The Effectiveness of Secondary Math 

Teachers from Teach For America 

and the Teaching Fellows Programs

September 2013 

U.S. Department of Education
This page has been left blank for double–sided copying.
The Effectiveness of Secondary Math 

Teachers from Teach For America 

and the Teaching Fellows Programs

September 2013 

Melissa A. Clark

Hanley S. Chiang

Tim Silva

Sheena McConnell

Kathy Sonnenfeld

Anastasia Erbe

Mathematica Policy Research

Michael Puma

Chesapeake Research Associates 

Elizabeth Warner

Project Officer

Institute of Education Sciences

NCEE 2013-4015

U.S. DEPARTMENT OF EDUCATION
U.S. Department of Education 

Arne Duncan

Secretary

Institute of Education Sciences

John Q. Easton 

Director

National Center for Education Evaluation and Regional Assistance 

Ruth Curran Neild

Commissioner 

September 2013 

The report was prepared for the Institute of Education Sciences under Contract No. ED-04-CO0112/0009. The project officer is Elizabeth Warner in the National Center for Education Evaluation 

and Regional Assistance.

IES evaluation reports present objective information on the conditions of implementation and 

impacts of the programs being evaluated. IES evaluation reports do not include conclusions or 

recommendations or views with regard to actions policymakers or practitioners should take in light 

of the findings in the reports. 

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

While permission to reprint this publication is not necessary, the citation should be: 

Clark, Melissa A., Hanley S. Chiang, Tim Silva, Sheena McConnell, Kathy Sonnenfeld, Anastasia 

Erbe, and Michael Puma. (2013). The Effectiveness of Secondary Math Teachers from Teach For 

America and the Teaching Fellows Programs (NCEE 2013-4015). Washington, DC: National 

Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. 

Department of Education.

This report is available on the IES website at http://ies.ed.gov/ncee. 

Upon request, this report is available in alternate formats such as Braille, large print, audiotape, or 

computer diskette. For more information, please contact the Department’s Alternate Format Center 

at 202-260-9895 or 202-205-8113. 
 iii

ACKNOWLEDGMENTS

This study would not have been possible without the contributions of many individuals and 

organizations. First and foremost, we are grateful for the cooperation of the school districts, 

schools, teachers, and students who participated in the study. We also thank national and 

regional staff at Teach For America and TNTP, who provided essential information about their 

programs over the course of the study. Stefanie Schmidt provided valuable guidance as the 

study’s IES project officer through the data collection and analysis phases of the study. 

We are grateful for input provided by members of the study’s technical working group, 

which included Julie Greenberg, Paul Holland, Tim Sass, Jeff Smith, Suzanne Wilson, and Jim 

Wyckoff. The study has benefited greatly from their expertise.

The study also benefited from the contributions of many individuals at Mathematica and its 

research partners, Chesapeake Research Associates and Branch Associates. Daniel Player and 

Alison Wellington were heavily involved in the early stages of the study and provided invaluable 

input on the study design, development of data collection instruments, and random assignment. 

Eric Zeidman and Charlotte Cabili led our large team of dedicated staff who recruited districts 

and schools into the study. Nancy Duda and Barbara Kennen were responsible for the collection 

and preparation of much of the data used in the study. Mason DeCamillis and Matt Jacobus 

provided excellent programming assistance in cleaning and analyzing the data, with expert 

guidance from Mary Grider. Phil Gleason provided thoughtful, critical reviews of the study 

design and final report. John Kennedy provided editorial support, and Jennifer Baskwell and 

Allie Clifford provided production support. 
This page has been left blank for double–sided copying
 v 

CONTENTS 

EXECUTIVE SUMMARY...............................................................................................xix

I INTRODUCTION.............................................................................................. 1 

A. Background................................................................................................ 2 

1. Concerns about Teacher Quality in Hard-to-Staff Schools 

and Subjects........................................................................................ 2 

2. Policies Targeting the Teacher Pipeline .............................................. 2 

3. TFA and the Teaching Fellows Programs ........................................... 3 

4. Past Research on Teachers from TFA and the Teaching 

Fellows Programs................................................................................ 4 

B. Our Evaluation........................................................................................... 5 

C. Looking Ahead........................................................................................... 7 

II STUDY DESIGN, DATA, AND METHODS ...................................................... 9 

A. Types of Teachers in the Study ................................................................. 9 

1. Eligible Routes to Certification............................................................. 9 

2. No Limits on Prior Teaching Experience ........................................... 10

B. Experimental Design................................................................................ 11

C. Recruitment of Districts, Schools, and Teachers ..................................... 12

1. Recruitment of Districts ..................................................................... 13

2. Recruitment of Schools ..................................................................... 14

3. Classroom Matches and Teachers in the Final Study 

Sample .............................................................................................. 15

4. Differences between the TFA and Teaching Fellows Study 

Samples ............................................................................................ 15

D. Selection and Assignment of Students .................................................... 16

E. Data Used in the Study............................................................................ 18

1. Data on Students............................................................................... 18

2. Data on Teachers.............................................................................. 20

3. Data on Schools ................................................................................ 21

4. Data on TFA and Teaching Fellows Programs.................................. 21

F. Overview of the Analytic Approach .......................................................... 21

1. Experimental Analyses...................................................................... 21

2. Nonexperimental Analyses................................................................ 23
Contents

 vi 

III SELECTION, TRAINING, AND SUPPORT OF TFA PROGRAM

PARTICIPANTS............................................................................................. 27

A. Application and Selection......................................................................... 27

1. Application Form and Eligibility Rules ............................................... 27

2. Selection Process.............................................................................. 28

3. Program Selectivity and Application Yields ....................................... 31

B. Preservice Training for New Corps Members .......................................... 31

1. Independent Study and Regional Induction....................................... 32

2. Summer Institute ............................................................................... 33

3. Post-Institute Activities ...................................................................... 34

C. Placement and Retention of TFA Corps Members .................................. 34

D. Instruction Provided to TFA Corps Members Through Local 

Teacher Certification Programs ............................................................... 35

1. Preservice Instruction........................................................................ 36

2. Instruction During and After the First Year of Teaching..................... 36

3. Total Amount of Instruction in Certification Programs ....................... 37

E. Training and Support for New Corps Members After They Begin 

Teaching.................................................................................................. 37

1. Instruction, Training, and Professional Development ........................ 37

2. Other Support Services ..................................................................... 37

F. Financial Support for Corps Members ..................................................... 38

IV TEACH FOR AMERICA STUDY TEACHERS: THEIR 

CHARACTERISTICS, THE SCHOOLS THEY TEACH IN, 

AND THE STUDENTS THEY TEACH............................................................ 39

A. Schools in the TFA Study Sample ........................................................... 39

B. TFA Teachers in the Study Sample Compared with Comparison 

Teachers.................................................................................................. 41

1. Demographic Characteristics ............................................................ 42

2. Educational Background and Math Content Knowledge ................... 42

3. Teaching and Nonteaching Work Experience ................................... 45

4. Teacher Training, Professional Development, and Support .............. 47

5. Views Toward Teaching .................................................................... 50

C. Students in the TFA Study Sample.......................................................... 51
Contents

 vii 

V TEACH FOR AMERICA: IMPACTS ON SECONDARY STUDENT 

MATH ACHIEVEMENT .................................................................................. 55

A. Impacts of TFA Teachers Relative to All Comparison Teachers.............. 55

1. Average Impact ................................................................................. 55

2. Variation in Impacts........................................................................... 57

B. Impacts of TFA Teachers Relative to Comparison Teachers 

from Traditional and Alternative Routes to Certification........................... 58

C. Impacts Within Other Teacher Subgroups............................................... 58

1. Subgroups Defined by Teaching Experience .................................... 58

2. Subgroups Defined by Middle and High School ................................ 59

D. Conclusions ............................................................................................. 61

VI SELECTION, TRAINING, AND SUPPORT OF TEACHING 

FELLOWS PROGRAM PARTICIPANTS........................................................ 63

A. Application and Selection......................................................................... 63

1. Application Form and Eligibility Rules ............................................... 63

2. Selection Process.............................................................................. 64

3. Program Selectivity and Application Yields ....................................... 66

B. Preservice Training for New Teaching Fellows........................................ 67

1. Independent Study and Orientation................................................... 67

2. Summer Institute ............................................................................... 67

3. Post-Institute Activities ...................................................................... 70

C. Placement and Retention of Teaching Fellows........................................ 70

D. Instruction Provided to Teaching Fellows Through Local 

Teacher Certification Programs ............................................................... 71

1. Preservice Instruction........................................................................ 72

2. Instruction During and After the First Year of Teaching..................... 72

3. Total Amount of Instruction in Certification Programs ....................... 72

E. Training and Support for New Teaching Fellows After They 

Begin Teaching........................................................................................ 73

1. Instruction, Training, and Professional Development ........................ 73

2. Other Support Services ..................................................................... 73

F. Financial Support for Teaching Fellows................................................... 74
Contents

 viii

VII TEACHING FELLOWS STUDY TEACHERS: THEIR 

CHARACTERISTICS, THE SCHOOLS THEY TEACH IN, 

AND THE STUDENTS THEY TEACH............................................................ 75

A. Schools in the Teaching Fellows Study Sample ...................................... 75

B. Teaching Fellows in the Study Sample Compared with 

Comparison Teachers.............................................................................. 77

1. Demographic Characteristics ............................................................ 78

2. Educational Background and Content Knowledge ............................ 78

3. Teaching and Nonteaching Work Experience ................................... 83

4. Teacher Training, Professional Development, and Support .............. 84

5. Views Toward Teaching .................................................................... 86

C. Students in the Teaching Fellows Study Sample..................................... 87

VIII TEACHING FELLOWS: IMPACTS ON SECONDARY STUDENT 

MATH ACHIEVEMENT .................................................................................. 91

A. Impacts of Teaching Fellows Relative to All Comparison 

Teachers.................................................................................................. 91

1. Average Impact ................................................................................. 91

2. Variation in Impacts........................................................................... 93

B. Impacts of Teaching Fellows Relative to Comparison Teachers 

from Traditional and Alternative Routes to Certification........................... 94

C. Impacts Within Other Teacher Subgroups............................................... 95

1. Subgroups Defined by Specific Levels of Teaching 

Experience ........................................................................................ 95

2. Subgroup of Teaching Fellows and Comparison Teachers 

with Similar Levels of Teaching Experience ...................................... 96

3. Subgroups Defined by Middle and High School ................................ 97

D. Conclusions ............................................................................................. 97

IX RELATIONSHIPS BETWEEN TEACHER CHARACTERISTICS 

AND TEACHER EFFECTIVENESS............................................................. 101

A. Analysis of Characteristics That Predict Teacher Effectiveness ............ 101

1. General Academic Ability ................................................................ 102

2. Exposure to and Knowledge of Math............................................... 104

3. Instructional Training and Experience ............................................. 105
Contents

 ix

B. Accounting for the Impact of TFA Teachers........................................... 106

1. Predictions Based on Each Individual Characteristic ...................... 107

2. Predictions Based on All Observed Characteristics ........................ 109

REFERENCES............................................................................................................ 111 

APPENDIX A: SUPPLEMENTARY TECHNICAL INFORMATION ON 

STUDY DESIGN AND DATA COLLECTION....................................A.1

APPENDIX B: SUPPLEMENTARY INFORMATION ON ANALYTIC 

METHODS .......................................................................................B.1

APPENDIX C: SUPPLEMENTARY INFORMATION ON TEACH FOR 

AMERICA AND TEACHING FELLOWS PROGRAMS.....................C.1

APPENDIX D: TEACH FOR AMERICA AND TEACHING FELLOWS 

TEACHERS COMPARED WITH COMPARISON 

TEACHERS BY ENTRY ROUTE 

(ALTERNATIVE OR TRADITIONAL) ...............................................D.1

APPENDIX E: SUPPLEMENTARY INFORMATION ON TEACH FOR 

AMERICA AND TEACHING FELLOWS TEACHERS 

COMPARED WITH COMPARISON TEACHERS.............................E.1

APPENDIX F: SUPPLEMENTARY ANALYSES OF THE IMPACTS OF 

TEACH FOR AMERICA AND TEACHING FELLOWS 

TEACHERS...................................................................................... F.1

APPENDIX G: SUPPLEMENTARY FINDINGS ON FACTORS 

ASSOCIATED WITH TEACHER EFFECTIVENESS....................... G.1
This page has been left blank for double–sided copying.
Tables

xi

TABLES

II.1 Number of Districts, Schools, Classroom Matches, Teachers, and Classes 

in the Study...............................................................................................................13

II.2 Distribution of Sample Sizes Across Districts in the Study ........................................14

II.3 Number of Classroom Matches and Study Classes, by Subject................................15

II.4 Number of Students in the Study ..............................................................................17

II.5 Changes in Composition of Study Classes During the School Year..........................18

II.6 Data Sources for the Evaluation................................................................................19

II.7 Teacher Characteristics Examined in the Nonexperimental Analysis ........................ 24 

III.1 Estimated Percentage of New TFA Corps Members Who Received 

Teaching Placements, on Average, Across the 2007–2008, 

2008–2009, and 2009–2010 School Years ...............................................................35

III.2 Hours of Instruction Toward Certification Reportedly Required in Focal AC 

Programs for TFA Secondary Math Teachers...........................................................36

IV.1 Characteristics of Study Schools with TFA Teachers Compared with All 

Secondary Schools with TFA Teachers and All Secondary Schools 

Nationwide................................................................................................................40

IV.2 Demographic Characteristics of TFA and Comparison Teachers in the 

Study and All Secondary Teachers Nationwide.........................................................43

IV.3 Educational Background of TFA and Comparison Teachers in the Study .................44

IV.4 Average Number of College-Level Math Courses Taken by TFA and 

Comparison Teachers in the Study...........................................................................45

IV.5 Praxis II Scores of TFA and Comparison Teachers in the Study...............................46

IV.6 Nonteaching and Teaching Work Experience of TFA and Comparison 

Teachers in the Study...............................................................................................47

IV.7 Training and Professional Development of TFA and Comparison 

Teachers in the Study...............................................................................................48

IV.8 Coursework Taken During the School Year by TFA and Comparison 

Teachers in the Study...............................................................................................49

IV.9 Mentoring Received During the School Year by TFA and Comparison 

Teachers in the Study...............................................................................................50

IV.10 Job Satisfaction of TFA and Comparison Teachers in the Study...............................51
Tables

xii

IV.11 Average Baseline Characteristics of Students in the Analysis Sample Who 

Were Assigned to TFA Teachers or Comparison Teachers ......................................52

V.1 Difference in Effectiveness Between TFA Teachers and All Comparison 

Teachers...................................................................................................................56

VI.1 Domains and Corresponding Competencies of TNTP’s Teaching for 

Student Achievement Framework .............................................................................69

VI.2 Characteristics of Math Immersion Programs Offered by Three Teaching 

Fellows Programs in the Study .................................................................................70

VI.3 Estimated Percentage of New Teaching Fellows Who Received Teaching 

Placements, on Average, Across the 2007–2008, 2008–2009, and 2009–

2010 School Years ...................................................................................................71

VI.4 Hours of Instruction Toward Certification Reportedly Required in Focal AC 

Programs for Secondary Math Teaching Fellows......................................................73

VII.1 Characteristics of Study Schools with Teaching Fellows Compared with All 

Secondary Schools with Teaching Fellows and All Secondary Schools 

Nationwide................................................................................................................76

VII.2 Demographic Characteristics of Teaching Fellows and Comparison 

Teachers in the Study and All Secondary Teachers Nationwide ...............................79

VII.3 Educational Background of Teaching Fellows and Comparison 

Teachers in the Study...............................................................................................80

VII.4 Average Number of College-Level Math Courses Taken by Teaching 

Fellows and Comparison Teachers in the Study .......................................................81

VII.5 Praxis II Scores of Teaching Fellows and Comparison Teachers in the 

Study ........................................................................................................................82

VII.6 Nonteaching and Teaching Work Experience of Teaching Fellows and 

Comparison Teachers in the Study...........................................................................83

VII.7 Training and Professional Development of Teaching Fellows and 

Comparison Teachers in the Study...........................................................................85

VII.8 Coursework Taken During the School Year by Teaching Fellows and 

Comparison Teachers in the Study...........................................................................86

VII.9 Mentoring Received During the School Year by Teaching Fellows and 

Comparison Teachers in the Study...........................................................................87

VII.10 Job Satisfaction of Teaching Fellows and Comparison 

Teachers in the Study...............................................................................................88

VII.11 Average Baseline Characteristics of Students in the Analysis Sample Who 

Were Assigned to Teaching Fellows or Comparison Teachers ................................. 89
Tables

xiii

VIII.1 Difference in Effectiveness Between Teaching Fellows and All 

Comparison Teachers...............................................................................................92

VIII.2 Difference in Effectiveness Between Teaching Fellows and Comparison 

Teachers with Similar Levels of Teaching Experience ..............................................97

IX.1 Differences in Student Math Achievement Associated with Differences in 

Teacher Characteristics ..........................................................................................103

IX.2 Predicted Differences in Effectiveness Between TFA Teachers and 

Comparison Teachers Based on Observed Teacher Characteristics ......................107 

A.1 Percentage of Classroom Matches in Which Students Receive 

Supplemental Math................................................................................................. A.4 

A.2 Number of Districts, Schools, Classroom Matches, Teachers, and Classes 

in the Study, by School Year...................................................................................A.7 

A.3 Structure of Classroom Matches in the TFA Study Sample.....................................A.7 

A.4 Structure of Classroom Matches in the Teaching Fellows Study Sample................A.8 

A.5 Average Baseline Characteristics of Students Assigned to TFA Teachers 

or Comparison Teachers ......................................................................................A.13

A.6 Average Baseline Characteristics of Students Assigned to Teaching 

Fellows or Comparison Teachers ..........................................................................A.14

A.7 Movement of Members of Research Sample During the School Year...................A.15

A.8 Characteristics of Nonstudy Students on End-of-Year Rosters 

of Classrooms in the TFA Study Sample...............................................................A.17

A.9 Characteristics of Nonstudy Students on End-of-Year Rosters 

of Classrooms in the Teaching Fellows Study Sample..........................................A.18

A.10 Realized Values for Key Precision Parameters .....................................................A.19

A.11 Reliability of the NWEA Assessments, by Subject ................................................A.20

A.12 Invalid NWEA Scores, by Treatment Status..........................................................A.21

A.13 NWEA Test Statistics in Analysis Sample .............................................................A.22

A.14 Characteristics of State Math Assessments from which End-of-Year 

Scores Were Used in the Study ............................................................................A.24

A.15 State Math Assessment Scores of Middle School Students in the Analysis 

Sample Relative to Proficiency Cut Points ............................................................A.25

A.16 Student Response Rates, by Type of Impact Estimate to Which the 

Student’s Classroom Contributes..........................................................................A.26

A.17 Characteristics of Students With and Without Valid Outcome Data.......................A.27
Tables

xiv

A.18 Teacher Response Rates and Sample Sizes........................................................A.28

A.19 Characteristics of Teachers, by Response to Teacher Survey ..............................A.29

A.20 Characteristics of Teachers, by Availability of Praxis II Scores .............................A.29

B.1 Means and Standard Deviations of Covariates Included in Models 

for Estimating the Impacts of TFA Teachers ........................................................... B.8 

B.2 Means and Standard Deviations of Covariates Included in Models 

for Estimating the Impacts of Teaching Fellows ...................................................... B.9 

C.1 Similarities and Differences in TFA and the Teaching Fellows Programs................C.6 

D.1 Demographic Characteristics of Teachers in the TFA Study Sample, 

by Entry Route........................................................................................................D.5 

D.2 Educational Background of Teachers in the TFA Study Sample, 

by Entry Route........................................................................................................D.6 

D.3 Average Number of College-Level Math Courses Taken by Teachers 

in the TFA Study Sample, by Entry Route...............................................................D.7 

