figure 10-3. The frequency of substance use in the home 

0.9

7.8

28.1

40.1

45.1

0 5 10 15 20 25 30 35 40 45 50

Household Member Uses

Drugs

Parent Reported Drinking

Every Week or more

Parent Reported Drinking

Alcohol in past 30 Days

Household Member

Drinks Alcohol 

Household Member

Smokes Cigarettes

Parents who drank or who lived with a drinker were significantly more likely to be depressed 

and to report their children to have more overall problem behavior than parents who did not drink or live 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-9 March 06 
in a household with a drinker. Children who lived with someone who drank alcohol scored lower on

vocabulary, color naming, and social awareness tasks.

Further exploration of the risks associated with drinking or having a drinker in the household 

was done using multivariate logistic regression models, again controlling for mother’s education and 

employment; household income; and child’s race, age, and gender. Odds ratios and 95 percent confidence

intervals for the associated risk factors included in the models are presented in Table 10-3. Parents who

drank alcohol or lived with a drinker were approximately 1.5 times more likely to report involvement in

the criminal justice system, exposure to violence, or domestic violence in their lives compared to parents

who did not drink or live with a drinker. Parents who drank or lived with a drinker were no more likely to

be single parents than those who lived in alcohol-free households. 

Involvement with the Criminal Justice System. In order to assess how many families had 

involvement with the criminal justice system, parents were asked if they, another household member, or a 

non-household biological parent had been arrested or charged with a crime since the birth of their Head

Start children. Almost one-fifth (19.2 percent) of the parents reported that someone had been arrested and 

charged with a crime and 16.7 percent reported someone had spent time in jail. Involvement with the 

criminal justice system did not vary much by race or ethnicity. About one-fifth of parents of White 

children, parents of Hispanic children, and parents of African American children reported having

someone in their family who was arrested (21.8 percent, 20.1 percent, and 18.9 percent, respectively). 

T-tests were conducted to examine if child behavior and cognitive outcomes differed

between children who were members of families with involvement in the criminal justice system and 

children from families without such involvement (Table 10-5). Children from families who had someone 

arrested scored lower on assessed vocabulary and were reported by their parents to be more aggressive,

more hyperactive, more withdrawn, and to have more overall problem behavior. They were also reported

by their teachers to be more aggressive and have more overall problem behavior than children from 

families who did not have someone arrested. 

Multivariate logistic regression models, controlling for mother’s education and employment;

household income; and child’s race, age, and gender were used to determine estimates of risk among 

those families who had someone close to them who was involved in the criminal justice system (odds 

ratios and 95 percent confidence intervals are reported in Table 10-3). These risk estimates indicated that 

parents who reported that they, another household member, or a non-household biological parent had

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-10 March 06 
been arrested or charged with a crime since the birth of their Head Start children were twice as likely to 

be depressed, over 2.5 times more likely to be single parents, and over 3.5 times more likely to have been

a victim of domestic violence than parents who did not have someone in their families involved in the

criminal justice system. 

Table 10-5. Significant group differences between families with involvement in the criminal justice 

system and families with no involvement in the criminal justice system on child behavior 

and cognitive outcomes 

Criminal justice 

involvement 

No criminal justice 

involvement 

Mean SD Mean SD T 

Vocabulary 80.72 17.53 80.72 17.53 -3.91*** 

Child Behavior (Parent-Reported) 

Aggressive Behavior 3.42 1.73 3.09 1.74 -3.70*** 

Hyperactive Behavior 2.01 1.51 1.81 1.50 -2.67** 

Withdrawn Behavior 0.77 0.99 0.57 0.91 -4.04*** 

Overall Problem Behavior 6.75 3.59 6.01 3.53 -4.03*** 

Child Behavior (Teacher-Reported) 

Aggressive Behavior 2.09 2.08 1.73 2.03 -3.34*** 

Overall Problem Behavior 6.18 4.86 5.67 5.10 -2.01* 

*p< .05; **p < .01, ***p < .001.

Children in families from which someone had been arrested were at great risk for witnessing 

or being a victim of violent crime and domestic violence compared to children in families where no one 

had been arrested or charged with a crime. These children were more than 3 times more likely to have 

been a witness to violent crime and almost 3.5 times more likely to have witnessed domestic violence in 

the past year. Their risk of victimization also increased greatly. These children were 3 times more likely

to have been both a victim of domestic violence and a victim of violent crime in the past year than 

children whose families did not report involvement with the criminal justice system. While there is a 

strong literature to suggest that children of incarcerated parents are at increased risk for negative 

outcomes (Lange, 2000), these findings suggest that risk greatly increases when there is any family

involvement with the criminal justice system. 

Cumulative Social and Economic Risk. Previous work has noted that social and economic 

risk factors may be associated with negative child outcomes, particularly when multiple risks are present 

(Annie E. Casey Foundation, 1999; ACYF, 2002). To explore this further, a standard list of family risk 

factors (Annie E. Casey Foundation, 1999) was adapted to investigate relationships with child outcomes.

These risk factors include: 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-11 March 06 
 The child lived with a single parent; 

 The mother was a high school dropout;

 The household income was below the poverty line; 

 The child was living with a parent(s) who did not have steady, full-time employment; 

 The family was receiving welfare benefits; and 

 The child did not have private health insurance. 

While a number of these risks are already included in broader analytic models looking at

child outcomes (see earlier chapters), the interest here is in how the cumulative effects of these risks may 

be associated with reduced school readiness. At least one of the six risks was evident in 89 percent of the

Head Start families. Across families, the most prevalent risks were having a mother without a high school

education (38.2 percent), being in a single-parent household (48.2 percent), and children not having 

private health insurance (64.6 percent).2

 The three other risks were reported for less than 30 percent of the

families. 

Increases in the number of risk factors, particularly counts of four or more risks, increased

the likelihood of negative child outcomes. About one-fifth of the families (20.3 percent) were found to

have four or more risk factors, with almost 10 percent having five or six risks. Less than one-fifth of the 

families of White children (18.6 percent) and Hispanic children (18.6 percent) had four or more of the

risk factors, while one quarter of the families of African American children (24.9 percent) were found to

have this high level of risk. 

As shown in Table 10-6, parents reporting four or more risk factors also had higher 

depression scores, a more external locus of control, and, interestingly, scored higher than parents with

fewer cumulative risks on both the authoritarian and authoritative parenting style scales. These same

parents also reported more problem behavior for their children, including aggressive and withdrawn 

behavior, and gave lower ratings on emergent literacy. In addition, the Head Start teachers also rated the 

children from families with four or more risks as having more withdrawn and hyperactive behavior. 

2

 The Fall 2000 FACES parent interview identified children without private health insurance, but was not clear on whether children received 

Medicaid or SCHIP.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-12 March 06 
In terms of the child cognitive assessments, the cumulative effect of four or more risk factors 

was clearly associated with lower child outcomes. This high level of risk meant significantly poorer 

performance on social awareness, design copying, color naming, one-to-one counting, book knowledge, 

comprehension, print concepts, vocabulary, letter identification, early math, and early writing. 

Table 10-6. Significant group differences between families with fewer than four risks and families with 

four or more risks on child behavior, child cognitive outcomes, and parent variables 

Less than four risk 

factors 

N = 1,706 

Four or more risk 

factors 

N = 505 

Mean SD Mean SD T 

Child Behavior (Parent-Reported) 

Aggressive Behavior 3.14 1.75 3.31 1.74 -1.94* 

Withdrawn Behavior 0.6 0.94 0.69 0.97 -1.84* 

Child Behavior (Teacher-Reported) 

Hyperactive Behavior 1.33 1.52 1.5 1.56 -2.22* 

Withdrawn Behavior 2.48 2.69 2.74 2.56 -1.93* 

Overall Problem Behavior 5.57 5.08 6.12 5.10 -2.13* 

Child Cognitive Status (Parent-Reported) 

Emerging Literacy 2.02 1.45 1.54 1.69 4.95*** 

Child Cognitive Assessments 

Vocabulary 81.19 17.56 78.23 15.71 3.29*** 

Early writing 85.52 14.21 82.66 13.01 2.53** 

Early math 88.31 15.10 83.54 16.61 3.75*** 

Letter identification 92.06 9.34 90.02 7.22 2.94** 

Social awareness 3.36 1.63 3.09 1.67 3.28*** 

Design copying 3.02 1.38 2.87 1.25 2.20* 

Color naming 11.17 7.30 8.95 7.22 6.05*** 

Counting 0.35 0.66 0.27 0.06 2.31* 

Book knowledge 1.57 1.25 1.14 1.24 2.48* 

Comprehension 0.54 0.71 0.46 0.66 2.27* 

Print concepts 0.24 0.57 0.18 0.48 1.97* 

Parent self-reports 

Parent Depression 6.18 6.64 7.96 7.21 -6.17*** 

Parent Locus of Control 14.71 3.20 13.85 3.39 4.42 

Authoritative Parenting 4.20 0.62 4.28 0.63 -3.45*** 

Authoritarian Parenting 2.18 0.69 2.30 0.73 -2.40* 

*p< .05; **p < .01, ***p < .001.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-13 March 06 
10.2.2 Family Involvement and its Relationship to School Readiness 

Family Activities. While the findings presented above show that the aggregated effect of

selected family characteristics has negative associations with children’s school readiness, the frequency of

families’ activities that include the Head Start children reflects potential family strengths that could 

improve school readiness. For example, do families that are more active with their children have children

with better behavior and better cognitive skills? 

Parents were asked how often family members engaged in selected activities over the

previous week as well as the previous month with their Head Start children. The weekly activities 

included telling the child a story; teaching letters, words, or numbers; teaching songs or music; doing arts 

and crafts; playing toys or games; doing errands; or doing household chores. Parents were also asked

about how often they read to their children over the past week, and findings related to this variable are 

addressed in Chapter 5. The monthly activities included visiting the library, shows, museums, and zoos;

attending community or sporting events; and discussing family history. Total activity scores are based on 

the sum of the weekly and monthly activity scores. 

The total activity score for combined weekly and monthly activities in Fall 2000 indicated 

that families engaged in a mean of 7.6 activities with the children, out of a possible 14 activities (National

Center for Education Statistics, 1996). Weekly activities made up most of that total, with a reported mean 

of 5.7 activities of a possible seven, while a mean of 1.9 monthly activities was reported, also out of a 

possible seven. Total reported activity with the children increased significantly from Fall 2000 to Spring

2001 and from Spring 2001 to Spring 2002 (means = 7.6, 8.3, and 8.5, respectively). 

Racial or ethnic differences were noted in the number of activities families engaged in with 

their children. For the activities in the previous week, African American children had higher family

activity than both White or Hispanic children, and White children had higher activity scores than Hispanic

children. For the activities covered for the previous month, there was a similar effect for ethnicity, as

African American children were engaged in more activity than White or Hispanic children. 

There were several positive relationships between family activities with children and child

behavioral and cognitive outcomes (Table 10-7). Partial correlations were run controlling for household 

income, education, and employment; child gender, age, and ethnicity; and how often the child was read to 

in the previous week. The frequency of weekly, monthly, and combined family activities was positively

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-14 March 06 
correlated with parent reports of positive child behaviors and emergent literacy skills. All three types of 

activity scores were negatively correlated with parent reports of aggressive behavior, while weekly and 

total behavior scores were negatively associated with overall problem behavior and the hyperactive 

behavior subscale. Teacher ratings of hyperactive and overall problem behavior were negatively 

correlated with reported monthly activities. Among parents, increased engagement in activities with their

children was correlated positively with both locus of control and authoritative parenting (Table 10-8). 

Table 10-7. Significant partial correlations between family activities with the child and child behavior 

and cognitive outcomes 

Weekly Activities 

with Child–Positive 

Child Behavior 

r =.22*** 

Monthly Activities with 

Child–Positive Child 

Behavior 

r =.11*** 

Overall Activities with 

Child–Positive Child 

Behavior 

r =.20*** 

Weekly Activities 

with Child–Emerging 

Literacy

r =.12*** 

Monthly Activities 

with Child–Emerging 

Literacy

r =.12*** 

Overall Activities with 

Child–Emerging Literacy 

r =.15*** 

Weekly Activities with 

Child–Aggressive 

Child Behavior 

r =-.10*** 

Monthly Activities 

with Child–

Aggressive Child 

Behavior 

r =-.04* 

Overall Activities 

with Child–

Aggressive Child 

Behavior 

r =-.09*** 

Weekly Activities with 

Child–Hyperactive Child 

Behavior 

r =-.09*** 

Overall Activities with 

Child–Hyperactive 

Child Behavior 

r =-.05* 

Weekly Activities 

with Child–Overall 

Problem Behavior 

r =-.09*** 

Overall Activities 

with Child– Overall 

Problem Behavior 

r =-.06* 

Monthly Activities with 

Child–Teacher-reported 

Hyperactive Child Behavior

r =-.05* 

Weekly Activities 

with Child–Color 

Naming 

r =-.05* 

Overall Activities with 

Child–Color Naming 

r =-.05* 

Weekly Activities with 

Child–Vocabulary

r =-.08*** 

*p< .05; **p < .01, ***p < .001.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-15 March 06 
Table 10-8. Significant partial correlations between family activities with parent outcomes 

Weekly Activities with 

Child–Internal Locus of Control 

r =.08*** 

Overall Activities with 

Child–Internal Locus of Control

r =.07*** 

Weekly Activities with 

Child–Authoritative Parenting 

r =.15*** 

Monthly Activities with 

Child–Authoritative Parenting 

r =.10*** 

Overall Activities with 

Child–Authoritative Parenting 

r =.15*** 

With regard to child cognitive scores, partial correlations identified a number of positive

relationships, with weekly activities having the strongest association with cognitive skills. For example, 

engaging in more activities with their children during the previous week was positively correlated with 

higher scores for the children on the color naming and vocabulary assessments. Participating in the 

monthly activities also had small positive correlations with the social awareness, color naming, 

one-to-one counting, book knowledge, and print concepts assessments. 

Parenting Style. FACES 2000 provided the opportunity to look at the correlations of 

parenting style with selected child cognitive and behavioral outcomes. The parents were scored on two 

different parenting styles: authoritarian and authoritative. The first of these styles is generally considered 

a stricter, directive style, while the authoritative style reflects a less harsh style with greater use of

rationales or explanations. The differences in these styles were apparent in their relationships with the 

parent and child outcomes in Table 10-9. As expected, the authoritative and authoritarian scales were

negatively correlated with each other. 

Table 10-9. Significant partial correlations between parenting style and child and parent outcomes 

Authoritative 

Parenting–Internal 

Locus of Control 

r =.09*** 

Authoritative 

Parenting–Social 

Awareness 

r =.06** 

Authoritative Parenting–

Prosocial Child Behavior 

r =.17*** 

Authoritative 

Parenting–Emerging 

Literacy

r =.08*** 

Authoritarian 

Parenting–Problem

Child Behavior 

r =.06** 

Authoritarian 

Parenting–Aggressive 

Child Behavior 

r =.04* 

Authoritarian Parenting–

Hyperactive Child Behavior

r =.04* 

Authoritarian 

Parenting–Withdrawn 

Child Behavior 

r =.05* 

Authoritarian 

Parenting–Emerging 

Literacy

r =-.05* 

Authoritarian 

Parenting–Color 

Naming 

r =-.05* 

Authoritarian Parenting–

Teacher-Reported 

Hyperactive Child Behavior

r =.05* 

Authoritarian 

Parenting–Internal 

Locus of Control 

r =-.10*** 

*p< .05; **p < .01, ***p < .001.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-16 March 06 
Partial correlations, controlling for household income, education, and employment; child

gender, age, and ethnicity; and how often the child was read to in the previous week, were used to assess

the relationship between parenting style and child behavioral and cognitive outcomes. Parents who scored

higher on the authoritative subscale also had higher internal locus of control (i.e., they felt more in control 

of their lives rather than at the mercy of external factors) and gave their children higher ratings of positive

social behavior and emergent literacy. In contrast, the authoritarian subscale scores were positively 

correlated with the overall ratings of children’s problem behavior, as well as with the three problem

behavior subscales of aggression, hyperactivity, and withdrawn behavior, and negatively correlated with

parents’ locus of control. 

There were generally weak relationships between parenting style and the cognitive 

outcomes. The authoritative parenting style scores were positively correlated with children’s social

awareness and the authoritarian parenting style was negatively correlated with color naming, but neither

parenting style was correlated with any of the other cognitive measures. Hyperactive behavior as rated by 

teachers was positively correlated with an authoritarian parenting style. 

Family Support from Head Start. In the Spring of 2001, parents were asked about the 

ways that they were involved in the Head Start program throughout the past school year. As presented in

Figure 10-4, parents most frequently reported attending parent-teacher conferences (79.0 percent), 

observing in their children’s classrooms for at least 30 minutes (74.9 percent), and meeting with a Head

Start staff member in their homes (69.4 percent). More than one-half of the parents volunteered in their 

children’s classrooms (60.0 percent) or prepared food or materials for special events (58.1 percent) and

slightly less than one-half helped with field trips (42.5 percent), or attended bazaars (42.3 percent) and

workshops (42.5 percent). Less than one-fourth of the parents participated in Policy Council (22.5 

percent). 

A summary score3 measuring total involvement was created for each parent who responded 

to the interview. A series of partial correlations, controlling for household income, education, and 

employment, and child gender, age, and ethnicity, were conducted to examine the relationship between

involvement at Head Start and other family and child factors (Table 10-10). Higher levels of Head Start 

3

 Summary parent involvement score is based on respondents’ reports of how frequently (not yet, 1-2 times, 3 or more times) they participated in 

each of 10 activities over the past school year. Summary score ranges from 10 to 30, with higher scores representing more involvement.

Mean score = 21.4; SD = 5.9.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-17 March 06 
involvement were significantly related to positive outcomes for the children. Parents who were more

involved at Head Start were likely to report more positive social behavior for their children and less 

aggressive and overall problem behavior, as well as higher emergent literacy skills than parents who were

less involved at Head Start. There was also a relationship between involvement and teachers’ reports of 

the children’s skills and with the children’s scores on cognitive assessments. For example, teachers rated 

the children of more involved parents as more creative and more socially aware. On the cognitive 

measures, children whose parents were more involved at Head Start scored higher on vocabulary, book 

knowledge, early writing, early math, and letter-identification tasks. 

Figure 10-4. The frequency of family participation in Head Start activities 

22.5

42.3

42.5

42.5

58.1

60

69.4

74.9

79

0 10 20 30 40 50 60 70 80 90

Participate in Policy Council

Attend Bazaars/ Social Events

Attend Workshops

Help with Field Trips

Help Prepare for Special Events

Volunteer in Classroom

Meet with staff in home

Observe Classroom at least 30 minutes

Attend Parent-Teacher Conference

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-18 March 06 
Table 10-10.Significant partial correlations between parental involvement at Head Start and child 

behavior and child cognitive outcomes 

Positive Social 

Behavior–Parent Report 

r = .09*** 

Aggressive 

Behavior–Parent 

Report 

r = -.08*** 

Overall Problem

Behavior–Parent Report 

r = -.04* 

Emergent 

Literacy–Parent 

Report 

r = .10*** 

Creativity–Teacher 

Report 

r = .04* 

Social 

Awareness–Teacher 

Report 

r = .06* 

Vocabulary–Direct 

Assessment 

r = .09*** 

Book 

Knowledge–Direct 

Assessment 

r = .07*** 

Early Writing–Direct 

Assessment 

r = .06* 

Word-Letter ID–Direct 

Assessment 

r =.11*** 

Early Math 

Skills–Direct Assessment 

r =.08*** 

*p< .05; **p < .01, ***p < .001.

Consistent with previous findings (ACYF, 2002), most parents reported high levels of

satisfaction with the Head Start program. For example, while more than one-half were very satisfied with

Head Start in every area, more than 82 percent of the parents reported they were very satisfied with how 

the program helped their children grow and develop, respected the family’s culture, identified child 

services, maintained a safe program, and prepared the children for kindergarten. There were very few 

unsatisfied parents, with reports of dissatisfaction generally under 2.5 percent. The area with the greatest

degree of reported dissatisfaction was how Head Start helped parents become involved in their 

community, but even this concern was cited by less than 7 percent of the parents. 

Parents also reported that they and their children had positive experiences at Head Start.

Almost 85 percent of the parents reported that their children “often” or “always” received individual 

attention, while more than 90 percent reported their children “often” or “always” felt safe and secure at

Head Start, were happy in the program, were treated with respect, and felt accepted by their teachers.

With regard to the teachers, more than 90 percent of the parents reported that their children’s teachers

“often” or “always” were open to new learning, were warm towards the children, were interested in the 

children, were supportive to parents, were welcoming, did not use harsh discipline, and were happy. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-19 March 06 
10.2.3 Head Start’s Protective Role for Families and Children 

Findings from the FACES 1997 cohort of families suggest that Head Start may play an 

important role in protecting families and children from the challenges that many families face. To validate 

these findings in the FACES 2000 cohort, a series of linear regression models, controlling for household 

income, education, and employment; child gender, age, and ethnicity; and parent level of activity with 

their children, tested whether the effect of parental depression, exposure to violence, domestic violence, 

alcohol use, or involvement in the criminal justice system on child behavior and child cognitive outcomes 

varied as a function of (or was moderated by) Head Start satisfaction, experience, or involvement. 

Summary scores were created for parents’ involvement at Head Start, for parents’ reports of having a

positive experience at Head Start, and parents’ reports of satisfaction with the program. Means and

standard deviations for these three variables are found in the Appendix. 

Table 10-11 presents the interaction terms found to be significant moderators of risk factors 

in the regression equations. These findings support the earlier results and suggest that Head Start may

play an important role in protecting families from the negative outcomes associated with these challenges. 

For example, there was a direct positive relationship between domestic violence and parent and teacher

reports of children’s problem behavior. This relationship remained consistent for children of parents who 

had fewer positive experiences with the program; however, when parents had positive experiences at 

Head Start, the effects of domestic violence on parent and teacher reports of increased aggressive,

hyperactive, withdrawn, and overall problem behavior for children were no longer evident. These findings 

indicate that the negative effects of being exposed to domestic violence on children were buffered by

parents’ positive experiences at Head Start. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-20 March 06 
Table 10-11.Significant Head Start moderators of negative outcomes associated with risk factors 

Head Start satisfaction, experience, and involvement as moderators of the negative outcomes for 

children and families related to parental depression 

Interaction term

(independent variable x moderator) Outcome variable Sig 

Depression x Head Start Satisfaction Withdrawn Behavior (parent report) ** 

Depression x Head Start Involvement Book Knowledge * 

Depression x Head Start Experience Early Math ** 

Depression x Head Start Experience Creativity (teacher report) * 

Head Start satisfaction, experience, and involvement as moderators of the negative outcomes for 

children and families related to exposure to violence 

Interaction term

(independent variable x moderator) Outcome variable Sig 

Violence x Head Start Involvement Hyperactive Behavior (parent report) * 

Violence x Head Start Involvement Emergent Literacy (parent report) ** 

Violence x Head Start Involvement Social Awareness ** 

Violence x Head Start Involvement Color Naming ** 

Violence x Head Start Experience One-to-One Counting * 

Head Start satisfaction, experience, and involvement as moderators of the negative outcomes for 

children and families related to domestic violence 

Interaction term

(independent variable x moderator) Outcome variable Sig 

Domestic Viol x Head Start Experience Social Skills (parent report) * 

Domestic Viol x Head Start Experience Total Problem Behavior (parent report) *** 

Domestic Viol x Head Start Experience Aggressive Behavior (parent report) * 

Domestic Viol x Head Start Experience Withdrawn Behavior (parent report) ** 

Domestic Viol x Head Start Satisfaction Hyperactive Behavior (parent report) * 

Domestic Viol x Head Start Experience Total Problem Behavior (teacher report) * 

Domestic Viol x Head Start Experience Social Score (teacher report) * 

* See note at end of table.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report 10-21 March 06 
Table 10-11.Significant Head Start moderators of negative outcomes associated with risk factors 

(continued) 

Head Start satisfaction, experience, and involvement as moderators of the negative outcomes for 

children and families related to alcohol use by family member 

Interaction term

(independent variable x moderator) Outcome variable Sig 

Alcohol Use x Head Start Experience Social Skills (parent report) ** 

Alcohol Use x Head Start Satisfaction Total Problem Behavior (parent report) * 

Alcohol Use x Head Start Experience Withdrawn Behavior (parent report) ** 

Alcohol Use x Head Start Satisfaction Hyperactive Behavior (parent report) ** 

Alcohol Use x Head Start Experience Total Problem Behavior (teacher report) ** 

Alcohol Use x Head Start Experience Aggressive Behavior (teacher report) ** 

Alcohol Use x Head Start Involvement Emergent Literacy (parent report) * 

Alcohol Use x Head Start Experience Social Score (teacher report) * 

Head Start satisfaction, experience, and involvement as moderators of the negative outcomes for 

children and families related to involvement with the criminal justice system

Interaction term

(independent variable x moderator) Outcome variable Sig 

Crime x Head Start Experience Social Skills (parent report) * 

Crime x Head Start Experience Withdrawn Behavior (parent report) ** 

Crime x Head Start Involvement Vocabulary * 

*p< .05; **p < .01, ***p < .001.