D.4 Praxis II Scores of Teachers in the TFA Study Sample, by Entry Route..................D.8 

D.5 Nonteaching and Teaching Work Experience of Teachers in the TFA 

Study Sample, by Entry Route ................................................................................D.9 

D.6 Training and Professional Development of Teachers in the TFA 

Study Sample, by Entry Route ..............................................................................D.10 

D.7 Coursework Taken During the School Year by Teachers in the TFA 

Study Sample, by Entry Route ..............................................................................D.12 

D.8 Mentoring Received During the School Year by Teachers in the TFA 

Study Sample, by Entry Route ..............................................................................D.13 

D.9 Job Satisfaction of Teachers in the TFA Study Sample, by Entry Route ...............D.14 

D.10 Demographic Characteristics of Teachers in the Teaching Fellows 

Study Sample, by Entry Route ..............................................................................D.15 

D.11 Educational Background of Teachers in the Teaching Fellows 

Study Sample, by Entry Route ..............................................................................D.16 

D.12 Average Number of College-Level Math Courses Taken by Teachers 

in the Teaching Fellows Study Sample, by Entry Route ........................................D.17

D.13 Praxis II Scores of Teachers in the Teaching Fellows Study Sample, 

by Entry Route......................................................................................................D.18

D.14 Nonteaching and Teaching Work Experience of Teachers in the Teaching 

Fellows Study Sample, by Entry Route ................................................................. D.19
Tables

xv

D.15 Training and Professional Development of Teachers in the Teaching 

Fellows Study Sample, by Entry Route ................................................................. D.20 

D.16 Coursework Taken During the School Year by Teachers in the Teaching 

Fellows Study Sample, by Entry Route ................................................................. D.22 

D.17 Job Satisfaction of Teachers in the Teaching Fellows Study Sample, 

by Entry Route......................................................................................................D.24 

E.1 Sensitivity of Differences in Praxis II Scores Between TFA and 

Comparison Teachers in the Study.........................................................................E.7 

E.2 Sensitivity of Differences in Praxis II Scores Between Teaching Fellows 

and Comparison Teachers in the Study ................................................................E.11

F.1 Differences in Effectiveness Between TFA Teachers and Comparison 

Teachers, Sensitivity Analyses ............................................................................... F.7 

F.2 Impact on Student Absences of TFA Teachers Relative to Comparison 

Teachers ................................................................................................................. F.9 

F.3 Differences in Effectiveness Between TFA Teachers and Comparison 

Teachers, by Subgroup......................................................................................... F.10

F.4 Differences in Effectiveness Between Teaching Fellows and Comparison 

Teachers, Sensitivity Analyses ............................................................................. F.11

F.5 Impact on Student Absences of Teaching Fellows Relative to Comparison 

Teachers ............................................................................................................... F.13

F.6 Differences in Effectiveness Between Teaching Fellows and Comparison 

Teachers, by Subgroup......................................................................................... F.14

G.1 Summary Statistics of Teacher Characteristics Examined in the 

Nonexperimental Analysis.......................................................................................G.6 

G.2 Estimated Associations Between Teacher Characteristics and Student 

Math Achievement in Models that Include Only a Single Teacher 

Characteristic..........................................................................................................G.7 

G.3 Estimated Associations Between Teacher Characteristics and Student 

Math Achievement in a Model that Includes Multiple Teacher 

Characteristics: Main Specification .........................................................................G.9 

G.4 Extent to Which Teacher Characteristics Explain the Difference 

in Effectiveness Between TFA Teachers and Comparison Teachers ....................G.10

G.5 Estimated Associations Between Teacher Characteristics and Student 

Math Achievement in Models that Include Multiple Teacher 

Characteristics: Specifications with Alternative Measures 

of College Selectivity.............................................................................................G.12
Tables

xvi 

G.6 Estimated Associations Between Teacher Characteristics and Student 

Math Achievement in Models that Include Multiple Teacher 

Characteristics: Specifications with Measures of Academic 

Degrees in Math or Math-Related Subjects...........................................................G.13

G.7 Estimated Associations Between Teacher Characteristics and Student 

Math Achievement in Models that Include Multiple Teacher 

Characteristics: Specifications with Alternative Measures 

of Praxis Achievement ..........................................................................................G.15

G.8 Estimated Associations Between Teacher Characteristics and Student 

Math Achievement in a Model that Includes Multiple Teacher 

Characteristics: Specification with Teacher Demographic 

Characteristics......................................................................................................G.16
Figures

xvii 

FIGURES

I.1 Conceptual Framework............................................................................................... 6 

III.1 TFA Selection Process and Applicant Flow...............................................................31

III.2 Overview of Placement and Training of TFA Corps Members...................................32

V.1 Differences in Effectiveness Between TFA Teachers and Comparison 

Teachers from Individual Classroom Matches...........................................................58

V.2 Differences in Effectiveness Between TFA Teachers and Comparison 

Teachers from Traditional and Alternative Routes to Certification.............................59

V.3 Differences in Effectiveness Between Novice TFA Teachers and 

Comparison Teachers, by Experience Level of Comparison Teacher.......................60

V.4 Differences in Effectiveness Between TFA Teachers and Comparison 

Teachers Within Middle Schools and High Schools ..................................................61

VI.1 Teaching Fellows Selection Process and Applicant Flow..........................................66

VI.2 Overview of Placement and Training of Teaching Fellows ........................................68

VIII.1 Differences in Effectiveness Between Teaching Fellows and Comparison 

Teachers from Individual Classroom Matches...........................................................93

VIII.2 Differences in Effectiveness Between Teaching Fellows and Comparison 

Teachers from Traditional and Alternative Routes to Certification.............................94

VIII.3 Differences in Effectiveness Between Novice Teaching Fellows and 

Comparison Teachers, by Experience Level of Comparison Teacher.......................95

VIII.4 Differences in Effectiveness Between Experienced Teaching Fellows and 

Comparison Teachers, by Experience Level of Comparison Teacher.......................96

VIII.5 Differences in Effectiveness Between Teaching Fellows and Comparison 

Teachers Within Middle Schools and High Schools ..................................................98

A.1 District and School Recruiting .................................................................................A.6 

A.2 Number of Students Involved in Each Stage of Random Assignment 

and Data Collection...............................................................................................A.12

C.1 Teach For America Regions, as of August 2011.....................................................C.3 

C.2 Teach For America’s Teaching as Leadership Rubric .............................................C.4 

C.3 TNTP’s Teaching Fellows Programs, as of August 2011 ........................................C.5 
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

 xix

EXECUTIVE SUMMARY

Teach For America (TFA) and the Teaching Fellows programs are an important and 

growing source of teachers of hard-to-staff subjects in high-poverty schools, but comprehensive 

evidence of their effectiveness has been limited. This report presents findings from the first 

large-scale random assignment study of secondary math teachers from these programs. The study 

separately examined the effectiveness of TFA and Teaching Fellows teachers, comparing 

secondary math teachers from each program with other secondary math teachers teaching the 

same math courses in the same schools. The study focused on secondary math because this is a 

subject in which schools face particular staffing difficulties.

The study had two main findings, one for each program studied: 

1. TFA teachers were more effective than the teachers with whom they were 

compared. On average, students assigned to TFA teachers scored 0.07 standard 

deviations higher on end-of-year math assessments than students assigned to 

comparison teachers, a statistically significant difference. This impact is equivalent 

to an additional 2.6 months of school for the average student nationwide. 

2. Teaching Fellows were neither more nor less effective than the teachers with 

whom they were compared. On average, students of Teaching Fellows and students 

of comparison teachers had similar scores on end-of-year math assessments.

By providing rigorous evidence on the effectiveness of secondary math teachers from TFA 

and the Teaching Fellows programs, the study can shed light on potential approaches for 

improving teacher effectiveness in hard-to-staff schools and subjects. The study findings can 

provide guidance to school principals faced with the choice of hiring teachers who have entered 

the profession via different routes to certification. The findings can also aid policymakers and 

funders of teacher preparation programs by providing information on the effectiveness of 

teachers from various routes to certification that use different methods to identify, attract, train, 

and support their teachers.

Background

High-quality, effective teachers are critical to students’ success in the classroom (Aaronson 

et al. 2003; Chetty et al. 2011), yet little is known about how best to identify, attract, train, and 

support such teachers. The need for effective teachers is especially acute in schools serving lowincome students who already face numerous disadvantages (Monk 2007; Jacob 2007). These 

schools face particular difficulty attracting qualified teachers to teach secondary math and 

science classes (Ingersoll and Perda 2009; Ingersoll and May 2012). 
Effectiveness of TFA and Teaching Fellows Teachers 

 xx 

TFA and The New Teacher Project (TNTP) Teaching Fellows programs take a distinctive 

approach to addressing the need for high-quality teachers of hard-to-staff subjects in highpoverty schools.1 Like other programs that offer alternative routes to teacher certification, both 

TFA and the Teaching Fellows programs aim to lower the barriers to entering the teaching 

profession; both programs recruit individuals without prior teaching experience and enable them 

to begin teaching before completing all of the training requirements for certification. However, 

unlike most programs providing alternative routes to certification that do not have restrictive 

selection criteria and admit most applicants (Walsh and Jacobs 2007; Mayer et al. 2003), TFA 

and the Teaching Fellows programs have highly selective admissions criteria designed to admit 

only applicants who have demonstrated a high level of achievement in academics or other 

endeavors and who possess characteristics that the programs view as being associated with 

effective teaching.

Research Questions and Study Design

The study addresses two analogous primary research questions, one for each program 

studied: 

1. How effective are TFA teachers at teaching secondary math compared with other 

teachers teaching the same math courses in the same schools? 

2. How effective are Teaching Fellows at teaching secondary math compared with 

other teachers teaching the same math courses in the same schools? 

The study used an experimental design to learn about the effectiveness of teachers from each 

of the two programs studied. At the beginning of the school year, the study team assigned 

students who enrolled in an eligible middle or high school math course to either a class taught by 

a math teacher from the program being studied (TFA or Teaching Fellows) or to a similar math 

class in the same school taught by a teacher who did not participate in either of the programs

studied. This latter teacher is referred to as the comparison teacher. The comparison teacher 

could have entered teaching after completing all certification requirements (the traditional route 

to certification) or through a less selective alternative route to certification. Students were 

assigned to teachers randomly—that is, completely by chance—to ensure that there would be no 

systematic differences between the types of students assigned to the different types of teachers. 

To estimate the effectiveness of the TFA or Teaching Fellows teachers relative to the comparison 

teachers, we compared the end-of-year math test scores of students assigned to the different 

types of teachers. The study design is summarized in the box below. 

 1 TNTP, formerly known as The New Teacher Project, is a national nonprofit organization that partners with 

urban school districts to establish and operate local Teaching Fellows programs that recruit and train new teachers.
Effectiveness of TFA and Teaching Fellows Teachers 

 xxi 

Study Design

Experimental design. We used the same experimental design to separately examine the 

effectiveness of teachers from each of two programs—TFA and the Teaching Fellows programs. In 

each participating school, we identified “classroom matches”—two or more classes covering the same

middle or high school math course at the same level, with at least one class taught by a teacher from 

the program being studied (TFA or Teaching Fellows) and at least one class taught by another teacher, 

referred to as a comparison teacher, who did not enter teaching through a highly selective alternative 

route. The comparison teacher could have entered teaching through either a traditional or less 

selective alternative route to certification. In each classroom match, students were randomly assigned 

at the beginning of the school year to a class taught by a teacher from the program being studied or a 

class taught by a comparison teacher.

Sample. In order to obtain a large enough sample of teachers and students, we recruited 

participants into the study in both the 2009–2010 and 2010–2011 school years. The final TFA study 

sample consisted of 4,573 students, 111 classroom matches, 136 math teachers, 45 schools, and 

11 districts in 8 states. The final Teaching Fellows study sample consisted of 4,116 students, 

118 classroom matches, 153 math teachers, 44 schools, and 9 districts in 8 states. There was limited 

overlap between the two samples—only one-third of study districts, 9 percent of study schools, and 

less than three classroom matches provided study teachers from both the TFA and Teaching Fellows 

programs. Most (75 percent) of the classroom matches in the TFA study sample were in middle 

schools, while most (69 percent) of the classroom matches in the Teaching Fellows study sample were 

in high schools. Forty-one percent of the comparison teachers in the TFA sample entered teaching 

through less selective alternative routes to certification, compared with 27 percent of the comparison 

teachers in the Teaching Fellows sample. 

Data on teacher characteristics. To collect information on the characteristics of teachers in the 

study, we administered a survey to all teachers in the study in the spring of each of the study school 

years. We also collected teachers’ scores from either the Praxis II Middle School Mathematics 

assessment (for middle school math teachers) or the Praxis II Mathematics Content Knowledge 

assessment (for high school math teachers), administering the test to teachers who had not taken it 

previously and gathering existing scores from those who had. 

Data on outcomes. The math achievement of students assigned to teachers in the study was the 

key outcome used to evaluate the teachers’ effectiveness. Student math achievement was measured by 

math assessments administered at the end of the school year in which the students were randomly 

assigned. For students in grades 6 to 8, we obtained scores on state-required assessments. For students 

in grades 9 to 12, we administered end-of-course math assessments developed by the Northwest 

Evaluation Association (NWEA). The state assessments were expected to align more closely with 

state curriculum standards, whereas the NWEA assessments were expected to be less prone to floor or 

ceiling effects for high- and low-achieving students.

Analysis. To estimate the effectiveness of TFA or Teaching Fellows teachers relative to the 

comparison teachers, we compared end-of-year test scores of the students assigned to the TFA or 

Teaching Fellows teachers and the students assigned to the comparison teachers. We estimated the 

effectiveness of TFA and Teaching Fellows teachers separately.
Effectiveness of TFA and Teaching Fellows Teachers 

 xxii 

This experimental design ensured that any differences in math achievement between the 

students of TFA or Teaching Fellows teachers and the students of comparison teachers could be 

attributed to differences in the teachers’ effectiveness rather than differences in the 

characteristics of the students they taught, the subject they taught, or the school in which they 

taught. 

Although students in the study were randomly assigned among teachers from different 

routes to certification, teachers were not randomly assigned to these routes. TFA and the 

Teaching Fellows programs may attract different types of candidates than other routes to 

certification—these differences can arise both from the programs’ approaches to recruitment and 

selection and from the teachers’ decisions on which programs to apply to and attend. Therefore, 

differences in effectiveness between TFA teachers and comparison teachers, and between 

Teaching Fellows and comparison teachers, do not reflect the effectiveness of the programs 

alone. Instead, they reflect the influence of both differences in the types of individuals who 

choose to enter teaching through TFA or a Teaching Fellows program versus some other training 

program and differences in the recruitment and selection procedures and training and support the 

programs offer. The study cannot rigorously disentangle these components. 

No restriction was placed on the experience levels of the TFA teachers, Teaching Fellows, 

or comparison teachers. Hence, in some comparisons, novice TFA (or Teaching Fellows) 

teachers were compared with more experienced comparison teachers. However, the study also 

explored the effectiveness of the TFA (or Teaching Fellows) teachers when they were compared 

with teachers with similar levels of experience.

The study was not designed to compare the effectiveness of TFA teachers with that of 

Teaching Fellows. There are some substantive differences between the programs; for instance, 

TFA requires its teachers to commit to two years in teaching, whereas Teaching Fellows 

programs expect their teachers to teach for many years. In addition, TFA focuses more on 

recruiting new college graduates, whereas the Teaching Fellows programs focus more on 

recruiting professionals who want to switch careers. However, there are also many reasons not 

directly related to the effectiveness of the programs that might lead estimates of the effectiveness 

of their teachers to differ. Students were not randomly assigned between TFA teachers and 

Teaching Fellows, and thus any differences in the estimated effectiveness of TFA teachers and 

Teaching Fellows could be due to differences in the students they teach, the teachers with whom 

they were compared, or the schools or districts in which they teach. 

In fact, TFA and Teaching Fellows teachers in the study largely taught in different schools 

and districts—only one-third of study districts, 9 percent of study schools, and less than three 

classroom matches provided study teachers from both the TFA and Teaching Fellows programs.

Moreover, TFA teachers in the study were more likely to teach in middle schools, whereas

Teaching Fellows were more likely to teach in high schools, consistent with the fact that, 

nationwide, secondary math teachers from TFA are more likely to be placed in middle schools

and those from Teaching Fellows programs are more likely to be placed in high schools. Because 

the challenges of teaching may vary across grade levels and because the study used different 

student assessments at the middle and high school levels, it could be misleading to directly 

compare the effectiveness of the TFA and Teaching Fellows teachers in the study. Finally, TFA 

and Teaching Fellows teachers were also compared with different types of teachers; 41 percent 

of the teachers with whom TFA teachers were compared entered teaching through less selective 

alternative routes to certification, while 27 percent of the teachers with whom Teaching Fellows 
Effectiveness of TFA and Teaching Fellows Teachers 

 xxiii

were compared entered teaching through less selective alternative routes. For all of these 

reasons, the study findings cannot be used to compare the effectiveness of TFA and Teaching 

Fellows teachers. 

Teach For America

Selection, Training, and Support of TFA Program Participants

TFA is a national program that places teachers in numerous regions across the country—43 

as of August 2011. TFA recruits, selects, trains, and supports its teachers. Each of these elements 

of the program could influence the effectiveness of its secondary math teachers, so information 

on TFA’s operations can provide important context for interpreting the study’s findings. 

TFA focuses its recruitment efforts on new college graduates, targeting seniors at many of 

the nation’s most distinguished colleges and universities. Individuals apply to TFA as a whole, 

not to a regional program; they may specify regional preferences, but the program will assign 

them to whatever region is deemed the best fit. Furthermore, TFA requires its teachers to commit 

to two years in teaching. The selection process includes a written application, a telephone 

interview, an analysis and writing exercise, an in-person interview, a monitored group 

discussion, and a five-minute sample teaching lesson. Using a computer-based algorithm to help 

identify applicants with the greatest potential to be effective teachers, TFA accepts about 12 

percent of applicants nationwide. 

TFA teachers receive training and support both before and after they start teaching. The 

main training experience before participants become classroom teachers is an intensive fiveweek summer institute in which they receive formal instruction and engage in practice teaching. 

Most TFA regional programs do not provide all of the instruction necessary for certification, so 

participants typically must also enroll in a separate state-authorized alternative certification 

program in order to complete coursework toward their certification during their first years of 

teaching. Staff from participating TFA programs reported that the alternative certification 

programs where most of their secondary math teachers had enrolled in the three preceding years 

involved an average of 137 hours of coursework. In addition, TFA provides information, 

feedback, and mentoring to its teachers in their first one to two years of teaching. 

TFA works with districts to place teachers in high-need schools. Compared with the average 

U.S. secondary school, secondary schools with new TFA teachers are more likely to be located 

in urban areas and to be eligible for Title I funds for schools with high percentages of lowincome students. In addition, they serve a higher percentage of students from racial and ethnic 

minorities and students eligible for free or reduced-price lunch. 

Study Schools with TFA Teachers

Because the study’s findings about TFA teachers pertain to the types of schools represented 

in the TFA study sample, it is important to understand the characteristics of these schools.

Schools with TFA teachers in the study served disadvantaged populations. Eighty-two

percent of schools with TFA teachers in the study were eligible for Title I funds. Eighty-nine 

percent of students in schools with TFA study teachers were Hispanic or black. Students in the 
Effectiveness of TFA and Teaching Fellows Teachers 

 xxiv 

TFA study sample scored below average for their states in both reading and math before 

participating in the study. 

Schools with TFA teachers in the study were similar to schools employing secondary 

math teachers from TFA nationwide. Over 80 percent of students at both sets of schools were 

from racial and ethnic minority groups, and close to 80 percent were eligible for free or reducedprice lunch. However, there were some differences—for example, urban schools were 

overrepresented and charter schools were underrepresented in the TFA study sample.

Teachers in the TFA Sample

Interpreting the study estimates of teacher effectiveness requires understanding the 

characteristics of both TFA teachers and the teachers with whom they were compared. TFA has 

unique procedures for recruiting and selecting individuals with particular characteristics that it 

believes are associated with effectiveness in the classroom. Hence, it is not surprising that we 

found many differences in the characteristics and experiences of the TFA teachers in the study 

and the teachers with whom they were compared.

TFA teachers had less teaching experience than comparison teachers. Consistent with 

TFA requiring a two-year commitment to teaching, TFA teachers in our study had significantly 

less teaching experience than comparison teachers. Eighty-three percent of the TFA teachers 

were in either their first or second year of teaching during the study school year, compared with 

10 percent of the comparison teachers. TFA teachers in the study also had less nonteaching work 

experience than the comparison teachers.

TFA teachers were less likely than comparison teachers to be from racial or ethnic 

minorities and less likely to be female. Eighty-nine percent of TFA teachers in the study were 

white and non-Hispanic, compared with 30 percent of the comparison teachers. Sixty-one 

percent of TFA teachers in the study were female, compared with 79 percent of the comparison 

teachers. In terms of both race and gender distribution, TFA teachers were more similar to 

secondary teachers nationwide than the comparison teachers—84 percent of secondary teachers 

nationwide were white and non-Hispanic, and 59 percent were female.

TFA teachers had graduated from more selective colleges than comparison teachers.

Eighty-one percent of TFA teachers in the study had graduated from a selective college or 

university, compared with 23 percent of the comparison teachers.

2

TFA teachers were less likely than comparison teachers to have majored in math, but 

scored higher on a test of math content knowledge. Relative to the comparison teachers, TFA 

teachers in the study were less likely to have a major or minor in math or secondary math 

education; they had also taken significantly fewer college-level math courses. Despite these 

differences, on average, TFA teachers scored significantly higher on the Praxis II math exam 

than the comparison teachers. TFA teachers who took the Mathematics Content Knowledge Test 

scored 22 points (or 0.93 standard deviations) higher than their counterparts from other routes; 

 2 College selectivity was defined based on Barron’s Profiles of American Colleges 2003. Selective colleges 

were defined as those ranked by Barron’s as very competitive, highly competitive, or most competitive.
Effectiveness of TFA and Teaching Fellows Teachers 

 xxv 

TFA teachers who took the Middle School Mathematics Test outscored their counterparts by 22 

points (or 1.19 standard deviations). 

TFA Teachers Were More Effective Than Comparison Teachers

On average, students assigned to TFA teachers scored higher (by 0.07 standard deviations) 

on end-of-year math assessments than students assigned to comparison teachers (Figure ES.1). 

This difference in math scores was equivalent to an increase in student achievement from the 

27th to the 30th percentile. This difference also translated into an additional 2.6 months of school 

for the average student nationwide. 

In addition, TFA teachers were more effective than the teachers with whom they were 

compared across several key teacher subgroups we examined.

• TFA teachers were more effective than their counterparts from both traditional 

and less selective alternative routes to certification. One criticism of alternative 

routes to certification, both less and highly selective routes, is that, because they 

provide less preparation for teaching, their teachers are less effective than teachers 

from traditional routes to certification (Darling-Hammond 1990, 2000; DarlingHammond et al. 2005). To explore the validity of this criticism as it applies to TFA 

teachers, we conducted a subgroup analysis estimating the effectiveness of TFA 

teachers relative to their counterparts from traditional routes. We found that students 

of TFA teachers outperformed those of teachers from traditional routes by 0.06 

standard deviations. We also examined the effectiveness of TFA teachers relative to 

their counterparts from less selective alternative routes—the hard-to-staff schools in 

which TFA teachers are placed may often be faced with the choice of hiring a TFA 

teacher or a teacher from these other alternative routes. We found that students of 

TFA teachers scored higher than students of teachers from less selective alternative 

routes by 0.09 standard deviations. 

• Novice TFA teachers were more effective than both novice and experienced 

comparison teachers. Another common criticism of TFA is that it seeks teachers 

willing to make a two-year rather than a longer-term commitment to teaching. Critics 

claim that too many TFA teachers leave teaching before they accumulate the 

experience needed to be as effective as their counterparts from other routes (Heilig 

and Jez 2010). To examine this concern, we compared novice TFA teachers (defined 

as those in their first three years of teaching) with both novice and experienced 

comparison teachers. We found that novice TFA teachers were more effective than 

comparison teachers regardless of the comparison teachers’ experience. Students of 

TFA teachers in their first three years of teaching scored higher on math assessments 

(by 0.08 standard deviations) than students of their counterparts in their first three 

years of teaching. Students of TFA teachers in their first three years of teaching also 

had higher student math achievement (by 0.07 standard deviations) compared with 

students of comparison teachers with more than three years of experience.
Effectiveness of TFA and Teaching Fellows Teachers 

 xxvi 

Figure ES.1. Differences in Effectiveness Between Teach For America Teachers and Comparison Teachers, 

Overall and by Entry Route into Teaching

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

TFA versus 

All Comparison Teachers

TFA versus Teachers 

from Traditional

Routes

TFA versus Teachers 

from Less Selective 

Alternative Routes

Difference in Effectiveness

(in standard deviations of test scores)

0.06*

0.09** 0.07**

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

 *Estimate is statistically significant at the 0.05 level based on a two-tailed test after adjusting for multiple hypothesis 

testing.

**Estimate is statistically significant at the 0.01 level based on a two-tailed test after adjusting for multiple hypothesis 

testing.

TFA = Teach For America.

• TFA teachers were more effective than comparison teachers in both middle and 

high schools. Because the effective teaching of math might require different 

knowledge or skills depending on the level of math being taught, we examined TFA 

teachers’ effectiveness separately in middle and high schools. We found that TFA 

teachers were more effective than comparison teachers at both the middle and high 

school levels. At the middle school level, students of TFA teachers outperformed 

students of comparison teachers by 0.06 standard deviations. At the high school level, 

students of TFA teachers outperformed students of comparison teachers by 0.13 

standard deviations. 

Teaching Fellows

Selection, Training, and Support of Teaching Fellows Program Participants 

TNTP works with districts—19 as of August 2011—to establish locally run Teaching 

Fellows programs. The local programs have distinct identities, but TNTP guidance ensures basic 

consistency in their approach to recruiting, selecting, training, and supporting their teachers. 

Teaching Fellows programs accept new college graduates but focus their recruitment efforts 

more on professionals who want to switch careers. Individuals apply to a specific Teaching 

Fellows program in the locality in which they want to teach. Teaching Fellows programs expect 

their participants to make an open-ended commitment to teaching rather than a short-term 
Effectiveness of TFA and Teaching Fellows Teachers 

 xxvii 

commitment. The selection process includes a written application, an analysis and writing 

exercise, an in-person interview, a monitored group discussion, and a five-minute sample 

teaching lesson. Trained staff apply specific selection criteria and use their judgment to identify 

applicants with the greatest potential to be effective teachers. Teaching Fellows programs 

nationwide accept about 13 percent of applicants. 

Teaching Fellows teachers receive training and support both before and after they start 

teaching. The main training experience before participants become classroom teachers is an 

intensive five- to seven-week summer institute in which they receive formal instruction and 

engage in practice teaching. Most Teaching Fellows programs do not provide all of the 

instruction necessary for certification, so participants typically must also enroll in a separate 

state-authorized alternative certification program in order to complete coursework toward their 

certification during their first years of teaching. Staff from participating Teaching Fellows 

programs reported that the alternative certification programs where most of their secondary math 

teachers had enrolled in the three preceding years involved an average of 137 hours of 

coursework. In addition, Teaching Fellows programs provide information, feedback, and 

mentoring to their teachers in their first one to two years of teaching.

Teaching Fellows programs work with districts to place teachers in high-need schools. 

Compared with the average U.S. secondary school, secondary schools with new Teaching 

Fellows teachers are more likely to be located in urban areas and to be eligible for Title I funds. 

In addition, they serve a higher percentage of students from racial and ethnic minorities and 

students eligible for free or reduced-price lunch. 

Study Schools with Teaching Fellows

Because the study’s findings about Teaching Fellows pertain to the types of schools 

represented in the Teaching Fellows study sample, it is important to understand the 

characteristics of these schools.

Schools with Teaching Fellows in the study served disadvantaged populations. Eightytwo percent of all study schools with Teaching Fellows were eligible for Title I funds. More than 

80 percent of students in study schools with Teaching Fellows were Hispanic or black. Students 

in the Teaching Fellows study sample scored below average for their states in both reading and 

math before participating in the study. 

Schools with Teaching Fellows in the study were similar to schools employing 

secondary math teachers from Teaching Fellows programs nationwide. Over 80 percent of 

students at both sets of schools were from racial or ethnic minority groups, and close to 80 

percent were eligible for free or reduced-price lunch. However, as in the TFA study sample, 

urban schools were overrepresented and charter schools were underrepresented in the Teaching 

Fellows study sample.

Teachers in the Teaching Fellows Sample

Teaching Fellows programs have unique procedures for recruiting and selecting individuals 

with particular characteristics that they believe are associated with effectiveness in the 

classroom. Hence, as with TFA teachers and their counterparts, we found many differences in 
Effectiveness of TFA and Teaching Fellows Teachers 

 xxviii 

the characteristics and experiences of the Teaching Fellows in the study and the teachers with 

whom they were compared. 

Teaching Fellows had less teaching experience than comparison teachers. Consistent 

with the Teaching Fellows programs’ expectations that their teachers remain in teaching for 

many years, 76 percent of Teaching Fellows had three or more years of teaching experience. 

However, on average, they still had less experience than comparison teachers. Twenty-three 

percent of Teaching Fellows were in their first or second year of teaching, compared with 7 

percent of the comparison teachers. This may reflect the fact that the Teaching Fellows programs 

were only launched in the year 2000 or after, and hence teachers from these programs have not 

had time to gain decades of experience. Consistent with the focus of Teaching Fellows programs 

on recruiting professionals to transition into teaching, Teaching Fellows had more nonteaching 

work experience than did the comparison teachers. 

Teaching Fellows were less likely than comparison teachers to be from racial or ethnic 

minorities. Seventy-one percent of Teaching Fellows in the study were white and non-Hispanic, 

compared with 43 percent of the comparison teachers. Teaching Fellows were more similar to 

secondary teachers nationwide than the comparison teachers in terms of racial and ethnic 

distribution—84 percent of secondary teachers nationwide were white and non-Hispanic. Both 

Teaching Fellows and comparison teachers were similar to the average secondary teacher 

nationwide in terms of gender distribution. Fifty-four percent of Teaching Fellows and 57 

percent of comparison teachers were female, compared with 59 percent of secondary teachers 

nationwide—these differences were not statistically significant. 

Teaching Fellows had graduated from more selective colleges than comparison 

teachers. Seventy-two percent of Teaching Fellows in the study had graduated from a selective 

college or university, compared with 34 percent of the comparison teachers.3

Teaching Fellows were less likely than comparison teachers to have majored in math, 

but scored higher on a test of math content knowledge. Relative to the comparison teachers, 

Teaching Fellows were less likely to have majored in math or secondary math education; 

nonetheless, they had taken about the same number of math courses. Despite being less likely to 

have majored in math, Teaching Fellows scored significantly higher on the Praxis II math exam 

than the comparison teachers. Teaching Fellows who took the Mathematics Content Knowledge 

Test scored 19 points (or 0.80 standard deviations) higher than their counterparts from other 

routes, whereas Teaching Fellows who took the Middle School Mathematics Test outscored their 

counterparts by 17 points (or 0.92 standard deviations). 

Teaching Fellows Did Not Differ in Effectiveness from Comparison Teachers Overall, but 

the Study Found Differences for Some Subgroups

On average, students of Teaching Fellows and students of comparison teachers had similar 

scores on end-of-year math assessments (Figure ES.2). However, we found that effectiveness 

varied for specific subgroups of Teaching Fellows and comparison teachers: 

 3 College selectivity was defined based on Barron’s Profiles of American Colleges 2003. Selective colleges 

were defined as those ranked by Barron’s as very competitive, highly competitive, or most competitive.
Effectiveness of TFA and Teaching Fellows Teachers 

 xxix

Figure ES.2. Differences in Effectiveness Between Teaching Fellows and Other Math Teachers in the Same 

Schools, Overall and by Entry Route into Teaching

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

Teaching Fellows versus

All Comparison Teachers

Teaching Fellows versus

Teachers from

Traditional Routes

Teaching Fellows versus

Teachers from 

Less Selective

Alternative Routes

Difference in Effectiveness

(in standard deviations of test scores)

-0.03

0.13*

0.00

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

 *Estimate is statistically significant at the 0.05 level based on a two-tailed test after adjusting for multiple hypothesis 

testing.

**Estimate is statistically significant at the 0.01 level based on a two-tailed test after adjusting for multiple hypothesis 

testing.

• Teaching Fellows were more effective than teachers from less selective 

alternative routes to certification, and neither more nor less effective than 

teachers from traditional routes to certification. As an alternative route to teacher 

certification, Teaching Fellows programs are subject to the same criticisms mentioned 

earlier regarding TFA—specifically, that they, like other alternative routes to 

certification, provide insufficient preparation for teaching relative to traditional 

routes. However, we found that students of Teaching Fellows did not perform 

significantly better or worse than students of teachers from traditional routes. We also 

compared the effectiveness of Teaching Fellows with that of teachers from less 

selective alternative routes, as many schools may be faced with the choice of hiring a 

Teaching Fellow or a teacher from these other alternative routes. We found that 

students of Teaching Fellows outperformed students of teachers from less selective

alternative routes by 0.13 standard deviations. 

• Novice Teaching Fellows were more effective than novice comparison teachers, 

but this difference dissipated among more experienced teachers. Schools may 

often be faced with the choice of hiring a new Teaching Fellow or a new teacher from 

some other route. We found that novice Teaching Fellows (those in their first three 

years of teaching) were more effective than novice comparison teachers, increasing

student achievement in math by 0.13 standard deviations. However, when Teaching 

Fellows from all levels of experience were compared with comparison teachers 

whose experience differed by no more than two years, there was no statistically 
Effectiveness of TFA and Teaching Fellows Teachers 

 xxx 

significant difference in math achievement between the students of these two groups 

of teachers.

• Teaching Fellows were neither more nor less effective than comparison teachers 

in both middle and high schools. We examined Teaching Fellows’ effectiveness 

separately at the middle and high school levels. We found that math achievement did 

not differ significantly between students of Teaching Fellows and students of 

comparison teachers at either the middle or high school level. 

Observed Characteristics and Teacher Effectiveness

Because teachers in the study varied substantially in their effectiveness, the study provided 

an opportunity to examine the associations between specific teacher characteristics and student 

math achievement. This analysis used the full sample of teachers in our study—TFA teachers, 

Teaching Fellows, and comparison teachers. Understanding the relationship between teacher 

characteristics and effectiveness can inform policies to improve teacher effectiveness and 

principals’ hiring decisions. Because this analysis relied on nonexperimental methods, the results 

can generate hypotheses about the characteristics of effective math teachers, but cannot provide 

conclusive evidence about whether these characteristics caused the higher student math 

achievement.

Consistent with previous research (Kane et al. 2008), we found that different teachers who 

took the same route into teaching varied considerably in their effectiveness in the classroom. Yet, 

few observed characteristics appeared to explain these differences. We examined eight teacher 

characteristics: (1) the selectivity of the teacher’s undergraduate institution, (2) amount of 

college-level math coursework completed, (3) use of college-level math in a prior nonteaching 

position, (4) performance on Praxis II math content knowledge assessments for teachers, 

(5) amount of pedagogy instruction received, (6) extent of student teaching completed, 

(7) amount of coursework taken during the school year, and (8) years of teaching experience. Of 

these characteristics, two were consistently associated with student achievement, and a third was 

associated with student achievement in some but not all analyses conducted: 

1. Teacher effectiveness increased with teacher experience. Students assigned to a 

second-year teacher were predicted to score 0.08 standard deviations higher on math 

assessments than students assigned to a first-year teacher. Among teachers with at 

least five years of teaching experience, each additional year of teaching experience 

was associated with an increase of 0.005 standard deviations in student achievement. 

2. Teacher effectiveness declined with increasing amounts of teacher coursework 

during the school year. For each additional 10 hours of coursework that teachers 

took during the school year, the math achievement of their students was predicted to 

drop by 0.002 standard deviations. These findings imply that a teacher who took an 

average amount of coursework during the school year, whether for initial certification 

or any other certification or degree, decreased student math achievement by 0.04 

standard deviations relative to a teacher who took no coursework while teaching.

Although we cannot directly examine why coursework was negatively related to 

teacher effectiveness, the findings are consistent with the hypothesis that coursework 

taken during the school year diverts teachers’ energy and attention from the classes 

they are teaching.
Effectiveness of TFA and Teaching Fellows Teachers 

 xxxi 

3. In some of the analyses we conducted, greater math content knowledge was 

positively associated with teacher effectiveness in high schools, but not in middle 

schools. In high schools, we found that teachers’ math content knowledge, as 

measured by their scores on the Praxis II math assessments, was positively associated 

with student achievement in some of our sensitivity analyses, but not in our main 

analysis. Our main analysis indicates that a one standard deviation increase in a high 

school teacher’s Praxis II score—equivalent to rising from the 50th to the 84th 

percentile of Praxis II scores—was associated with an increase in student math 

achievement of 0.04 standard deviations, but this difference was not statistically 

significant at the 5 percent level (p-value = 0.051). Our sensitivity analyses found that 

high school students taught by teachers in the top half of the Praxis II score

distribution had higher math achievement, by a statistically significant degree, than 

those taught by teachers in the bottom half of the distribution. In middle schools, we 

found no association between teachers’ scores on the Praxis II and student 

achievement.

Collectively, the teacher characteristics we examined could not account for any portion of 

the difference in effectiveness between TFA teachers and the teachers with whom they were 

compared. Although TFA teachers would have been predicted to be less effective than 

comparison teachers on the basis of their characteristics—primarily because of the TFA teachers’ 

relative inexperience in the classroom—TFA teachers were, in fact, more effective than their 

counterparts. The nonexperimental methods used for this analysis cannot provide conclusive 

evidence about the causal relationship between the characteristics examined and student math 

achievement, but the results suggest that TFA teachers’ greater effectiveness might have been 

driven by teacher characteristics that we did not observe. 

Conclusions

Teachers in the study who entered teaching through either TFA or the Teaching Fellows 

programs were at least as effective at teaching secondary math as those who entered via 

traditional or less selective alternative routes to certification, and in some cases they were more 

effective. Therefore, TFA and the Teaching Fellows programs represent two examples of 

program models for recruiting, selecting, training, and supporting teachers that can address 

teacher shortages in secondary math within high-need schools without decreasing student 

achievement.

The study findings can provide guidance to school principals considering hiring decisions. 

Although a specific teacher from TFA or a Teaching Fellows program might be more or less 

effective than a teacher from a traditional or less selective alternative route, our findings can shed 

light on the average effectiveness of the teachers from TFA relative to teachers from another 

route and on the average effectiveness of Teaching Fellows relative to teachers from another 

route. 

Our study suggests that, on average, principals of the secondary schools in the study would 

raise student math achievement by hiring a TFA teacher rather than a teacher from a traditional 

or less selective alternative route to teach the math classes examined in the study. Although the 

TFA teachers in the study were less experienced, on average, than the comparison teachers, 

students of TFA teachers outperformed students of other teachers in the same grades and schools 

by a statistically significant margin. This result held true whether the comparison teachers were 
Effectiveness of TFA and Teaching Fellows Teachers 

 xxxii 

from traditional routes or less selective alternative routes. Similarly, students of TFA teachers in 

their first three years of teaching outperformed students of other novice teachers in the same 

grades and schools as well as students of more experienced teachers. This latter finding is 

particularly important given the fact that TFA requires its teachers to make only a two-year 

commitment to teaching. 