The moderating effects of Head Start on negative outcomes for children were consistent

across all risk factors presented in Table 10-11, and included moderation of the relationship between risk 

factors and lower cognitive outcomes, as well as negative child behavior. For example, parents’ 

depression, exposure to violence, or involvement in the criminal justice system were related, in some 

cases, to poorer cognitive outcomes for children, such as early math skills, book knowledge, color 

naming, one-to-one counting, and vocabulary. Having a parent who reported positive Head Start

experiences or who was more involved with the program moderated this relationship and appeared to

protect the children from these negative outcomes. All significant modifying relationships are presented

below. 

The difficult challenges or risks that parents face—depression, exposure to violence, 

domestic violence, alcohol use, and involvement with the criminal justice system—are often associated 

with negative behavioral and cognitive outcomes for their children. The findings cited above provide 

some evidence that Head Start may play an important role in protecting children and their families from

the consequences of these risk factors. Parent involvement at Head Start, parent reports that they and their 

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FACES 2000 Technical Report 10-22 March 06 
children had positive experiences at Head Start, and parent satisfaction with the program significantly

moderated relationships between these risk factors and many negative child behavior and cognitive 

outcomes. These findings provide support for the theory that children’s school readiness is enhanced 

when programs work with families as well as with children. It is suggested that studies of subsequent

cohorts of FACES families ask teachers to record and report on parents’ activities as a means of 

improving the overall measures of parent involvement in the program. 

10.3 Summary 

This chapter examined family and parent characteristics that are related to school readiness 

in early childhood, and parents’ important role in preparing children for school. The challenges families

face and the strengths they possess are important considerations in understanding how best to prepare 

children for school. The main findings are summarized below. 

 One-quarter of the parents were classified as moderately or severely depressed.

Parents who were more depressed reported that their children had more problem 

behaviors and fewer positive social behaviors, a finding supported by the teachers’

reports of children’s behavior. Their children also had lower scores on one-to-one 

counting, creativity, design copying, early writing, letter identification, and early math

assessments; 

 More than one-fifth of the parents reported they had witnessed violent crime. Five 

percent reported being victims of violent crime in the neighborhood, while a similar 

percentage reported being victims of violence in their homes. Almost 10 percent of 

the children were reported to have witnessed domestic violence during the previous 

year. Less than 2 percent of the children were reported to have been victims of violent 

crime or victims of domestic violence. Positive correlations were found between

increased exposure to neighborhood violence and reports of child problem behavior, 

while children in more violent neighborhoods had lower assessment scores on the

color naming and book knowledge assessments; 

 Almost 13 percent of the parents indicated that they have been victims of domestic

violence. Teachers and parents reported children in these families had more overall 

problem behaviors. However, no direct relationship was found between parent reports

of domestic violence and child cognitive outcomes; 

 Almost one-half of the Head Start children lived in households with at least one

individual who smoked cigarettes and about two-fifths of the households reported 

having at least one individual who drank alcohol. Living in a household with someone 

who drinks increased the risk of parental depression, while the children in these

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FACES 2000 Technical Report 10-23 March 06 
homes were reported to have more overall problem behavior and scored lower on 

vocabulary, color naming, and social awareness assessments; 

 Almost one-fifth of the parents reported that someone in their household had been 

arrested and charged with a crime. Children in these families were more than three 

times more likely to have been a witness to violent crime or domestic violence in the

past year. These children were also three times more likely to have been a victim of 

domestic violence or violent crime. These children had lower vocabulary scores, and 

were reported by both parents and teachers to be more aggressive and have more

overall problem behaviors; 

 At least one of a set of selected risk factors was evident in over 90 percent of the

families. Almost one-quarter of the families had four or more risk factors. Children in 

these families had lower parent ratings on emergent literacy and higher teacher and

parent ratings of problem behavior. In the assessments, these children scored lower on 

design copying, color naming, one-to-one counting, book knowledge, vocabulary, 

early math, early writing, and letter identification; 

 Families engaged their children in a number of weekly and monthly activities. The 

number of activities was positively correlated with positive child behaviors and

emergent literacy and negatively correlated with problem behaviors. In particular, the 

weekly activities had positive correlations with scores on the social awareness, color 

naming, one-to-one counting, book knowledge, vocabulary, early math, early writing, 

and letter identification tasks; 

 Higher authoritative parenting style scores were significantly positively correlated 

with children’s social awareness, but not with any of the other cognitive measures. On 

the other hand, higher authoritarian scores were significantly negatively correlated

with comprehension, color naming, vocabulary, and early math assessments; 

 More than two-thirds of parents had attended parent-teacher conferences, observed in 

their children’s classrooms for at least 30 minutes, or met with a Head Start staff

member in their homes. Parent involvement in Head Start was positively correlated 

with parental reports of positive social behavior and higher emergent literacy skills 

and negatively correlated with aggressive and overall problem behavior. Children with 

more involved parents scored higher on vocabulary, book knowledge, early writing,

early math, and letter identification tasks; and 

 Head Start may play an important role in protecting families and children from the 

challenges that low-income families face. Parent involvement at Head Start, parent 

reports that they and their children had positive experiences at Head Start, or parent 

satisfaction with the program significantly moderated relationships between risk

factors (e.g., parental depression, exposure to violence and domestic violence,

substance use, and involvement with the criminal justice system) and many negative 

child behavior and lower cognitive outcomes. 

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FACES 2000 Technical Report 10-24 March 06 
CHAPTER 11. 

PREDICTIVE VALIDITY OF COGNITIVE AND BEHAVIORAL MEASURES: 

RELATIONSHIPS WITHIN AND ACROSS COGNITIVE AND SOCIAL DEVELOPMENTAL 

DOMAINS 

The child assessment measures for the Family and Child Experiences Survey (FACES) was

designed to provide a comprehensive description of Head Start children’s development in both the

cognitive and social-emotional domains. As an indicator of the validity of the FACES instruments,

criterion-related validity, that is the degree to which the test or questionnaire correlates with one or more 

outcome criteria, was assessed. Systematic evidence for criterion validity is often described in terms of

predictive validity. Predictive validity is assessed when the outcome criterion is measured at a later time

point after the evaluated test (e.g., later school year). This chapter evaluates how well the FACES 

measures predict children’s achievement and school adjustment at the end of their kindergarten year. The 

analyses presented in this chapter are conducted with data from FACES measures administered in

Spring 2001 of the Head Start year and on kindergarten data from Spring 2002. All of the described 

analyses were conducted on children who were assessed in English at all timepoints. 

11.1 Research Questions 

This chapter will address the following research questions: 

 How well do the FACES measures predict children’s early reading skills and general

knowledge at the end of kindergarten? 

 How well do the FACES parent and teacher ratings of children’s social competence

predict children’s school adjustment at the end of kindergarten? 

 Do the FACES parent and teacher ratings of children’s social competence contribute

to the FACES measures’ prediction of children’s reading skills and general knowledge 

at the end of kindergarten? 

 How well do cognitive gains during Head Start predict reading and general knowledge 

at the end of kindergarten? 

 How well do changes in behavior ratings during Head Start predict social competence

at the end of kindergarten? and 

 Do FACES cognitive and behavior measures predict promotion to first grade? 

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FACES 2000 Technical Report 11-1 March 06 
11.2 Findings 

11.2.1 Children’s Scores on the FACES Instruments at the End of Head Start Predict

Kindergarten Outcomes 

The FACES cognitive measures were designed to assess preliteracy skills, as well as general 

school readiness. In order to determine the predictive validity of these measures, relationships between

the FACES assessment scale scores obtained during the Head Start year and the Reading and General

Knowledge scale scores obtained at the end of kindergarten were examined by two approaches. In the 

first approach, Reading and General Knowledge scale scores from the end of the kindergarten year were

correlated with the scores from each of the FACES subtests from the end of the Head Start year. The 

second approach assessed the ability of the FACES scale scores from the end of the Head Start year to 

predict Reading and General Knowledge scale scores at the end of the kindergarten year, controlling for 

child’s age at time of assessment (i.e., the end of their Head Start year), in two multiple regression

analyses. 

Children’s scores on each of the component tasks in the FACES measures at the end of Head 

Start were significantly positively correlated with their Reading scale scores at the end of kindergarten

(Table 11-1). Bivariate correlations with the Reading scale ranged from .51 (for the Woodcock-JohnsonRevised Letter-Word Identification or WJ-R LWI) to .26 (for the WJ-R Draw-a-Design). These moderateto-high correlations indicate that the FACES measures may have predictive power on outcome criteria at

later time points. Similarly, children’s scores on each of the component tasks in the FACES battery at the

end of Head Start also correlated significantly with their scores on the General Knowledge scale at the

end of kindergarten. Bivariate correlations with the General Knowledge scale ranged from .61 (for the

Peabody Picture Vocabulary Test-III or PPVT-III) to .18 (for the WJ-R LWI). 

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FACES 2000 Technical Report 11-2 March 06 
Table 11-1. Pearson’s product moment correlation coefficients between FACES assessment scores at end 

of Head Start and Reading and General Knowledge scale scores at end of kindergarten 

Correlation coefficients 

Assessment score Reading General Knowledge 

PPVT-III .36 .61 

WJR Applied Problems .39 .48 

WJR Dictation .43 .26 

WJR Letter-Word ID .51 .18 

Social Awareness .28 .20 

Draw-A-Design .26 .19 

Color Naming .35 .27 

One-to-One Counting .31 .23 

Book Knowledge .29 .37 

Note: Ns for bivariate correlations with Kindergarten Reading scale scores range from 1,394-1,511. Ns for bivariate correlations with 

Kindergarten General Knowledge scale score range from 1,386-1,501. All correlation coefficients are significant at p < .0001.

When the subtest scores were combined in a multiple regression model, the model did quite 

well at predicting children’s early reading skills at the end of kindergarten, accounting for 34 percent of

the variance in Reading scale scores. The best predictor of Reading scale scores was the WJ-R LWI task 

(beta = .30), which also showed the highest bivariate correlation with the Reading scale (Table 11-2). The 

model predicting General Knowledge scale scores accounted for 41 percent of the variance in General

Knowledge scale scores. The best predictor in this multiple regression was the PPVT-III (beta = .50), 

which also showed the highest bivariate correlation with the General Knowledge scale. 

Table 11-2. Summary of multiple linear regression analysis for FACES assessment scores at end of Head 

Start predicting Reading and General Knowledge scale scores at end of kindergarten 

(NReading = 1,282; NGeneral Knowledge = 1,275)

Reading scale General Knowledge scale

Assessment score B SE B Beta B SE B Beta 

PPVT-III .13 .03 .13  .41 .02 .50** **

WJR Applied Problems .03 .02 .06 .05 .01 .13 

WJR Dictation .04 .01 .13** * .00 .01 .02 

WJR Letter-Word ID .16 .02 .30**** -.04 .01 -.09** 

Social Awareness .33 .19 .04 .30 .15 .05* 

Draw-A-Design .27 .14 .05 .03 .11 .01 

Color Naming .31 .07 .12 .07 .05 .03 

One-to-One Counting .23 .21 .03 -.01 .16 -.00 

Book Knowledge .05 .21 .01 .68 .16 .11****

Child’s Age at Head Start 

Assessment -.18 .05 -.09*** -.12 .04 -.07** 

Note: R2 = .34 for Reading Scale; R2 = .41 for General Knowledge; (ps < .0001).

*p < .05; **p < .01; ***p < .001;  p < .0001.

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FACES 2000 Technical Report 11-3 March 06 
The Book Knowledge score was not a significant predictor of the Reading scale score in its

multiple regression model, though scores on this task correlated significantly with the Reading score 

(r = .29). It is noteworthy to also mention that the best predictor of the Reading score, namely WJ-R LWI, 

had a very small, and counterintuitive, relationship with General Knowledge in the multiple regression 

analysis. 

Although these findings are not as strong as what has been found in similar analyses with 

FACES 1997 data (ACF, 2003), they do support the notion that the Reading and General Knowledge

assessments may be tapping two distinct clusters of skills, both of which have been shown to be important

for children’s future reading proficiency and academic achievement. The skills tapped by the Reading

scale during kindergarten were primarily what Whitehurst and Lonigan (1998) have called “inside-out” 

skills such as letter recognition, letter-sound association, and word decoding. The skills tapped by the

General Knowledge assessment were “outside-in” skills, such as general information, word knowledge, 

and conceptual understanding that children need to help them comprehend and evaluate what they read

and relate it to facts and concepts they have previously acquired. The FACES battery showed its validity

by predicting well children’s later learning in both skill domains. In addition, these results suggest that 

development in both skill domains should receive attention in preschool curricula and practice in order to 

foster both types of school-age abilities. 

Although both domains were predicted well, the combination of subtests that produced the

best forecasts differed across the two skill clusters. The LWI test was the best predictor of inside-out

skills, with Dictation, Color Naming, and PPVT-III contributing additional predictive power. The

PPVT-III was by far the best predictor of outside-in skills, with Book Knowledge, Applied Problems,

Social Awareness, and LWI showing much smaller but significant regression coefficients as well. 

Predictive Validity of Abbreviated FACES Battery. In order to further explore the 

validity of the FACES battery, multivariate regression analyses were carried out with the set of

norm-referenced tests (i.e., PPVT-III and the WJ-R subtests) at the end of Head Start predicting the

Reading and General Knowledge scale at the end of kindergarten, controlling for the child’s age at the 

end of the Head Start assessment. These analyses were repeated with the set of criterion-referenced

measures (i.e., Social Awareness, McCarthy Draw-a-Design, Color Names, One-to-One Counting, and 

Book Knowledge) as the predictors. 

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FACES 2000 Technical Report 11-4 March 06 
The four norm-referenced tests at the end of Head Start did almost as well as the full battery 

at predicting the Reading scores at the end of kindergarten (Table 11-3), predicting 32 percent of the 

variance. The LWI was most closely associated with the Reading scores. Applied Problems, Dictation, 

and PPVT-III had significant coefficients as well. The four norm-referenced tests at the end of Head Start 

also did as well as the full battery at predicting the General Knowledge scores at the end of kindergarten, 

predicting 40 percent of the variance. The PPVT-III was most closely associated with the General

Knowledge scores. Applied Problems also had a significant regression coefficient, but Dictation and LWI

did not. 

Table 11-3. Summary of multiple linear regression analysis for norm reference FACES assessment 

scores at end of Head Start predicting Reading and General Knowledge scale scores at end 

of kindergarten (NReading = 1,315; NGeneral Knowledge = 1,308) 

Reading scale General Knowledge scale

Assessment score B SE B Beta B SE B Beta 

PPVT-III .15 .03 .15** ** .43 .02 .53 

WJR Applied Problems .05 .01 .11** * .07 .01 .18****

WJR Letter-Word ID .19 .02 .34  -.02 .01 -.05 

WJR Dictation .05 .01 .16** ** .01 .01 .03 

Child’s Age at Head Start 

Assessment -.17 .05 -.08** -.15 .04 -.09*** 

Note: R2 = .32 for Reading Scale; R2 = .40 for General Knowledge; (ps < .0001).

*p < .05; **p < .01; ***p < .001;  p < .0001.

The five criterion-referenced FACES tasks significantly predicted the Reading and General 

Knowledge assessments at the end of kindergarten, though notably less well than either the full battery or

the abbreviated battery composed of norm-referenced tests, predicting 20 percent and 18 percent of the 

respective variances (Table 11-4). All five subtests were significant predictors of the Reading score. As

with the full battery, tasks that tapped perceptual-motor skills and knowledge of print conventions were 

more closely related to kindergarten Reading scores than were tasks that tapped vocabulary or general

information. In the model predicting General Knowledge, four of the five subtests had significant 

regression coefficients (One-to-One Counting was the only measure with a non-significant regression

coefficient). The pattern of relative magnitudes of the significant regression coefficients was different

than that for Reading. Book Knowledge was most closely related with General Knowledge. 

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FACES 2000 Technical Report 11-5 March 06 
Table 11-4. Summary of multiple linear regression analysis for criterion reference FACES assessment 

scores at end of Head Start predicting Reading and General Knowledge scale scores at end 

of kindergarten (NReading = 1,469; NGeneral Knowledge = 1,459) 

Reading scale General Knowledge scale

Assessment score B SE B Beta B SE B Beta 

Social Awareness .97 .18 .13** ** .41 .15 .07** 

Draw-A-Design .69 .13 .13**** .26 .11 .06* 

Color Naming .41 .06 .19**** .19 .05 .11*** 

One-to-One Counting .93 .20 .12  .31 .17 .05 

Book Knowledge 1.00 .19 .13 1.71 .16 .28** **

Child’s Age at Head Start 

Assessment -.09 .04 -.05 .04 .04 .03 

Note: R2 = .20 for Reading Scale; R2 = .18 for General Knowledge; (ps < .0001).

*p < .05; **p < .01; ***p < .001;  p < .0001.

The combination of the four norm-referenced tests at the end of Head Start that were more

extended (and hence more reliable in terms of internal consistency) did a better job of predicting

children’s kindergarten achievement than the combination of the five FACES criterion-referenced tasks.

However, further analyses revealed that the five criterion-referenced measures provide significant unique

contributions to the prediction of the Reading scale score, over and above the contributions of the 

norm-referenced tests, increasing the predictive power of the assessment battery by 1 percent (Table 11-

5). The criterion-referenced measures also provided significant unique contributions to the prediction of

the General Knowledge scale score increasing the predictive power by 2 percent. These results indicate

that the criterion-referenced measures significantly contribute to the assessment battery by picking up 

variance not accounted for by the norm-referenced tests. 

11.2.2 FACES Behavioral Ratings at the End of Head Start Predict Children’s Social 

Competence in Kindergarten 

Social competence is an important developmental domain measured by the FACES battery.

Two sources of information are tapped for assessing children’s social competencies by collecting ratings

of the children’s behavior from their teachers and parents. These analyses examine the ability of the

teacher and parent ratings of children’s social competencies during Head Start to predict children’s school 

adjustment at the end of kindergarten. Analyses of the predictive validity of the behavior ratings mirror

those for the cognitive measures. First, teacher ratings of cooperative classroom behavior and total 

problem behaviors from the end of the kindergarten year were correlated with the behavior ratings from 

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FACES 2000 Technical Report 11-6 March 06 
teachers and parents at the end of the Head Start year. Then the teacher and parent ratings were combined

in multiple regressions predicting teacher ratings of cooperative classroom behavior and total problem 

behaviors at the end of the kindergarten year, controlling for child’s age at the end of the Head Start

assessment, in two multiple regression analyses.1

Table 11-5. Summary of hierarchical regression analysis for FACES assessment scores at end of 

Head Start predicting Reading and General Knowledge scale scores at end of kindergarten 

(NReading = 1,282; NGeneral Knowledge = 1,275)

Reading General Knowledge 

Assessment score B SE B Beta B SE B Beta 

Step 1 

PPVT-III .15 .03 .15** ** .43 .02 .53 

WJR Applied Problems .05 .01 .11** * .07 .01 .18****

WJR Letter-Word ID .19 .02 .34  -.02 .01 -.05 

WJR Dictation .05 .01 .16** ** .01 .01 .03 

Child’s Age at Head Start Assessment -.17 .05 -.08** -.15 .04 -.09*** 

Step 2 

PPVT-III .13 .03 .13  .41 .02 .50** **

WJR Applied Problems .03 .02 .06 .05 .01 .13 

WJR Letter-Word ID .04 .01 .13** ** .00 .01 .02 

WJR Dictation .16 .02 .30  -.04 .01 -.09**  

Social Awareness .33 .19 .04 .30 .15 .05* 

Draw-A-Design .27 .14 .05 .03 .11 .01 

Color Naming .31 .07 .12**** .07 .05 .03 

One-to-One Counting .23 .21 .03 -.01 .16 -.00 

Book Knowledge .05 .21 .01 .68 .16 .11 

Child’s Age at Head Start Assessment -.18 .05 -.09** * -.12 .04 -.07** 

Note: Reading: R2 = .32 for Step 1 (p < .0001); ΔR2 = .01 for Step 2 (p < .001). General Knowledge: R2 = .40 for Step 1 (p < .0001); ΔR2 = .02 

for Step 2 (p < .001). 

*p < .05; **p < .01; ***p < .001; ****p < .0001.

All 10 parent and teacher ratings of behavior at the end of Head Start were significantly

correlated with teacher ratings of cooperative classroom behavior at the end of kindergarten (Table 11-6). 

Correlations were significant in the expected directions. Problem behaviors as rated by both parents and

teachers at the end of Head Start had significant negative correlations with teacher ratings of cooperative 

classroom behavior at the end of kindergarten, ranging from -.33 (for teacher reported ratings of total 

behavior problems) to -.06 (for parent reported ratings of withdrawn behavior). Kindergarten teacher 

1

 In all multiple regression analyses involving the behavior ratings, teacher and parent ratings of total problem behavior were excluded as

predictor variables from the models. Because these ratings are summative scores of the ratings for aggression, withdrawn behavior, and 

hyperactivity, including them would introduce multicollinearity among these predictor variables to the model. They are included in the bivariate 

correlation analyses. 

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FACES 2000 Technical Report 11-7 March 06 
ratings of cooperative classroom behavior were positively correlated with teacher ratings of cooperative 

classroom behavior (r = .33) and parent ratings of positive approaches to learning (r = .11) at the end of 

Head Start. These moderate-sized correlation coefficients indicate that the FACES measures may have 

predictive power on kindergarten outcomes. In general, teacher ratings showed stronger relationships than 

the parent ratings did with the kindergarten outcomes. 

Table 11-6. Pearson’s product moment correlation coefficients between FACES behavior ratings at end 

of Head Start and teacher ratings of cooperative classroom behavior and total problem

behaviors at end of kindergarten 

Correlation coefficients 

Behavior rating 

Cooperative classroom

behavior 

Total problem

behaviors 

Teacher Reported Aggression -.31 .39 

Teacher Reported Hyperactivity -.32 .41 

Teacher Reported Withdrawal -.23 .27 

Teacher Reported Total Problem Behaviors -.33 .41 

Teacher Reported Cooperative Classroom Behavior .33 -.34 

Parent Reported Aggression -.19 .22 

Parent Reported Hyperactivity -.23 .26 

Parent Reported Withdrawal -.06* .10** 

Parent Reported Total Problem Behaviors -.22 .26 

Parent Reported Positive Approaches to Learning .11*** -.15 

Note: Ns for correlations with Kindergarten Teacher Ratings of Cooperative Classroom Behavior range from 1,146-1,191. Ns for correlations

with Kindergarten Teacher Ratings of Total Problem Behavior range from 1,147-1,193. 

All p-values < .0001 except for *p < .05; **p < .01; ***p < .001.

Similarly, all 10 parent and teacher ratings of behavior at the end of Head Start were

moderately correlated with teacher ratings of total problem behaviors at the end of kindergarten 

(Table 11-6). Correlations were significant in the expected directions. Problem behaviors as rated by both

parents and teachers at the end of Head Start had significant positive correlations with teacher ratings of

total problem behaviors at the end of kindergarten, ranging from .41 (for teacher reported ratings of

hyperactive behavior and total problem behaviors) to .10 (for parent reported ratings of withdrawn

behavior). Teacher ratings of cooperative classroom behavior (r = -.34) and parent ratings of positive

approaches to learning (r = -.15) were both negatively correlated with teacher ratings of total problem 

behavior at the end of kindergarten. In general, teacher ratings showed stronger relationships than the 

parent ratings did with the kindergarten outcomes. 

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FACES 2000 Technical Report 11-8 March 06 
When the ratings were combined in a multiple regression, the model accounted for

14 percent of the variance in kindergarten teacher ratings of cooperative classroom behavior (Table 11-7). 

The best predictor in the multiple regression was teacher-reported ratings of cooperative classroom 

behavior (beta = .15). The model predicting kindergarten teacher ratings of total problem behavior

accounted for 21 percent of the variance in kindergarten teacher ratings of total problem behavior. The 

best predictor in the multiple regression was teacher-reported ratings of aggressive behavior (beta = .19). 

Table 11-7. Summary of multiple linear regression analysis for FACES behavior ratings at end of Head 

Start predicting teacher ratings of cooperative classroom behavior and total problem

behaviors at end of kindergarten 

(NCooperative Classroom Behavior = 1,060; NTotal Problem Behaviors = 1,061) 

Cooperative classroom behavior Total problem behaviors 

Behavior rating B SE B Beta B SE B Beta 

Teacher Reported Aggression -.21 .10 -.09* .49 .10 .19****

Teacher Reported Hyperactivity -.40 .14 -.13** .61 .15 .17 

Teacher Reported Withdrawal .01 .07 .00 .06 .08 .03 

Teacher Reported Cooperative 

Classroom Behavior .16 .04 .15** * -.07 .05 -.06 

Parent Reported Aggression -.15 .09 -.05 .15 .10 .05 

Parent Reported Hyperactivity -.33 .11 -.10** .37 .12 .10** 

Parent Reported Withdrawal .02 .16 .00 .13 .17 .02 

Parent Reported Positive 

Approaches to Learning -.05 .09 -.02 -.06 .09 -.02 

Child’s Age at Head Start 

Assessment -.01 .02 -.01 -.01 .03 -.02 

Note: R2 = .14 for Teacher Ratings of Cooperative Classroom Behavior; R2 = .21 for Teacher Ratings of Total Problem Behaviors; (ps < .0001).