Our main impact findings for Teaching Fellows suggest that a secondary school in the study 

would experience neither higher nor lower student math achievement if its principal hired 

Teaching Fellows math teachers rather than math teachers from traditional or less selective 

alternative routes. Nevertheless, a principal faced with a more specific choice between a novice 

Teaching Fellow and a novice teacher from another route or a choice between a Teaching Fellow 

and a teacher from a less selective alternative route should expect higher student achievement, on 

average, from hiring the Teaching Fellow. If comparing a Teaching Fellow with another teacher 

with the same years of experience, on average, the principal would do just as well hiring either 

teacher.
Effectiveness of TFA and Teaching Fellows Teachers 

1 

I. INTRODUCTION

 

High-quality, effective teachers are critical to students’ success in the classroom (Aaronson 

et al. 2003; Rockoff 2004; Hanushek et al. 2005; Rivkin et al. 2005; Chetty et al. 2011), yet little 

is known about how best to identify, attract, train, and support such teachers. The need for 

effective teachers is especially acute in schools serving low-income students who already face 

numerous disadvantages (Monk 2007; Jacob 2007). These schools face particular difficulty 

attracting qualified teachers to teach secondary math and science classes (Ingersoll and Perda 

2009; Ingersoll and May 2012). 

Two programs—Teach For America (TFA) and the TNTP Teaching Fellows programs—

take a distinctive approach to addressing the need for high-quality teachers of hard-to-staff 

subjects in high-poverty schools.4 Like other programs that offer alternative routes to teacher 

certification (AC routes), both TFA and the Teaching Fellows programs aim to lower the barriers 

to entering the teaching profession—both programs recruit new college graduates and 

professionals without prior teaching experience and enable them to begin teaching before 

completing all of the training requirements for certification. However, unlike most programs 

providing alternative routes to certification that do not have restrictive selection criteria and 

admit most applicants (Walsh and Jacobs 2007; Mayer et al. 2003), TFA and the Teaching 

Fellows programs have highly selective admissions criteria designed to admit only applicants 

who have demonstrated a high level of achievement in academics or other endeavors and who 

possess characteristics that the programs view as being associated with effective teaching. Both 

programs provide their teachers with intensive training the summer before they begin teaching 

and provide ongoing support and professional development after their teachers begin teaching. 

To learn about the effectiveness of teachers from these programs, the U.S. Department of 

Education’s (ED’s) Institute of Education Sciences (IES) commissioned an evaluation of the 

impact on student achievement of middle and high school math teachers from the TFA and 

Teaching Fellows programs. The evaluation followed an experimental design: students were 

randomly assigned to a class taught by a teacher from either TFA or a Teaching Fellows program 

or to a class taught by a comparison teacher, a teacher who entered the teaching profession 

through a traditional or less selective alternative route to certification. Because the students were 

randomly assigned, any difference in the outcomes of students taught by a TFA or Teaching 

Fellows teacher and the outcomes of students taught by a comparison teacher can be attributed to 

differences in the teachers’ effectiveness.5 The study was conducted by Mathematica Policy 

Research, Branch Associates, and Chesapeake Research Associates.

4 TNTP, formerly known as The New Teacher Project, is a national nonprofit organization that partners with 

urban school districts to operate local Teaching Fellows programs that recruit and train new teachers.

5 Because teachers were not randomly assigned between TFA, Teaching Fellows programs, less selective 

alternative routes, and traditional routes, estimates of effectiveness reflect the combined effect of the characteristics 

and motivations of teachers who choose to enter teaching through each route and the recruitment and selection 

procedures and training and support provided by the programs themselves.
Effectiveness of TFA and Teaching Fellows Teachers 

2 

A. Background

1. Concerns about Teacher Quality in Hard-to-Staff Schools and Subjects

ED has a significant interest in programs and policies designed to address teacher shortages 

in high-need schools and hard-to-staff subjects, and in approaches for improving teacher quality 

more generally. In recognition of the difficulties schools face filling certain vacancies with 

qualified teachers, Title II of the No Child Left Behind Act of 2001 (NCLB) allows state funds to 

be used for “carrying out programs that establish, expand, or improve alternative routes for state 

certification of teachers and principals, especially in the areas of mathematics and science.” 

Title II funds also support research on issues of teacher preparation and teacher quality. Because 

TFA and the Teaching Fellows represent a distinctive approach to addressing issues of teacher 

quality and teacher shortages in hard-to-staff schools and subjects, research on the success of 

their approach could assist ED in developing policies to address these issues. 

Teacher quality is of particular concern in schools serving high concentrations of lowincome students. On average, low-income students are taught by teachers with weaker 

qualifications—less teaching experience and lower certification examination scores—than 

students who are not economically disadvantaged (Clotfelter et al. 2007; Lankford et al. 2002; 

Carroll et al. 2000). Although the evidence is mixed, some studies have also found that teachers 

in high-poverty schools are, on average, less effective than those elsewhere (Glazerman and Max 

2011; Sass et al. 2010). Taken together, the evidence suggests that high-poverty schools tend to 

have greater difficulty in attracting and retaining qualified, effective teachers (Monk 2007; Jacob 

2007). 

Math and science are among the subjects for which secondary schools—especially those 

serving lower-income populations—have the greatest difficulty retaining qualified teachers. 

Relative to the new supply of teachers in a given subject, rates of departure from teaching are 

highest among math and science teachers. Consequently, school principals report greater 

difficulty filling vacancies in math and science than in other subjects (Ingersoll and Perda 2009). 

For high-poverty schools in particular, these challenges are compounded by a net tendency for 

math and science teachers to transfer from high- to low-poverty schools (Ingersoll and May 

2012). 

2. Policies Targeting the Teacher Pipeline

One approach for improving teacher quality seeks to expand the supply of qualified, capable 

individuals who enter teaching. One of the most common policies to expand the teacher supply is 

the use of AC routes. Instead of requiring teachers to complete all certification-related 

coursework and student teaching before becoming full-time teachers—the traditional route to 

teaching certification (TC route)—these AC routes enable participants to begin full-time 

teaching before completing all the requirements for certification. Participants in a typical AC

program, to the extent one exists, take a few weeks of coursework in the summer, possibly 

supplemented with some fieldwork—such as observing and helping in a summer school 

classroom—and then begin regular, full-time teaching in the fall. During their first (and 

sometimes second) year of teaching, they complete the remaining required coursework and then 

receive their teaching certificates. As of 2010, 45 states and the District of Columbia reported 

that they had approved AC routes (U.S. Department of Education 2011). 
Effectiveness of TFA and Teaching Fellows Teachers 

3 

Most AC programs do not have very selective entrance requirements and consequently 

admit nearly all applicants (Mayer et al. 2003; Walsh and Jacobs 2007). A large-scale, random 

assignment evaluation of elementary school teachers from less selective AC programs—those 

that did not require applicants to have a grade point average above 3.0—found that teachers from 

these programs were neither more nor less effective than teachers in the same schools who 

entered teaching through a TC program and had about the same amount of teaching experience 

(Constantine et al. 2009). 

3. TFA and the Teaching Fellows Programs

TFA, founded in 1989, and TNTP, founded by a TFA alumna in 1997, both seek to provide 

high-quality teachers to low-income schools. While TFA directly provides teachers to school 

districts, TNTP instead established locally run Teaching Fellows programs that recruit and train 

teachers, also known as Teaching Fellows, to teach in low-income schools. In 2011, TFA placed 

approximately 5,200 new teachers, or “corps members,” in classrooms in 43 regions across the 

country; TNTP’s 19 Teaching Fellows programs placed approximately 1,900 new Teaching 

Fellows in classrooms.

Both TFA and the Teaching Fellows programs are highly selective, admitting less than 

15 percent of applicants nationwide. The programs have a multi-stage application process that 

includes in-person interviews, group discussions, writing exercises, and sample teaching lessons. 

Both programs apply specific selection criteria based on factors they believe to be associated 

with effective teaching. 

Before entering the classroom, TFA and Teaching Fellows programs require participants to 

attend an intensive summer training program. These five- to seven-week summer institutes 

include both instruction and practice teaching. The programs typically do not provide 

certification; hence, TFA and Teaching Fellows participants must also enroll in a separate, stateauthorized AC program. Both programs provide information, feedback, and mentoring to the 

teachers in their first one to two years of teaching. 

Despite their many similarities, TFA and Teaching Fellows programs differ in three main 

ways:

1. Recruitment focus. Although both TFA and Teaching Fellows programs recruit new 

college graduates and more seasoned professionals, TFA focuses more on recruiting 

new college graduates, whereas the Teaching Fellows programs focus more on 

recruiting professionals who want to switch careers. 

2. Teaching commitment. TFA requires its teachers to commit to two years in 

teaching. Teaching Fellows programs do not ask their teachers for a minimum time 

commitment but expect them to teach for many years.

3. Choice of teaching location. Individuals apply to a specific Teaching Fellows 

program in the locality in which they want to teach, but applicants to TFA apply to 

the national program and are assigned by the program to a region. 

Appendix C provides a detailed description of the similarities and differences between the two 

programs. 
Effectiveness of TFA and Teaching Fellows Teachers 

4 

Proponents of TFA and the Teaching Fellows programs argue that they are important 

sources of new teachers for disadvantaged schools, whereas critics of the programs argue that 

teachers who enter the profession through these programs and other AC routes are less well 

prepared than those who enter through TC programs and thus could be less effective (DarlingHammond 1990). An additional criticism of TFA is that because it expects a commitment of only 

two years, TFA teachers are less likely than other teachers to remain in the profession and 

become more effective with experience (Heilig and Jez 2010).

4. Past Research on Teachers from TFA and the Teaching Fellows Programs

Despite the controversy over the effectiveness of teachers from TFA and the Teaching 

Fellows programs, the most rigorous available experimental evidence suggests that TFA teachers 

at the elementary school level are more effective than their non-TFA counterparts at teaching 

math, and neither more nor less effective at teaching reading. Research on the Teaching Fellows 

programs is more limited, with mixed results. No rigorous experimental study of TFA and 

Teaching Fellows programs has been conducted at the secondary level, a gap this study seeks to 

fill.

Experimental evidence. To date, there have been no large-scale experimental studies of the 

effectiveness of Teaching Fellows and only one experimental study of the effectiveness of TFA 

teachers, focused at the elementary school level.

6 Decker et al. (2004) randomly assigned nearly 

1,800 students to either TFA teachers or teachers who received their certification through other 

routes within 17 elementary schools across seven districts. No limit was placed on the years of 

experience for either group of teachers, but 93 percent of the TFA teachers were “novices” (with 

no more than three years of experience), compared with 31 percent of the comparison teachers. 

The results showed that students of TFA teachers performed as well as students of non-TFA 

teachers in reading and scored statistically better in math (by approximately 0.15 standard 

deviations). A subgroup analysis of novice TFA teachers compared with novice non-TFA 

teachers found the difference in math scores was even greater (0.26 standard deviations) and still 

statistically significant; no discernible difference was found for this subgroup comparison in 

reading.

Nonexperimental evidence. Three recent nonexperimental studies have examined the 

student achievement of TFA and Teaching Fellows teachers based on a variety of analytic 

methods to control for nonrandom sorting of students to teachers. Boyd et al. (2006) and Kane et 

al. (2008) examined the achievement of students taught by TFA teachers in New York City 

public schools. Both used longitudinal data on students and compared students with teachers who 

entered the profession via different routes within the same school, controlling for the student’s 

prior achievement. Boyd et al. (2006) found that, in math, students of TFA teachers scored 

higher than those of TC teachers at the middle school level, but lower at the elementary school

level. In language arts, they found that students of TFA teachers scored lower than those of TC 

teachers at both the elementary and middle school levels. Kane et al. (2008) found that students 

 6 Mathematica is currently conducting another large-scale, experimental evaluation of TFA elementary school 

teachers, as TFA attempts to scale up its program under an Investing in Innovation grant from ED’s Office of 

Innovation and Improvement (Clark et al. 2012). This study will be completed by December 2014.
Effectiveness of TFA and Teaching Fellows Teachers 

5 

of middle school TFA teachers scored higher in math than students of TC teachers, and neither 

higher nor lower in reading. The third study examined TFA high school teachers in North 

Carolina (Xu et al. 2008). Because they were unable to control for prior student achievement, the 

authors instead compared the performance of students within the same subject with different 

types of teachers, controlling for their academic performance in other subjects. They found that 

students of TFA teachers generally scored higher than those of non-TFA teachers, and that 

differences in scores were most pronounced in math and science courses. Although all three of 

these studies attempt to adjust for unobserved differences in student characteristics, their 

nonexperimental designs leave open the possibility that observed differences in student 

achievement are due to unobserved student characteristics rather than differences in teacher 

effectiveness.

B. Our Evaluation

This evaluation seeks to address the gaps in the existing literature with experimental 

evidence on the effectiveness of secondary math teachers from TFA and the Teaching Fellows 

programs. Teacher effectiveness is measured as the difference in end-of-year math scores 

between students taught by TFA or Teaching Fellows teachers and comparable students taught 

by teachers from other routes. The study was not designed to compare the effectiveness of TFA 

teachers with that of Teaching Fellows. Because students were not randomly assigned between 

TFA teachers and Teaching Fellows teachers, any observed difference in their impacts could be 

due to differences in the students they teach, the teachers to whom they are compared, or the 

schools or districts in which they teach. 

The study addresses two primary research questions:

1. How effective are TFA teachers at teaching secondary math compared with other 

teachers teaching the same math courses in the same schools? 

2. How effective are Teaching Fellows at teaching secondary math compared with other 

teachers teaching the same math courses in the same schools? 

To answer these questions, TFA teachers and Teaching Fellows were each compared with 

comparison teachers teaching the same subject in the same school. Comparison teachers could 

have entered teaching via a TC or a less selective AC route, but may not have entered through 

TFA or a Teaching Fellows program, or any other AC program with a similarly selective 

admissions process. No restriction was placed on the experience levels of the TFA teachers,

Teaching Fellows, or comparison teachers. To explore possible reasons for differences in 

effectiveness, the study also examines differences in characteristics between TFA teachers and 

comparison teachers and between Teaching Fellows and comparison teachers. These 

characteristics include demographic characteristics, educational background, teaching and 

nonteaching work experience, and differences in their knowledge of mathematics. It also 

documents how TFA and Teaching Fellows programs select, train, place, and support their

teachers.

Finally, the study explores the relationship between student math achievement and 

observable teacher characteristics, such as educational background, teaching experience, and

math content knowledge, as hiring authorities could potentially use these types of characteristics 

to predict an applicant’s future effectiveness in the classroom. It also explores the extent to 

which these characteristics might explain any differences in teacher effectiveness that are found
Effectiveness of TFA and Teaching Fellows Teachers 

6 

between TFA teachers or Teaching Fellows and teachers from other routes to certification. That

section of the study is based on nonexperimental methods and hence is less conclusive than the 

other components of the study.

The evaluation was guided by a conceptual framework that illustrates the mechanisms

through which secondary math teachers, and the programs that select and train them, can

influence students’ achievement (Figure I.1). Students’ achievement might be affected by the

personal and professional background characteristics of their teachers (column A). These teacher 

characteristics might also influence the type of preparation program into which the teachers are 

selected. The preparation and support they receive through their teacher preparation programs

and school districts (column B) may influence teachers’ classroom practices (column C), which, 

in conjunction with social context, could in turn influence students’ math achievement

(column D).

Teachers who enter teaching via TFA and the Teaching Fellows programs can differ from 

those who enter teaching via other preparation programs in two main ways: (1) the professional 

and personal background characteristics they possess before entering the programs (column A)

and (2) the training and support they receive from their programs (column B). Differences in

background characteristics can arise from the programs’ approaches to recruitment and selection 

as well as the teachers’ decisions on which programs to attend. This study thus provides

estimates of differences in effectiveness that reflect both differences in the types of individuals 

who enter TFA or Teaching Fellows programs versus other training programs and differences in 

the training and support their programs offer. It cannot rigorously disentangle these components. 

Figure I.1. Conceptual Framework

A. Selection: Teacher 

Background Characteristics

Personal Background 

Characteristics

Age

Race/ethnicity

Gender

General academic ability

Math knowledge and 

ability

Leadership ability

Determination

Professional 

Background 

Characteristics

Education

Nature, extent of previous 

work history

Prior classroom 

experience

Motivation to teach

Views toward teaching

B. Training and Support 

for Teaching

Content

Math content

Math-specific pedagogy

Classroom management

Diagnostics and assessments

Instructional logistics

Psychological and moral support

Instructional strategies for 

struggling learners and diverse 

classrooms

Activities

Courses

Mentoring

Observations

Personal support

Other induction activities

Other professional 

development

Sources

Teacher preparation program

School/district

C. Classroom Practices/

Social Context

Classroom Practices

Curriculum coverage

Pedagogical practices

Classroom management

Commitment to 

Teaching

Expectation for continuing

Social Context

Student characteristics

School culture

Family characteristics

Community 

characteristics

D. Student 

Performance

Math Achievement
Effectiveness of TFA and Teaching Fellows Teachers 

7 

Student math achievement is the ultimate outcome of interest that we used to estimate 

teacher effectiveness. Classroom practices and commitment to teaching are intermediate 

outcomes that we did not measure in this evaluation. Commitment to teaching may differ 

between TFA and other teachers due to the fact that TFA teachers are expected to make only a 

two-year commitment to the profession—this could negatively influence their effectiveness if 

they leave teaching before accumulating valuable experience or positively influence their 

effectiveness if, for instance, the short-term nature of their commitment increases their 

motivation and enthusiasm for teaching. 

As shown in Figure I.1, both the intermediate and final outcomes can be influenced by the 

social context that is, the characteristics of the students and their schools, families, and 

communities. In this study, the random assignment of students ensured that similar students in 

the same schools were assigned to the TFA or Teaching Fellows teachers’ classes and the 

comparison teachers’ classes and thus enabled us to control for the social context that might

influence student achievement. 

In addition to highlighting potential approaches for improving teacher quality in hard-tostaff subjects within high-need schools, the findings from this evaluation are informative for 

policymakers, funders of teacher preparation programs, school district administrators, and school 

principals. They can aid policymakers and funders of teacher preparation programs by providing 

information on the effectiveness of teachers from routes to certification with differing methods 

of identifying, attracting, training, and supporting their teachers. They can also inform district 

officials and school principals faced with the choice between hiring secondary math teachers 

from TFA or teachers who entered teaching through other routes, and with the choice between 

hiring teachers secondary math from Teaching Fellows programs or teachers who entered 

through other routes. 

C. Looking Ahead

The rest of this report describes in detail the study’s design and its findings. Chapter II 

explains the experimental design, data collection, and analytic approaches. Chapters III, IV, 

and V focus on TFA. Chapter III describes the regional TFA programs represented in the study, 

Chapter IV describes the participating TFA teachers and the teachers with whom they were 

compared, and Chapter V presents the estimates of the impact of TFA teachers on student math 

achievement. Chapters VI through VIII then present similar analyses for the Teaching Fellows 

programs and their teachers. Chapter IX presents the nonexperimental analysis of the teacher 

characteristics that are correlated with student achievement.
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

9 

II. STUDY DESIGN, DATA, AND METHODS

This chapter describes the research design, data, and analytic approaches used in the study. 

Section A describes the groups of teachers included in the study. Section B discusses the study’s 

experimental design. Section C describes our strategies for recruiting and selecting districts, 

schools, and teachers into the study, and Section D explains the procedures by which students 

were randomly assigned to the participating teachers’ classrooms. Section E specifies the data 

that were collected, and Section F describes the methods used to analyze these data to address 

the study’s research questions. 

A. Types of Teachers in the Study

This study separately compared the effectiveness of Teach For America (TFA) teachers and 

Teaching Fellows with the effectiveness of teachers from other certification routes. Because the 

effectiveness of the latter group served as the point of comparison for the effectiveness of TFA 

teachers and Teaching Fellows, we refer to teachers from certification routes other than TFA and 

the Teaching Fellows programs as comparison teachers. In designing the study and deciding 

which teachers to include in the sample, our goal was to ensure that the comparison teachers 

represented a meaningful and appropriate counterfactual—the types of teachers that would have 

been available had teachers from TFA or the Teaching Fellows programs not been available in a 

particular school. Below we describe our eligibility criteria for the teacher sample, for both 

TFA/Teaching Fellows teachers and comparison teachers. In particular, we discuss (1) eligible 

routes to certification and (2) our decision not to limit the teacher sample by years of teaching 

experience.

1. Eligible Routes to Certification

All secondary math teachers who entered teaching through TFA or a Teaching Fellows 

program were potentially eligible to be included in the study sample. In particular, the TFA 

sample included teachers who were still fulfilling their two-year commitment to the program 

(TFA corps members) and those who remained in teaching after completing their two-year 

commitment (TFA alumni). 

To be eligible to serve as comparison teachers in the study, teachers could have entered 

teaching through any certification routes other than TFA, a Teaching Fellows program, or 

another alternative route to certification that was similar to TFA and the Teaching Fellows 

programs in terms of its selectivity. The routes that were excluded from the study due to their 

similarity to TFA and the Teaching Fellows programs were small in both number and size; we 

excluded five programs that, collectively, trained only 14 math teachers nationwide in 2007 

(Clark et al. 2008).7

 

Teachers from all other routes to certification were potentially eligible to be 

included in the sample of comparison teachers—in particular, teachers from both traditional 

7 The five excluded programs were the Mississippi Teacher Corps, the Massachusetts Initiative for New 

Teachers, Los Angeles’ TeachLA program, the St. Louis Career Transition Certification Program, and New York 

City’s Teaching Opportunity Program. 
Effectiveness of TFA and Teaching Fellows Teachers 

10 

routes to certification (TC teachers) and less selective alternative routes to certification that 

accepted the majority of their applicants (AC teachers).

8

These comparison group eligibility criteria satisfied two objectives. First, by excluding a 

small number of routes that were similar to TFA and the Teaching Fellows programs, we ensured 

that the teachers being compared in the study entered teaching through meaningfully different 

routes. Second, because there were no other restrictions on the comparison teachers’ routes to 

certification, the comparison teachers in the study reflected the pool of teachers who could have 

taught study students had the TFA or Teaching Fellows teachers not been available. 

2. No Limits on Prior Teaching Experience

We did not impose any restrictions on the amount of prior teaching experience that teachers 

in the study could possess. Therefore, any disparities in teaching experience between TFA or 

Teaching Fellows teachers and comparison teachers could contribute to the differences in 

effectiveness that we estimated in this study. The benefit of this approach is that the study’s 

findings on differences in effectiveness reflect, among other factors, the real experience gaps 

between secondary math teachers from TFA, Teaching Fellows programs, and other routes to 

certification in the same schools. Below, we elaborate on the implications of this approach 

separately for TFA and Teaching Fellows teachers.

A common criticism of TFA is that it seeks teachers willing to make a two-year rather than a 

longer-term commitment to teaching. Critics claim that too many TFA teachers leave teaching 

before they accumulate the experience needed to be as effective as their counterparts from other 

routes (Heilig and Jez 2010). As expected, the TFA teachers in the study were predominantly in 

their first two years of teaching and had significantly less experience than comparison teachers 

(see Chapter IV). The study’s comparison of less experienced TFA teachers with more 

experienced non-TFA teachers therefore highlights the choice that a hiring authority faces when 

selecting what type of teachers should fill vacancies, given that the TFA teachers may be more 

likely to leave after only two years. 

Because the Teaching Fellows programs are relatively new, impact findings for Teaching 

Fellows must be interpreted with more caution. Unlike TFA, the Teaching Fellows programs 

encourage a long-term commitment to teaching. Accordingly, the Teaching Fellows in the study 

included a diverse mix of less experienced and more experienced teachers (see Chapter VII), 

reflecting the current distribution of experience among Teaching Fellows in the study schools. 

Although Teaching Fellows in the study had less experience than comparison teachers, it is 

unclear whether this gap would persist in the long run. The relatively lower experience levels of 

the Teaching Fellows may be due to the fact that no Teaching Fellows program existed before 

2000, effectively limiting the amount of experience that Teaching Fellows teachers in the study 

could have had. In that case, it may not be appropriate to generalize the findings from this study 

to future periods in which experience gaps between Teaching Fellows and comparison teachers 

could be smaller. 

 8 Throughout this report, the term “AC teachers” refers only to comparison teachers who entered teaching 

through a less selective AC route that accepted the majority of its applicants. 
Effectiveness of TFA and Teaching Fellows Teachers 

11 

B. Experimental Design

To assess the impacts of TFA and Teaching Fellows teachers compared with teachers from 

other certification routes, the study used an experimental design based on the random assignment 

of students to teachers. Students in the same school who enrolled in the same math course were 

randomly assigned to a math class taught by a TFA or Teaching Fellows teacher or to a 

comparable class taught by a comparison teacher. Random assignment ensured that there were 

no systematic differences at the start of the school year between students assigned to TFA or 

Teaching Fellows teachers and those assigned to teachers from other certification routes. 

Therefore, differences in end-of-year math scores between these groups capture the causal 

impact on students’ math achievement of being assigned to a TFA teacher or Teaching Fellow 

rather than a teacher who entered teaching through some other route. This impact represents the 

difference in effectiveness between (or the relative effectiveness of) the teachers being 

compared.

We refer to a group of classes between which students could be randomly assigned as a 

classroom match. The study included two main sets of classroom matches—those that included 

TFA and comparison teachers, and those that included Teaching Fellows and comparison 

teachers. Within both types of matches (TFA or Teaching Fellows), students who were randomly 

assigned to a TFA or Teaching Fellows teacher constituted the treatment group, and those who 

were randomly assigned to a comparison teacher constituted the control group. As discussed in 

more detail in Appendix A, classes of TFA teachers or Teaching Fellows and those of 

comparison teachers in the same school could form an eligible classroom match only if the 

classes met the following criteria:

• The classes covered a math course that was deemed eligible for the study. Any 

middle school math course was eligible. At the high school level, the eligible courses 

were general math (such as pre-algebra or remedial math), Algebra I, Geometry, and 

Algebra II. The study did not include more advanced courses, such as trigonometry or 

calculus, because appropriate assessments for these subjects were not available. Fullyear classes were eligible, as well as classes that covered a full year’s worth of 

material in a single semester.

• The classes were similar in subject taught and class conditions. In particular, the 

classes needed to cover the same general topic (for instance, Algebra I), be taught at 

the same level (for instance, honors or regular), be of similar sizes, have the same 

number of teacher’s aides with the same roles (for instance one teacher aide who 

assisted all students), be the same length (one or two semesters), and have the same 

arrangements for inclusion of English language learners and special education 

students.

• The classes were in the same period. In most cases, the classes needed to be in the 

same period in order for the study team to be able to randomly assign students to 

classes in the match without disrupting the students’ schedules in other periods. For 

example, it would not be possible to randomly assign students to either math in period 

1 or math in period 2 if all of the Spanish classes were in period 2. There were a few 

exceptions to this rule, which we describe in Appendix A. 
Effectiveness of TFA and Teaching Fellows Teachers 

12 

• Students in the classes did not receive supplemental math instruction in a way 

that would systematically inflate or dampen the effects of their regular math 

teachers. Many schools provide supplemental math classes to students to reinforce 

the content taught in the main classes. In some circumstances, this instruction could 

cause the impacts of the regular math teachers to be systematically overestimated or 

underestimated. For example, if students were assigned to supplemental math 

instruction during the school year to compensate for poor performance in their main 

math class, then ineffective teachers would appear to be better—due to the extra help 

provided to their students—than they actually are. The study included classes in 

schools with supplemental instruction only if the supplemental instruction would not 

lead to systematic errors in the impact estimates (see Appendix A). 

Although most classroom matches consisted of only two classes, some contained more than 

two. Ninety-three percent of the matches in the TFA study sample and 83 percent in the 

Teaching Fellows study sample consisted of exactly one class taught by a TFA or Teaching 

Fellows teacher and one class taught by a comparison teacher (Appendix Tables A.3 and A.4). 

The remaining matches consisted of more than two classes. This could occur if, for example, 

students were randomly assigned among three comparable math classes—such as three sections 

of Algebra I taught by two TFA teachers and one comparison teacher—held at the same time.

C. Recruitment of Districts, Schools, and Teachers

We conducted the study over a two-year period and recruited two cohorts of sample 

members—one cohort that participated in the 2009–2010 school year (cohort 1) and a second 

cohort that participated in the 2010–2011 school year (cohort 2). A separate sample of districts, 

schools, and teachers was recruited into the study for each of the two study years, but sample 

members could be included in both years. The final sample consisted of 11 states, 15 districts, 

82 schools, 228 classroom matches, 287 teachers, and 517 classes (Table II.1, last column). 

The sample consisted of two distinct sets of study participants. One set of participants, 

referred to as the TFA study sample, consisted of TFA and comparison teachers who taught 

matched classes and included the students who were assigned to those classes and the schools 

and districts in which those classes were located. The other set of participants, referred to as the 

Teaching Fellows study sample, consisted of Teaching Fellows and comparison teachers who 

taught matched classes, along with the corresponding students, schools, and districts. A 

comparison teacher could belong to both study samples if he or she was compared with both 

TFA and Teaching Fellows teachers.9

Study participants were recruited in similar ways for both the TFA and Teaching Fellows 

study samples. Next, we describe the recruitment of districts, schools, and teachers into the 

study. Appendix A provides details on the numbers of districts, schools, and potential classroom 

matches that were involved in each stage of recruitment. 

 9 Fewer than three comparison teachers were included in both the TFA and Teaching Fellows samples; the 

exact number is not reported in accordance with National Center for Education Statistics statistical standards to 

protect respondent confidentiality (National Center for Education Statistics 2000).
Effectiveness of TFA and Teaching Fellows Teachers 

13 

Table II.1. Number of Districts, Schools, Classroom Matches, Teachers, and Classes in the Study

Number of Sample Members in

TFA Study 

Sample

Teaching 

Fellows Study 

Sample

Both Samples 

Combineda 

States 8 8 11

Districts 11 9 15

Schools 45 44 82

Classroom Matchesb 111 118 228

With TC comparison teachers 58 92 149

With AC comparison teachers 53 30 83

Teachers 136 153 287

TFA or Teaching Fellows teachers 66 69 135

Comparison teachers 70 84 152

TC teachers 41 61 100

AC teachers 29 23 52

Classes 248 270 517

Taught by TFA or Teaching Fellows teachers 123 135 258

Taught by comparison teachers 125 135 259

a

Counts of sample members in the TFA and Teaching Fellows study samples can sum to more than the total 

count in the combined sample because some comparison sample members belonged to both the TFA and 

Teaching Fellows study comparison samples.

b

Counts of matches with TC teachers and those with AC teachers sum to more than the total number of 

matches because some matches contained both TC and AC teachers.

AC = alternative route to certification; TC = traditional route to certification; TFA = Teach For America.

1. Recruitment of Districts

We focused recruitment efforts on districts with large concentrations of secondary math 

teachers from TFA or a Teaching Fellows program. Using fall 2008 placement data from TFA 

and the Teaching Fellows programs, we identified districts with the largest numbers of secondary 

math teachers trained by these programs, and we contacted 42 of these districts prior to the first 

study year. Of those districts, 15 agreed to participate in the study by allowing the study team to 

conduct random assignment and data collection activities (Table II.1). 

2. Recruitment of Schools

Within participating districts, we contacted schools in the spring prior to each study year to 

identify those in which the study could be implemented in the upcoming year. We placed priority 

on contacting schools in which TFA and Teaching Fellows programs had previously placed 

secondary math teachers because those schools had the greatest likelihood of having teachers 

eligible for the study in the upcoming study year. In each contacted school, we ascertained 

course schedules and teaching assignments to determine whether the school would have any 

eligible classroom matches in the following school year. Of the 792 schools that were initially 

contacted, the final sample of 82 schools consisted of those that contained eligible classroom 

matches, agreed to allow random assignment of students, and provided verification that students 
Effectiveness of TFA and Teaching Fellows Teachers 

14 

had been placed into classes in accordance with the results of the random assignment 

(Table II.1). 

Because schools could be included in the study only if they had TFA teachers or Teaching 

Fellows, the distribution of participating schools across the 15 study districts was influenced by 

the number of TFA teachers and Teaching Fellows who taught in those districts. Some districts 

had substantially larger populations of teachers from these programs than other districts, 

contributing to an uneven distribution of study schools across districts. This was particularly true 

in the Teaching Fellows study sample; of the 44 schools with Teaching Fellows in the study, 22 

belonged to a single district (Table II.2). As a result, this district contributed 54 percent (82 of 

153) of the teachers in the Teaching Fellows study sample. 

Table II.2. Distribution of Sample Sizes Across Districts in the Study

Type of Sample Size

Number of 

Districts

Distribution of Schools and Teachers Across Districts

Mean Median Minimum Maximum

In Teach For America Study Sample: 11

Number of study schools per district 4 3 1 12

Number of study teachers per district 12 8 2 41

In Teaching Fellows Study Sample: 9

Number of study schools per district 5 3 1 22

Number of study teachers per district 17 8 2 82

As we discuss in Chapters IV and VII, the schools in the study were, on many dimensions, 

similar to all secondary schools with TFA and Teaching Fellows teachers. However, our 

recruitment approach led to an underrepresentation of certain types of schools. First, smaller 

schools were less likely to have multiple sections of the same math course—a requirement for 

classroom matches to be formed—and were thus underrepresented. Second, although we 

contacted charter schools to determine whether they could be included in the study, none had 

eligible matches. Finally, the schools in the study were disproportionately from the large, urban 

districts that the study targeted in its recruitment.

3. Classroom Matches and Teachers in the Final Study Sample

The final set of classroom matches in the study spanned several types of middle school and 

high school math courses (Table II.3). Courses were represented in different proportions in the 

TFA and Teaching Fellows study samples. In particular, middle school math courses constituted 

75 percent of classroom matches with TFA teachers and 31 percent of classroom matches with 

Teaching Fellows.
Effectiveness of TFA and Teaching Fellows Teachers 

15 

Table II.3. Number of Classroom Matches and Study Classes, by Subject

Subject

Teach For America Study Sample Teaching Fellows Study Sample

Classroom 

Matches

Classes 

with TFA 

Teachers 

Classes with 

Comparison 

Teachers

Classroom 

Matches

Classes with

Teaching 

Fellows

Classes with

Comparison 

Teachers

6th-Grade Math 31 33 35 9 11 10

7th-Grade Math 33 33 34 14 18 14

8th-Grade Math 19 20 19 14 21 16

Algebra I or General 

High School Math 9 14 14 34 38 46

Geometry 14 18 18 23 23 23

Algebra II 5 5 5 24 24 26

Total 111 123 125 118 135 135

TFA = Teach For America.

Of the 287 teachers in the study, about half (135) were either TFA or Teaching Fellows 

teachers (Table II.1). The number of TFA teachers (66) was similar to the number of Teaching 

Fellows (69). The total number of teachers in the study (287) was not twice the number of 

classroom matches (228) because some matches had more than two teachers. Moreover, some 

teachers in the study taught classes in more than one match—in different periods during the 

school day and/or in both study years. 

Our approach to recruiting may have led to an underrepresentation of TFA and Teaching 

Fellows teachers in their first year of teaching as well as more experienced TFA teachers. 

Because we placed priority on contacting schools in which TFA or Teaching Fellows teachers 

had been previously placed as indicated by the programs’ placement data, we might not have 

been aware of schools that began hiring new teachers from these programs during the study’s 

recruitment period. In addition, although TFA was aware of many schools with more 

experienced TFA teachers, it maintains less comprehensive information on teachers who have 

completed their two-year commitment to the program. Thus, more experienced TFA teachers 

may also have been underrepresented in the sample. 

4. Differences between the TFA and Teaching Fellows Study Samples

We evaluated the impacts of TFA and Teaching Fellows teachers separately, in part, because 

of key differences in the study samples used for evaluating these two groups. Chapters IV and 

VII discuss the characteristics of the sample members in detail, but several differences between 

the TFA and Teaching Fellows study samples are evident in Tables II.1 through II.3. First, the 

TFA teachers and Teaching Fellows in our study taught largely in different districts. Of the 

15 districts in the study, only 5 included both TFA and Teaching Fellows teachers. Second, even 

within a district, TFA and Teaching Fellows teachers taught in different schools. Seventy-five of 

the 82 study schools (91 percent) had either TFA or Teaching Fellows teachers in the study, but 

not both; as discussed earlier, TFA teachers were more likely than the Teaching Fellows to teach 

in middle schools (Table II.3). Third, the TFA and Teaching Fellows teachers were compared 

with different groups of comparison teachers. Whereas AC teachers represented 41 percent 

(29 of 70) of the comparison teachers with whom TFA teachers were compared, they represented 
Effectiveness of TFA and Teaching Fellows Teachers 

16 

27 percent (23 of 84) of the comparison teachers with whom Teaching Fellows were compared 

(Table II.1). Differences in impact findings from the two study samples could be due to any of 

these differences in sample characteristics, as well as other unobserved differences stemming 

from the fact that students were not randomly assigned between TFA and Teaching Fellows 

teachers. For all of these reasons, study findings cannot be used to compare the effectiveness of 

TFA and Teaching Fellows teachers.

D. Selection and Assignment of Students

Before the start of each new school year, schools sent us lists of students whom they wanted 

placed into one of the classes in the identified classroom matches. We randomly assigned the 

students into the classes, specifying the teacher for each class. The schools then assigned the 

students to classes in accordance with the random assignment results. Students who wanted to 

enter one of the classes after this initial assignment but before the end of the first month of the 

school year were also randomly assigned to one of the classes. Schools could explicitly request a 

specific assignment for a given student, in which case the student was excluded from the study 

(which was rare, as described below). Appendix A provides further details on the random 

assignment process.

Based on the random assignment conducted in the study, a student was included in the 

research sample—that is, the beginning-of-year sample representing the students to whom study 

findings pertain—if he or she met two criteria. First, the student was randomly assigned to a 

study class by the end of the first month of the school year. Second, the student did not leave the 

school in which the study was being conducted prior to the first day of the school year. With 

these criteria, the research sample consisted of 5,790 students in the TFA study sample and 

6,909 students in the Teaching Fellows study sample (Table II.4). As discussed in Section E, all 

research sample students with valid end-of-year math scores were included in the impact 

estimates; these students are referred to as the analysis sample. 

Table II.4. Number of Students in the Study

Subject

Teach For America Study Sample Teaching Fellows Study Sample

Assigned 

to TFA 

Teachers

Assigned to

Comparison 

Teachers Total

Assigned to 

Teaching 

Fellows

Assigned to

Comparison 

Teachers Total

Number of Students in the 

Research Samplea 2,884 2,906 5,790 3,466 3,443 6,909

Number of Students in the 

Analysis Sampleb 2,292 2,281 4,573 2,127 1,989 4,116

Note: 24 students from the research sample—of whom 20 were in the analysis sample—were assigned to a 

comparison teacher who was in both the Teach For America study sample and the Teaching Fellows study 

sample. a

Research sample includes all students who were randomly assigned to a study class by the end of the first month of 

school and did not leave the school prior to the start of the school year.

b

Analysis sample includes all students in the research sample for whom the study obtained valid end-of-year math 

achievement scores.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

17 

The vast majority of students (97.4 percent) who enrolled in a study class before or during 

the first month of school were randomly assigned and are included in the research sample. Rates 

were similar in the classes of TFA teachers and Teaching Fellows (97.2 percent) and the classes 

of comparison teachers (97.5 percent) (Table II.5). The remaining students either left the study 

school before the start of the school year or were excluded from random assignment at the 

school’s request. 