*p < .05; **p < .01; ***p < .001;  p < .0001.

Predictive Validity of Abbreviated Sets of Behavior Ratings. In order to further explore 

the validity of the behavior ratings, multivariate regression analyses were carried out with the set of 

teacher-reported ratings at the end of Head Start predicting the teacher-reported ratings of cooperative 

classroom behavior and total problem behavior at the end of kindergarten. 

The teacher-reported ratings at the end of Head Start did almost as well as the full set of 

behavior ratings at predicting the teacher-reported ratings of cooperative classroom behavior at the end of 

kindergarten (Table 11-8). The model explained 14 percent of the variance in kindergarten cooperative

classroom behavior ratings, and the rating of cooperative classroom behavior at the end of Head Start was 

most closely associated with the teacher ratings at the end of kindergarten (beta = .18). The ratings of 

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FACES 2000 Technical Report 11-9 March 06 
hyperactive (beta = -.15) and aggressive behavior (beta = -.11) both had significant regression coefficients 

as well, but the ratings of withdrawn behavior did not. 

Table 11-8. Summary of multiple linear regression analysis for FACES teacher ratings at end of Head 

Start predicting teacher ratings of cooperative classroom behavior and total problem

behaviors at end of kindergarten 

(NCooperative Classroom Behavior = 1,125; NTotal Problem Behaviors = 1,126) 

Cooperative classroom behavior Total problem behaviors 

Behavior rating B SE B Beta B SE B Beta 

Teacher Reported Aggression -.25 .09 -.11**  .50 .10 .19****

Teacher Reported Hyperactivity -.47 .14 -.15*** .74 .15 .20 

Teacher Reported Withdrawal .00 .07 .00 .04 .08 .02 

Teacher Reported Cooperative 

Classroom Behavior .18 .04 .18** ** -.12 .04 -.10**

Child’s Age at Head Start 

Assessment -.01 .02 -.02 -.01 .03 -.01 

Note: R2 = .14 for Teacher Ratings of Cooperative Classroom Behavior; R2 = .20 for Teacher Ratings of Total Problem Behaviors; (ps < .0001).

*p < .05; **p < .01; ***p < .001;  p < .0001.

Similarly, the teacher-reported ratings at the end of Head Start did almost as well as the full 

set of behavior ratings at predicting the teacher-reported ratings of total problem behavior at the end of

kindergarten. The model explained 20 percent of the variance in kindergarten total problem behavior 

ratings, and the rating of hyperactive behavior was most closely associated with the total problem

behavior ratings (beta = .20). The ratings of cooperative classroom behavior (beta = -.10) and aggressive 

behavior (beta = .19) both had significant regression coefficients as well, but the ratings of withdrawn 

behavior did not. 

The four parent-reported behavior ratings significantly predicted the teacher ratings of 

cooperative classroom behavior at the end of kindergarten, though notably less well than either the full set 

of behavior ratings or the set of teacher-reported ratings (Table 11-9). The model explained 6 percent of 

the variance in teacher-reported cooperative classroom behavior and the strongest predictor was ratings of 

hyperactive behavior (beta = -.18), followed by ratings of aggressive behavior (beta = -.10). Parent ratings

of positive approaches to learning and withdrawn behavior did not have significant regression

coefficients. 

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FACES 2000 Technical Report 11-10 March 06 
Table 11-9. Summary of multiple linear regression analysis for FACES parent ratings at end of Head 

Start predicting teacher ratings of cooperative classroom behavior and total problem

behaviors at end of kindergarten (NCooperative Classroom Behavior = 1,166; NTotal Problem Behaviors = 

1,168) 

Cooperative classroom behavior Total problem behaviors 

Behavior rating B SE B Beta B SE B Beta 

Parent Reported Aggression -.27 .09 -.10**  .32 .10 .11**

Parent Reported Hyperactivity -.59 .11 -.18  .74 .12 .20** *

Parent Reported Withdrawal .19 .15 .04 -.09 .17 -.02 

Parent Reported Positive 

Approaches to Learning .07 .08 .03 -.19 .09 -.06* 

Child’s Age at Head Start 

Assessment .04 .02 .05 -.06 .03 -.06* 

Note: R2 = .06 for Teacher Ratings of Cooperative Classroom Behavior; R2 = .09 for Teacher Ratings of Total Problem Behaviors; (ps < .0001).

*p < .05; **p < .01; ***p < .001;  p < .0001.

The four parent-reported behavior ratings also significantly predicted the teacher ratings of 

total problem behavior at the end of kindergarten, though notably less well than either the full set of

behavior ratings or the set of teacher-reported ratings. The model explained 9 percent of the variance in 

kindergarten teacher-reported total problem behavior and parent-reported ratings of hyperactive behavior 

had the largest regression coefficient (beta = .20), followed by ratings of aggressive behavior (beta = .11) 

and ratings of positive approaches to learning (beta = -.06). Parent ratings of withdrawn behavior did not 

have a significant regression coefficient. 

The combination of the four teacher-reported behavior ratings at the end of Head Start did a 

better job of predicting children’s kindergarten behavior than the combination of the four parent-reported

behavior ratings (Table 11-10). When added to the regression model, the four parent ratings provided 

unique contributions at the trend level (p < .10) to the prediction of the cooperative classroom behavior

ratings, over and above the contributions of the teacher ratings, increasing the predictive power of the 

assessment battery by 1 percent. These results indicate that the parent ratings provide some unique

contributes to the assessment battery. 

The four parent ratings also provided significant unique contributions to the prediction of the 

total problem behavior ratings, over and above the contributions of the teacher ratings, increasing the 

predictive power of the assessment battery by almost 2 percent. These results further indicate that the

parent ratings significantly contribute to the assessment battery, by picking up significant variance not 

accounted for by the teacher-reported ratings. 

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FACES 2000 Technical Report 11-11 March 06 
Table 11-10. Summary of hierarchical regression analysis for FACES behavior ratings at end of Head 

Start predicting teacher ratings of cooperative classroom behavior and total problem

behaviors at end of kindergarten 

(NCooperative Classroom Behavior = 1,060; NTotal Problem Behaviors = 1,061) 

Cooperative classroom

behavior Total problem behaviors 

Behavior rating B SE B Beta B SE B Beta 

Step 1 

Teacher Reported Aggression -.25 .09 -.11**  .50 .10 .19****

Teacher Reported Hyperactivity -.47 .14 -.15*** .74 .15 .20 

Teacher Reported Withdrawal .00 .07 .00 .04 .08 .02 

Teacher Reported Cooperative 

Classroom Behavior .18 .04 .18** ** -.12 .04 -.10** 

Child’s Age at Head Start 

Assessment -.01 .02 -.02 -.01 .03 -.01 

Step 2 

Teacher Reported Aggression -.21 .10 -.09* .49 .10 .19****

Teacher Reported Hyperactivity -.40 .14 -.13** .61 .15 .17 

Teacher Reported Withdrawal .01 .07 .00 .06 .08 .03 

Teacher Reported Cooperative 

Classroom Behavior .16 .04 .15** * -.07 .05 -.06 

Parent Reported Aggression -.15 .09 -.05 .15 .10 .05 

Parent Reported Hyperactivity -.33 .11 -.10** .37 .12 .10** 

Parent Reported Withdrawal .02 .16 .00 .13 .17 .02 

Parent Reported Positive 

Approaches to Learning -.05 .09 -.02 -.06 .09 -.02 

Child’s Age at Head Start 

Assessment -.01 .02 -.01 -.01 .03 -.02 

Note: Teacher Ratings of Cooperative Classroom Behavior: R2 = .14 for Step 1 (p < .0001); ΔR2 = .01 for Step 2 (p < .10). Teacher Ratings of

Total Problem Behaviors: R2

 = .20 for Step 1 (p < .0001); ΔR2 = .02 for Step 2 (p < .05). 

*p < .05; **p < .01; ***p < .001;  p < .0001.

11.2.3 Behavior Ratings at the End of Head Start Predict Reading Skills and General

Knowledge at the End of Kindergarten 

Given that certain positive behaviors may foster learning, while other negative behaviors

may impede learning, the ability of these behavior ratings obtained during the Head Start year to predict 

Reading and General Knowledge scale scores obtained at the end of kindergarten was also examined. 

Eight of the ten parent and teacher ratings of behavior at the end of Head Start correlated

significantly with Reading scale scores at the end of kindergarten, indicating that the FACES measures 

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FACES 2000 Technical Report 11-12 March 06 
may have some predictive power on outcome criteria at later time points. The parent-reported ratings of 

positive approaches to learning and withdrawn behavior were correlated with kindergarten Reading scores 

at the trend level (p < .10). Significant correlations were in the expected directions. Ratings of problem

behaviors were negatively correlated with kindergarten Reading scale scores, suggesting that behaviors 

that may impede learning are associated with lower reading skills in kindergarten (Table 11-11). 

Table 11-11.Pearson’s product moment correlation coefficients between FACES behavior ratings at end 

of Head Start and Reading and General Knowledge scale scores at end of kindergarten 

Correlation coefficients 

Behavior rating Reading General Knowledge 

Teacher Reported Aggression -.14** * -.12*** 

Teacher Reported Hyperactivity -.21*** -.16*** 

Teacher Reported Withdrawal -.27*** -.25*** 

Teacher Reported Total Problem Behaviors -.25*** -.22*** 

Teacher Reported Cooperative Classroom Behavior .20*** .19*** 

Parent Reported Aggression -.08** -.06* 

Parent Reported Hyperactivity -.12*** -.10*** 

Parent Reported Withdrawal NS NS 

Parent Reported Total Problem Behaviors -.12*** -.09** 

Parent Reported Positive Approaches to Learning NS .06* 

Note: Ns for correlations with Reading Scale Scores range from 1,395-1,453. Ns for correlations with General Knowledge Scale Scores range 

from 1,387-1,443.

*p < .05; **p < .01; ***p < .0001.

Significant correlations were also found between children’s scores on 9 of the 10 parent- and

teacher-reported behavior ratings at the end of Head Start and General Knowledge scale scores at the end

of kindergarten (the association with parent ratings of withdrawn behavior was not significant). 

Significant bivariate correlations between parent teacher ratings and General Knowledge scale scores

were in expected directions and ranged in absolute value from .25 (for teacher ratings of withdrawn

behavior) to .06 (for parent ratings of positive approaches to learning behavior), again indicating that the 

FACES measures may have some predictive power on outcome criteria at later time points. Ratings of 

problem behaviors were negatively correlated with kindergarten General Knowledge scale scores, again

suggesting that behaviors that may impede learning are associated with lower skills in the natural sciences 

and social studies in kindergarten. 

When the behavior ratings were combined in a multiple regression model, the model 

accounted for 9 percent of the variance in Reading scale scores (Table 11-12). However, the only

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FACES 2000 Technical Report 11-13 March 06 
significant predictor in the multiple regression was teacher-reported ratings of withdrawn behavior 

(beta = -.22) which also showed the strongest bivariate correlation with reading scores (r = -.27). 

Table 11-12. Summary of multiple linear regression analysis for FACES behavior ratings at end of Head 

Start predicting Reading and General Knowledge scale scores at end of kindergarten 

(NReading = 1,283; NGeneral Knowledge = 1,277)

Reading General knowledge 

Behavior rating B SE B Beta B SE B Beta 

Teacher Reported Aggression .09 .19 .02 -.07 .15 -.02 

Teacher Reported Hyperactivity -.36 .28 -.05 .25 .22 .05 

Teacher Reported Withdrawal -.88 .14 -.22* -.72 .11 -.22* 

Teacher Reported Cooperative Classroom Behavior .04 .09 .02 .08 .07 .04 

Parent Reported Aggression .03 .18 .01 .05 .15 .01 

Parent Reported Hyperactivity -.42 .22 -.06 -.38 .18 -.07* 

Parent Reported Withdrawal .06 .30 .01 .66 .24 .08** 

Parent Reported Positive Approaches to Learning -.10 .17 -.02 .06 .14 .01 

Child’s Age at Head Start Assessment .21 .05 .12* .21 .04 .15* 

Note: R2 = .09 for Reading; R2 = .09 for General Knowledge; (ps < .0001). 

*p < .0001.

When the behavior ratings were combined in a multiple linear regression model predicting 

General Knowledge, the model accounted for 9 percent of the variance in General Knowledge scale 

scores. The strongest predictor in the multiple regression was teacher-reported ratings of withdrawn

behavior (beta = -.22), which also had the strongest bivariate correlation. 

FACES Behavior Ratings Contribute to the Prediction of General Knowledge at the 

End of Kindergarten. In order to further examine the usefulness of the behavior ratings, the unique 

contribution of the set of behavior rating measures to the prediction of kindergarten outcomes was 

assessed (Table 11-13). The eight behavior ratings did significantly provide unique contributions to the

prediction of the General Knowledge scale score, over and above the cognitive assessments, increasing 

the predictive power of the assessment battery by 2 percent. Further, the eight behavior ratings did 

provide unique contributions at the trend level (p < .10) to the prediction of the Reading scale score, over 

and above the contributions of the cognitive tests, increasing the predictive power of the assessment 

battery by almost 1 percent. This indicates that the behavior ratings provide some unique contributions to

the prediction of kindergarten outcomes.

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FACES 2000 Technical Report 11-14 March 06 
Table 11-13. Summary of hierarchical regression analysis for FACES behavior ratings at end of Head 

Start predicting Reading and General Knowledge scale scores at the end of kindergarten 

(NReading = 1,105; NGeneral Knowledge = 1,100)

Reading General Knowledge 

Assessment score/behavior rating B SE B Beta B SE B Beta 

Step 1

PPVT-III .13 .03 .13**** .41 .02 .50 

WJR Applied Problems .03 .02 .06 .05 .01 .13** **

WJR Letter-Word ID .04 .01 .13  .00 .01 .02 

WJR Dictation .16 .02 .30** ** -.04 .01 -.09** 

Social Awareness .33 .19 .04 .30 .15 .05* 

Draw-A-Design .27 .14 .05 .03 .11 .01 

Color Naming .31 .07 .12**** .07 .05 .03 

One-to-One Counting .23 .21 .03 -.01 .16 -.00 

Book Knowledge .05 .21 .01 .68 .16 .11 

Child’s Age at Head Start 

Assessment -.18 .05 -.09** * -.12 .04 -.07** 

Step 2

PPVT-III .13 .03 .13  .41 .02 .51** **

WJR Applied Problems .02 .02 .05 .05 .01 .13***

WJR Dictation .03 .01 .11** .00 .01 .00 

WJR Letter-Word ID .16 .02 .30  -.04 .01 -.10**  

Social Awareness .13 .21 .02 .32 .16 .05* 

Draw-A-Design .30 .15 .06* .05 .11 .01 

Color Naming .27 .08 .10*** .07 .06 .03 

One-to-One Counting .36 .22 .05 -.13 .17 -.02 

Book Knowledge .07 .22 .01 .68 .17 .11 

Teacher Reported Aggression -.08 .17 -.02 -.05 .13 -.01 

Teacher Reported Hyperactivity -.26 .26 -.04 .12 .19 .02 

Teacher Reported Withdrawal -.42 .13 -.10**  -.40 .10 -.12****

Teacher Reported Cooperative 

Classroom Behavior -.14 .08 -.06 -.06 .06 -.03 

Parent Reported Aggression -.07 .17 -.01 -.11 .13 -.02 

Parent Reported Hyperactivity .10 .20 .01 -.11 .15 -.02 

Parent Reported Withdrawal -.22 .28 -.02 .27 .21 .03 

Parent Reported Positive 

Approaches to Learning -.32 .16 -.05 -.01 .12 -.11 

Child’s Age at Head Start 

Assessment -.16 .06 -.08** -.12 .04 -.07** 

Note: Reading: R2 = .34 for Step 1 (p < .0001); ΔR2 = .01 for Step 2 (p < .10). General Knowledge: R2 = .41 for Step 1 (p < .0001); ΔR2 = .02 for

Step 2 (p < .05). 

*p < .05; **p < .01; ***p < .001; ****p < .0001.

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FACES 2000 Technical Report 11-15 March 06 
11.2.4 Head Start Fall-to-Spring Gain Scores from the FACES Battery Predict Kindergarten 

Outcomes 

As a further assessment of the predictive validity of the cognitive measures from the FACES

battery, the predictive validity of their Fall-to-Spring gain scores was assessed. To determine the 

children’s gains during their Head Start year, differences between the Fall 2000 and Spring 2001 mean 

scores were calculated for each of the measures by subtracting the Fall score from the Spring score for

each child in the study.

The ability of the Fall-to-Spring gain scores from the cognitive measures of the FACES 

battery to predict later school readiness was assessed by two approaches. In the first approach, Reading 

and General Knowledge scale scores from the end of the kindergarten year were correlated with the gain 

scores from each of the FACES subtests from the end of the Head Start year. In these analyses, partial

correlations were calculated, controlling for individual difference in Fall 2000, baseline scores.2

 The 

second approach assessed the ability of the Fall-to-Spring gain scores from the FACES instruments to 

predict Reading and General Knowledge scale scores at the end of the kindergarten year, controlling for 

child’s age at time of assessment (i.e., the end of their Head Start year), in two multiple linear regression

analyses.3

Children’s Fall-to-Spring gain scores on each of the component tasks in the FACES battery

correlated significantly with their Reading scale scores at the end of kindergarten (Table 11-14). Bivariate

correlations with the Reading scale ranged from .33 (for the WJ-R LWI gain score) to .18 (for the Social

Awareness gain score). Similarly, children’s Fall-to-Spring gain scores on all of the component tasks in

the FACES battery correlated significantly with their General Knowledge scale scores at the end of

kindergarten. Significant bivariate correlations with the General Knowledge scale ranged from .33 (for

the PPVT-III gain score) to .10 (for the gain scores for WJ-R LWI and Color Naming). 

2

 In analyses of gains scores, baseline scores are controlled for, effectively examining the effect of the gain scores if all students had the same

baseline score. 

3

 Control of the Fall baseline score for each gain score in the multiple linear regression models was accomplished through the use of residual

scores. A residual score was created for each gain score with the effects of its respective baseline score partialled out. These residual scores

were then entered as independent variables in the multiple linear regression, predicting the kindergarten outcome variables.

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FACES 2000 Technical Report 11-16 March 06 
Table 11-14. Pearson’s product moment correlation coefficients between FACES assessment gain scores 

during Head Start and Reading and General Knowledge scale scores at end of kindergarten 

Correlation coefficients 

Assessment gain score Reading General Knowledge 

PPVT-III .23 .33 

WJR Applied Problems .23 .23 

WJR Letter Word .33 .10* 

WJR Dictation .30 .11** 

Social Awareness .18 .11 

Draw-A-Design .20 .14 

Color Naming .19 .10 

One-to-One Counting .22 .17 

Book Knowledge .22 .29 

Note: Ns for bivariate correlations with Kindergarten Reading scale scores range from 637 -1,475. Ns for bivariate correlations with Kindergarten

General Knowledge scale score range from 629-1,468. All correlation coefficients are significant at p < .0001 except *p < .05 and **p < .01.

When the gain scores were combined in a multiple regression model, the model did well at

predicting children’s early reading skills at the end of kindergarten, accounting for 20 percent of the 

variance in Reading scale scores (Table 11-15). The best predictor of Reading scale scores was the gain

score for WJ-R Dictation task (beta = .16), followed by the LWI gain score (beta = .15) (which showed

the highest bivariate correlation with the Reading scale). The model also did well at predicting children’s 

general knowledge at the end of kindergarten, accounting for 23 percent of the variance in General 

Knowledge scale scores. The best predictor in the model was the gain score for the PPVT-III gain score 

(beta = .31), which had the highest bivariate correlation with the General Knowledge scores. 

11.2.5 Head Start Fall-to-Spring Change Scores from the Behavior Ratings Predict Social

Competence in Kindergarten 

The Fall-to-Spring change scores from all but one of the parent and teacher ratings of

behavior were moderately correlated with teacher ratings of cooperative classroom behavior at the end of

kindergarten. Parent ratings of changes in withdrawn behavior were not significantly correlated with the 

kindergarten teacher ratings (Table 11-16). Correlations were significant in the expected directions. 

Declines in problem behaviors as rated by both parents and teachers at the end of Head Start were

significantly associated with higher teacher ratings of cooperative classroom behavior at the end of

kindergarten, with correlation coefficients ranging from -.24 (for the change score for parent-reported

ratings of hyperactivity) to -.13 (for the change score for parent-reported ratings of aggression). Increases

in teacher ratings of cooperative classroom behavior at the end of Head Start were significantly associated

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FACES 2000 Technical Report 11-17 March 06 
with higher teacher ratings of cooperative classroom behavior at the end of kindergarten (r = .24), as were 

increases in parent ratings of positive approaches to learning (r = .09). In general, change scores for the 

teacher ratings showed stronger relationships with the kindergarten outcomes than those for the parent

ratings. However, this could be due to the fact that parents did not report significant Fall-to-Spring change

in their children’s behavior. 

Table 11-15. Summary of multiple linear regression analysis for FACES gain scores during Head Start 

predicting Reading and General Knowledge scale scores at end of kindergarten 

(NReading = 510; NGeneral Knowledge = 503) 

Reading scale General Knowledge scale

Assessment gain scale B SE B Beta B SE B Beta

PPVT-III .17 .07 .11* .39 .05 .31****

WJR Letter-Word ID .11 .03 .15*** -.02 .03 -.04 

WJR Dictation .06 .02 .16  .01 .01 .02 

WJR Applied Problems .01 .03 .02 .02 .02 .04 

Draw-A-Design .29 .21 .06 -.05 .17 -.01 

Book Knowledge .23 .36 .03 1.44 .29 .21** **

Social Awareness .76 .37 .08* .51 .30 .07 

Color Naming .26 .14 .08 -.15 .11 -.06 

One-to-One Counting .77 .37 .09* .69 .29 .10* 

Child’s Age at Head Start 

Assessment .11 .10 .05 .11 .08 .06 

Note: R2 = .20 for Reading Scale; R2 = .23 for General Knowledge; (ps < .0001).

*p < .05; **p < .01; ***p < .001; ****p < .0001.

Similarly, the Fall-to-Spring change scores from all of the parent and teacher ratings of 

behavior were moderately correlated with teacher ratings of total problem behavior at the end of 

kindergarten. Correlations were significant in the expected directions. Declines in problem behaviors as 

rated by both parents and teachers at the end of Head Start were significantly associated with lower 

teacher ratings of total problem behavior at the end of kindergarten, with correlation coefficients ranging 

from .29 (for the change score for teacher-reported ratings of hyperactive behavior) to .07 (for the change 

score for parent-reported ratings of withdrawn behavior). Increases in teacher ratings of cooperative 

classroom behavior were significantly associated with lower teacher ratings of total problem behavior at 

the end of kindergarten (r = -.24), as were increases in parent ratings of positive approaches to learning

(r = -.12). In general, change scores for the teacher ratings showed stronger relationships with the

kindergarten outcomes than those for the parent ratings. 

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FACES 2000 Technical Report 11-18 March 06 
Table 11-16.Pearson’s product moment correlation coefficients between FACES behavior ratings gain 

scores at end of Head Start and teacher ratings of cooperative classroom behavior and total 

problem behaviors at end of kindergarten 

Correlation coefficients 

Behavior rating gain score

Cooperative classroom

behavior 

Total problem

behaviors 

Teacher Reported Aggression -.18 .24 

Teacher Reported Hyperactivity -.24 .29 

Teacher Reported Withdrawal -.18 .19 

Teacher Reported Total Problem Behaviors -.23 .28 

Teacher Reported Cooperative Classroom Behavior .24 -.24 

Parent Reported Aggression -.13 .17 

Parent Reported Hyperactivity -.17 .17 

Parent Reported Withdrawal Ns .07* 

Parent Reported Total Problem Behaviors -.15 .17 

Parent Reported Positive Approaches to Learning .09** -.12 

Note: Ns for correlations with Kindergarten Teacher Ratings of Cooperative Classroom Behavior range from 1,146-1,191. Ns for correlations

with Kindergarten Teacher Ratings of Total Problem Behavior range from 1,147-1,193. 

All p-values < .0001 except for *p < .05; **p < .01.

When the rating change scores were combined in a multiple regression predicting 

kindergarten teacher ratings of behavior, the model accounted for 8 percent of the variance in

kindergarten teacher ratings of cooperative classroom behavior. The best predictor in the multiple 

regression was the change score for teacher-reported ratings of cooperative classroom behavior 

(beta = .14). The model predicting kindergarten teacher ratings of total problem behaviors accounted for 

10 percent of the variance in teacher ratings of total problem behaviors. The best predictor in the multiple

regression was the change score for teacher-reported ratings of hyperactive behavior, (beta = .14) 

(Table 11-17). 

11.2.6 Head Start Fall-to-Spring Change Scores from the Behavior Ratings Predict Reading 

Skills and General Knowledge at the End of Kindergarten 

All of the Fall-to-Spring change scores for teacher ratings of behavior correlated

significantly with Reading scale scores at the end of kindergarten, however, only one of the parent ratings 

change scores of behavior had a significant correlation coefficient with kindergarten Reading (parent 

ratings of changes in hyperactive behavior: r = -.06; p < .05 - see Table 11-18). Correlations for teacher

ratings were significant in the expected directions. Declines in teacher ratings of problem behaviors were 

significantly associated with higher kindergarten Reading scale scores, adding more evidence that

behaviors that may impede learning are associated with lower reading skills in kindergarten. All of the 

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FACES 2000 Technical Report 11-19 March 06 
Fall-to-Spring change scores for teacher ratings of behavior also correlated in the expected directions with

General Knowledge scale scores at the end of kindergarten. None of the parent rating change scores were

significantly associated with kindergarten General Knowledge scores. 

Table 11-17. Summary of multiple linear regression analysis for FACES behavior rating gain scores at 

end of Head Start predicting teacher ratings of cooperative classroom behavior and total 

problem behaviors at end of kindergarten 

(NCooperative Classroom Behavior = 946; NTotal Problem Behaviors = 947) 

Cooperative classroom

behavior Total problem behaviors 

Behavior rating gain score B SE B Beta B SE B Beta 

Teacher Reported Aggression .01 .11 .01 .20 .12 .07 

Teacher Reported Hyperactivity -.48 .16 -.13** .60 .18 .14***

Teacher Reported Withdrawal .01 .09 .01 -.02 .09 -.01 

Teacher Reported Cooperative Classroom

Behavior .16 .05 .14*** -.13 .05 -.10* 

Parent Reported Aggression -.12 .11 -.04 .26 .12 .07* 

Parent Reported Hyperactivity -.37 .13 -.10** .31 .15 .07* 

Parent Reported Withdrawal -.05 .18 -.01 .22 .20 .04 

Parent Reported Positive Approaches to 

Learning .01 .10 .00 -.02 .11 -.01 

Child’s Age at Head Start Assessment .01 .03 .01 -.05 .03 -.05 

Note: R2 = .08 for Teacher Ratings of Cooperative Classroom Behavior; R2 = .10 for Teacher Ratings of Total Problem Behaviors; (ps < .0001).

*p < .05; **p < .01; ***p < .001;  p < .0001.

Table 11-18.Pearson’s product moment correlation coefficients between FACES behavior ratings gain 

scores during Head Start and Reading and General Knowledge scale scores at end of 

kindergarten 

Correlation coefficients 

Behavior rating gain score Reading General knowledge 

Teacher Reported Aggression -.09**  -.09** 

Teacher Reported Hyperactivity -.13  -.10** * 

Teacher Reported Withdrawal -.21**** -.20  

Teacher Reported Total Problem Behaviors -.18** ** -.16  

Teacher Reported Cooperative Classroom Behavior .13** ** .10*** 

Parent Reported Aggression NS NS 

Parent Reported Hyperactivity -.06* NS 

Parent Reported Withdrawal NS NS 

Parent Reported Total Problem Behaviors NS NS 

Parent Reported Positive Approaches to Learning NS NS 

Note: Ns for correlations with Reading Scale Scores range from 1,395-1,453. Ns for correlations with General Knowledge Scale Scores range 

from 1,387-1,443.

*p < .05; **p < .01; ***p < .001; ****p < .0001.

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FACES 2000 Technical Report 11-20 March 06 
When the teacher ratings change scores were combined in a multiple regression model, the 

model accounted for 6 percent of the variance in Reading scale scores (Table 11-19).

4

 The only

significant predictor in the multiple regression was the change score for teacher-reported ratings of 

withdrawal behavior (beta = -.19). The multiple regression model of teacher rating change scores 

predicting kindergarten General Knowledge scale scores accounted for 7 percent of the variance in 

General Knowledge scale scores. Similar to the model predicting kindergarten Reading, the only 

significant predictor in this multiple regression was the change score for teacher-reported ratings of

withdrawal behavior (beta = -.22). 

Table 11-19. Summary of multiple linear regression analysis for FACES behavior rating gain scores 

during Head Start predicting Reading and General Knowledge scale scores at end of 

kindergarten (NReading = 1,262; NGeneral Knowledge = 1,338)

Reading General knowledge 

Behavior rating gain score B SE B Beta B SE B Beta 

Teacher Reported Aggression .07 .20 .01 -.10 .16 -.02 

Teacher Reported Hyperactivity .05 .30 .01 .40 .24 .06 

Teacher Reported Withdrawal -.88 .16 -.19* -.80 .13 -.22* 

Teacher Reported Cooperative Classroom

Behavior .06 .09 .02 -.00 .07 -.00 

Child’s Age at Head Start Assessment .26 .05 .15* .27 .04 .19* 

Note: R2 = .06 for Reading; R2 = .07 for General Knowledge; (ps < .0001). 

*p < .0001.

11.2.7 Children’s Scores on the FACES Instruments and Behavior Ratings at the End of Head 

Start Predict Promotion to First Grade 

Another measure of the predictive validity of the FACES battery is to examine how well

scores on the FACES instruments and behavior ratings at the end of Head Start are related to practical

decision-making at the end of kindergarten, namely, the teacher’s decision of whether the child gets

promoted to first grade or repeats the kindergarten year. In these analyses, the ability of the FACES scale 

scores from the end of the Head Start year to predict the teacher’s decision at the end of the kindergarten 

year to have the child repeat a year of kindergarten (versus promote the child to first grade) was examined 

4 Because of their low correlations with kindergarten Reading and General Knowledge scale scores, parent rating gain scores were not included

in the multiple regression models.

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FACES 2000 Technical Report 11-21 March 06 
in a multiple logistic regression analysis. This approach was then repeated with the parent- and

teacher-reported behavior ratings. 

Children’s Scores on the FACES Instruments at the End of Head Start Predict

Repeating Kindergarten. When the subtest scores were combined in a multiple logistic regression

model, the model did quite well at predicting whether children repeated kindergarten, accounting for 20

percent of the variance in the prediction of repeating kindergarten. Information on scores from the 

FACES instruments led to an 81 percent accuracy rate in predicting whether or not a child was assigned 

by his or her teacher to repeat kindergarten. The strongest predictor of whether or not children were 

assigned by their teachers to repeat kindergarten was the Draw-A-Design task, in which for every unit 

increase in Draw-A-Design scores, children were 22 percent less likely to repeat kindergarten (Table 11-

20). 

Table 11-20. Summary of multiple logistic regression analysis for FACES assessment scores at end of 

Head Start predicting teacher decision to have child repeat kindergarten (N = 906) 

Assessment score B SE B Odds ratio 95 Percent confidence limit

PPVT-III -.02 .00 .981 .979 - .983 

WJR Applied Problems -.03 .00 1.004 1.003-1.005 

WJR Letter Word .00 .00 .975 .973-.976 

WJR Dictation -.01 .00 .989 .989-.990 

Social Awareness .16 .01 .864 .853-.875 

Draw-A-Design -.15 .01 .778 .766-.790 

Color Naming -.33 .00 .937 .933-.940 

One-to-One Counting .02 .01 .900 .887-.914 

Book Knowledge -.05 .01 .872 .858-.886 

Child’s Age at Head Start Assessment -.01 .00 .976 .973-.979 

Note: R2

Logit = .20 (p < .0001). Percent Concordant = 81 percent. All regression coefficients significant at p < .0001.

Children’s Behavior Ratings at the End of Head Start Predict Repeating Kindergarten.

When the teacher ratings were combined in a multiple logistic regression model, the model did well at 

predicting whether children repeated kindergarten, although not as well as the FACES assessment tasks, 

accounting for 6 percent of the variance in the prediction of repeating kindergarten. Information from the 

FACES teacher ratings led to a 66 percent accuracy rate in predicting whether or not a child was assigned

by his or her teacher to repeat kindergarten. The strongest predictor of whether or not children were 

assigned by their teachers to repeat kindergarten was parent ratings of withdrawn behavior, in which for

every unit increase in these parent ratings, children were 13 percent more likely to repeat kindergarten

(Table 11-21). 

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FACES 2000 Technical Report 11-22 March 06 
Table 11-21. Summary of multiple logistic regression analysis for teacher behavior ratings and parent 

behavior ratings at end of Head Start predicting teacher decision to have child repeat 

kindergarten (N = 926) 

Behavior rating B SE B

Odds 

ratio 

95 Percent 

confidence limit 

Teacher Reported Aggression -.01* .01 .987 .977-.997 

Teacher Reported Hyperactivity .10** .01 1.110 1.094-1.126 

Teacher Reported Withdrawal .12** .00 1.126 1.118-1.134 

Teacher Reported Cooperative Classroom Behavior -.04** .00 .964 .960-.969 

Parent Reported Aggression .10** .01 1.106 1.094-1.117 

Parent Reported Hyperactivity .02* .01 1.016 1.004-1.029 

Parent Reported Withdrawal .12** .01 1.128 1.109-1.147 

Parent Reported Positive Approaches to Learning .12** .01 1.122 1.111-1.134 

Child’s Age at Head Start Assessment -.04** .00 .966 .963-.968 

Note: R2

Logit = .06 (p < .0001). Percent Concordant = 66 percent. *p < .05; **p < .0001.

The Combination of Children’s Scores on the FACES Instruments and Behavior 

Ratings at the End of Head Start Predict Repeating Kindergarten. When the teacher ratings were

combined with the subtest scores from the FACES instruments in a multiple logistic regression model, the 

model did quite well at predicting whether children repeated kindergarten, accounting for 30 percent of 

the variance in the prediction of repeating kindergarten (Table 11-22). This is an increase of 10 percent in 

the variance that was explained by the subtest scores alone. Information from the combination of the 

FACES behavior ratings and the subtest scores led to an 82 percent accuracy rate in predicting whether or 

not a child was assigned by his or her teacher to repeat kindergarten. This suggests that the additional

information provided by the behavior ratings adds to the predictive validity of the FACES instruments in 

predicting kindergarten repetition. 

11.3 Conclusions 

The FACES measures have strong predictive validity with outcomes at the end of

kindergarten. As an indicator of preliteracy skills, the cognitive measures show strong associations with

reading ability at the end of the kindergarten year. As an indicator of school adjustment and social

competence, the behavior ratings demonstrate ability to predict kindergarten behaviors that promote 

learning. These analyses show that: 

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FACES 2000 Technical Report 11-23 March 06 
 The instruments used in FACES predict later behavior and performance in

kindergarten;

 The instruments used in FACES also predict whether a child gets promoted to first 

grade; 

 The instruments used in FACES may tap different types of abilities (“inside-out” vs.

“outside-in”) that are important for children’s future reading proficiency and academic

achievement; and 

 The multi-measure and multi-method approach to the measurement of children’s

abilities provides a variety of information sources that significantly contribute to the

prediction of kindergarten outcomes. 

Table 11-22. Summary of multiple logistic regression analysis for FACES assessment scores, teacher 

behavior ratings, and parent behavior ratings at end of Head Start predicting teacher decision 

to have child repeat kindergarten (N = 794) 

Assessment score/behavior rating B SE B Odds ratio 

95 Percent 

confidence limit 

PPVT-III -.03 .00 .968 .965-.970 

WJR Applied Problems .01 .00 1.007 1.006-1.008 

WJR Letter Word -.02 .00 .976 .974-.977 

WJR Dictation -.01 .00 .992 .991-.993 

Social Awareness -.17 .01 .847 .835-.860 

McCarthy Drawing -.26 .01 .768 .754-.781 

Color Naming -.07 .00 .932 .928-.936 

One-to-One Counting -.13 .01 .880 .866-.894 

Book Knowledge -.15 .01 .860 .845-.876 

Teacher Reported Aggression .01(ns) .01 1.005 .993-1.017 

Teacher Reported Hyperactivity .10 .01 1.110 1.091-1.131 

Teacher Reported Withdrawal .04 .00 1.038 1.028-1.047 

Teacher Reported Cooperative Classroom Behavior .00(ns) .00 1.003 .997-1.010 

Parent Reported Aggression .10 .01 1.108 1.095-1.122 

Parent Reported Hyperactivity -.02* .01 .983 .969-.998 

Parent Reported Withdrawal .19 .01 1.210 1.186-1.235 

Parent Reported Positive Approaches to Learning .22 .01 1.247 1.232-1.263 

Child’s Age at Head Start Assessment -.02 .00 .980 .977-.983 

Note: R2

Logit = .30 (p < .0001). Percent Concordant = 82 percent. All regression coefficients significant at p < .0001 except where indicated 

(*p < .05). 

Children who made greater gains during the Head Start year on the LWI, Dictation,

One-to-One Counting, Social Awareness, and the PPVT-III tasks tended to have greater early reading 

skills at the end of kindergarten. Children’s improved scores on the PPVT-III, Book Knowledge, and the

One-to-One Counting tasks at the end of Head Start were associated with greater General Knowledge 

scores at the end of kindergarten. These results suggest that children who show greater improvement in

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FACES 2000 Technical Report 11-24 March 06 
preschool show greater school readiness and school adjustment when they are preparing to enter first 

grade. 

In the assessment of children’s social competencies, the use of parent and teacher ratings

provides data on children’s behavior skills in different situations and provides a more comprehensive 

picture of their behavior. Equally important, both parent and teacher ratings significantly contribute to the 

prediction of social skills at the end of kindergarten. The parent and teacher ratings also significantly 

predict reading skills and general knowledge at the end of kindergarten. Ratings of problem behaviors 

were negatively correlated with kindergarten Reading and General Knowledge scale scores, suggesting

that behaviors that may impede learning are associated with lower reading skills in kindergarten. High

ratings of behaviors that enhance learning, positive approaches to learning and cooperative classroom 

behavior, were positively correlated with kindergarten outcomes. 

The multi-measure and multi-method approach to the measurement of children’s 

development and school readiness provides a comprehensive assessment of children’s abilities. The 

addition of the criterion-referenced measures to the norm-referenced measures improves the cognitive 

assessment battery in many ways. First, they are short tasks that cover more specific topic areas that are 

typically taught in preschool curricula and are also fun for the children to do in the assessment. And 

second, they significantly (although moderately) increase the measures’ ability to predict kindergarten 

outcomes, improving its predictive validity. The addition of the parent and teacher behavior ratings adds

another source of information that predicts kindergarten outcomes, namely an assessment of behaviors 

that can either foster or impede learning. They also provide some unique contributions to the battery’s 

ability to predict kindergarten outcomes, particularly in the practical decision of whether a child is

promoted to first grade or repeats kindergarten. 

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FACES 2000 Technical Report 11-25 March 06 
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FACES 2000 Technical Report R-8 March 06 
APPENDIX A 

METHODOLOGY 
A.1 Sample Design Overview

The Head Start children for FACES 2000 were selected as a two-stage sample. The first 

stage sampling units were Head Start programs; the second stage units were classes within sampled 

programs. In each sampled classroom, all children in their first year of Head Start were included in the 

sample. 

A.1.1 Programs 

The sampling frame of eligible Head Start programs was constructed from the 1998-1999

Program Information Report (PIR). Migrant and Seasonal Head Start programs, American Indian/Alaska

Native Head Start programs, Early Head Start programs, programs in the territories, and programs that do

not serve children directly were excluded, resulting in a frame of 1,675 programs. The programs were 

stratified by Census region (North East, Midwest, South, and West), percent minority (above/below 

50 percent), and metro or urban/rural status (Metropolitan Statistical Area (MSA)/non-MSA). These are 

the same stratification variables used in sampling programs for the FACES 1997 cohorts. 

A sample of 45 programs was selected for FACES 2000. The sample size in each stratum 

was proportional to the stratum first year Head Start enrollment. The programs were selected with 

probability proportional to the program’s first year enrollment using systematic sampling. The first year 

enrollment was calculated from the PIR by subtracting the reported second and third year enrollment from

the total enrollment. A Keyfitz procedure was used to minimize the overlap with the 40 programs

sampled for the FACES 1997 cohorts. As a result, there was no overlap with the previous program

sample. Of the 45 programs selected, two were later discovered to be ineligible because they had been

defunded, resulting in a total of 43 sampled programs for FACES 2000. 

A.1.2 Classrooms 

In the 43 remaining Head Start programs, lists of the anticipated classes for Fall 2000 were 

obtained in late Summer 2000. The programs also provided the expected number of first-year Head Start 

children in each class. 

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FACES 2000 Technical Report A-2 March 06 
These lists formed the basis for the classroom sampling frame, after excluding classes with

no first-year children. Classes with fewer than five first-year children expected were combined with 

another class in the same center to form a “class group.” The class groups were treated as a single unit for 

sampling purposes and sample size calculations. The total target sample size of first-year children was

2,825 or 66 per program. In general, the desired sample size of classes in each program was determined as 

66/(average class size for the program), where the average class size was in terms of the number of firstyear children. The actual initial sample size was increased by 2 classes to allow for a reserve sample in 

each program. In programs where the total first year enrollment, as obtained from the class rosters, was

more than twice the measure of size used to sample the program, the initial class sample size was 

increased to prevent large variation in class weights. In small programs where the initial sample size 

exceeded the number of classes available, all classes were taken with certainty. 

Classes were sorted by center within program and were sampled with equal probabilities. A 

subsample of the initial sample was selected with equal probabilities to obtain a main sample of the 

desired sample size and a reserve sample of two classes in each program. A total of 367 classes was

selected: 279 classes for the main sample and 88 for the reserve sample. The number of main sample

classes in each program varied from 3 to 15, with an average of 6 classes. (In terms of collapsed 

classrooms, a total of 252 classroom groups was sampled for the main sample and 82 for the reserve 

sample, for an average of 6 per program and a range of 3 to 10.)

In Fall 2000, the eligibility status of the main sample classes was determined. One or two

reserve classes were added in some programs to prevent a shortfall in the target number of first-year 

children for the study. The final sample for weighting purposes included all sampled classes where an

attempt was made to collect data from the classroom, including those discovered to be ineligible. The

rationale for this is because ineligible classes in the sample represent ineligible classes on the Head Start 

program frame. A total of 307 main and reserve classes were in the sample in Fall 2000. When the 

program was contacted by field staff in Fall 2000, 20 of the 307 classes were discovered to be ineligible

because they no longer existed, they did not receive Head Start funding, or they had no first-year Head 

Start children. In 286 of the remaining 287 eligible classes (one teacher refused to allow the children in 

her class to be sampled), all first-year Head Start children were taken into the sample. 

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FACES 2000 Technical Report A-3 March 06 
A.2 Response Rates 

 Fall 2000 

 2,508 Child assessments were completed out of 2,790 for a completion rate of 90 

percent; 

 2,488 Parent interviews were completed out of 2,790 families selected for the sample 

(89 percent); 

 Teacher Report forms were obtained on 2,532 of the 2,790 sample children (91 

percent); 

 Assessment, parent, and teacher data were obtained on 2,396 of the 2,790 sample

children (86 percent); and 

 A total of 278 classrooms were observed out of 286 in the sample for a completion 

rate of 97 percent. 

 Spring 2001

 2,232 Child assessments were completed out of 2,288, representing 98 percent of the 

children who remained in the program, and 80 percent of the original sample of 2,790

children; 

 2,166 Parent interviews were completed out of 2,288, representing 95 percent of the

children who remained in the program, and 78 percent of the original sample; 

 Teacher report forms were obtained on 2,236 of the sample children, representing 98 

percent of the children who remained in the program and 80 percent of the original

sample; 

 Assessment, parent, and teacher data were obtained on 2,115 of the 2,288 sample

children who remained in the program (92 percent); and 

 A total of 275 classrooms were observed out of 284 in the sample for a completion 

rate of 97 percent. 

A.3 Sampling Weights 

There are two main reasons why weights are desirable and are calculated for FACES data.

The most important reason for the use of weights is that all units generally do not have the same 

probability of selection. In FACES, probabilities of selection vary among sample programs, among 

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FACES 2000 Technical Report A-4 March 06 
sample centers, among sample classes, and among sample children. The first function of weights is to

reflect the probability of selection. For example, large programs were selected with higher probabilities 

than small programs, and large centers within a given program were selected with higher probabilities 

than small centers. Thus, probabilities of selection among centers vary considerably. If there tend to be 

differences in center characteristics according to the size of the center or the size of the program the 

center is in, then weighted estimates may be different from unweighted estimates. 

A second important reason for using weights is to reduce bias and sampling error. Inevitably,

there is some level of nonresponse in all surveys. Use of nonresponse adjustment factors in the weighting

process can reduce the bias caused by nonresponse. For example, there are differences in response rates in

FACES by gender of child. To the extent that there are also differences in test scores by gender, then 

forming nonresponse cells based on gender reduces the bias caused by differential gender response rates. 

Also, known population totals can frequently be used as poststratification controls in the weighting,

which reduces both bias and sampling error. Poststratification, however, has not been deemed feasible for

FACES. 

A.3.1 Program Weights 

The program weight was calculated as the inverse of the program’s probability of selection.

As mentioned earlier, a Keyfitz procedure was used to minimize the overlap with the program sample

drawn for FACES 1997. This procedure involved calculating conditional probabilities of selection which 

are based on whether the program was sampled previously or not, and whether its probability of selection

increased compared with the previous sample. Prior to sampling for the FACES 2000 cohort 3, the 

unconditional probability of selection for each program on the cohort 3 frame was calculated as 

where Nh is the number of programs on the frame in stratum h, NEWSMPSZh is the sample size for

stratum h for the cohort 3 design, and FIRSTYRi is the first year enrollment for program i from the PIR.

The probability of selection for each program under the Abt sample design for Cohorts 1 and 2 was also

calculated as

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FACES 2000 Technical Report A-5 March 06 
where Nh was the number of programs on the Abt frame in stratum h, was the sample size

for stratum h under the Abt design, and 

SAMPSIZEh

ENRTOTi was the total enrollment for the i-th program from an 

earlier PIR. 

The conditional probability of selection was calculated for each program on the cohort 3

frame according to the Keyfitz procedure as: 

 Case 1: NEWPSEL ≥ 1 – ORIGPSEL

CONDPROB = 

NEWPSEL (1 ORIGPSEL)

ORIGPSEL

− − if the program was sampled 

for cohorts 1 and 2, 

= 1 if the program was not sampled for cohorts 1 and 2.

 Case 2: NEWPSEL < 1 – ORIGPSEL

CONDPROB = 0 if the program was sampled for cohorts 1 and 2, 

= 1-

NEWPSEL

ORIGPSEL

 if the program was not sampled for 

cohorts 1 and 2. 

These conditional probabilities of selection were the measures of size used to select the 

cohort 3 program sample. It can be shown that the Keyfitz procedure preserves the unconditional cohort 

3 program probabilities of selection, while at the same time minimizing the overlap. Thus the cohort 

3 program weight is the inverse of NEWPSEL, the unconditional probability of selection under the cohort 

3 design. 

All 43 eligible programs cooperated with the study, so that nonresponse adjustments at the 

program level were unnecessary.

For each program, a set of 43 jackknife replicate weights was created for calculating 

standard errors. The replicate weights were created using a standard stratified jackknife procedure. One 

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FACES 2000 Technical Report A-6 March 06 
program at a time was dropped (i.e., given a zero replicate weight) and the weights of the remaining 

programs in the same stratum were adjusted by a factor of nh (nh −1) , where nh is the number of 

sampled programs in stratum h. The program weights in the other strata were left unchanged. By 

repeating it 43 times, 43 replicate weights were obtained for each program. For estimates involving child

or classroom data from all 43 programs, the degrees of freedom for the variance of the estimate is

#PSUs - #varstrat = 43 – 12 = 31. (One of the 13 original sampling strata was collapsed with an adjacent

stratum for variance estimation purposes because it contained only one eligible sampled program.) 

A.3.2 Classroom Weighting 

Two sets of class weights were produced for classroom level estimation: one set for 

Fall 2000 cross-sectional estimates and a second set for Fall 2000–Spring 2001 longitudinal classroom

analysis. Class base weights were first created that reflected the overall probability of selection for the 

class, including the program probability of selection. These base weights were adjusted for classroom 

level nonresponse, using the following criteria for a complete classroom: 

Fall 2000 Cross-Sectional Estimates. Classroom must have complete Fall 2000 observation 

data. Classroom observation data includes counts of children and adults, Assessment Profile 

(Scheduling, Learning Environment, and Individualizing), ECERS-R, Arnett Caregiver 

Interaction Scale, Teacher-Directed Activities Checklist and Wrap-Up measures; and 

Fall 2000–Spring 2001 Longitudinal Analysis. Classroom must have complete observation 

data for either Fall 2000 or Spring 2001 and child assessment data for both Fall 2000 and

Spring 2001.

A.3.2.1 Class Base Weights 

A class base weight was created for each of the 367 initially sampled classes in Fall 2000.

Fifty-four reserve classes that were never used were given base weights of zero. Six main sample classes

were sampled out on an ad hoc basis by field staff to reduce burden and to have independence between

classes. They were assigned base weights of zero, since they were not part of the final sample. In this

situation, a teacher had both a morning and an afternoon class in the sample. One class out of the

morning/afternoon pair was subsampled. 

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FACES 2000 Technical Report A-7 March 06 
The remaining 307 classes considered to constitute the sample were each assigned a class 

base weight equal to the inverse of their overall probability of selection. The overall probability of 

selection is the product of the program probability of selection and the probability of selecting the class 

within the program. The inverse of the overall probability of selection can also be written as the product 

of the program weight and the within-program class weight: 

Class Base Weight = Program Weight * (Total # Classes in Program / # sampled classes fielded). 