Table II.5. Changes in Composition of Study Classes During the School Year

Average Number of Students per Class 

(unless otherwise indicated)

All Study 

Classes

Classes of TFA 

Teachers or 

Teaching Fellows

Classes of 

Comparison 

Teachers

Enrolled in Study Classes Before the End of the First 

Month of Schoola 

Number of students 25.2 25.3 25.2

Number of students who belong to the research sample 24.6 24.6 24.5

Percentage of students who belong to the research 

sample 97.4% 97.2% 97.5%

Listed on End-of-Year Class Rosters

Number of students 23.3 23.3 23.2

Number of students who belong to the research sample 

and stayed in originally assigned class 19.0 19.1 18.9

Percentage of students who belong to the research 

sample and stayed in originally assigned class 81.5% 81.8% 81.3% 

Number of Classes 517 258 259

Note: Calculations are unweighted. Tests of differences between TFA/Teaching Fellows and comparison

classes were conducted using independent-sample t-tests with unequal variances. No differences were 

statistically significant at the 0.05 level.

a

This category excludes students who were enrolled in study classes before the start of the school year but never 

showed up to school.

TFA = Teach For America. 

There was some student movement into and out of the study classes after the random 

assignment period. Some research sample members transferred out of their originally assigned 

classes and some late-enrolling students were placed by schools into study classes after the first 

month of the school year. Despite this mobility, study classes remained primarily composed of 

research sample members throughout the year. On end-of-year class rosters, 81.5 percent of 

students in study classes were research sample members who had been originally assigned to 

those classes, with similar rates in the classes of TFA teachers and Teaching Fellows 

(81.8 percent) and the classes of comparison teachers (81.3 percent) (Table II.5). In Appendix A, 

we document the types of mobility experienced by research sample members.

E. Data Used in the Study

We collected data on students, teachers, schools, and the TFA and Teaching Fellows 

programs in the study (Table II.6). Appendix A provides details on the response rates for each 

major data source.
Effectiveness of TFA and Teaching Fellows Teachers 

18 

1. Data on Students

We attempted to collect data on math achievement and demographic characteristics for all 

students in the research sample for whom we received parental consent to collect this data.

Math achievement outcomes. We measured end-of-year math achievement based on 

different sources of data for middle school and high school students in the study. For students in 

grades 6 to 8, we obtained scores on state assessments from district administrative records. These 

assessments, required by federal law, were part of states’ accountability systems, which gauge 

school performance in part based on students’ test scores. The assessments were thus designed to 

measure the math skills that students were expected to learn at their grade level in each state. 

Because we requested district records, it was possible to obtain scores for any consenting middle 

school students in the study who had taken state assessments within a participating district, even 

if they had switched schools within the district during the school year. 

Table II.6. Data Sources for the Evaluation

Domain Data Source

Schedule of Data Collection

Cohort 1

(2009–2010)

Cohort 2

(2010–2011)

Student Math Achievement 

Outcomes

Middle school District administrative records Summer/Fall 2010 Summer/Fall 2011

High school NWEA assessments (studyadministered)Spring 2010a Spring 2011b 

Baseline Student Achievement 

and Characteristics

District administrative records Summer/Fall 2010 Summer/Fall 2011

Student Mobility Class rosters Summer 2009, Fall 

2009, Winter 2010, 

Spring 2010

Summer 2010, Fall 

2010, Winter 2011, 

Spring 2011

Teachers’ Route to Certification Teacher background form Summer/Fall 2009 Summer/Fall 2010

Teachers’ Professional 

Background and Experiences

Teacher survey Spring 2010 Spring 2011

Teachers’ Math Content 

Knowledge

Praxis (study-administered or 

existing score from Educational 

Testing Service)

Fall 2009 Fall 2010

School Characteristics Common Core of Data 2009–2010 2009–2010

TFA and Teaching Fellows 

Program Characteristics

Program administrator interviews Spring 2010 n.a.

a

Assessments for single-semester fall 2009 classes were conducted in winter 2009–2010. b

Assessments for single-semester fall 2010 classes were conducted in winter 2010–2011.

TFA = Teach For America; NWEA = Northwest Evaluation Association.

n.a. = not applicable.

For students in grades 9 to 12, we administered end-of-course math assessments developed 

by the Northwest Evaluation Association (NWEA). Based on the content of their math course, 

students took computer-adaptive assessments in general high school math, Algebra I, Geometry, 

or Algebra II. We attempted to administer assessments to all consenting high school students in 

the study who had not moved out of the school district by the time of testing, regardless of 

whether they had stayed in their original class or school. We chose not to use high school 

students’ scores on state assessments for several reasons. First, high school state math 
Effectiveness of TFA and Teaching Fellows Teachers 

19 

assessments were not consistently available for all states and grades in the study, as federal law 

required states to assess students in math in only one grade at the high school level. Second, we 

expected that some high school state assessments would measure minimum overall math 

competency required for graduation and, hence, would not be aligned with the content of 

particular courses.

Students in the research sample with valid outcome scores constituted the final sample used 

in the analysis. A student may not have had a valid outcome score for one of four reasons: (1) the 

student’s parents did not give consent for data collection; (2) we were not able to administer an 

NWEA assessment to the student (if in high school); (3) the student’s score on the NWEA 

assessment was invalid based on criteria defined by NWEA (Table A.12); or (4) the district did 

not have a state assessment score for the student (if in middle school). We obtained valid 

outcome scores for 68 percent of students in the research sample—in particular, for 70 percent of 

treatment group students and 67 percent of control group students (Figure A.2). As we discuss in 

Chapters IV and VII, treatment and control group students with outcome data were statistically 

similar on most baseline characteristics, suggesting that patterns of missing outcome data did not 

generate imbalance between these groups. Table A.17 provides further comparisons of the 

characteristics of students with and without outcome data. 

Achievement and demographic characteristics at baseline. We collected information on 

baseline measures—measures whose values were determined prior to random assignment—of 

students’ achievement and demographic characteristics. Baseline data for all students were based 

on district administrative records. These data served as covariates in the impact analyses, 

provided contextual information on the types of students included in the study, and indicated 

whether random assignment produced treatment and control groups that were similar at the 

beginning of the school year. 

Baseline achievement was measured by students’ prior scores on state assessments in math 

and reading. We used each student’s math and reading score from the most recent prior grade at 

which end-of-grade state assessments were administered. Appendix B provides details on the 

construction of the baseline achievement measures. Because students’ prior scores in both math 

and reading were predictive of their outcome math scores, controlling for baseline achievement 

in both subjects improved the precision of the impact estimates. Other characteristics available 

from district administrative records included age, gender, race and ethnicity, free and reducedprice lunch eligibility, special education status, and English language learner status.

Student mobility. To monitor compliance with random assignment and the mobility of 

students into and out of the classes in the study, we obtained class rosters from participating 

schools several times during the school year. Each roster provided an updated list of students 

who were enrolled in a specified class. We collected rosters four times: (1) immediately after 

random assignment; (2) at the end of the first month of school in the fall; (3) in the first week of 

classes after winter break; and (4) approximately eight weeks before the end of the school year.

2. Data on Teachers

Route to certification. Before each year of the study, we verified the certification route of 

all teachers whose classes could potentially be included in classroom matches by asking 

principals to complete a background form on each study teacher. 
Effectiveness of TFA and Teaching Fellows Teachers 

20 

Professional background and experiences. In the spring of each study year, we 

administered a survey to teachers in the study to collect information on their professional

background and experiences. The survey asked about teachers’ educational background, 

nonteaching and teaching work experience, preparation for teaching, support received during the 

school year, views toward teaching, and demographic characteristics. 

Math content knowledge. Some researchers have argued that the effectiveness of math 

teachers is related to their knowledge of math concepts (Hill et al. 2005). To measure the math 

content knowledge of teachers in the study, we used teachers’ scores on one of two assessments 

developed by the Educational Testing Service: (1) the Praxis II Middle School Mathematics 

assessment (for middle school math teachers) and (2) the Praxis II Mathematics Content 

Knowledge assessment (for high school math teachers). These assessments were designed to 

measure general and subject-specific teaching skills and knowledge appropriate for beginning 

math teachers. As of 2006, 37 states required new secondary math teachers to pass one of these 

tests as part of the licensure and certification process (Gitomer and Qi 2010). 

The collection of Praxis II scores varied across states depending on whether the state 

required secondary math teachers to pass a Praxis II math assessment for certification. In states 

that required math teachers at a particular school level (middle or high) to pass the relevant 

Praxis II exam (Middle School Math or Math Content Knowledge, respectively), we asked 

teachers to release their existing scores to the study.10 In states that did not require the relevant 

Praxis II exam, we administered the tests directly to teachers in the study.

3. Data on Schools 

To describe the schools included in the study sample, we collected data on school 

characteristics, including grade span, school size, and general demographic information on the 

student body. We obtained these data from the 2009-2010 Common Core of Data. The Common 

Core of Data is a publicly available database covering all public schools in the United States. 

4. Data on TFA and Teaching Fellows Programs 

Through semi-structured telephone interviews with program officials, we collected detailed 

information about TFA and the Teaching Fellows programs to document how they selected, 

trained, placed, and supported program participants. The interviews solicited information on both 

national and local/regional program operations. Staff at the TFA national office and TNTP, the 

national organization that oversees the Teaching Fellows programs, identified the most 

appropriate respondents for the interviews. In some cases, national office staff gave us 

information about local/regional program operations, especially if policies and practices were 

standardized across different locations. In other cases, we spoke directly with local or regional 

program staff. We obtained information on all 10 regional TFA programs and all seven Teaching 

Fellows programs represented in the study, as well as national-level operations of both TFA and 

TNTP.

 10 One state in the study required middle school math teachers to pass the Math Content Knowledge assessment 

(rather than the Middle School Math assessment). In that case, we used scores on the Math Content Knowledge 

assessment for teachers at all grade levels.
Effectiveness of TFA and Teaching Fellows Teachers 

21 

F. Overview of the Analytic Approach

The study included two key types of analyses: (1) experimental analyses to estimate the 

impacts of TFA teachers and Teaching Fellows on student math achievement in the full sample 

and key subgroups, and (2) nonexperimental analyses to explore the association between teacher 

characteristics and teacher effectiveness. Appendix B provides more technical details of the 

analytic methods.

1. Experimental Analyses

The experimental analyses provided separate estimates for the impacts of TFA teachers and 

Teaching Fellows in the study relative to the comparison teachers in the same classroom 

matches. Random assignment was the key to the causal validity of these estimates because it 

ensured that students assigned to the TFA or Teachings Fellows teachers were no different, on 

average, than students assigned to comparison teachers in the same match at the time of random 

assignment. The analytic approaches we describe next were applied identically to estimating the 

impacts of the TFA teachers and Teaching Fellows in the study.

Outcome measure. Students’ math assessment scores constituted the outcome measure for 

the analysis. The scales of the test scores differed between the state assessments and NWEA 

assessments and, among state assessments, differed across states and grade levels. To express 

test scores in a common unit, we converted each score into a z-score by subtracting the mean 

score of a reference population and dividing the difference by the standard deviation of scores in 

that reference population. For a student’s score on a state assessment, the reference population 

was the full population of students in the same state, year, and grade who took the same 

assessment; for a student’s score on an NWEA assessment in a given course, the reference 

population was the NWEA’s nationwide norming sample for that assessment. Thus, impacts on 

z-scores in this analysis represented increments to math achievement expressed in standard 

deviations within a statewide or national student population. 

Estimation method. Because teachers in the same classroom matches were assigned similar 

students at the beginning of the year, the simple average difference in end-of-year achievement 

between their students could provide causally valid estimates of their relative effectiveness. In 

our main analysis, we separately estimated the average impacts of TFA teachers and Teaching 

Fellows relative to comparison teachers on the basis of regression models that built upon the 

simple test score differences. The regression models pooled data across all classroom matches 

involving teachers from the specified group and the comparison teachers with whom they were 

compared. The model controlled for classroom match indicators so that comparisons were made 

only within the same match. The average impact estimated by each model was therefore similar 

to a weighted average of impacts from all relevant classroom matches, such that matches with 

more students received more weight. To enhance the precision of the estimates, the models 

controlled for students’ baseline characteristics, including prior test scores in math and reading 

and several demographic characteristics.

Subgroup analyses. Impacts of TFA or Teaching Fellow teachers relative to comparison 

teachers could depend on the specific characteristics of the teachers who are compared with each 

other. Therefore, we applied similar analytic methods to estimate differences in effectiveness 

between TFA or Teaching Fellows teachers and comparison teachers in subgroups of matches 

defined by specific teacher characteristics. To define the subgroups, we chose a number of 
Effectiveness of TFA and Teaching Fellows Teachers 

22 

characteristics that could potentially influence the magnitude or direction of the impacts. First, 

we estimated separately the impacts of TFA teachers and Teaching Fellows relative to 

comparison teachers from each of the two major types of certification routes—TC and less 

selective AC routes—as the two routes could attract very different types of comparison teachers 

and provide very different types of training. Second, given that a key expected difference 

between TFA or Teaching Fellows teachers and comparison teachers is the gap in their 

experience levels, we defined subgroups by experience to understand whether our impact 

findings would change if teachers with more similar levels of experience were compared with 

each other. Third, we estimated impacts within subgroups delineated by school level (middle or 

high)because math instruction at different levels might require different sets of skills. 

Adjustments for spurious significant findings. Estimating multiple impacts increases the 

chance of falsely identifying an impact as significant when, in fact, there is no true impact. In 

this study, we estimated many impacts—for TFA and Teaching Fellows teachers separately and 

for various subgroups. Corrections can be made to reduce the chance of obtaining spurious 

significant findings, but adjusting for all impact estimates included in the study would have 

severely limited the study’s power to detect any impacts at all. To balance these competing 

factors, we adjusted the significance tests (using the Benjamini and Hochberg [1995] method) 

only for the impact estimates we considered to be of primary policy relevance the impacts of 

TFA teachers or Teaching Fellows relative to all comparison teachers, TC teachers, and AC 

teachers.11

Accounting for students who switched to a different type of teacher. Our main estimates 

capture the relative effects of TFA or Teaching Fellows teachers and comparison teachers on all 

students who were randomly assigned to their classes, including students who left their original 

classes and switched to a different type of teacher during the school year. The advantage of these 

estimates is that they are based purely on the experimental design. In supplemental analyses, we 

also estimated impacts on only students who stayed with their originally assigned type of 

teacher.

We regarded the subgroups defined by the comparison teachers’ route to certification 

(AC or TC) to be the most policy relevant of the subgroups we examined because of their 

potential to inform principals’ hiring decisions. We did not adjust significance tests in any of the 

remaining subgroup analyses because we did not consider them to be of primary policy relevance 

and did not want to compromise the study’s power to detect impacts for the groups of most 

interest. Hence, the significant findings from these remaining analyses are more likely to be 

spurious than the main significant findings. Further discussion of these adjustments is provided 

in Appendix B. 

2. Nonexperimental Analyses

We used nonexperimental methods to examine the extent to which teacher effectiveness was

associated with teacher characteristics other than their routes to certification. These additional 

types of information could potentially be useful to hiring authorities in predicting applicants’ 

likely effectiveness in the classroom. Accordingly, we focused on analyzing characteristics 

 11 None of the impact findings changed as a result of these adjustments. In other words, no impact estimates 

that were statistically significant prior to the adjustments became insignificant after the adjustments.
Effectiveness of TFA and Teaching Fellows Teachers 

23 

observable at the time of hiring, including educational background, performance on math content 

knowledge tests, professional experience, and instructional training. Understanding the teacher 

characteristics associated with teacher effectiveness may also shed light on the reasons for any 

difference in effectiveness between teachers who enter teaching via different routes. 

The objectives of this analysis differed from those of the experimental subgroup analysis 

described earlier. The experimental subgroup analysis was aimed at examining dimensions on 

which the impacts of TFA or Teaching Fellows teachers relative to comparison teachers could 

vary. Accordingly, for that analysis, we focused on a small set of characteristics that could lead 

to larger or smaller differences in effectiveness between TFA or Teaching Fellows teachers and 

comparison teachers. For the nonexperimental analysis, we sought to identify factors that could 

generally predict teacher effectiveness, regardless of the teachers’ certification route, to generate 

hypotheses for future research. Therefore, as described below, this analysis focused on a broader 

set of characteristics.

The associations found by the nonexperimental analysis cannot provide rigorous evidence 

for the causal effects of teacher characteristics on student achievement. Any association between 

a given teacher characteristic and student achievement could be due to some unobserved factor 

rather than the one under study. Nonetheless, this analysis may suggest hypotheses that could be 

examined in future research.

We conducted two basic analyses in sequence: (1) estimating relationships between teacher 

characteristics and effectiveness based on the full sample of teachers in the study; and 

(2) assessing the extent to which those relationships could account for the actual, experimentally 

estimated differences in effectiveness between specific groups of teachers. We describe the 

methods for these analyses next.

Estimating relationships between teacher characteristics and effectiveness. We 

estimated regression models in which student math scores were the dependent variable and the 

characteristics of the students’ math teachers were the key independent variables of interest. The 

models also controlled for classroom match indicators and all variables included in the 

experimental impact models. The regression coefficients on the variables of interest captured the 

association between teacher characteristics and student math achievement. Because the estimated 

associations were intended to apply generally to all teacher groups examined in the study, we 

pooled data from both the TFA and Teaching Fellows study samples to maximize the precision 

of the analyses.

Although student math achievement was the outcome variable, estimating relationships 

between teacher characteristics and student math achievement was equivalent to estimating 

relationships between teacher characteristics and teacher effectiveness. With controls for 

classroom match indicators, the regression models related differences in student achievement 

between classes in the same match to differences in the characteristics of their teachers. 

Crucially, students of matched classes were similar at the beginning of the school year due to 

random assignment, so achievement differences between matched classes could only have been 

the result of differences in teacher effectiveness. Consequently, teacher characteristics that were 

found to vary with student math achievement were those that were predictive of teacher 

effectiveness.
Effectiveness of TFA and Teaching Fellows Teachers 

24 

Characteristics examined. The characteristics in the analysis generally belonged to three 

broad categories: (1) measures of teachers’ general academic ability; (2) measures of teachers’ 

exposure to and knowledge of mathematics; and (3) measures of teachers’ instructional training 

and experience. Table II.7 lists the main set of characteristics we examined and the specific 

measures we used for each characteristic.

Table II.7. Teacher Characteristics Examined in the Nonexperimental Analysis

Teacher Characteristic Variables Measuring the Teacher Characteristic

Variable 

Structure

General Academic Ability

College selectivity Graduated from selective college or universitya Dichotomous

Exposure to and Knowledge 

of Math

College-level math 

coursework

Number of college-level math courses taken is above medianb Dichotomous

Math-related nonteaching 

experience

Used college-level math in nonteaching job Dichotomous

Math content knowledge Score on Praxis II test in Math Content Knowledge (z-score) Continuous

Score on Praxis II test in Middle School Math (z-score) Continuous

Instructional Training and 

Experience

Math pedagogy 

instruction

Number of hours of math pedagogy instruction during training is 

above medianc 

Dichotomous

Student teaching in math Number of days of student teaching in math during training is 

above mediand 

Dichotomous

Coursework during the 

school year

Hours of coursework during the school year (divided by 10) Continuous

Teaching experience Has more than one year of teaching experience Dichotomous

Number of additional years of teaching experience beyond two 

total years (until teacher has five total years of experience)

Continuous

Number of additional years of teaching experience beyond five 

total years

Continuous

a

Selective colleges are those ranked by Barron’s as being very competitive, highly competitive, or most 

competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching.