Collapsed classrooms were counted as one classroom in the base weight calculations, since 

they were treated as a single unit in sampling. The ad hoc subsampling was reflected by multiplying the

base weight of the retained class in the am/pm pair by a factor of 2 and the dropped class by zero. One 

class that had merged with another was given a zero base weight, and the newly merged class had its base

weight multiplied by a factor of .5 to reflect its increased probability of selection. 

Forty-three jackknife class replicate base weights were created from the program replicate 

weights: 

Class Replicate Base Weight j = Program Replicate Weight j * (Total # Classes in Program /

# sampled classes fielded); j = 1, 2, ...43. 

A.3.2.2 Cross-Sectional Fall 2000 Class Weights 

Of the 307 sampled classes that were fielded in Fall 2000, 279 were eligible and had 

complete classroom data, 8 were eligible but didn’t complete data collection, and 20 were discovered to

be ineligible. A class nonresponse adjustment factor was applied to the class base weights of the 279. The 

nonresponse adjustment factor was computed separately by program. Both the 8 incomplete and the 20

ineligible classes were given a zero final class weight. The classroom replicate base weights were also

adjusted for nonresponse by program, so that the sampling variability in the nonresponse adjustments 

were reflected in the standard error estimates. 

The sum of the nonresponse-adjusted Fall 2000 classroom weights is 34,638. The 

unweighted and weighted completion rates are both 97 percent, excluding ineligibles from both numerator 

and denominator. The unweighted and weighted eligibility rates are both 94 percent. The class base 

weight was used in calculating the weighted rates. 

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FACES 2000 Technical Report A-8 March 06 
A.3.2.3 Longitudinal Fall 2000–Spring 2001 Class Weights 

Of the 286 eligible classes in Fall 2000, 280 completed data collection in Spring 2001. Note

that the 279 Fall 2000 classroom completes are not a subset of the 280 Spring 2001 completes. Five

classes that completed Fall 2000 data collection did not complete the Spring 2001, and six classes that 

completed Spring 2001 data collection did not complete the Fall 2000. There were 79 new classes added 

in Spring 2001 because children who switched classes after the Fall 2000 data collection were followed to

the new class. However, no classroom observations were done at these new classes, so they were not

considered to be part of the classroom sample and were assigned a zero base weight. 

A class nonresponse adjustment factor was applied to the class base weights of the 280 

eligible completes. The nonresponse adjustment factor was computed separately by program. The 

classroom replicate base weights were also adjusted for nonresponse by program, so that the sampling 

variability in the nonresponse adjustments were reflected in the standard error estimates. The incomplete 

and ineligible classes, along with the 79 new classes, were given a final class weight of zero. 

The sum of the nonresponse-adjusted Fall 2000 – Spring 2001 classroom weights is 34,768.

The unweighted and weighted completion rates are both 98 percent, excluding ineligibles from both

numerator and denominator. Both unweighted and weighted eligibility rates are 94 percent. The class base

weight was used in calculating the weighted rates. 

A.3.3 Child Weights 

Three sets of child weights were produced: a cross-sectional set for Fall 2000 estimates, a

Fall 2000 – Spring 2001 set for base year longitudinal analyses, and a Fall 2000 – Spring 2003 set for

longitudinal analysis including the kindergarten school year. Child base weights were first created that

reflected the overall probability of selection for the child, including the program and classroom stages of

sampling. These base weights were adjusted for child nonresponse, using the following criteria for a

complete child case: 

Fall 2000 Cross-Sectional Analysis. A child is considered a complete case if the child has a

parent interview from either a Fall 2000 or Spring 2001 and a Fall 2000 child assessment or

teacher rating;

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FACES 2000 Technical Report A-9 March 06 
Fall 2000 – Spring 2001 Longitudinal Analysis. A child is considered a complete case if

the child has either a Fall 2000 or Spring 2001 parent interview and one of the following

data pairs: a child assessment for both Fall 2000 and Spring 2001, or a teacher rating for 

both Fall 2000 and Spring 2001; and 

Fall 2000 – Spring 2003 Longitudinal Analysis. A child is considered a complete case if

there was at least one parent interview, an assessment while the child was in Head Start,

either in Fall 2000 or Spring 2001, and an assessment while the child was in kindergarten, 

either Spring 2002 or Spring 2003. 

A.3.3.1 Child Base Weights 

In 286 eligible Fall 2000 classes, all eligible children in their first year of Head Start were

included in the sample with certainty. A base weight was created for each child as the product of their

program weight and nonresponse-adjusted classroom weight. Note that these nonresponse adjusted class 

weights are not the same as those described earlier, which were designed for use in classroom level

analyses. The creation of special classroom weights for the child weights was necessary because there

were eligible classrooms that did not have complete classroom observations, but did allow their children 

to be sampled, and vice versa. To create this special classroom weight, the classroom base weight was

adjusted for classes which had eligible children but where “sampling” of children did not take place. This 

nonresponse-adjusted classroom weight was then used in calculating the child base weight. Since there 

was no subsampling of children within classrooms, the within-classroom child weight is equal to one and 

the overall child weight can be written as: 

Child Base Weight = Program Weight * Nonresponse-adjusted Classroom Weight. 

A set of 43 jackknife (JKn) replicate base weights was also created for each child using the

program replicate weights and the special full-sample nonresponse-adjusted classroom weight: 

Child Replicate Base Weight j = Program Replicate Weight j * Nonresponse-adjusted

Classroom Weight; j = 1, 2, ...43. 

A.3.3.2 Child Fall 2000 Cross-Sectional Weights 

Of the 3,100 children in the Fall 2000 sample, 2,535 were considered complete for the 

Fall 2000 data collection, 251 were eligible but incomplete (30 of these had assessments but no parent 

interview), and 314 were ineligible. Children could be ineligible if either they came from classrooms that

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-10 March 06 
were ineligible or they were discovered to be in their second year of Head Start or were otherwise 

ineligible when Fall 2000 data collection began. 

The child base weights of the eligible, complete children in each classroom were adjusted for

nonresponse separately by classroom. The ineligible and incomplete children were given a zero final child 

weight and were dropped from the sample for the Spring 2001 data collection. The replicate child base 

weights were also adjusted for nonresponse by classroom, so that the sampling variability in the

nonresponse adjustments were reflected in the standard error estimates. 

The sum of the nonresponse-adjusted Fall 2000 child weights is 337,247. The unweighted

and weighted completion rates are both 91 percent, excluding ineligibles from both the numerator and

denominator. The unweighted and weighted eligibility rates are 90 percent and 91 percent, respectively.

The child base weight was used in calculating the weighted rates. 

A.3.3.3 Child Fall 2000 – Spring 2001 Longitudinal Weights 

In Spring 2001, the eligible first-year children were again given assessments, a teacher

rating, and an attempt was made to interview the child’s parent(s). Of the 2,535 eligible children who had

completed Fall 2000 data collection, 2,359 were eligible, complete cases for the Fall 2000 – Spring 2001

data collection; 171 were eligible, incompletes; and five became ineligible because they moved out of the 

area. 

Children who had switched to new classes in the Spring 2001 were followed up, but 

classroom observations were not done at the new classes. There were 91 children from the Fall 2000 

sample who were followed to 79 new classrooms in Spring 2001. In calculating their base weights, these

children were given the classroom probability of selection associated with the classroom from which they

were originally sampled in Fall 2000. 

The child base weights of the eligible, complete children in each classroom were adjusted for

nonresponse separately by classroom. The ineligible and incomplete children were given a zero final child 

weight. The replicate child base weights were also adjusted for nonresponse by classroom, so that the

sampling variability in the nonresponse adjustments will be reflected in the standard error estimates. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-11 March 06 
The sum of the nonresponse-adjusted Fall 2000 – Spring 2001 child weights is 338,047. The

unweighted and weighted conditional Spring 2001 completion rates are both 93 percent. The conditional

rate is the percent of Fall 2000 eligible completes who also completed the Spring 2001 data collection. 

The overall (unconditional) completion rate is the product of the completion rates for the Fall 2000 and

Spring 2001 data collections: 91 percent * 93 percent = 85 percent. This rate is the percent of eligible, 

sampled children in Fall 2000 that completed the Spring 2001 data collection. 

A.3.3.4 Child Fall 2000 – Spring 2003 Longitudinal Weights 

For the year in which the children were in kindergarten, either Spring 2002 or Spring 2003,

the children were again given assessments, a teacher rating, and an attempt was made to interview the

child’s parent(s). No classroom observations were done for these children. Of the 2,535 eligible children 

who had completed Fall 2000 data collection, 1,895 were respondents again for kindergarten data 

collection, either Spring 2002 or Spring 2003, and 640 were nonrespondents. 

The child base weights of the eligible, responding children in each classroom were adjusted

for nonresponse separately by classroom. Classrooms were collapsed within centers and within programs 

when necessary to prevent excessively large nonresponse adjustment factors. The ineligible and 

nonresponding children were given a zero final child weight. The replicate child base weights were also

adjusted for nonresponse by classroom.

The sum of the nonresponse-adjusted Spring 2002-2003 child weights is 337,247. The

unweighted completion rate is 68 percent, i.e., 68 percent of eligible sampled children were Spring 2002-

2003 (kindergarten) respondents. The weighted completion rate is 69 percent. 

A.4 Variance Estimation 

Estimates obtained from the FACES sampled children will differ from the true population 

parameters because they are based on a randomly chosen subset of the population, rather than on a

complete census of all Head Start children. This type of error is known as sampling error or variance. The 

precision of an estimate is measured by the standard error (defined as the square root of the variance). The

calculation of the standard error must reflect not only the sample size on which the estimate is based, but

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-12 March 06 
the manner in which the sample was drawn. Otherwise, the standard errors can be misleading and result in 

incorrect confidence intervals and p-values in hypothesis testing. The FACES sampling involved

stratification, clustering, and unequal probabilities of selection, all of which must be reflected in the 

standard error calculations. 

Jackknife replication is a commonly used variance estimation method for complex surveys

involving multi-stage sampling (Wolter, 1985). Replication methods work by dividing the sample into

subsample replicates that mirror the design of the sample. A weight is calculated for each replicate using

the same procedures as for the full-sample weight. This produces a set of replicate weights for each

sampled child. To calculate the standard error of a survey estimate, the estimate is first calculated for each 

replicate using the replicate weight and the same form of estimator as for the full sample. The variation 

among the replicates is then used to estimate the variance for the full sample estimate. Replication has the 

advantage that it can reflect the different features of the weighting and estimation by simply repeating all

steps separately for each replicate. 

For each child, a set of 40 jackknife replicate weights was created for calculating standard 

errors. The replicate weights were created using a standard stratified jackknife (“JKn”) procedure. One 

Head Start program at a time was dropped (i.e., given a zero replicate weight) and the weights of children 

in the remaining programs in the same stratum were adjusted by an inflation factor to account for the

reduction of the sample. The weights in the other strata were left unchanged. By repeating this for each of

the 40 sampled programs, 40 replicate weights were obtained for each child. The replicate weights are

used in the formula below to calculate the variance: 

∑=

− − =

G

g

g

h

h

n

n

v

1

2

( ) ) ˆ ˆ (

1 )ˆ (θ θ θ

where is the estimate of θ based on the observations included in the g-th replicate (i.e., using the g-th 

replicate weight), is the estimate of θ based on the full sample, G is the total number of replicates 

formed, n

( ) ˆθ g

θ

ˆ

h is the number of programs in stratum h, and (nh -1)/nh is the “JKn” factor. When creating a var 

file in WesVar, the JKn factors must be imported using the “Attach Factors” option in the Data menu. For 

estimates involving data from all 40 programs, the degrees of freedom for the variance of the estimate is #

programs - # strata = 40 – 10 = 30. (Six of the original 14 sampling strata were collapsed for variance

estimation purposes because they contained only one eligible sampled program, resulting in 10 pseudo 

strata.) 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-13 March 06 
A.5 Data Collection Instruments 

A.5.1 Direct Child Assessment 

The child assessment was an essential component of FACES. It provided direct measures of

how well Head Start programs were achieving the goals of assisting children to be physically, socially,

and educationally ready for success in kindergarten. The assessment battery was composed of a short 

series of tasks that were feasible and interesting for preschoolers and kindergartners to carry out, and that 

have been shown to be predictive of later school achievement or learning difficulties. The areas of the 

FACES assessment battery included vocabulary development, emerging literacy (recognizing letters of 

the alphabet, hearing similarities in the sounds at the beginnings or ends of different words, showing

familiarity with printed words and story books), emerging numeracy (counting, adding, or taking away 

blocks to show a given number), perceptual-motor development (drawing copies of simple geometric 

figures), and social and communicative competence (telling basic facts about self and family to another

person). These tasks were drawn or adapted from well-established and widely used instruments. 

A Spanish version of the assessment battery was also developed for assessing children 

whose primary language was Spanish. Spanish versions of the measures, when available, (e.g., Test de

Vocabulario en Imagenes Peabody, Woodcock-Muñox Pruebas de Aprovechamiento-Revisada) were 

employed in the Spanish battery. Otherwise, the English versions of the measures (e.g., one-to-one 

counting, social awareness, color names, etc.) were directly translated. 

A screener was used to determine whether English-language learners were to be administered

the direct child assessment battery in English or not. The screener involved information provided by teachers

and assessors which was used to determine the language of administration. In Fall 2000, English-language 

learners who were determined to be primarily Spanish-speaking received the entire direct child assessment

battery in Spanish, e.g., TVIP, Woodcock Munoz Letter-Word Identification, Applied Problems, Dictation, 

etc. They also were administered the PPVT and Woodcock Johnson Letter-Word Identification in English, as

well. In Spring 2001 and Spring 2002 (for children who were in Head Start for 2 years), these same children 

received the entire direct child assessment battery in English. They were also administered the TVIP and 

Woodcock Munoz Letter Word Identification in Spanish for the purpose of comparison. The children who 

had been administered assessments in Spanish and English in Fall 2000, with some Spanish sections, in

Spring 2001 and Spring 2002 (Head Start only) were administered the entire assessment in English during the 

Spring of their kindergarten year (either Spring 2002 or Spring 2003). 

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FACES 2000 Technical Report A-14 March 06 
In Fall 2000, English-language learners who were determined to primarily speak a language 

other than Spanish did not receive any portion of the direct child assessment battery in their native languages

and were assessed in English, if possible. In Spring 2001, Spring 2002, and Spring 2003 (if applicable), these 

same children received the entire direct child assessment battery in English, if possible. 

Norm Referenced Cognitive Tests 

In these assessment tasks, norms are available for a nationally representative sample of U.S. 

children of the same age (including children from all family income groups). Average scores, factoring in 

the age of the children, a.k.a. standard or scale scores, are reported throughout this report. However, most

of the results detailed in Appendix A. Tables A-2 through A-18 are for raw scores only. These standard 

scores are adjusted for the child’s age and constructed to have an overall mean and standard deviation of

specific values, e.g., a mean of 100 and a standard deviation of 15. This is useful for comparing children 

from Head Start programs to other children on a nationwide basis on specific school readiness measures 

to determine the growth and progress of these Head Start children in these domains relative to all others in 

the nation. 

A.5.1.1 Peabody Picture Vocabulary Test – Third Edition – Revised 

The Peabody Picture Vocabulary Test (PPVT-III) (Dunn and Dunn, 1997) is designed to 

assess children's knowledge of the meaning of words by asking them to say or indicate by pointing which 

of four pictures best shows the meaning of a word that is said aloud by the assessor. A series of words is 

presented, ranging from easy to difficult for children of a given age, each accompanied by a picture plate

consisting of four line drawings. The test takes about 10 minutes to administer. It is suitable for a wide

range of ages from 21⁄2 through adulthood and has established age norms based on a national sample of 

2,725 children and adults tested at 240 sites across the U.S. 

The PPVT-III has been extensively revised from earlier versions of the test. These 

improvements were undertaken to promote easier testing and more accurate scoring. Also, new drawings 

have been added and dated illustrations dropped so as to achieve better gender and ethnic balance. 

Individual test items that showed statistical bias by race or ethnicity, gender, or region were deleted from 

the item pool for the scale prior to standardization. 

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FACES 2000 Technical Report A-15 March 06 
PPVT-III scores have high reliability, with the test publisher reporting internal-consistency 

reliability (alpha) coefficients ranging from .92 to .98, with a median of .95, and test-retest reliability

ranging from .91 to .94. The alpha coefficients for the PPVT-III results from FACES were .97 for Fall 

2000, Spring 2001, Spring 2002/2003 (Kindergarten), and .96 for Spring 2002 (Head Start). 

A Spanish-language test, the Test de Vocabulario en Imagenes Peabody (TVIP), is also 

available, but has not been updated to be directly comparable to the PPVT-III. For FACES, the TVIP was 

used with children whose primary language was Spanish. The TVIP was reported to be highly reliable 

utilizing FACES data with internal-consistency alpha coefficients of .92 for both Fall 2000 and Spring 

2001, and .94 for Spring 2002 (Head Start). 

A.5.1.2 Woodcock-Johnson Psycho-Educational Battery – Revised 

The updated edition of the Woodcock-Johnson Battery (WJ-R) is a carefully constructed and 

widely used test battery. The set of individually administered tests is designed to assess the intellectual

and academic development of individuals from preschool through adulthood (Woodcock and Johnson, 

1989; Salvia and Ysseldyke, 1991). FACES used three subtests from the Achievement Battery that 

together constitute an "Early Development -- Skills" cluster, according to the test developers. The cluster 

is comprised of the Letter-Word Identification, Applied Problems, and Dictation tests. The same three

subtests of the Spanish version (Woodcock-Muñox Pruebas de Aprovechamiento-Revisada) were used in 

the Spanish version of the FACES assessment battery. 

Letter-Word Identification. The first five Letter-Word Identification items involve 

symbolic learning, or the ability to match a rebus (pictographic representation of a word) with an actual 

picture of the object. The remaining items measure children's reading identification skills in identifying

isolated letters and words that appear in large type on the pages of the test book. As well as being part of

the Early Development cluster, this subtest is also part of the Basic Reading Skills cluster. The internal 

reliability of the Letter-Word Identification subtest with preschool age children averages .92 (Woodcock 

and Johnson, 1989). The internal reliability of this subtest with FACES children averaged .84 for Fall 

2000, and .86 for Spring 2001 and Spring 2002 (Head Start). The internal reliability of the Spanish 

version of this subtest (Woodcock Munoz) was .75 for Fall 2000, .78 for Spring 2001, and .83 for Spring

2002 (Head Start). 

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FACES 2000 Technical Report A-16 March 06 
Applied Problems. This subtest measures children's skill in analyzing and solving practical 

problems in mathematics. In order to solve the problems, the child must recognize the procedure to be 

followed and then perform relatively simple counting, addition or subtraction operations. Because many

of the problems include extraneous stimuli or information, the child must also decide which data to

include in the count or calculation. As well as being part of the Early Development cluster, the subtest is 

also part of a Broad Mathematics cluster. The internal reliability of the Applied Problems subtest with 

preschool age children averages .91 (Woodcock and Johnson, 1989). The internal reliability of this

subtest with FACES children averaged .90 for Fall 2000, .91 for Spring 2001, .89 for Spring 2002 (Head 

Start), and .88 for Spring 2002/2003 (Kindergarten). The internal reliability of the Spanish version of this

subtest (Woodcock Munoz) was .85 for Fall 2000. 

Dictation. The first six items in this subtest measure prewriting skills, such as drawing lines 

and copying letters. The remaining items measure the child's skill in providing written responses when 

asked to write specific upper- or lower-case letters of the alphabet. Later parts of the test ask the child to 

write specific words and phrases, punctuation, and capitalization. The internal reliability of the Dictation 

subtest with preschool age children averages .90 (Woodcock and Johnson, 1989). The internal reliability

of this subtest with FACES children averaged .77 for Fall 2000, Spring 2001, and Spring 2002/2003

(Kindergarten), and .71 for Spring 2002 (Head Start). The internal reliability of the Spanish version of 

this subtest (Woodcock Munoz) was .77 for Fall 2000. 

A.5.1.3 Leiter International Performance Scale – Revised (Leiter-R) – Attention Sustained 

The Leiter-R by Roid and Miller (1997) assesses cognitive function in children and 

adolescents. The battery includes measures of nonverbal intelligence in fluid reasoning and visualization, 

as well as appraisals of visuospatial memory and attention. In Spring 2001, the Leiter-R Attention

Sustained (AS) Subtest was added to the FACES direct child assessment battery to permit assessments of

children’s visuospatial memory and attention. The subtest is primarily nonverbal and is administered in 

two subsections – the first being for those 2-3 years of age and the second being for those 4-5 years of

age. Assessors provide minimal instructions throughout the administration of the Leiter-R AS. Children 

are presented with a series of pages containing pictures and are instructed to mark off all pictures that

resemble a reference picture. The assessor times the child, with times ranging from 30 seconds to 120 

seconds allotted for completion of the tasks. The internal reliability of the Leiter-R Attention Sustained

subtest for 2-3 year olds and 4-5 year olds is .83 (Roid and Miller, 1997). The internal reliability of this 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-17 March 06 
subtest with FACES children, by age groupings, averaged .71 for 3 year olds and .81 for 4-5 year olds in

Spring 2001 and .80 for 4-6 year olds in Spring 2002 (Head Start). 

A.5.1.4 Test of Language Development (TOLD) – Primary – 3rd Edition – Phonemic Analysis

(Kindergarten Only) 

The Phonemic Analysis test from the Test of Language Development (TOLD; Newcomer 

and Hamill, 1997) is a supplemental subtest designed to assess children’s awareness of phonemes, that is,

the significant speech sounds that comprise words. For this test, the child is presented with a compound 

word, and then asked to repeat part of the word’s component phonemes back to the assessor (e.g., “Say

‘popcorn.’ Now say it again without ‘pop’.”) The internal reliability of this supplemental subtest with

FACES children averaged .96 for Spring 2002/2003 (Kindergarten). 

A.5.1.5 ECLS-K Reading and General Knowledge Scales (Kindergarten Only) 

In the Early Childhood Longitudinal Study-Kindergarten cohort (ECLS-K), the Reading 

scale taps a variety of skills that indicate reading ability (including familiarity with print), recognition of

letters and phonemes, vocabulary, and reading comprehension skills (e.g., children’s understanding of the

text), as well as their personal reflection and critical evaluation of the text. The General Knowledge scale

taps skills in the natural sciences (e.g., their conceptual understanding of why things occur as they do, and 

their ability to pose questions and investigate answers in the natural sciences) and social studies (e.g., 

their basic knowledge of History, Government, and Culture). Both scales follow the guidelines of the 

1996 National Assessment of Educational Progress, have been reviewed by curriculum experts, as well as

elementary school teachers, and have been found to be both reliable and valid measures of reading 

achievement and basic knowledge acquisition.1

The Reading assessment was administered in two stages. First, a routing test was

administered to estimate the child's reading ability. Based on his/her performance on the routing test 

(either “high,” “medium,” or “low”), an appropriate “second stage” test was administered. The Reading 

assessment had three levels of second stage tests: low (red), medium (yellow), and high (blue). For the 

1

 For more information on the Reading and General Knowledge measures, please refer to the Early Childhood Longitudinal Study website at

http://nces.ed.gov/ecls/. 

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FACES 2000 Technical Report A-18 March 06 
General Knowledge assessment, each child was administered only the routing test. Estimates of reliability 

with FACES data, as measured by Cronbach’s coefficient alpha, were as follows: 1.) for Reading –

Spring 2002/2003 (Kindergarten) – Routing = .87, Red (Low Form) = .95, Yellow (Middle Form) and 

Blue (High Form) = .94, and 2.) for General Knowledge – Spring 2002/2003 (Kindergarten) = .77. 

Criterion Referenced Cognitive Tasks 

These tasks cover areas of basic knowledge, verbal, mathematical, and perceptual-motor 

skills that children typically learn in the preschool and kindergarten years and are often included in 

assessments of children’s school readiness and progress. These tasks do not have national norms. All

results referenced in Table A-2a through A-3c and throughout the entire Report for these Tasks pertain to 

raw scores. 

A.5.1.6 McCarthy Scales of Children’s Abilities 

The McCarthy Scales of Children's Abilities is a widely used and well-documented test

battery. FACES employed one subtest from the battery, the Draw-A-Design Task. The Draw-A-Design

Task was used to assess children's perceptual-motor skills. This task asks the child to draw copies of a 

series of increasingly complex geometric figures. For FACES, this task was directly translated as part of 

the Spanish version of the assessment. The FACES reliabilities for the McCarthy Draw-A-Design

measure were .58 for Fall 2000, .70 for Spring 2001, and .72 for Spring 2002 (Head Start). The FACES 

reliability for the Spanish version of this measure for Fall 2000 was .57. 

A.5.1.7 Story and Print Concepts 

The Story and Print Concepts task was an adaptation of earlier prereading assessment 

procedures developed by Marie Clay (1979), William Teale (1988, 1990), and Mason and Stewart (1989). 

In these procedures, a child is handed a children’s storybook (FACES Battery - Where’s My Teddy?

(Alborough, 1992) or ¿Dónde Está Mi Osito? (Alborough, Castro, Trans. 1992)) upside down and 

backwards. The assessor asks a series of questions designed to test the child's knowledge of books. These 

include questions regarding the location of the front of the book, the point at which one should begin 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-19 March 06 
reading, and information relating to the title and author of the book. The assessor reads the story to the 

child and asks basic questions about both the mechanics (print conventions) of reading and the content

(comprehension) of the story. The print conventions questions pertain to children's knowledge of the leftto-right and up-and-down conventions of reading, while the comprehension questions pertain to children's 

recall of key facts from the story. Additionally, for FACES, questions were added tapping rhyming 

awareness (e.g., "I'll say some words from the story and you tell me whether they rhyme, OK - bawl and

small, etc.") and phonological awareness (e.g., "What word would be left if I took “teh” away from

Ted?"). These additions were only included in the Fall 2000 direct child assessment battery. The FACES

reliabilities for Fall 2000, Spring 2001, and Spring 2002 (Head Start) were as follows: Book Knowledge 

(.57, .59, and .61); Print Conventions (.73, .75, and .84); and Comprehension (.43, .42, and .40). The

reliabilities for the Spanish version of these measures for Fall 2000 were .43 – Book Knowledge, 

.59 - Print Conventions, .39 – Comprehension. 

A.5.1.8 Social Awareness 

This measure was adapted from a subtest of the Comprehensive Assessment Program (CAP) 

Early Childhood Diagnostic Instrument used by Snow et al. (1995) among others to test children’s

general knowledge and awareness of the social environment. The child is asked to give his/her “full 

name,” which includes both first and last name, his/her age (either verbally, which is given full credit or 

by holding up the correct number of fingers, which is given partial credit) and month/day of birth. The

FACES reliabilities for the Social Awareness measure were .63 for Fall 2000, .62 for Spring 2001, .62 for 

Spring 2002 (Head Start), and .65 for Spring 2002/2003 (Kindergarten). The FACES reliability for the

Spanish version of the Social Awareness measure for Fall 2000 was .36. 

A.5.1.9 Color Names and One-to-One Counting 

This was also a subtest of the CAP Early Childhood Diagnostic Instrument used by 

Snow et al. (1995) and developed by Marie Clay (1979), William Teale (1988, 1990) and Mason and

Stewart (1989) as a battery of emergent literacy and school readiness measures. For the FACES battery, 

10 teddy bears of different colors are presented randomly arranged on a page and the child is asked to

point to each in turn and name the color. Following the Color Names task, the child is asked to count the 

bears and the assessor marks the final number the child arrives at when finished counting (correct answer 

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FACES 2000 Technical Report A-20 March 06 
is “10”). After this, the child is asked to report the total number of bears. The verbatim response is then

recorded. Following these questions, the assessor must rate the child’s one-to-one counting performance 

using a 5-point scale. At the extremes, a score of 5 indicated that the child made no mistakes and score of

1 indicated that the child could not count or did not try to count. The FACES reliabilities for the Color 

Naming task were .95 for Fall 2000, .94 for Spring 2001, and .90 for Spring 2002 (Head Start). The 

FACES reliability for the Spanish version of the Color Naming task for Fall 2000 was .92. 

A.5.1.10 Writing Name (Kindergarten Only) 

The Writing Name task was designed to assess the child’s ability to write his or her first or 

last name correctly. 

A.5.1.11 Interviewer Ratings 

At the end of the one-on-one testing sessions with the children, the assessor completes a set

of rating scales evaluating the child’s behavior in the test situation, including the child’s approaches to 

learning and problem behaviors. There are two sections to these ratings. The first consists of eight scales

rating the child’s response during the assessment on eight different domains: task persistence, attention 

span, body movement, attention to directions, comprehension of directions, verbalization, ease of

relationship, and the child’s level of confidence. Ratings use 4-point scales with descriptive anchors at

each point. For example, the “task persistence” scale consists of the following anchor points: persists with 

task (4), attempts task briefly (3), attempts task after much encouragement (2), refuses (1). The FACES

reliabilities for the Interviewer Ratings were .82 for Fall 2000, .80 for Spring 2001, .70 for Spring 2002 

(Head Start), and .75 for Spring 2002/2003 (Kindergarten). The FACES reliability for the Spanish version

of the Interviewer Ratings for Fall 2000 was .77. 

The second section asks the assessor to indicate any special concerns regarding the child’s 

ability to complete the assessment: responding nonverbally, using nonstandard English such as dialect, 

speaking English as a second language, having limited English proficiency, experiencing difficulty

hearing or seeing the assessor/test materials, or reporting the child’s speech was difficult to understand. 

These items use 3-point ratings to indicate the degree to which the child displayed any of these

characteristics (i.e., “not at all,” “somewhat,” and “very much”). 

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FACES 2000 Technical Report A-21 March 06 
Table A-1 summarizes the modifications to the assessment battery from the Fall 2000

through the Spring 2002-2003 kindergarten followup.

A.5.2 Classroom Observation Instruments

In FACES 2000, quality was considered to include not only the number of children and

adults in each classroom, but process factors such as the availability of learning materials, the types of 

classroom activities, scheduling and the variety of learning opportunities provided to all children. Lead 

teachers2

 in Head Start classrooms were also interviewed to collect teacher background information 

(experience and qualifications) as well as more detailed information about their curriculum, classroom 

activities, and attitudes and knowledge about early childhood education practices. 

A.5.2.1 Counts of Children and Adults, Child-Adult Ratio 

The Counts of Children and Adults provide information needed to calculate child-adult 

ratios and for other calculations to be used in assessing specific measures of classroom quality. Classroom

observers counted the number of children, the number of adults and the number of paid staff at two

separate time periods during the classroom day. The two occasions were separated by at least one hour

and involved one structured (teacher-directed) and one unstructured activity. The child-adult ratio is 

calculated as the average number of children per adult (both paid and volunteer) across the two

observations. A related measure, the child-staff ratio, was calculated using only the number of paid staff

across the two observations. Higher child-adult or child-staff ratios are indicative of lower quality. 

A.5.2.2 Assessment Profile for Early Childhood Programs: Research Edition I 

The Assessment Profile for Early Childhood Programs: Research Edition I (Abbott-Shim 

and Sibley, 1987) is a structured observation guide designed to provide a quantitative assessment of

classrooms and teaching practices that facilitate the learning and development of children. Three

subscales were used in FACES: Scheduling, Learning Environment, and Individualizing. 

2

 The results of teacher data presented in this chapter were based on interviews and ratings of the lead or senior teacher in each classroom.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-22 March 06 
FACE

 

Table A-1. Summary of measures administered from Fall 2000 through Spring 2003 

Fall 2000 

(Head Start) 

Spring 2001 and Sprin

g

2002 

(Head Start) 

Spring 200

(kin

Social Awareness Social Awareness Social Awareness PPVT-III / TVIP PPVT-III / TVIP PPVT-III McCarthyDraw-A-Design 

McCarthyDraw-A-Design 

TOLD – Primary -3Phonemic Analysis 

Color Names and Counti

n

g Leiter-R AS 

(Attention Sustained) Subset 

Reading ECLS-K Routing an

Woodcock Johnson R (Munoz): Letter-Word Identification 

Color Names and Counti

n

g Woodcock Johnson 

Applied Problems

Woodcock Johnson R (Munoz): Applied Problems

Woodcock Johnson R (Munoz): Letter-Word Identification 

Woodcock Johnson Dictation 

Woodcock Johnson R (Munoz): Dictation 

Woodcock Johnson R: Applied Problems

Writing Name 

Story and Pri

nt Concepts Woodcock Johnson R: 

Dictation 

General Kno

wledge 

ECLS-K Routing 

Interviewer Rating: Assessment Behavior 

Story and Pri

nt Concepts Interviewer Rating: 

Assessment Behavio

Interviewer Rating: Assessment Behavior 

___________________________________________________________________________________________________________________________________

S 2000 Technical Report A-23 March 06 
The Scheduling subscale assesses the written plans for classroom scheduling and how

classroom activities are implemented. The appropriateness and completeness of the classroom activity

plan are also noted. The subscale also assesses the balance and variety of learning contexts (e.g., 

individual, small group, and large group) and learning opportunities (i.e., child- vs. teacher-directed and 

active vs. quiet activities). The 14 observation items are scored in a yes/no format. High scores on this 

measure are indicative of a teacher that uses a “planful” approach to classroom activities. The reliability

of the Scheduling subscale was reported as .89 for Fall 2000, .87 for Spring 2001, and .82 for Spring 2002 

(Head Start).

The Learning Environment subscale focuses on the accessibility of a variety of learning 

materials to children in the classroom. Variety is assessed across various conceptual areas, such as

science, math, language, fine motor, etc. and also within each conceptual area. The subscale also assesses 

how classroom space is arranged to determine whether the classroom encourages independence (e.g., 

whether the learning materials are located on low shelves and clearly labeled) and reflects the child as an

individual. When materials are both available and accessible, and in sufficient numbers (typically a

minimum of three in each group), the item is given a positive score. High scores on this 7-item measure 

indicate a “learning rich” environment filled with toys and learning materials that address a variety of 

developmental domains. The reliability of the Learning Environment subscale was reported as .68 for 

Fall 2000, .77 for Spring 2001, and .65 for Spring 2002 (Head Start). 

The Individualizing subscale is based on a scale from the Assessment Profile for Early 

Childhood Programs. For FACES 2000 it was shortened to five observational items measuring whether

the teacher plans classroom activities to meet the varying learning needs of each child, how the teacher

keeps track of the children's work during the year through the use of individual child portfolios and 

whether the teacher accommodates children with disabilities through an inclusionary approach. A high

score indicates that teachers are able to adjust classroom activities to meet the learning needs of individual 

children. The reliability of the Individualizing subscale was reported as .50 for Fall 2000, .54 for Spring 

2001, and .44 for Spring 2002 (Head Start). 

A.5.2.3 Early Childhood Environment Rating Scale – Revised (ECERS-R) 

The Early Childhood Environment Rating Scale (ECERS) is a global rating of classroom 

quality based on structural features of the classroom (Harms and Clifford, 1980). It has been widely used

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-24 March 06 
in child development research and has predicted optimal child outcomes in a number of studies (e.g., 

Phillips, Voran, Kisker, Howes, and Whitebook, 1994). The revised version of the ECERS (ECERS-R) 

provides improvements to the items and allows for a more standardized approach to assigning scores. In 

addition, the ECERS-R is easier to train on and gain inter-rater reliability. The ECERS-R contains 37 

items representative of classroom quality. Each item is coded on a 7-point scale with a score of 1

representing “inadequate”, a score of 3 representing “minimal quality,” a score of 5 representing “good 

quality,” and a score of 7 representing “excellent quality.” The internal consistency of the ECERS-R 

mean score for all combined items was .92 for both Fall 2000 and Spring 2001, and .89 for Spring 2002

(Head Start).

The ECERS-R items were grouped into seven subscales for usage in analyses of FACES

classroom quality, each pertaining to different elements of classroom quality.

3

 These are as follows: 

 Personal Care Routines are measured using six items: greeting/departing, 

meals/snacks, nap/rest, toileting/diapering, health practices, and safety practices;

 Furnishings is measured using four items: indoor space, furniture for routine care,

play, and learning, furniture for relaxation and comfort, and room arrangement for 

play; 

 Language Skills are measured using four items: books and pictures, encouraging 

children to communicate, using language to develop reasoning skills, and informal use 

of language; 

 Motor Skills are measured using four items: space for gross motor play, gross motor 

equipment, fine motor activities, and supervision of gross motor activities; 

 Creativity is measured using six items: child-related display, art, music/movement,

blocks, sand/water, and dramatic play; 

 Social Skills are measured using four items: supervision other than gross motor 

activity, discipline, staff-child interactions, and interactions among children; and 

 Program Structure is measured using four items: space for privacy, schedule, free

play, and group time.

3

 It should be noted that these subscales do not correspond to the subscales and item groupings developed by the instrument developer.

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-25 March 06 
Five items were not incorporated into any of the subscales which are as follows:

nature/science, math/numbers, use of TV, video, and/or computers, promoting acceptance of diversity, 

and provisions for children with disabilities. Thus there were only 32 of the 37 available items included in 

the subscales.

The Language Skills subscale was used as a key classroom quality measure in many of the 

analyses, and also contributed to the Quality Factor score (described in Chapter 4). Devised to assess the 

quality of the language environment in Head Start classrooms, a high score indicates a classroom with a 

rich language environment, in terms of the availability and use of books and printed materials, receptive 

and expressive language activities, language to engage logical and reasoning skills, and the informal use 

of language throughout the classroom day. 

A.5.2.4 Classroom Observation of Teacher – Directed Activities 

The Classroom Observation of Teacher-Directed Activities is a checklist completed by 

classroom observers of observed teacher-directed activities in 21 specific areas, e.g., reading stories, 

singing songs, etc. The classroom observer indicates whether observed activities were directed toward 

individual children (Individual Attention), a small group of children (Small Group = 3 to 8 children), or a 

whole group of children (Whole Group = entire classroom). Observers were instructed to mark down,

only once for any item, any teacher-directed activities observed throughout the course of the classroom 

observation and whether these observed activities were directed toward individuals, a small group of 

children, or the entire classroom. This checklist was introduced in Spring 2001.

A.5.2.5 Arnett Caregiver Interaction Scale 

The Arnett Caregiver Interaction Scale (Arnett, 1989) is a rating scale of teacher behavior 

towards the children in the classroom. The Arnett Caregiver Interaction Scale consists of 30 items and

five subscales labeled Sensitivity, Harshness, Detachment, Permissiveness, and Independence. At the end

of the observational period, the observer completes the scale for an individual teacher, typically the lead 

teacher in the classroom. For example, in evaluating whether the teacher “speaks warmly to the children,”

the observer will assign a rating indicating the extent to which the statement is characteristic of the 

teacher, from 1 “never seen” to 4 “always or almost always.” A high score indicates greater teacher 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-26 March 06 
sensitivity, responsiveness and encouragement of children’s independence and self-help skills, and lower

levels of punitiveness and detachment. The Cronbach Coefficient Alphas for all of the items were .94 for 

both Fall 2000 and Spring 2001, and .93 for Spring 2002 (Head Start). 

A.5.2.6 Teacher Backgrounds, Qualifications, and Attitudes 

The Lead Teacher Background Information is based on individual interviews with the

lead teacher of the classrooms that were being observed. The interviews collected extensive information 

about the teachers’ backgrounds (e.g., age, ethnicity), experience (e.g., total years teaching, years teaching

Head Start), and qualifications (e.g., whether the teacher has a BA or AA, whether the teacher had a

graduate degree or some graduate school education, whether the teacher has a Child Development

Associate certificate, teaching certificate, or whether the teacher took any early childhood education or 

development courses). Ethnicity was included in these analyses because it may be related to differences in 

teacher qualifications and experience and because the types of teachers in the classrooms may be

influenced by the backgrounds of the families and children attending the Head Start program as well as 

the larger community served by the program.

4

 There were also questions about the nature of the 

curriculum used, the training and resources provided to support the curricula used, as well as questions 

about how teachers monitor the progress of individual children, and what accommodations the teacher

makes to meet the learning needs of each student, including those with special needs. 

The 24-item Teacher Beliefs Scale (Burts, Hart, Charlesworth, and Kirk, 1990) was included

in the teacher interview, and consists of statements worded to reflect positive attitudes and knowledge of 

generally accepted practices in preschool settings, or to reflect a lack of these attitudes and knowledge. In 

FACES 2000, one factor comprising 9 items that explained most of the variation in scores for the entire

scale was used. A high score indicates higher positive attitudes and knowledge about early childhood

education practices. 

4

 While age was also included in the teacher interview, it was so highly correlated with the teacher’s years of experience that it was not included 

in analyses beyond the descriptive level. However, since ethnicity did prove to be related to other factors in classroom quality, we continued to

include it in our analyses. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-27 March 06 
A.5.2.7 Quality Composite 

As a result of principal components analyses of the quality measures, several of the 

measures–the ECERS-R Language subscale, the Assessment Profile Scheduling subscale and the 

Assessment Profile Learning Environment subscale–were found to be highly correlated with each other, 

suggesting that a greater amount of variation in quality can be explained by reducing these three quality 

indicators to one measure. Additional principal components analyses which included other quality 

measures (e.g., the Arnett Caregiver Interaction Scale, the child:adult ratio and even the ECERS-R total

score) found that these measures did not add significantly to the explained variation and in some cases 

may have detracted from it. Thus, these other quality measures were used independently in the analyses of 

classroom quality. Scores from the three measures that formed the quality composite were combined to 

form a single factor score for quality. A higher score indicates higher levels of quality.

A.5.3 Teacher's Child Reporting Form 

Teacher ratings of children were important sources of information about children’s learning

and behavior because teachers see children over extended periods of time and in a variety of settings. 

Using a rating form known as the Teacher's Child Report (TCR), teachers were first asked to rate each

child on a set of behaviors that assessed the child’s basic social skills and classroom behavior. In these 

two sections, the teacher is asked to indicate the extent to which a given statement (e.g., “follows the 

teacher’s directions”) is characteristic of the child, from 1 “never” to 3 “very often.” The items making up

these ratings form two scales. 

A.5.3.1 Cooperative Classroom Behavior 

There are 12 ratings items for the teacher to indicate how often the child engages in

cooperative classroom behaviors such as following teacher’s directions, helping put things away, 

complimenting classmates, and following rules when playing games. The ratings include items drawn

from the Personal Maturity Scale (Alexander and Entwisle, 1988) and the Social Skills Rating System 

(Elliott, Gresham, Freeman, and McCloskey, 1988) to assess positive behavior such as cooperation, 

sharing, and expression of feelings. A summary score is created from the 3-point scale items with a range

from 0 to 24, with high scores indicating more frequent cooperative behavior. The internal consistency for 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-28 March 06 
this measure was .88 for Fall 2000, Spring 2001, and Spring 2002/2003 (Kindergarten), and .87 for 

Spring 2002 (Head Start). 

A.5.3.2 Total Behavior Problems

The Behavior Problems scale is based on measures of negative child behaviors that are

associated with learning problems and later grade retention. Items come from an abbreviated adaptation 

of the Personal Maturity Scale (Alexander and Entwisle, 1988), the Child Behavior Checklist for 

Preschool-Aged Children, Teacher Report (Achenbach, Edelbrock, and Howell, 1987) and The Behavior 

Problems Index (Zill, 1990). The items ask about the frequency of aggressive behavior (e.g., hits/fights 

with others), hyperactive behavior (e.g., is very restless), and anxious or depressed and withdrawn 

behavior (e.g., is unhappy). The summary score from the scale’s 14 behavior items ranges from 0 to 28, 

with higher scores representing more frequent or severe negative behavior. 

The Total Problem Behavior items were grouped into three subscales for usage in analyses 

of children’s behavior, each pertaining to different types of problem behavior: Aggressive, Hyperactive, 

and Withdrawn behavior. The Aggressive behavior subscale, comprised of four items, assesses the

frequency of disobeying rules or requests, disrupting ongoing activities, hitting or fighting with others, 

and having temper tantrums. The Aggressive behavior scale score ranges from 0 to 8, with higher scores 

representing more frequent or severe aggressive behavior. The Hyperactive behavior subscale, comprised

of three items, assesses the frequency of being unable to concentrate or pay attention for long; being

nervous, high strung, or tense; and being very restless. The Hyperactive behavior scale score ranges from 

0 to 6, with higher scores representing more frequent or severe hyperactive behavior. The Withdrawn 

behavior subscale, comprised of seven items, assesses the frequency of acting too young for age; being 

hard to understand; keeping to self; lacking confidence in learning new things or trying new activities;

often seeming sleepy or tired in class; often seeming unhappy, sad, or depressed; and worrying about 

things for a long time. The Withdrawn behavior scale score ranges from 0 to 14, with higher scores 

representing more frequent or severe withdrawn behavior. 

The reliabilities (internal consistency) for these measures for Fall 2000, Spring 2001, Spring 

2002 (Head Start), and Spring 2002/2003 (Kindergarten) were as follows: Total Problem Behaviors - .86,

.86, .87, and .86; Aggressive behavior - .83, .85, .83, and .85; Hyperactive behavior - .72, .72, .75, and 

.74; and Withdrawn behavior - .77, .76, .76, and .77. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-29 March 06 
The teacher is then asked to rate the child's problem solving skills and initiative, social 

relationships, creative representations, music/movement skills, and language/math skills. The teacher is

asked to rate the child’s highest level of behavior in each of the above domains observed in the past week. 

Scale points for each item are described on paper and there is a glossary that provides concrete examples

of each anchor point. For the purpose of FACES, 14 items from the Child Observation Record (COR;

High/Scope Educational Research Foundation, 1992) were selected with a demonstrated reliability of .94 

for both Fall 2000 and Spring 2001, and .93 for Spring 2002 (Head Start). These 14 items were further 

divided into the following scales: social relationships, creative representations, music and movement, and 

cognitive. 

A.5.3.3 Social Relationships (3 Items) 

A composite score was based on teacher’s ratings of how well the child makes friends, 

works with other children, and understands and expresses feelings. Each item is rated on a five-point scale 

with higher scores representing greater skill in coping with social situations and expressing feelings 

appropriately. The summary score is the average of the three items and ranges from one to five. The 

measure shows good reliability with the FACES study, with Alpha Coefficients of .83 for both Fall 2000 

and Spring 2001, and .80 for Spring 2002 (Head Start). 

A.5.3.4 Creative Representations (3 Items) 

A composite score was based on the teacher’s ratings of how well the child uses creative

materials for self-expression in making and building things, drawing and painting, and engaging in 

pretend play. Each item is rated on a five-point scale with higher scores representing greater proficiency.

The summary score is the average of the three items and ranges from one to five. The measure shows 

good reliability with the FACES study, with Alpha Coefficients of .80 for both Fall 2000 and Spring 2002

(Head Start), and .81 for Spring 2001. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-30 March 06 
A.5.3.5 Music and Movement (4 Items) 

A composite score was based on teacher’s ratings of how well the child can imitate

movements to a steady beat, follow music and movement directions, exhibit body coordination, and

manipulate small objects and perform precise actions. Each item is rated on a five-point scale with higher

scores representing greater proficiency. The summary score is the average of the four items and ranges

from one to five. The measure shows good reliability with the FACES study, with Alpha Coefficients of 

.88 for both Fall 2000 and Spring 2001, and .86 for Spring 2002 (Head Start). 

A.5.3.6 Cognitive (4 Items) 

A composite score was based on teacher’s ratings of how well the child can solve problems,

engage in complex play, show interest in reading, and exhibit classification skills by sorting objects. Each

item is rated on a five-point scale with higher scores representing greater proficiency. The summary score

is the average of the four items and ranges from one to five. The measure shows good reliability with the 

FACES study, with Alpha Coefficients of .82 for Fall 2000, .83 for Spring 2001, and .80 for Spring 2002 

(Head Start).

A.5.4 Parent Interview 

Data from the FACES Parent Interview, administered in Fall 2000, Spring 2001, Spring

2002, and Spring 2003, provide Head Start with a comprehensive understanding of the families it serves 

or served, including the characteristics of households and household members, levels and types of 

participation in the program and in other community services, involvement with their children, and 

understanding of their children's development. 

Parents were also asked to rate their child on a set of behaviors that assessed the child’s basic

social skills and behavior problems. In this section, the parent is asked to indicate the extent to which a

given statement (e.g., “makes friends easily”) is characteristic of the child, from 1 “not true” to 3 “very

true or often true.” The items making up these ratings were drawn from two well-known measures of

children's positive behavior and behavior problems: the Entwisle Scale of Personal Maturity (Entwisle,

Alexander, Cadigan, and Pallis, 1987) and the Child Behavior Checklist for Preschool-Aged Children 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-31 March 06 
(Achenbach, Edelbrock, and Howell, 1987). Two scales were formed to assess children’s social

competence. 

A.5.4.1 Social Skills and Positive Approaches to Learning 

Parents were asked to rate their child’s social skills and positive approaches to learning by 

describing their children’s skills in making friends and accepting their ideas, as well as enjoying learning 

and trying new things. A summary score based on the scale’s seven items ranges from 0 to 14, with 

higher scores representing more positive behavior. Tables A-23 through A-30 show the reliabilities for

the Social Skills measure for Fall 2000, Spring 2001, and Spring 2002 (Head Start), and Spring 

2002/2003 (Kindergarten). 

A.5.4.2 Total Problem Behaviors 

Parents were also asked to rate their children on negative behaviors that are relatively 

common among preschool children and that are associated with adjustment problems in elementary

school. Parents were asked about three domains of problem behavior: hyperactive behavior, aggressive 

behavior, and depressed or withdrawn behavior. The 12 behavior items were combined in a summary

score ranging from 0 to 24, with higher scores representing more frequent or severe negative behavior. 