To enhance the precision of the analyses, we used a parsimonious set of variables to 

measure the characteristics of interest. Some characteristics, such as whether a teacher attended a 

selective college or university, were naturally captured by dichotomous variables. For 

characteristics based on survey questions whose possible responses were ordered categories—for 

example, categories denoting different ranges of student teaching experience—we constructed a 

dichotomous variable for whether a teacher’s reported category was above the median reported 
Effectiveness of TFA and Teaching Fellows Teachers 

25 

category in the sample.12 Characteristics that could be expressed in well-defined increments, 

such as hours of coursework during the school year, were usually formulated as a single 

continuous variable. As an exception, the measure of teaching experience was formulated as 

three continuous variables such that the predicted gain in effectiveness per additional year of 

experience could differ at different levels of total experience (one to two years, three to five

years, and more than five years). This formulation reflected previous evidence that the gains 

from additional experience decline with total experience (Rivkin et al. 2005; Hanushek et al. 

2005). 

Robustness of evidence. Our analytic approach assessed whether an observed association 

between a characteristic and teacher effectiveness was robust across model specifications. For 

each characteristic, we estimated its association with teacher effectiveness in two different ways: 

(1) without controls for any other teacher characteristics besides TFA/Teaching Fellow status 

and (2) with controls for all teacher-level variables in Table II.7. If the association between a 

specified characteristic and teacher effectiveness was statistically significant in both estimation 

approaches, the finding was regarded as representing more robust evidence than a finding of a 

statistically significant association in only one approach. In sensitivity analyses, we explored 

alternative formulations of the teacher characteristics in Table II.7 and considered models with 

additional characteristics (see Appendix G).

Explaining differences in effectiveness between specific groups of teachers. Findings on 

the relationships between teacher characteristics and effectiveness could potentially help account 

for differences in effectiveness between specific groups of teachers. Hence, in cases where 

teachers who entered teaching through either TFA or the Teaching Fellows programs differed in 

effectiveness from the full group of comparison teachers with whom they were compared, we 

assessed whether differences in teacher characteristics could account for—that is, predict—the 

groups’ difference in effectiveness. Specifically, for each characteristic, we calculated the 

predicted difference in effectiveness, expressed in student z-score units, between TFA or 

Teaching Fellows teachers and comparison teachers based on only the specified characteristic. 

This predicted impact, which represented the portion of the actual impact accounted for by the 

specified characteristic, was equal to the product of two quantities: (1) the estimated association 

between the characteristic and teacher effectiveness and (2) the average difference in the 

characteristic between TFA or Teaching Fellows teachers and comparison teachers. Because the 

predicted impacts depended on nonexperimental estimates, they provided only suggestive—but 

not causally valid—explanations for the experimental findings. 

 12 We constructed dichotomous variables rather than including an indicator for each category because, if we 

had included an indicator for each category, there would have been too few teachers in each category to detect 

differences between pairs of categories.
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

27 

III. SELECTION, TRAINING, AND SUPPORT

OF TFA PROGRAM PARTICIPANTS

Teachers who enter the profession through Teach For America (TFA) may differ from other 

teachers in their effectiveness in teaching mathematics for one or both of two broad reasons: 

(1) they may have different characteristics, knowledge, and experiences when they enter TFA, 

and (2) they may receive different preparation for teaching and support once they start teaching. 

This chapter describes how participants in TFA apply for the program, are selected for the 

program, are trained before they begin teaching (“preservice training”), receive instruction or 

training in local alternative certification (AC) programs, and are supported while teaching.

13

Appendix C presents some additional information on TFA. 

A. Application and Selection

TFA has a national application and selection process. Individuals apply to TFA as a whole, 

not to a regional program, but they may specify ranked preferences for the regions in which they 

would like to teach (Appendix Figure C.1 lists the 43 TFA regions as of August 2011). At the 

time of our interviews, the application and selection process included three possible stages, 

depending how far an applicant advanced: (1) submission of an online application, (2) a 

telephone interview, and (3) an in-person assessment. 

1. Application Form and Eligibility Rules

TFA estimates that the online application takes about two hours to complete. It collects 

information in four general areas: 

1. Personal data, including contact information; gender and ethnicity (both optional); 

citizenship/residency status; disclosures regarding criminal charges and academic 

deficiencies or misconduct; and family background information (also optional). The 

family background information covers whether the applicant is a first-generation 

college student, his or her parents’ income, and his or her parents’ highest level of 

education completed. 

2. Academic and professional information, including names of undergraduate and 

graduate schools attended, dates attended, areas of study, and degrees awarded or 

expected; cumulative undergraduate grade point average (GPA) and GPA by year; 

disclosure of failing grades and course withdrawals; leadership roles in 

extracurricular, paid work, or volunteer activities; longest amount of time spent 

pursuing a goal or refining a skill; and experience in low-income communities. 

3. Nonacademic activities during undergraduate and graduate school, including 

names of organizations the applicant was involved with, whether the activity was 

extracurricular or for pay, organization size, title/position in the organization, primary 

 13 The interview questions asked about “instruction or training.” For simplicity, hereafter, we refer only to 

“instruction.”
Effectiveness of TFA and Teaching Fellows Teachers 

28 

responsibilities, personal awards/recognitions received, number of people applicant 

led (if applicable), and length and timing of involvement with the organization. 

4. Postgraduate activities, including names of organizations the applicant was involved 

with, title/position in the organization, primary responsibilities, most significant 

contribution, personal awards/recognitions received, and reasons for leaving (if 

applicable). 

In addition to entering the requested information online, applicants must provide 

supplementary materials and information. All applicants must upload a resume and a “letter of 

intent” explaining why they want to join TFA, what they hope to accomplish in the program, and 

how they would determine their success in the program. Applicants who progress to the two 

stages beyond the application stage are asked to provide the names of two people who will 

submit online recommendations; one reference whom program staff could contact to discuss the 

applicant’s candidacy; regional preferences; preferences for the subject and grade they would 

like to teach; information extracted from their postsecondary transcripts; official postsecondary 

transcripts; and proof of citizenship/residency status. 

TFA also requires all applicants to meet three firm, objective criteria for eligibility: an 

applicant must (1) be a U.S. citizen or national or legal permanent resident; (2) have a 

cumulative undergraduate GPA of at least 2.5 on a 4.0 scale; and (3) receive a bachelor’s degree 

from an accredited college/university before the start of TFA’s training program, the “Summer 

Institute.” Although the minimum GPA is 2.5, the average GPA of admitted applicants in recent 

years, according to national TFA staff, has been about 3.6. 

Applicants who receive an offer of admission are notified about relevant hiring and 

certification eligibility requirements such as any coursework they will have to complete or any 

new-teacher examinations they will have to pass. The tests may measure basic academic skills in 

areas such as reading, writing, and mathematics or more advanced content knowledge in the 

teacher’s subject area. Some states have their own tests, and others rely on various tests from The 

Praxis SeriesTM developed and administered by the Educational Testing Service. Newly admitted 

corps members are encouraged to start working on these requirements as soon as possible. 

2. Selection Process

The application and selection process is intended to produce a complex, “holistic view” of 

each applicant. It is also designed to produce multiple measures of each of seven core 

competencies that TFA officials view as broadly applicable to strong leaders in any field and, 

more important, believe to be common operating principles for highly successful corps members. 

The competencies are:

1. Demonstrated leadership and achievement in academic, professional, extracurricular, 

or volunteer arenas 

2. Perseverance and sustained focus in the face of challenges

3. Critical thinking skills

4. Organizational ability

5. Respect for individuals’ diverse experiences and the ability to work effectively with 

people from a variety of backgrounds 
Effectiveness of TFA and Teaching Fellows Teachers 

29 

6. Interpersonal skills to motivate and lead others

7. An understanding of and a desire to work relentlessly in pursuit of the organization’s 

vision 

Most applicants who receive consideration beyond the application stage are asked to 

participate in a 25- to 45-minute telephone interview with a program representative. Interviewers 

follow a general set of guidelines, asking applicants about their accomplishments, how they 

approach problems, and issues such as educational inequity. 

Applicants deemed promising based on the telephone interview are invited to an in-person 

assessment called the “final interview.” (Applicants deemed very promising based on their 

application alone may bypass the telephone interview.) In 2010, final interviews were conducted 

in approximately 100 cities nationwide, with many cities hosting multiple sessions. Each session, 

which can last a full day, involves 4 to 14 applicants. At the time of our interviews, the final 

interview comprised four activities, in the following order: 

• Sample teaching lesson. Candidates take turns presenting a five-minute sample 

teaching lesson. They “teach” the other candidates in attendance that day, with 

program staff observing. The lesson may target any grade level on any topic. 

Although all applicants know at the outset about the sample lesson requirement, they 

receive no detailed instructions for how to approach it until they are invited to the 

final interview, about 8 to 15 days before the event. At that time, they receive 

guidance on how to set up and introduce the lesson, and some tips on what to 

consider or include to help make their lesson successful. 

• Group discussion. Applicants engage in a 15-minute group discussion among 

themselves. In advance of the final interview, applicants receive several articles to 

read on various education topics, such as the gap between minority and white student 

achievement or the nature of educational assessment, taken from a publication such as 

Education Week or Educational Leadership. On site, staff members introduce a 

subject or a hypothetical situation that teachers might encounter and that relates to the 

assigned reading. Staff members then simply observe the applicants as they discuss 

the issue.

• Problem-solving activity. Applicants are provided with two short articles similar to 

those described above; watch a video clip; and provide brief written answers to a 

series of questions about the issues addressed in the materials. They are also 

presented with a series of multiple-choice questions, both qualitative and quantitative. 

The activity, which takes place in an online format, lasts about one hour. (In 2011, as 

this program description was being prepared, the problem-solving activity was moved 

to before the telephone or final interview to help officials learn more about candidates 

earlier in the selection process.)

• One-on-one interview. Candidates participate in a one-on-one interview, lasting 25 

to 45 minutes. The approach is generally similar to that used in the telephone 

interviews. Trained interviewers systematically collect certain kinds of information. 

The conversation may address information on the application, additional information 

obtained since submission of the application, or events that occurred earlier in the 

day.
Effectiveness of TFA and Teaching Fellows Teachers 

30 

At each stage of the process, a mathematical selection model heavily influences decisions 

about whether applicants will progress to the next stage. TFA developed the model using data 

about the characteristics of corps members deemed most effective in their classrooms, measured

by the average annual achievement growth of their students. The model produces a score for 

each applicant that predicts the likelihood that he or she will be a highly effective corps member.

Virtually all the information available from applications, interviews, and related 

documents—with the exception of personal demographic data such as age, gender, and 

race/ethnicity—is entered into the model.14

TFA runs the model three times to gauge which applicants should move to the next stage, 

each time adding more data. The first run uses data from only the application, resume, and letter 

of intent. Each applicant’s score leads to an initial recommendation, based on different cutoff

points, to move the applicant straight to the final interview, offer him or her a telephone 

interview, or terminate his or her consideration for admission. Staff members who act as 

selectors during a given admission cycle consider the model’s recommendation in light of the 

evidence they reviewed regarding the applicant and may propose either supporting or changing 

the recommendation. A selection committee then considers both the model’s recommendation 

and the selectors’ recommendation and makes the final determination regarding each applicant. 

The model’s second run adds data collected through the telephone interview or submitted after 

the original application. The numeric recommendation and selectors’ opinions are again used to 

determine which applicants will be invited to the final interview. Finally, after all the data from 

the final interview are added to the model, TFA runs the model a third time and again uses both 

the numeric recommendation and selectors’ opinions to determine which applicants will be 

offered admission to the program. TFA revises the model and the admissions cutoff point over 

time as it learns more about what competencies seem to matter most for teacher effectiveness in 

raising student test scores. But once it adopts a new model and sets a new cutoff point for a given 

admissions cycle, TFA does not lower the cutoff point to admit more candidates than would 

otherwise be selected—not even, for example, if the existing cutoff point would yield fewer

secondary math teachers than desired.

Qualitative information such as written answers to 

application questions and answers to interview questions are judged by selectors and quantified 

on various rubrics using 3-, 4-, or 5-point scales. The model includes more than 20 variables, or 

indicators, that collectively encompass the seven competencies listed above. Whenever possible, 

several measurements capture each of the seven competencies of interest. TFA officials do not 

publicly reveal details about the model, such as the exact number of indicators, what they 

measure, or how the weights are used in constructing an overall score. But officials are generally 

satisfied with the model’s predictive abilities and its ability to select candidates who are very 

strong on several competencies. Moreover, as TFA collects more data on corps members’ 

effectiveness, it reassesses and refines the model.

Admission offers include a regional placement and teaching subject/grade assignment. In 

some years, some applicants may not gain admission immediately but are instead placed on a 

waiting list. For example, in 2010, TFA had a substantial increase in its applicant pool, but 

 14 TFA officials said that these factors have no bearing on admission decisions. TFA has internally important 

goals concerning the diversity of its corps members on these and other characteristics, but officials work toward 

those goals through targeted efforts to recruit a diverse applicant pool rather than adjusting admissions processes.
Effectiveness of TFA and Teaching Fellows Teachers 

31 

because of economic conditions and budget issues, some districts could not be sure how many 

openings they would have until later than usual.

3. Program Selectivity and Application Yields

For an overall perspective on program selectivity, we show in Figure III.1 the movement of 

applicants through the selection process in the three years preceding our interviews. According to 

national TFA officials, for every 100 applicants, on average, 65 advanced past the application 

stage, 50 were invited to the final interview (about 85 percent of those attended), 12 were offered 

admission, and 9.6 enrolled. So although 12 percent of applicants had an opportunity to join 

TFA, 80 percent of those offered the chance became corps members.

Figure III.1. TFA Selection Process and Applicant Flow

Source: National TFA officials.

B. Preservice Training for New Corps Members

The main preservice training for new TFA teachers is a full-time, residential summer 

institute located on university campuses around the country; it is preceded by two shorter 

training sessions and followed by another short training experience. All TFA training, both 

before and after corps members begin teaching, is guided by its Teaching As Leadership rubric, 

which lists six major principles of leadership: (1) set big goals, (2) invest students and their 

families/influencers in working hard to reach the big goals, (3) plan purposefully, (4) execute 

effectively, (5) continuously increase effectiveness, and (6) work relentlessly. The rubric also 
Effectiveness of TFA and Teaching Fellows Teachers 

32 

lists 28 associated actions that teachers can take to promote student achievement (a list of the 

actions associated with each principle appears in Appendix Figure C.2). In Figure III.2, we 

outline the timing of placement and of all training and support activities before and after corps 

members begin teaching.

Figure III.2. Overview of Placement and Training of TFA Corps Members

Spring Summer Fall Winter Spring Summer Fall Winter Spring Summer

First School Year 

Teaching

Second School Year 

Teaching

Third School Year 

Teaching

School Placements Are 

Determined

Independent Study

TFA Regional Induction

TFA Summer Institute

TFA Post-Institute Training 

(“Round Zero”)

TFA Training and Support

Instruction/Training Provided 

by Local Alternative 

Certification Program

*

**

Source: National TFA officials.

Note: The shaded areas of this figure indicate the seasons in which various activities generally take place; 

shading does not imply that any given activity takes up the full season. This chapter provides 

information on the hours associated with various activities.

*When their two-year commitment is complete, corps members become TFA alumni.

**Timing of coursework, where required, varies; it may start just before corps members begin teaching and may last 

into their third year of teaching; when coursework extends beyond the first year of teaching, it may or may not take 

place during summer.

1. Independent Study and Regional Induction

Soon after joining TFA, all new corps members must complete a few self-directed 

assignments to help them begin to prepare for their future teaching responsibilities and to learn 

more about TFA’s overall approach and expectations. They read a set of six or seven curriculum 

texts that will be used at the summer institute, observe experienced teachers and watch video 

clips of classroom instruction, and reflect in writing on these materials and experiences. 

Altogether, TFA estimates that the independent study activities take 30 to 40 hours. 

Early in the summer, new corps members attend an induction program in the region where 

they will teach in the fall. They participate in a series of meetings to learn more about TFA’s 

mission and their roles as corps members and to gain familiarity with district- and schoolspecific curricula, policies, and programs. On average, regional induction may last two to four 

days.
Effectiveness of TFA and Teaching Fellows Teachers 

33 

2. Summer Institute

As of 2011, TFA held summer institutes in eight locations—Atlanta, Chicago, Houston, Los 

Angeles, the Mississippi Delta, New York, Philadelphia, and Phoenix—each hosting corps 

members from four to seven regional programs. Regardless of location, each institute follows the 

same model—it lasts five weeks, covers the same instruction guide, and involves the same 

activities. However, to improve the quality of instruction each year, a subset of institutes 

implements a few pilot programs. If the pilots prove successful, they are incorporated into the 

overall institute model. The five main types of activities during the summer institute include:

1. Instructor-led coursework (“curriculum sessions”). Corps members spend part of 

virtually every weekday, most often in the evening, in small- or large-group 

curriculum sessions. Topics include lesson planning, content delivery, classroom 

management, student assessment, literacy, and effective interactions with diverse 

constituents. Some sessions are relevant for all corps members; other sessions are 

tailored for those who will teach certain subjects at certain grade levels, such as 

secondary math. TFA estimates the total amount of instruction at 109 hours. 

2. Practice teaching (“experiential learning”). Groups of three or four corps members 

team up in “collaboratives” to lead small-group or whole-class instruction in a real 

classroom in a local district’s summer school program, under the direct supervision of 

the regular classroom teacher. Each participant, together with his or her teammates, 

spends about 20 hours tutoring small groups of students and about 20 hours leading 

instruction for the whole class. Participants may also spend an additional 4 to 8 hours 

observing each other, observing veteran teachers, or tutoring individual students. 

3. Independent work and reflection. Corps members plan and rehearse lessons, watch 

video recordings of their own practice teaching, and review student work. These 

activities are estimated to take a total of about 71 hours. 

4. Discussions with advisors. TFA instructors observe corps members in practice 

teaching several times each week and provide them with written and oral feedback to 

help them refine their skills. Formal one-on-one discussions total about 4 hours. 

5. Administrative activities. Events such as opening and closing ceremonies and a 

campus tour take up about 19 hours. 

Altogether, these activities add up to about 243 hours of effort for corps members during the 

summer institute, an average of about 49 hours per week.

At the time of our interviews, TFA did not widely offer any services to help candidates 

become qualified to teach secondary math. However, in partnership with a university, TFA had 

developed an online training course to help qualified secondary math teacher candidates brush up 

on their math knowledge and skills. The course was piloted in 2009 with a small number of corps 

members at one summer institute. TFA’s perception that the pilot improved participants’ 

preparedness and teaching led it to offer the online course to substantially more corps members 

who would be attending that same summer institute in 2011. 

From 2008 to 2010, according to national TFA staff, an average of 98.5 percent of corps 

members who started the summer institute completed it and thus moved to post-institute 

activities.
Effectiveness of TFA and Teaching Fellows Teachers 

34 

3. Post-Institute Activities

After the summer institute, new corps members return to their placement regions for a final 

set of meetings and training activities, a period referred to as “Round Zero.” While the summer 

institute focuses mainly on daily, general teaching skills, Round Zero focuses on longer term 

planning and strategies relevant to the subject, grade level, school, and district of corps 

members’ teaching assignments. Corps members study these topics in part through required 

online coursework that takes about 25 hours to complete. Even though these activities may 

extend a month or two into the school year, we discuss them in this section on preservice training 

because they are foundational in nature and TFA does not classify them as part of the ongoing 

support provided to corps members after they start teaching (described below). 

C. Placement and Retention of TFA Corps Members

Corps member placement is a two-stage process. First, at the point of admission, national 

program staff assign each corps member to a regional TFA program. Regional assignment 

decisions take into account the corps member’s preferences, the number and types of teachers 

sought by each region, and whether the corps member meets a given region’s coursework 

requirements for hiring or certification, such as any special requirements for secondary math and 

science teachers.