The 12 total problem behavior items were grouped into three subscales for usage in analyses 

of children’s behavior, each pertaining to different types of problem behavior: Aggressive, Hyperactive, 

and Withdrawn behavior. The Aggressive behavior subscale, comprised of four items, assesses the

frequency of having temper tantrums, hitting or fighting with others, not getting along with other kids, 

and being disobedient at home. The Aggressive behavior scale score ranges from 0 to 8, with higher 

scores representing more frequent or severe aggressive behavior. The Hyperactive behavior subscale,

comprised of three items, assesses the frequency of being unable to concentrate or pay attention for long; 

being very restless; and being nervous, high strung, or tense. The Hyperactive behavior scale score ranges

from 0 to 6, with higher scores representing more frequent or severe hyperactive behavior. The

Withdrawn behavior subscale, comprised of five items, assesses the frequency of being unhappy, sad, or 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-32 March 06 
_______________________________________________________________________________________________________________________________

FACE

 

____

S 2000 Technical Report A-33 March 06 A.5.4.3 Other Parent Interview Scales/Measures Referenced in the Report Other parent interview scales/measures referenced in the report are listed below. Names and sources for other parent interview scales/measures referenced in the report Name Source Descripti

Pearlin Mastery Scale (Locus of Control) Pearlin, L.I. and Schooler, C. (1978). The structure of coping. Journ

al of Health 

and 

Social Behavi

or, 22, 337-356. 

Seven items measured the degree to whiover their own lives and their self-confidlife’s problems. 

CES-D Depression Scale Radloff, L.S. (1977). The CES-D: A selfreport depression scale for research in the 

general population. Applied Psychological Measurement, 1, 385-401.

Twelve items measured levels of depres

Family Activities with Children National Household Education Survey - 

FACES Research Team 

Eleven items asked respondents to indicas telling a story; teaching letters, wordsgoing on errands) were undertaken b

y t

h

children in the past week. Another set of indicate which types of outings, such as mall, they participated in with their child

Parental Involvement in Head Start 

Head Start Q

uality Research Consortium

(QRC) 

Asked in the Spring parent interview, 15 how often the

y participated in various ac

classroo

m, prepared food or materials fo

Head Start center. 

Exposure to Violence FACES Research Team Five items tapped the extent that the resp

violent crime in his/her neighborhood or 
_______________________________________________________________________________________________________________________________

FACE

 

Names and sources for other parent interview scales/measures referenced in the report 

Name Source Descripti

Do

mestic Violence Screener Feldous, K.M., Koziol-McLain, J., 

A

msbury, H.L. et. al. (1997). Accuracy of 

three brief screening questions for detecting partner violence in the emergency room. JAMA, 227(1

7), 1357. 

Three ite

ms ask the respondent to indica

victim of domestic violence, and whethevictim or wit

ness of domestic violence. 

Substance Abuse Screener Ad

ministration for Children and Families 

(1997). National Impact Evaluation of t

he 

Co

mprehensive Child Development 

Program. Washington, DC: U.S. Department of Health and Hu

man Services. 

Three items ask the respondent to indicamember of the household, who uses alcointo trouble with family or friends, has gor has missed work or school because of items were asked for drug use if there is uses drugs. 

Involvement with Criminal Justice System 

FACES Research Tea

m Three ite

ms ask the respondent to indica

household member have been arrested othe child was born; and whether he/she/atime in jail. 

Parenting Style National Lon

gitudinal Stu

d

y of Youth 

(NLSY), Early Head Start Evaluation (EHS), QRC 

Parents were also asked to rate a series othey were raising their child at home. Fothat assesses whether the parent had an aThree state

ments form a scale that asses

authoritarian parenting style. 

____

S 2000 Technical Report A-34 March 06 
depressed; worrying about things for a long time; and feeling worthless and inferior. The Withdrawn

behavior scale score ranges from 0 to 10, with higher scores representing more frequent or severe

withdrawn behavior. 

Tables A-23, A-27, and A-28 show the reliabilities for both parent and teacher reported 

behavior problem measures for Fall 2000, Spring 2001, Spring 2002 (Head Start), and Spring 2002/2003 

(Kindergarten). 

A.6 Field Staff Training 

A weeklong training was conducted prior to each data collection period to prepare field staff

for successful completion of data collection. The field staff members consisted of experienced,

professionally trained staff working for the FACES data collection efforts. The training included a wide

variety of activities covering all the procedures, techniques, and contents required to carry out successful

data collection in the Head Start centers, over the telephone, and elsewhere, e.g., homes: 

 Lecture, incorporating slides, overheads, and videotapes; 

 Exercises that simulate various procedures such as assessing classroom scheduling; 

 Video demonstration of assessment techniques and components of classroom scoring 

procedures; 

 Exercises to achieve pre-established levels of inter-rater reliability; 

 Participatory involvement of all trainees in small groups so that trainers may evaluate 

individual performance; 

 Multiple occasions of practice in real classroom settings that simulate what they are 

expected to do in the field, with the presence of a trainer and a small group of trainees 

to discuss the classroom ratings and provide valuable guidance on scoring reliability 

and agreement; and 

 One-on-one practice and role-play in the administration of child assessment

procedures under supervision of training staff. 

The field procedures manual contained information about working with a research team, 

appropriate behaviors within Head Start classrooms and children’s homes, and how to orchestrate Head 

Start center or other visits. Moreover, the manual covered an overview of all data collection instruments 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-35 March 06 
and administrative procedures. Complete scoring rules and question-by-question specifications for the

child assessment, parent interviews, and classroom observation instruments were also discussed in the 

manual. 

During the training, trainees were introduced to the purpose and goals of the study and 

provided background information on Head Start. Trainees were also introduced to the data collection 

materials and general issues regarding children and early childhood learning environments. Each day of 

training included a question and answer period. For administering child assessments in Spanish, a special

training for English-Spanish speaking bilingual trainees was held. The bilingual trainees had an 

opportunity to practice assessments with Spanish-speaking children. 

A.7 Data Collection Procedures 

A.7.1 Site Visit Arrangements 

The FACES research team obtained feasible dates for the 2-week site visit from each of the 

sampled Head Start programs. Site visit dates for each program were coordinated within the data

collection period and programs were notified about the visit dates. Three weeks before the site visit, a 

scheduling packet which contained the final visit schedule, a list of sampled children by classroom, a

reminder list, and a request for maps and directions to aid the research team was sent to the on-site

coordinator (OSC). OSC’s are members of the Head Start program staff specially designated to 

coordinate the data collection efforts by scheduling parent interviews, classroom visits with teachers and

obtaining consent forms. 

When a sampled child was a kindergartner (either Spring 2002 or Spring 2003), a field staff 

member would contact the parent(s), in advance, to arrange for a time to conduct the Parent Interview 

over the telephone. An arrangement also would be made for conducting the child assessment at a location

chosen by the parent(s), usually the home. If the Parent Interview could not been conducted over the 

telephone, for whatever reasons, the field staff member would try to administer the Parent Interview

during the visit to conduct the child assessment. Teacher-Child Report and Lead Teacher questionnaires 

would be sent to the child’s school to be filled out and returned by the child’s lead teacher. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-36 March 06 
A.8 Quality Control Visits 

In FACES, Quality Control (QC) visits were built into every step of the data collection to

ensure the highest quality data possible. The QC visitors consisted of the FACES research project staff 

who had been involved in designing the instruments, preparing the training materials, and conducting the

training. The QC visitors were trained in both observation and assessment data collection and also served 

as technical consultants in the field. During the Fall 2000 data collection, one 3-day QC visit to several 

selected program sites was made. 

A.9 Data Preparation and Data File Creation 

A.9.1 Data Entry 

Key entry and verification were performed on the study instruments using a sophisticated

production data entry system. This system provides entry form layout, application of edit specifications, 

data verification control, and provides data entry quality and production reports. 

A.9.2 Frequency Review 

The frequencies of responses to all data items (both individually and in conjunction with 

related data items) were reviewed to ensure that appropriate skip patterns were followed. Members of the 

data preparation team checked each item to make sure the correct number of responses was represented

for all items. If a discrepancy was discovered, the problem case was identified and reviewed. 

A.9.3 Data Edit 

To code and edit questionnaire data, an integrated collection of software was utilized. 

Through this system of software, coding manuals and codebooks were developed, data editing was 

performed, and SAS source code was generated. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-37 March 06 
A.9.4 Data file Creation 

Data files were created and analyses performed to provide summaries and assessments of 

Head Start children and their families during this period and to assess the reliability and validity of 

information contained within the data collection instruments. Numerous derived variables were created to 

increase the magnitude and scope of analytical capabilities. The coding for these derived variables may be

obtained upon request. 

A.10 Reliability and Data Summary 

In FACES, various data collection instruments were used to assess the accomplishments and

behaviors of children in Head Start programs, as well as the educational and familial support that is

provided to them. As noted in Section IV: Data Collection Instruments, these instruments are widely used 

and report mostly high reliabilities. The reliabilities for each data collection instrument and summaries for

these data collection instruments are provided in the Appendix A Table A-2 through Table A-30. 

___________________________________________________________________________________________________________________________________

FACES 2000 Technical Report A-38 March 06 
_______________________________________________________________________________________________________________________________

FACE

 

Table A-2. Reliability of Fall 2000 FACES child assessment data—English language and Spanish language assessments 

Fall 2000 (E

n

glish language assessments) Fall 2000 (S

panish 

Scales 

Nu

mber of 

items

Nu

mber of 

cases 

Cronbach 

alphas 

Nu

mber of 

items

Nu

m

c

Social Awareness 5 2,068 .63 5 PPVT-III*1 144 2,508 .97 - 

TVIP* - - - 125 McCarthy: Draw-A-Desig

n 9 2,068 .58 9 

Color Names 10 2,055 .95 10 WJR: Letter-Word Identification*† 23 1,273 .84 - 

WM: Letter-Word Identification* - - - 18 WJR: Applied Problems* 23 1,054 .90 - WM: Applied Problems* - - - 23 WJR Dictation* 12 1,054 .77 - WM: Dictation* - - - 12 Story and Pri

nt Concepts: Print 

Conventions 2 2,116 .73 2 Story and Pri

nt Concepts: Book 

Knowledge 5 2,116 .57 5 Story and Pri

nt Concepts: Co

mprehension

2 2,116 .43 2 

Interviewer Rating: Assessment Behavior 8 2,021 .82 8 

* Raw scores were used.

1 For Fall 2000, Spanish-speaking English Language Learners were ad

ministered the PPVT-III in English and their results are incorporated with those of other child

(English Language Assess

ments).

† For Fall 2000, Spanish-speaking English Language Learners were ad

ministered the WJR: Letter-Word Identification in English and their results are incorporated 

reflected under Fall 2000 (

English Language Assess

ments).

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S 2000 Technical Report A-39 March 06 
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FACE

 

Table A-3. Reliability of Spring 2001 and Spring 2002 (Head Start) FACES child assessment data—English language ass

additional Spanish language measures for Spanish-speaking English language learner children 

Fall 2000 (E

n

glish language assessments) Fall 2000 (S

panish 

Scales 

Nu

mber of 

items

Nu

mber of 

cases 

Cronbach 

alphas 

Nu

mber of 

items

Nu

Social Awareness 5 2,304 .62 5 PPVT-III* 144 2,344 .97 144 TVIP*1 125 364 .92 125 

McCarthy: Draw-A-Desig

n 9 2,298 .70 9 

Leiter-R AS – Age 3 4 406 .71 - Leiter-R AS - Ages 4 to 5 4 1,763 .81 - Leiter-R AS - Ages 4 to 6 - - - 4 Color Names 10 2,298 .94 10 WJR: Letter-Word Identification* 23 1,902 .86 23 WM: Letter-Word Identification*† 18 307 .78 18 

WJR: Applied Problems* 23 1,902 .91 23 WJR Dictation* 12 1,902 .77 12 Story and Pri

nt Concepts: Print Conventions 2 2,344 .75 2 

Story and Pri

nt Concepts: Book Knowledge 5 2,344 .59 5 

Story and Pri

nt Concepts: Co

mprehension 2 2,344 .42 2 

Interviewer Rating: Assessment Behavior 8 2,254 .80 8 

* Raw scores were used.

1 For Spring 2001 and Spring 2002 (

Head Start), Spanish-speaking English Language Learners were ad

ministered the T

VIP in Spanish to gauge progress in Spanish 

from earlier data collection periods.

† For Spring 2001 and Spring 2002 (Head Start), Spanish-speaking English Language Learners were ad

ministered the W

M: Letter-Word Identification in Spani

____

letter/word knowledge from earlier data collection periods. 

S 2000 Technical Report A-40 March 06 
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FACE

 

Table A-4. Reliability of Spring 2002/2003 (kindergarten) FACES child assessment data—English language assessments 

Spring 2002/2003 (kindergarten) 

Scales Nu

mber of items Nu

mber of cases Cro

Social Awareness 7 1,833 PPVT-III* 204 1,913 TOLD – Pho

nemic Analysis 14 1,913 

Reading – E

CLS-K Routing* 20 1,913 

Red (Low Form)* 18 1,913 Yellow (Middle Form)* 29 1,913 Blue (High Form)* 29 1,913 

WJR: Applied Problems* 31 1,912 WJR: Dictation* 20 1,912 Writing Name 1 Not Applicable NoGeneral Kno

wledge – ECLS-K Routing** 16 1,913 

Interviewer Rating: Assessment Behavior 8 1,816 

*Raw scores were used. **Scale scores were used. 

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S 2000 Technical Report A-41 March 06 
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FACE

 

Table A-5. Summary statistics for Fall 2000 FACES child assessment data—English language and Spanish language asse

Fall 2000 (E

n

glish language assessments) Fall 2000 (S

panis

Scales 

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean S

Social Awareness 2,101 3.36 1.69 0 - 6 0 - 6 390 2.62 1PPVT-III*1 2,379 31.86

18.4

2 0 - 98 0 - 144 - - - 

TVIP* - - - - - 369 11.3

4 8

McCarthy: Draw-A-Desig

n 2,112 2.92 1.33 0 - 13 0 - 19 392 3.37 1

Color Names 2,101 11.3

2 7.37 0 - 20 0 - 20 386 8.90 6

WJR: Letter-Word Identification*2 1,144 5.13 2.49 0 - 21 0 - 23 - - - WM: Letter-Word Identification* - - - - - 195 4.37 1WJR: Applied Problems* 963 7.52 4.36 0 - 21 0 - 23 - - - WM: Applied Problems* - - - - - 200 5.29 3WJR: Dictation* 916 5.11 1.83 0 - 12 0 - 12 - - - WM: Dictation* - - - - - 188 4.99 1Story and Pri

nt Concepts: Print 

Conventions 2,089 0.23 0.57 0 - 2 0 - 2 391 0.17 0Story and Pri

nt Concepts: Book Knowledge 2,087 1.62 1.27 0 - 5 0 - 5 376 1.25 1

Story and Pri

nt Concepts: Co

mprehension 2,102 0.54 0.70 0 - 2 0 - 2 386 0.47 0

Interviewer Rating: Assessment Behavior 2,094 17.14 5.02 0 - 24 0 - 24 383 17.54 4

* Raw scores were used.

1 See Table Note 1 under Table A-2a.2 See Table Note 2 under Table A-2a.

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S 2000 Technical Report A-42 March 06 
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FACE

 

Table A-6. Summary statistics for Fall 2000 and Spring 2001 FACES child assessment data—children who were assessed 

both Fall and Spring 

Fall 2000 Spring 2001 

Scales

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Repo

respo

rang

PPVT-III* 1,811 35.23 17.73 0 – 98 0 – 144 1,811 45.80 18.62 3 – WJR: Letter-Word Identification* 839 5.32 2.60 0 – 21 0 – 23 839 7.26 3.35 0 – WJR: Applied Problems* 867 7.58 4.35 0 – 21 0 – 23 867 10.4

7 4.65 0 – 

WJR: Dictation* 805 5.13 1.84 0 – 12 0 – 12 805 6.36 2.11 0 – McCarthy: Draw-ADesign 1,925 2.93 1.34 0 – 13 0 – 19 1,925 3.54 1.70 0 – Story and Pri

nt Concepts: 

Book Knowledge 1,886 1.63 1.28 0 – 5 0 – 5 1,886 2.43 1.30 0 Story and Pri

nt Concepts: 

Co

mprehension 1,906 0.54 0.70 0 – 2 0 – 2 1,906 0.72 0.75 0 

Story and Pri

nt Concepts: 

Print Knowledge 1,895 0.24 0.58 0 – 2 0 – 2 1,895 0.38 0.70 0 Social Awareness 1,904 3.38 1.69 0 – 6 0 – 6 1,904 4.01 1.57 0 Color Names 1,904 11.38 7.38 0 – 20 0 – 20 1,904 15.69 5.89 0 – One-to-One Counting 1,859 2.52 1.24 1 – 5 1 – 5 1,859 3.27 1.38 1 Interviewer Rating: Assessment Behavior 1,878 17.13 5.03 0 – 2

4 0 – 2

4 1,878 19.1

2 4.31 0 – 

*Raw scores were used.

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S 2000 Technical Report A-43 March 06 
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FACE

 

Table A-7. Summary statistics for Fall 2000 and Spring 2001 FACES child assessment norm-referenced data—children 

assessed in English in both Fall and Spring

Fall 2000 Spring 20

Scales

Nu

mber of 

cases Mean SD 

Nu

mber of 

cases Mean 

PPVT-III Standard Score 1,811 85.36 14.69 1,811 89.4WJR: Letter-Word Identification Standard Score 837 92.3

9 9.39 837 92.6

WJR: Applied Problems Standard Score 863 88.1

6 15.2

9 863 89.3

WJR: Dictation Standard Score 803 85.1

0 13.93 803 87.2

PPVT-III W Abilit

y Score 1,811 64.85 12.60 1,811 71.8

WJR: Letter-Word Identification W Abilit

y Score 839 356.94 14.36 839 367.4

WJR: Applied Problems W Abilit

y Score 867 402.10 24.58 867 415.7

WJR: Dictation W Ability Score 805 348.89 33.93 805 369.6

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S 2000 Technical Report A-44 March 06 
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FACE

 

Table A-8. Summary statistics for Fall 2000 and Spring 2001 FACES child assessment norm-referenced data—3-year ol

who were assessed in English in both Fall and Spring

Fall 2000 Spring 20

Scales

Nu

mber of 

cases Mean SD 

Nu

mber of 

cases Mean 

PPVT-III Standard Score 922 82.53 14.33 922 87.17 WJR: Letter-Word Identification Standard Score 0 -- -- 0 -- WJR: Applied Problems Standard Score 0 -- -- 0 -- WJR: Dictation Standard Score 0 -- -- 0 -- PPVT-III W Abilit

y Score 922 59.08 11.54 922 66.74 

WJR: Letter-Word Identification W Abilit

y Score 1 376.00 -- 1 386.00 

WJR: Applied Problems W Abilit

y Score 1 441.00 -- 1 435.00 

WJR: Dictation W Ability Score 1 416.00 -- 1 406.00 

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S 2000 Technical Report A-45 March 06 
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FACE

 

Table A-9. Summary statistics for Fall 2000 and Spring 2001 FACES child assessment norm-referenced data—4-year ol

children who were assessed in English in both Fall and Spring

Fall 2000 Spring 20

Scales

Nu

mber of 

cases Mean SD 

Nu

mber of 

cases Mean 

PPVT-III Standard Score 889 88.30 14.50 889 91.73 WJR: Letter-Word Identification Standard Score 837 92.3

9 9.39 837 92.6

4 

WJR: Applied Problems Standard Score 863 88.1

6 15.2

9 863 89.33 

WJR: Dictation Standard Score 803 85.1

0 13.93 803 87.2

9 

PPVT-III W Abilit

y Score 889 70.83 10.73 889 77.12 

WJR: Letter-Word Identification W Abilit

y Score 838 356.92 14.35 838 367.43 

WJR: Applied Problems W Abilit

y Score 866 402.05 24.55 866 415.71 

WJR: Dictation W Ability Score 804 348.80 33.87 804 369.57 

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S 2000 Technical Report A-46 March 06 
_______________________________________________________________________________________________________________________________

FACE

 

Table A-10. Summary statistics for Fall 2000 and Spring 2001 FA

CES child assessment data—children who were assessed 

Fall 2000 an

d English i

n S

pring 2001 

Fall 2000 Spring 2001 

Scales

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Repo

respo

rang

TVIP * 300 10.82 7.90 1 – 43 0 – 125 300 16.10 9.80 1 – WM: Letter-Word Identification* 175 4.35 1.18 0 – 10 0 – 23 175 5.15 1.76 3 – WM: Applied Problems* 184 5.37 3.36 0 – 1

4 0 – 23 -- -- -- 

WM: Dictation* 172 4.96 1.25 1 – 11 0 – 1

2 -- -- -- 

McCarthy: Draw-ADesign (SP) 361 3.38 1.32 0 – 13 0 – 1

9 -- -- -- 

Story and Pri

nt Concepts: 

Book Knowledge (SP) 338 1.24 1.15 0 – 5 0 – 5 -- -- -- Story and Pri

nt Concepts: 

Co

mprehension 352 0.48 0.68 0 – 2 0 – 2 -- -- -- 

Story and Pri

nt Concepts: 

Print Knowledge 356 0.17 0.55 0 – 3 0 – 3 -- -- -- Social Awareness (SP) 355 2.63 1.21 0 – 6 0 – 6 -- -- -- Color Names (SP) 354 9.05 6.61 0 – 2

0 0 – 2

0 -- -- -- 

One-to-One Counting (SP) 338 2.22 1.12 1 – 5 1 – 5 -- -- -- PPVT-III* 306 13.46 9.72 0 – 49 0 – 144 306 23.28 13.26 1 – 

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S 2000 Technical Report A-47 March 06 
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FACE

 

Table A-10. Summary statistics for Fall 2000 and Spring 2001 FA

CES child assessment data—children who were assessed 

Fall 2000 an

d English i

n S

pring 2001 (continued) 

Fall 2000 Spring 2001 

Scales

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Repo

respo

rang

WJR: Letter-Word Identification* 179 4.32 1.49 0 – 13 0 – 23 179 5.50 2.29 3 – WJR: Applied Problems* -- -- -- -- -- 291 5.83 4.13 0 – WJR: Dictation* -- -- -- -- -- 290 5.72 1.74 0 – McCarthy: Draw-ADesig

n

(ENG) -- -- -- -- -- 361 4.06 1.91 0 – Story and Pri

nt Concepts: 

Book Knowledge (ENG) -- -- -- -- -- 338 1.72 1.13 0 Story and Pri

nt Concepts: 

Co

mprehension -- -- -- -- -- 352 0.50 0.68 0 

Story and Pri

nt Concepts: 

Print Knowledge -- -- -- -- -- 356 0.14 0.46 0 Social Awareness (ENG) -- -- -- -- -- 355 2.57 1.30 0 Color Names (ENG) -- -- -- -- -- 354 13.4

9 6.47 0 – 

One-to-One Counting (ENG) -- -- -- -- -- 338 3.03 1.44 1 Interviewer Rating: Assessment Behavior 348 17.6

6 4.43 0 – 2

4 0 – 2

4 348 18.01 3.49 3 – 

*Raw scores were used.(SP) = Spanish translation; (ENG) = English translation. ____

S 2000 Technical Report A-48 March 06 
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FACE

 

Table A-11. Summary statistics for Fall 2000 and Spring 2001 FACES child assessment norm-referenced data—children w

assessed in Spanish in Fall 2000 and English in Spring 2001 

Fall 2000 Spring 20

Scales

Nu

mber of 

cases Mean SD 

Nu

mber of 

cases Mean 

TVIP Standard Score 300 85.1

4 11.81 300 84.1

9 

WM: Letter-Word Identification Standard Score 174 89.6

7 5.54 174 86.18 

WM: Applied Problems Standard Score 184 81.8

6 13.7

0 -- -- 

WM: Dictation Standard Score 172 85.31 8.81 -- -- WM: Letter-Word Identification W Abilit

y Score 175 351.78 7.27 175 356.40 

WM: Applied Problems W Ability Score 184 391.53 22.29 -- -- WM: Dictation W Abilit

y Score 172 347.01 20.28 -- -- 

PPVT-III Standard Score 306 59.80 13.55 306 66.75 WJR: Letter-Word Identification Standard Score 178 89.53 6.37 178 87.38 WJR: Applied Problems Standard Score -- -- -- 290 76.03 WJR: Dictation Standard Score -- -- -- 289 86.6

6 

PPVT-III W Abilit

y Score 306 45.80 12.58 306 56.01 

WJR: Letter-Word Identification W Abilit

y Score 179 351.45 9.05 179 358.18 

WJR: Applied Problems W Abilit

y Score -- -- -- 291 391.65 

WJR: Dictation W Ability Score -- -- -- 290 358.90 

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S 2000 Technical Report A-49 March 06 
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FACE

 

Table A-12. Summary statistics for Fall 2000 and Spring 2001 FACES child assessment norm-referenced data—3-year old 

who were assessed in Spanish in Fall 2000 and English in Spring 2001 

Fall 2000 Spring 20

Scales

Nu

mber of 

cases Mean SD 

Nu

mber of 

cases Mean 

TVIP Standard Score 142 89.3

4 9.84 142 86.15 

WM: Letter-Word Identification Standard Score -- -- -- -- -- WM: Applied Problems Standard Score -- -- -- -- -- WM: Dictation Standard Score -- -- -- -- -- WM: Letter-Word Identification W Abilit

y Score -- -- -- -- -- 

WM: Applied Problems W Abilit

y Score -- -- -- -- -- 

WM: Dictation W Abilit

y Score -- -- -- -- -- 

PPVT-III Standard Score 144 59.58 13.88 144 67.21 WJR: Letter-Word Identification Standard Score -- -- -- -- -- WJR: Applied Problems Standard Score -- -- -- -- -- WJR: Dictation Standard Score -- -- -- -- -- PPVT-III W Abilit

y Score 144 41.07 13.34 144 52.23 

WJR: Letter-Word Identification W Abilit

y Score -- -- -- -- -- 

WJR: Applied Problems W Abilit

y Score -- -- -- -- -- 

WJR: Dictation W Ability Score -- -- -- -- -- 

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S 2000 Technical Report A-50 March 06 
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FACE

 

Table A-13. Summary statistics for Fall 2000 and Spring 2001 FA

CES child assessment norm-referenced data—4-year old 

children who were assessed in Spanish in Fall 2000 and English in Spring 2001 

Fall 2000 Spring 20

Scales

Nu

mber of 

cases Mean SD 

Nu

mber of 

cases Mean 

TVIP Standard Score 158 81.3

7 12.18 158 82.4

2 

WM: Letter-Word Identification Standard Score 174 89.6

7 5.54 174 86.18 

WM: Applied Problems Standard Score 184 81.8

6 13.7

0 -- -- 

WM: Dictation Standard Score 172 85.31 8.81 -- -- WM: Letter-Word Identification W Abilit

y Score 175 351.78 7.27 175 356.40 

WM: Applied Problems W Ability Score 184 391.53 22.29 -- -- WM: Dictation W Abilit

y Score 172 347.01 20.28 -- -- 

PPVT-III Standard Score 162 60.01 13.28 162 66.33 WJR: Letter-Word Identification Standard Score 178 89.53 6.37 178 87.38 WJR: Applied Problems Standard Score -- -- -- 199 74.05 WJR: Dictation Standard Score -- -- -- 199 86.03 PPVT-III W Abilit

y Score 162 50.00 10.20 162 59.37 

WJR: Letter-Word Identification W Abilit

y Score 179 351.45 9.05 179 358.18 

WJR: Applied Problems W Abilit

y Score -- -- -- 200 395.63 

WJR: Dictation W Ability Score -- -- -- 200 363.86 

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S 2000 Technical Report A-51 March 06 
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Table A-14. Summary statistics for Spring 2001 and Spring 2002 (Head Start) F

ACES child assessment data—English lan

including additional Spanish language measures for Spanish-Speaking English language learner children 

Spring 2001 Spring 2

Scales 

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean 

Social Awareness 2,327 3.76 1.63 0 - 6 0 - 6 950 4.55 PPVT-III* 2,278 41.88 19.72 1 - 98 0 - 144 925 53.93 TVIP*1 322 16.27 10.04 1 - 48 0 - 125 88 23.01 

McCarthy: Draw-A-Desig

n 2,344 3.61 1.74 0 - 15 0 - 19 955 4.55 

Leiter-R AS - Age 3 420 41.71 12.2

0 1 - 64 0 - 71 - - 

Leiter-R AS - Ages 4 to 5 1,833 40.4

9 10.43 4 - 70 0 - 71 - - 

Leiter-R AS - Ages 4 to 6 - - - - - 933 45.9

2 

Color Names 2,331 15.2

6 6.11 0 - 20 0 - 20 954 18.2

4 

WJR: Letter-Word Identification* 1,808 6.37 3.09 0 - 22 0 - 23 940 7.95 WM: Letter-Word Identification*2 295 5.01 1.68 0 - 12 0 - 18 111 5.85 WJR: Applied Problems* 1,836 8.47 4.76 0 - 22 0 - 23 949 10.9

0 

WJR: Dictation* 1,784 5.65 2.05 0 - 12 0 - 12 934 6.42 Story and Pri

nt Concepts: Print 

Conventions 2,328 0.34 0.67 0 - 2 0 - 2 949 0.58 Story and Pri

nt Concepts: Book 

Knowledge 2,316 2.30 1.30 0 - 5 0 - 5 950 2.74 Story and Pri

nt Concepts: Co

mprehension

2,32

7 0.68 0.74 0 - 2 0 - 2 952 0.93 

Interviewer Rating: Assessment Behavior 2,310 18.89 4.27 0 - 24 0 - 24 938 20.12 

* Raw scores were used.1 See Table Note 1 under Table A-2b.2 See Table Note 2 under Table A-2b. ____

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Table A-15. Summary statistics for Spring 2002/2003 (kindergarten) FACES child assessment data—English language ass

Spring 2002/2003 (kindergarten) 

Scales Nu

mber of cases Mean SD 

Reported respons

range 

Social Awareness 1,884 5.98 1.68 0 - 8 PPVT-III* 1,856 71.93 17.63 14 - 136 TOLD – Pho

nemic Analysis 1,911 8.54 5.27 0 - 14 

Reading – E

CLS-K – Routing and 

Second Stage Sections** 1,908 30.6

9 9.96 9.14 - 68.56 

WJR: Applied Problems* 1,867 17.3

4 4.53 1 - 29 

WJR: Dictation* 1,842 11.48 2.75 1 - 19 Writing Name 1,894 1.89 0.35 0 - 2 General Kno

wledge – ECLS-K 

Routing** 1,887 24.30 8.28 8.47 - 46.77 Interviewer Rating: Assessment Behavior 1,858 19.63 3.68 1 - 24 

* Raw scores were used.** Scale scores were used. 

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Table A-16. Summary Statistics for Fall 2000 and Spring 2001 FACES child assessment data—children who were assesse

Fall 2000 an

d English i

n S

pring 2001 

Fall 2000 Spring 2001 

Scales

number 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Repo

respo

rang

TVIP * 300 10.82 7.90 1 – 43 0 – 125 300 16.10 9.80 1 – WM: Letter-Word Identification* 175 4.35 1.18 0 – 10 0 – 23 175 5.15 1.76 3 – WM: Applied Problems* 184 5.37 3.36 0 – 1

4 0 – 23 -- -- -- 

WM: Dictation* 172 4.96 1.25 1 – 11 0 – 1

2 -- -- -- 

McCarthy: Draw-ADesign (SP) 361 3.38 1.32 0 – 13 0 – 1

9 -- -- -- 

Story and Pri

nt Concepts: 

Book Knowledge (SP) 338 1.24 1.15 0 – 5 0 – 5 -- -- -- Story and Pri

nt Concepts: 

Co

mprehension 352 0.48 0.68 0 – 2 0 – 2 -- -- -- 

Story and Pri

nt Concepts: 

Print Knowledge 356 0.17 0.55 0 – 3 0 – 3 -- -- -- Social Awareness (SP) 355 2.63 1.21 0 – 6 0 – 6 -- -- -- Color Names (SP) 354 9.05 6.61 0 – 2

0 0 – 2

0 -- -- -- 

One-to-One Counting (SP) 338 2.22 1.12 1 – 5 1 – 5 -- -- -- PPVT-III* 306 13.46 9.72 0 – 49 0 – 144 306 23.28 13.26 1 – 

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Table A-17. Summary statistics for Fall 2000 and Spring 2001 FA

CES child assessment data—children who were assessed 

Fall 2000 an

d English i

n S

pring 2001 (continued) 

Fall 2000 Spring 2001 

Scales

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Repo

respo

rang

WJR: Letter-Word Identification* 179 4.32 1.49 0 – 13 0 – 23 179 5.50 2.29 3 – WJR: Applied Problems* -- -- -- -- -- 291 5.83 4.13 0 – WJR: Dictation* -- -- -- -- -- 290 5.72 1.74 0 – McCarthy: Draw-ADesign (ENG) -- -- -- -- -- 361 4.06 1.91 0 – Story and Pri

nt Concepts: 

Book Knowledge (ENG) -- -- -- -- -- 338 1.72 1.13 0 Story and Pri

nt Concepts: 

Co

mprehension -- -- -- -- -- 352 0.50 0.68 0 

Story and Pri

nt Concepts: 

Print Knowledge -- -- -- -- -- 356 0.14 0.46 0 Social Awareness (ENG) -- -- -- -- -- 355 2.57 1.30 0 Color Names (ENG) -- -- -- -- -- 354 13.4

9 6.47 0 – 

One-to-One Counting (ENG) -- -- -- -- -- 338 3.03 1.44 1 Interviewer Rating: Assessment Behavior 348 17.66 4.43 0 – 24 0 – 24 348 18.01 3.49 3 – *Raw scores were used.(SP) = Spanish translation; (ENG) = English translation. 

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Table A-18. Summary statistics for Fall 2000 and Spring 2001 FACES child assessment norm-referenced data—children w

assessed in Spanish in Fall 2000 and English in Spring 2001 

Fall 2000 Spring 20

Scales

Nu

mber of 

cases Mean SD 

Nu

mber of 

cases Mean 

TVIP Standard Score 300 85.1

4 11.81 300 84.1

9 

WM: Letter-Word Identification Standard Score 174 89.6

7 5.54 174 86.18 

WM: Applied Problems Standard Score 184 81.8

6 13.7

0 -- -- 

WM: Dictation Standard Score 172 85.31 8.81 -- -- WM: Letter-Word Identification W Abilit

y Score 175 351.78 7.27 175 356.40 

WM: Applied Problems W Ability Score 184 391.53 22.29 -- -- WM: Dictation W Abilit

y Score 172 347.01 20.28 -- -- 

PPVT-III Standard Score 306 59.80 13.55 306 66.75 WJR: Letter-Word Identification Standard Score 178 89.53 6.37 178 87.38 WJR: Applied Problems Standard Score -- -- -- 290 76.03 WJR: Dictation Standard Score -- -- -- 289 86.6

6 

PPVT-III W Abilit

y Score 306 45.80 12.58 306 56.01 

WJR: Letter-Word Identification W Abilit

y Score 179 351.45 9.05 179 358.18 

WJR: Applied Problems W Abilit

y Score -- -- -- 291 391.65 

WJR: Dictation W Ability Score -- -- -- 290 358.90 

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Table A-19. Reliability of Fall 2000 and Spring 2001 FACES classroom observation data selected 

measures 

Fall 2000 Spring 2

Scales 

Nu

mber of 

items

Nu

mber of 

cases 

Cronbach 

alphas 

Nu

mber of 

items

Nu

mbe

case

Assessment Profile: Scheduling 14 227 .89 14 243 Assessment Profile: Learning Environment 18 228 .68 18 228 Assessment Profile: Individualizing 5 250 .50 5 250 ECERS (Total) 37 270 .92 37 235 

Personal Care 6 146 .73 6 269 Furnishings 4 263 .52 4 263 Language 4 260 .77 4 272 Motor Skills 4 248 .67 4 274 Creative 6 253 .60 6 262 Social 4 264 .86 4 269 Program Structure 4 256 .60 4 261 

Arnett Scale of Caregiver Behavior: Lead Teacher (Total) 30 256 .94 30 258 

Sensitivity 10 262 .94 10 266 Harshness 9 265 .83 9 271 Detachment 4 266 .71 4 272 Permissiveness 3 266 .52 3 274 Independence 4 263 .58 4 269 

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Table A-20. Reliability of Spring 2002 (Head Start) 

F

ACES classroom observation data selected measures 

Spring 2002 (

Head Start) 

Scales Nu

mber of items Nu

mber of cases C

Assessment Profile: Scheduling 14 178 Assessment Profile: Learning Environment 18 180 Assessment Profile: Individualizing 5 195 ECERS (Total) 37 191 

Personal Care 6 200 Furnishings 4 202 Language 4 204 Motor Skills 4 202 Creative 6 202 Social 4 202 Program Structure 4 200 

Arnett Scale of Caregiver Behavior: Lead Teacher (Total) 30 191 

Sensitivit

y 10 199 

Harshness 9 197 Detachment 4 200 Permissiveness 3 200 Independence 4 197 

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Table A-21. Summary statistics for Fall 2000 and Spring 2001 FACES classroo

m observation data selected measures 

Fall 2000 Spring 200

Scales 

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Assessment Profile: Scheduling 270 11.1

2 3.20 0 - 14 0 - 14 270 11.00 3.15 

Assessment Profile: Learning Environment 270 14.4

4 2.57 5 - 18 0 - 18 274 14.2

2 2.92 

Assessment Profile: Individualizing 260 3.58 1.15 0 - 5 0 - 5 271 3.42 1.11 ECERS (Total) (Mean) 258 4.84 0.87 1.8 - 6.7 1.0 - 7.0 265 4.91 1.00 

Personal Care (Mean) 261 5.22 1.33 1.0 - 7.0 1.0 - 7.0 273 4.84 1.63 Furnishings (

Mean) 268 5.48 1.01 1.3 - 7.0 1.0- 7.0 266 5.52 1.02 

Language (Mean) 270 4.86 1.20 1.0 - 7.0 1.0 -7.

0 274 5.01 1.27 

Motor Skills (Mean) 264 4.79 1.27 1.3 - 7.0 1.0 -7.

0 277 4.89 1.34 

Creative (Mean) 268 4.31 0.90 2.0 - 6.3 1.0 -7.

0 277 4.26 1.02 

Social (Mean) 266 5.39 1.38 1.3 - 7.0 1.0 -7.

0 276 5.59 1.56 

Program Structure (Mean) 268 4.87 1.24 1.0 - 7.0 1.0 -7.

0 276 5.12 1.28 

Arnett Scale of Caregiver Behavior: Lead Teacher (Total) 267 71.48 12.42 26 - 90 0 - 90 274 72.84 12.99 

Sensitivity 262 20.99 6.52 1 - 30 0 - 30 266 21.74 6.42 Harshness 265 24.28 3.22 4 - 27 0 - 27 271 24.3

4 3.16 

Detachment 266 11.0

6 1.54 4 - 12 0 - 12 272 11.08 1.79 

Permissiveness 266 7.47 1.37 1 – 9 0 -9 274 7.39 1.45 Independence 263 7.77 2.31 1 - 12 0 -12 269 8.39 2.32 

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Table A-22. Summary statistics for Spring 2002 (Head Start) FACES classroom observation data selected measures 

Spring 2002 (

Head Start) 

Scales 

Nu

mber of 

cases Mean SD 

Reported 

response range 

Assessment Profile: Scheduling 198 11.3

9 2.56 4 - 14 

Assessment Profile: Learning Environment 203 14.63 2.48 5 - 18 Assessment Profile: Individualizing 202 3.52 0.96 0 - 5 ECERS (Total) (Mean) 202 4.84 0.86 1.8 - 6.7 

Personal Care (Mean) 203 4.82 1.44 1.0 - 7.0 Furnishings (Mean) 202 5.55 0.92 2.3 - 7.0 Language (Mean) 204 5.06 1.13 1.0 - 7.0 Motor Skills (Mean) 204 4.70 1.27 1.0 - 7.0 Creative (Mean) 204 4.12 0.97 1.7 - 6.7 Social (Mean) 204 5.58 1.39 1.0 - 7.0 Program Structure (Mean) 203 5.02 1.17 1.0 - 7.0 

Arnett Scale of Caregiver Behavior: Lead Teacher (Total) 201 73.65 11.81 22 - 90 

Sensitivit

y 199 21.95 6.29 1 - 30 

Harshness 197 24.43 2.83 10 - 2

7 

Detachment 200 11.1

2 1.51 3 - 12 

Permissiveness 200 7.60 1.35 0 - 9 Independence 197 8.66 2.13 2 - 12 

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Table A-23. Reliability of Fall 2000 and Spring 2001 FACES teacher’s child report data selected measures 

Fall 2000 Spring 2

Scales 

Nu

mber of 

items Nu

mber of cases

Cronbach 

alphas 

N

umber of items

Nu

mbe

case

Social Skills 12 2,522 .88 12 2,25Behavioral Problems (Total) 14 2,522 .86 14 2,25

Withdrawn 7 2,522 .77 7 2,25Aggressive 4 2,522 .83 4 2,25Hyperactive 3 2,522 .72 3 2,25

Child Observation Record (Total) 14 2,522 .94 14 2,25

Social Relationships 3 2,522 .83 3 2,25Creative Representations 3 2,522 .80 3 2,25Music and Movement 4 2,522 .88 4 2,25Cognitive 4 2,522 .82 4 2,25

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Table A-24. Reliability of Spring 2002 (Head Start) and Spring 2002/2003 (kindergarten) FACES teacher’s child report da

Spring 2002 (

Head Start) Spring 2002/2003 

Scales 

Nu

mber of 

items Nu

mber of cases

Cronbach 

alphas 

N

umber of items

Nu

mbe

case

Social Skills 12 963 .87 12 1,612 Behavioral Problems (Total) 14 963 .87 14 1,612 

Withdrawn 7 963 .76 7 1,612 Aggressive 4 963 .83 4 1,612 Hyperactive 3 963 .75 3 1,612 

Child Observation Record (Total) 14 963 .93 - 

Social Relationships 3 963 .80 - Creative Representations 3 963 .80 - Music and Movement 4 963 .86 - Cognitive 4 963 .80 - 

Literacy - - - 8 1,533 

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Table A-25. Summary statistics for Fall 2000 and Spring 2001 FACES teacher’s child report data selected measures 

Fall 2000 Spring 200

Scales 

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Social Skills 2,518 14.52 4.85 0 - 24 0 - 24 2,251 16.58 4.63 Behavioral Problems (Total) 2,484 5.76 5.06 0 - 28 0 - 28 2,215 5.30 4.89 

Withdrawn 2,453 2.59 2.65 0 - 14 0 - 14 2,186 2.34 2.49 Aggressive 2,449 1.80 2.04 0 - 8 0 - 8 2,189 1.74 2.03 Hyperactive 2,466 1.37 1.53 0 - 6 0 - 6 2,194 1.21 1.47 

Child Observation Record (Total) (Mean) 2,403 2.82 0.77 1.0 - 5.0 1.0 - 5.0 2,174 3.50 0.81 

Social Relationships (Mean) 2,464 2.83 1.01 1.0 - 5.0 1.0 - 5.0 2,230 3.51 0.99 Creative Representations (Mean) 2,459 2.83 0.83 1.0 - 5.0 1.0 - 5.0 2,230 3.52 0.87 Music and Movement (Mean) 2,446 2.95 0.85 1.0 - 5.0 1.0 - 5.0 2,217 3.65 0.89 Cognitive (Mean) 2,403 2.75 0.82 1.0 - 5.0 1.0 - 5.0 2,184 3.41 0.89 

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Table A-26. Summary statistics for Spring 2002 (Head Start) and Spring 2002/2003 (kindergarten) FACES teacher’s child 

measures 

Spring 2002 (

Head Start) Spring 2002/2003 (k

Scales 

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Social Skills 961 18.12 4.28 0 - 24 0 - 24 1,602 17.58 4.68 Behavioral Problems (Total) 951 4.52 4.72 0 - 27 0 - 28 1,605 5.69 5.30 

Withdrawn 937 2.05 2.40 0 - 14 0 - 14 1,585 2.60 2.77 Aggressive 937 1.49 1.93 0 - 8 0 - 8 1,594 1.62 2.04 Hyperactive 945 0.97 1.40 0 - 6 0 - 6 1,600 1.46 1.69 

Child Observation Record (Total) (Mean) 932 4.06 0.70 1.1 - 5.0 1.0 - 5.0 - - - 

Social Relationships (Mean) 954 4.00 0.89 1.0 - 5.0 1.0 - 5.0 - - - Creative Representations (Mean) 958 4.06 0.79 1.0 - 5.0 1.0 - 5.0 - - - Music and Movement (Mean) 952 4.24 0.75 1.0 - 5.0 1.0 - 5.0 - - - Cognitive (Mean) 939 3.96 0.80 1.3 - 5.0 1.0 - 5.0 - - - 

Literacy (Mean) - - - - - 1,602 2.58 1.12 

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Table A-27. Reliability of Fall 2000 and Spring 2001 FACES parent interview data selected measures 

Fall 2000 Spring 2

Scales 

Nu

mber of 

items Nu

mber of cases

Cronbach 

alphas 

N

umber of items

Nu

mbe

case

Pearlin Mastery Scale (Locus of Control) 7 2,485 .76 7 2,29CES-D Depression Scale 12 2,485 .87 12 2,29Positive Approaches to Learning 7 2,485 .61 7 2,29Behavior Pro

blems Index (Total) 12 2,485 .71 12 2,29

Behavior Pro

blems (Aggressive) 4 2,485 .59 4 2,29

Behavior Pro

blems (Hy

peractive) 3 2,485 .55 3 2,29

Behavior Pro

blems (Withdrawn) 5 2,485 .36 5 2,29

Co

mbined Activities Scale 22 2,419 .69 22 2,2

Weekly Activities Subscale 11 2,441 .60 11 2,23Monthly Activities Subscale 11 2,459 .58 11 2,26

Emerging Literacy Scale 5 2,469 .60 5 2,27

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Table A-28. Reliability of Spring 2002 (

Head Start) and Spring 2002/2003 (

kindergarten) FACES parent interview data se

Spring 2002 (

Head Start) Spring 2002/2003 (

Scales 

Nu

mber of 

items Nu

mber of cases

Cronbach 

alphas 

N

umber of items

Nu

mbe

case

Pearlin Mastery Scale (Locus of Control) 7 906 .76 7 2,0CES-D Depression Scale 12 907 .87 12 2,0Positive Approaches to Learning 7 907 .66 13 1,9Behavior Pro

blems Index (Total) 12 907 .76 13 2,0

Behavior Pro

blems (Aggressive) 4 907 .63 5 2,0

Behavior Pro

blems (Hy

peractive) 3 907 .61 3 2,0

Behavior Pro

blems (Withdrawn) 3 907 .39 5 2,0

Co

mbined Activities Scale 22 873 .71 17 2,0

Weekly Activities Subscale 11 884 .61 7 2,0Monthly Activities Subscale 11 895 .64 10 2,02

Emerging Literacy Scale 5 902 .57 5 2,0

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Table A-29. Summary statistics for Fall 2000 and Spring 

2001 FACES parent interview data selected 

measures 

Fall 2000 Spring 200

Scales 

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Pearlin Mastery Scale (Locus of Control) 2,471 14.80 3.28 0 - 21 0 - 21 2,284 15.30 3.31 CES-D Depression Scale 2,473 6.81 6.72 0 - 36 0 - 36 2,285 6.59 6.36 Positive Approaches to Learning 2,479 12.08 1.76 3 - 14 0 - 14 2,287 12.15 1.75 Behavior Pro

blems Index 

(Total) 2,480 6.16 3.55 0 - 22 0 - 24 2,287 5.64 3.57 

Behavior Pro

blems

(Aggressive) 2,468 3.16 1.74 0 - 8 0 - 8 2,275 2.87 1.74 Behavior Pro

blems

(Hy

peractive) 2,471 1.85 1.50 0 - 6 0 - 6 2,275 1.63 1.45 

Behavior Pro

blems

(Withdrawn) 2,459 0.61 0.93 0 - 6 0 - 6 2,267 0.63 0.94 

Co

mbined Activities Scale 2,469 10.6

7 3.76 0 - 22 0 - 22 2,285 11.1

9 3.80 

Weekly Activities Subscale 2,473 6.28 2.52 0 - 11 0 - 11 2,290 6.23 2.56 Monthly Activities Subscale 2,477 4.39 2.09 0 - 11 0 - 11 2,285 4.95 2.14 

Emerging Literacy Scale 2,469 1.94 1.44 0 - 5 0 - 5 2,290 2.95 1.51 

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Table A-30. Summary statistics for Spring 2002 (Head Start) and 

S

pring 2002/2003 (kindergarten) FACES parent interview 

measures 

Spring 2002 (

Head Start) Spring 2002/2003 (k

Scales 

Nu

mber 

of cases Mean SD 

Reported 

response 

range 

Possible 

response 

range 

Nu

mber 

of cases Mean SD 

Pearlin Mastery Scale (Locus of Control) 906 15.3

2 3.24 5 - 21 0 - 21 2,026 15.2

4 3.19 

CES-D Depression Scale 906 5.14 6.04 0 - 36 0 - 36 896 5.19 5.80 Social Score Positive 905 12.49 1.69 5 - 14 0 - 14 2,030 26.23 5.88 Behavior Pro

blems Index 

(Total) 905 5.20 3.70 0 - 22 0 - 24 2,030 9.63 5.39 

Behavior Pro

blems

(Aggressive) 900 2.61 1.80 0 - 8 0 - 8 2,030 4.74 2.80 Behavior Pro

blems

(Hy

peractive) 900 1.45 1.47 0 - 6 0 - 6 2,024 2.22 1.88 

Behavior Pro

blems

(Withdrawn) 894 0.62 0.95 0 - 6 0 - 6 2,030 2.66 2.08 

Co

mbined Activities Scale 902 11.8

7 3.95 1 - 22 0 - 22 2,028 8.47 3.09 

Weekly Activities Subscale 903 6.46 2.64 0 - 11 0 - 11 2,029 3.61 1.80 Monthly Activities Subscale 905 5.42 2.32 0 - 11 0 - 11 2,030 4.86 2.05 

Emerging Literacy Scale 902 3.98 1.21 0 - 5 0 - 5 2,032 4.74 0.66 

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S 2000 Technical Report A-68 March 06