Second, new teachers are matched with appropriate vacancies in designated high-need 

schools in the regions to which they are assigned. The process is conducted within each region 

with the aid of a matching tool that combines data on the corps members and the vacancies in the 

region. In the 10 regional TFA programs in the study, the process varied in terms of how much 

effort new participants must exert in the job search and how much choice they have in where 

they interview or teach. Staff from all 10 regional programs reported that corps members 

interview with school principals. Interviews could start as early as mid-February, but more

typically start in April or May, and most take place around the time of regional induction and the 

summer institute. 

Corps members in different regions may receive different types of assistance during the 

matching process. In one region in the study, for example, new corps members receive a list of 

schools, particularly ones with a high percentage of students from low-income families, and are

strongly encouraged to interview for openings at those schools. In other regions in the study, 

corps members are directed to one or more schools for interviews based on the program staff’s 

views about which corps members would be a good fit for particular schools, requests from 

principals who have reviewed applicant materials and have requested to meet with certain 

candidates, or program and/or district staff’s predeterminations about where corps members will 

be placed. In such predetermined cases, interviews are generally a courtesy rather than a means 

for reaching a hiring decision. Even when corps members interview in more than one school and 

placements are not decided by others in advance, corps members do not necessarily have free 

choice in deciding where they will teach. In one region in the study, for example, principals and 

district officials decide which corps members will teach at which school after interviews are 

completed.

In the three hiring cycles before our interviews, nearly all new teachers (98 percent, on 

average) and all new secondary math teachers in the 10 regional programs were hired before the 
Effectiveness of TFA and Teaching Fellows Teachers 

35 

start of the school year, and all teachers not hired before the start of the school year were hired 

after the year started (Table III.1). 

Table III.1. Estimated Percentage of New TFA Corps Members Who Received Teaching Placements, on 

Average, Across the 2007–2008, 2008–2009, and 2009–2010 School Years

Hired Before Start of 

School Year

Hired After Start of 

School Year Total

All Candidates 98% 2% 100%

Secondary Math Candidates 100% 0% 100%

Source: Interviews with regional TFA officials.

Regional staff typically try to place new corps members in schools where current or former 

TFA corps members are teaching, so that the new teachers can benefit from an added source of 

support. The programs in the study had typically succeeded in arranging such placements over 

the three school years preceding our interviews. On average, across fall 2007, 2008, and 2009, 

according to program representatives, an estimated 92 percent of all new teachers and 93 percent 

of new secondary math teachers were hired in schools where current or former corps members 

were teaching.

For the corps members nationwide who entered TFA as secondary math teachers in 2007, 

2008, or 2009 (around the time of some sample members), TFA officials estimate that, on 

average, 94.3 percent completed their first year in the program, 91.2 percent started their second 

year, and 90.3 percent completed their two-year commitment in the program.

D. Instruction Provided to TFA Corps Members Through Local Teacher 

Certification Programs

In 9 of the study’s 10 regional TFA programs, new secondary math teachers were required 

to enroll in a state-authorized alternative certification (AC) program. The 10th program had no 

such requirement, because state law allowed teachers to gain initial certification, good for three 

years, without enrolling in a certification program, as long as they had a relevant college major 

for the subject they would teach and passed both a general knowledge test and a test in their 

teaching subject area. All secondary math corps members in recent years reportedly had taken 

and passed the tests and did not enroll immediately in an AC program.

To gain a general sense of the instruction that TFA secondary math teachers in our study 

might have received from local AC programs, because teacher-level data collection was not 

feasible, we asked officials in each region to identify the one program that had enrolled the 

largest number, whether a majority or a plurality, of their secondary math teachers over the three 

most recent years before 2010. This was the time period, we believed, during which most study 

teachers would have enrolled in a local AC program. (The later addition of study teachers from 

TFA’s summer 2010 entering cohort means that their AC program experiences may not be as 

well represented by the AC program information we collected.) In seven of the regions we 

examined, the identified AC programs reportedly served all the TFA secondary math teachers. In 

both of the other two regions, the identified program reportedly served 70 percent of secondary 

math TFA teachers in that region. Hereafter, we refer to these AC programs as “focal,” as they 

were the focus of our questions. 
Effectiveness of TFA and Teaching Fellows Teachers 

36 

The nine focal AC programs were operated by a variety of institutions; five were operated 

by a nearby university. Secondary math teachers from two regions attended a single AC program 

operated by TNTP. One program was operated by a local school district in collaboration with a 

university. In the final case, the regional TFA program was the state-authorized AC provider. 

Additional TFA regional programs also now serve as state-authorized certification providers. 

1. Preservice Instruction

Two of the nine focal AC programs reportedly involved a preservice component in addition 

to the TFA’s preservice and Round Zero activities. One involved one week of full-time, inperson instruction for a total 40 hours; the other involved 25 hours of independent study. Across 

all 10 regional TFA programs, the average preservice instruction requirement faced by new 

secondary math teachers was 6.5 hours. 

2. Instruction During and After the First Year of Teaching

All nine focal AC programs involved instruction during the teachers’ first year of teaching. 

The certification program with the most extensive requirement for participants’ first year 

involved 112 hours of instruction; participants attended classes or other training activities

4 hours a week for 28 weeks. The certification program with the least extensive first-year 

requirement involved 54 hours of instruction; participants attended classes or other training 

activities 3 hours a week for 18 weeks. Across all 10 regional TFA programs, the average firstyear instruction requirement faced by new secondary math teachers in their focal certification 

programs was 70 hours. Three of the programs reportedly involved instruction during the 

summer after corps members’ first year of teaching, ranging from 40 to 60 hours (Table III.2).

Table III.2. Hours of Instruction Toward Certification Reportedly Required in Focal AC Programs for 

TFA Secondary Math Teachers

Regions with This Instructional Component

Instruction Provided

Number of 

Regions Minimum Maximum Mean

Mean for All 

10 Regionsb

Before first year of teaching 2 25 40 32.5 6.5

During first year of teaching 9 54 112 77.8 70.0

During summer after first year of teaching 3 40 60 49.3 14.8

During second year of teaching 3 100 210 153.3 46.0

Total Hours, All Programsb 10 0 315 137.3 137.3

Source: Interviews with regional TFA officials.

Note: This table excludes training provided directly by the TFA summer institute and regional TFA 

programs.

a

The focal AC program for each participating TFA regional program is the program that enrolled the largest 

number of its secondary math teachers from 2007 to 2009.

b

Includes the one regional TFA program whose participants did not have to attend an AC program. For these 

calculations, the program received a value of 0 hours at each time period.

Finally, required instruction at three certification programs extended into new corps 

members’ second year of teaching. The certification program with the most extensive 

requirement in this period involved about 7.5 hours of instruction a week for 28 weeks, for a 
Effectiveness of TFA and Teaching Fellows Teachers 

37 

total of 210 hours. The certification program with the least extensive second-year requirement 

involved 5 hours of instruction a week for 20 weeks, for a total of 100 hours. Across all 10 TFA 

programs, the average second-year instruction requirement faced by new secondary math 

teachers in their focal certification programs was 46 hours. 

3. Total Amount of Instruction in Certification Programs

The total hours of instruction that secondary math teachers in the 10 regions reportedly had 

to complete for certification, before and during their first two years of teaching, ranged from 0 to 

315 hours, with a mean of about 137 hours. In Table III.2, we present average instruction hours 

required, overall and by time period. 

E. Training and Support for New Corps Members After They Begin Teaching

Regional program staff continue to work with corps member after they begin teaching. 

1. Instruction, Training, and Professional Development 

All TFA regional programs provide some type of instruction, training, or professional 

development (hereafter “training”) to their participants after they began teaching. In this 

paragraph, we exclude from our discussion the one program in the study that was a stateauthorized AC provider. For this program it was difficult to distinguish between training 

provided as part of the state certification program and that provided as a regular part of TFA. The 

training in the other nine programs took place on weeknights and/or weekends during the school 

year. The programs provided an average of 42 hours of training, according to representatives’ 

reports, with a range of 16 to 70 hours. Most of these programs (eight of nine) covered classroom 

management and lesson plans or unit plans (five of nine). Programs also sometimes covered goal 

setting, creating assessments or judging student work, and instructional practices or pedagogy. 

Subjects are not necessarily set in advance but sometimes are determined throughout the year

according to participants’ needs—gauged, for example, through classroom observations. Six of 

the nine programs reportedly provided some training specifically for secondary math teachers. 

2. Other Support Services

All 10 TFA programs provided individualized support for new teachers, such as classroom 

observations and mentoring. Each program appointed staff members, known as “program 

directors,” to work with participants after they started teaching. Each program director typically 

worked with about 30 new teachers. Where possible, new secondary math teachers were matched 

with program directors who were themselves former secondary math teachers. At the time of the 

interviews, six programs reported that 100 percent of their secondary math teachers were in such 

a pairing, and two programs reported that none of their secondary math teachers was in such a 

pairing; the mean of the percentages reported across the programs was 68 percent. Nine of the 

TFA programs reported that new teachers were supported by program directors for their full two 

years of program participation, whereas one program reported that the support lasted one year.

• Classroom observations. Program directors in all 10 regions reportedly conducted 

formal observations of new teachers in their classrooms. The average number of 

observations per teacher ranged from 1 to 16, with a mean of 6; six programs reported 

that they typically observed each new teacher four or five times over his or her two 
Effectiveness of TFA and Teaching Fellows Teachers 

38 

years in the program. All program directors provided the teachers with feedback from 

the observations to help them with their development. In some cases, program 

directors made the assessment available to the principal (for example, if the teacher 

was struggling or the principal requested the information) or to other TFA staff 

(either routinely or if the teacher was struggling and the program director wanted 

additional advice on how to help the teacher). 

• One-on-one meetings. Beyond providing feedback from classroom observations, 

program directors in 7 of the 10 regions reportedly also held other planned one-onone meetings with new teachers over their two years in the program. The purpose of 

the meetings was to mentor the new teachers and provide information, advice, or 

encouragement. The average number of planned discussions with teachers across the 

programs ranged from 2 to 40, with a mean of 10.5, and the average length of 

discussions across programs ranged from 60 to 90 minutes, with a mean of 

71 minutes. 

• Group meetings. Program directors or other staff at 8 of the 10 regional TFA 

programs reportedly also scheduled meetings with groups of new teachers to provide 

various types of support or information. The topics covered in the sessions varied 

with assessments of corps members’ needs. The average staff-to-teacher ratio in these 

meetings, across the six programs that provided an estimate, ranged from 1:5 to 1:10. 

The average number of meetings that TFA staff scheduled for new teachers over their 

two years in the program, across the five programs that provided an estimate, ranged 

from 2 to 20, with a mean of 10.8. The average length of the meetings, across the 

seven programs that provided an estimate, ranged from 90 to 150 minutes, with a 

mean of 99 minutes. 

F. Financial Support for Corps Members

Corps members may receive financial support while in training. First, TFA covers the costs 

of room and board during the summer institute and regional orientation. Second, TFA offers 

needs-based no-interest loans and grants of $1,000 to $6,000 to cover transitional costs such as 

travel expenses to the summer institute and placement region, relocation expenses, and testing 

and certification fees. Third, TFA corps members may receive financial support from other 

sources. Most corps members, at the time of our program interviews (spring 2010), were eligible 

for an AmeriCorps education award of $5,350 at the end of each of their two years of teaching. 

(Participants who had received one AmeriCorps award before joining TFA were eligible for only 

one more award; those who had already received two awards were ineligible for additional 

awards.) AmeriCorps awards could be used to cover teacher training and certification costs as 

well as repayment of qualified student loans and future graduate school expenses. Fourth, at the 

time of the interviews, participants in four of the regional TFA programs could reportedly 

receive some form of financial assistance to help cover at least some of the current costs 

associated with the AC programs discussed above. The support ranged from $1,000 per 

participant in one region to $3,000 per participant, per year, in another region. 
Effectiveness of TFA and Teaching Fellows Teachers 

39 

IV. TEACH FOR AMERICA STUDY TEACHERS: THEIR CHARACTERISTICS,

THE SCHOOLS THEY TEACH IN, AND THE STUDENTS THEY TEACH

Teach For America (TFA) aims to place high quality teachers in schools that serve some of 

the most disadvantaged students in the United States. TFA’s screening procedures suggest that 

teachers accepted into the program will differ from teachers who enter the profession through 

other routes. Its placement procedures suggest that the schools these teachers are placed in and 

the students they serve are also likely to differ from typical schools and students. To provide 

context for the estimates of the effectiveness of TFA teachers presented in Chapter V, this 

chapter describes the schools (Section A), teachers (Section B), and students (Section C) in the 

TFA study sample.

To summarize the findings from this chapter, we found that TFA teachers in the study were 

typically placed in urban schools that served economically disadvantaged students, largely from 

racial and ethnic minority groups. The non-TFA study teachers in these schools were primarily 

nonwhite women, typically with more than five years of teaching experience. In contrast, the 

TFA teachers in the study were overwhelmingly white, less likely to be female, and had 

significantly less teaching (and general work) experience. The TFA teachers were also far more 

likely to have attended a selective undergraduate university. While the TFA teachers were less 

likely to have majored in math, they had significantly greater math content knowledge test scores 

than the typical math teachers in the schools in which they taught. 

A. Schools in the TFA Study Sample

Even though study schools were not randomly selected from the full set of secondary 

schools employing TFA teachers nationwide, the study schools were similar to secondary schools 

employing TFA teachers nationwide along many dimensions (Table IV.1). For instance, both 

sets of schools served predominantly students from racial and ethnic minority groups. Less than 

10 percent of students at both the average study school and the average secondary school with 

TFA teachers nationwide were white, non-Hispanic, while 57 percent at both types of schools 

were black, non-Hispanic, and around 30 percent were Hispanic. Close to 80 percent of students 

at both types of schools were eligible for free or reduced-price lunch. More than 80 percent of 

both schools in the TFA study sample and schools with TFA teachers nationwide were eligible 

for Title I funds for schools with high percentages of low-income students. Consistent with 

TFA’s mission to place its corps members in schools in low-income communities, schools in the 

study sample were on average more disadvantaged than the average secondary school 

nationwide. For instance, compared with students in the average secondary school nationwide, 

students in the average school in the TFA study sample were more likely to be eligible for free or 

reduced-price lunch and to be from racial and ethnic minorities.

There were also some differences between study schools and all TFA schools nationwide, 

many of which may have been due to our recruitment approach and study eligibility 

requirements. The average study school had significantly more students per grade than the 

average secondary school employing TFA teachers (240 versus 184 students per grade), 

consistent with the fact that schools with more students per grade were more likely to have 

eligible classroom matches. Although 23 percent of secondary schools with TFA placements 

nationwide were charter schools, there were no charter schools in the study sample. This reflects 

the fact that charter schools were typically smaller than average and therefore less likely to have 
Effectiveness of TFA and Teaching Fellows Teachers 

40 

Table IV.1. Characteristics of Study Schools with TFA Teachers Compared with All Secondary Schools with 

TFA Teachers and All Secondary Schools Nationwide

Study Schools 

with TFA 

Teachers

All Secondary 

Schools with 

TFA Teachersa

All Secondary 

Schools 

Nationwide

Characteristic Mean Mean

p-Value of 

Difference 

from Study 

Schools Mean

p-Value of 

Difference 

from Study 

Schools

Racial/Ethnic Distribution of 

Students

Percentage Asian, non-Hispanic 2.8 3.8 0.150 3.5 0.091

Percentage Black, non-Hispanic 57.4 57.0 0.918 18.8** 0.000

Percentage Hispanic 31.3 32.1 0.852 20.2* 0.016

Percentage White, non-Hispanic 8.0 8.9 0.545 59.4** 0.000

Percentage other race/ethnicity 0.5 4.5** 0.000 9.8** 0.000

Student Socioeconomic Status

Percentage eligible for 

free/reduced-price lunch 78.9 79.7 0.663 50.5** 0.000

Percentage Title I-eligible 

schools 82.2 88.5 0.267 60.0** 0.000

Enrollment and Staffing

Average total enrollment 836.0 714.3 0.090 551.2** 0.000

Average enrollment per grade 240.2 183.6** 0.003 134.5** 0.000

Average student/teacher ratio 14.4 14.7 0.339 16.1** 0.000

Grade Levelb

Percentage middle schools 66.7 59.0 0.278 66.1 0.932

Percentage high schools 37.8 54.8* 0.019 45.3 0.301

School Type

Percentage charter schools 0.0 22.5** 0.000 6.9** 0.000

Percentage magnet schools 26.7 6.2** 0.001 2.3** 0.000

School Location

Percentage urban 80.0 70.1 0.098 25.5** 0.000

Percentage suburban 11.1 21.2* 0.038 37.8** 0.000

Percentage rural 8.9 8.5 0.922 36.4** 0.000

Census Bureau Region

Percentage in Northeast 13.3 13.2 0.974 14.3 0.844

Percentage in Midwest 13.3 14.6 0.799 27.7** 0.005

Percentage in South 66.7 53.3 0.060 30.8** 0.000

Percentage in West 6.7 18.7** 0.003 26.9** 0.000

Sample Size 45 471 63,148

Sources: TFA placement data; Common Core of Data, Public Elementary/Secondary School Universe Survey, 

2009–2010 . 

Note: Secondary schools are defined as any school that includes at least one grade above 5th grade.

a

Estimates are based on schools in which new TFA teachers were placed in the 2009–2010 school year. 

b

Middle schools are defined as schools with at least one grade from 6 to 8. High schools are defined as those with at 

least one grade from 9 to 12. Thus the two categories are not mutually exclusive, as a given school could contain 

both middle and high school grades.

 *Difference between this group and study schools with TFA teachers (first column) is statistically significant at the 

0.05 level, two-tailed test.

**Difference between this group and study schools with TFA teachers (first column) is statistically significant at the 

0.01 level, two-tailed test.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

41 

eligible classroom matches. Study schools were also significantly more likely than the typical 

secondary school with TFA placements to be magnet schools (27 versus 6 percent) and 

significantly less likely to be high schools, defined as those serving at least one grade from 9 to

12 (39 versus 55 percent). Eighty percent of study schools were located in urban areas, as were 

70 percent of the average secondary schools employing TFA teachers; this difference was not 

statistically significant at the 5 percent level. The average study school was less likely to be 

located in a suburban area (11 versus 21 percent). Study schools were also significantly less 

likely than the full set of TFA secondary schools to be located in the West (7 versus 19 percent). 

B. TFA Teachers in the Study Sample Compared with Comparison Teachers 

TFA selects teachers with characteristics and attitudes it believes are associated with 

effectiveness in the classroom, provides them with five weeks of training before they begin 

teaching, and provides additional training and support throughout the teachers’ two-year 

commitment to teaching. Hence, TFA study teachers may differ from comparison teachers in the 

same classroom matches—the non-TFA teachers teaching the same math course in the same 

school—in their background characteristics, experience, preparation for teaching, training, 

support, or attitudes toward teaching. In fact, TFA teachers did differ from comparison teachers 

in many ways, as described further below.

Compared with comparison teachers, TFA teachers:

• Were younger and less likely to be members of racial or ethnic minorities 

• Were more likely to have graduated from a selective college or university

• Had greater math content knowledge as measured by scores on the Praxis II math 

exams

• Were less likely to have majored in math and had taken fewer college-level math 

courses 

• Had fewer years of teaching and nonteaching experience

• Completed similar amounts of math pedagogy instruction and student teaching in 

math during their preparation for teaching 

• Were more likely to have taken coursework during the study school year and to have 

had a mentor during that year, which is consistent with the fact that TFA teachers 

were more likely to be in their first or second year of teaching 

• Were less satisfied with some aspects of teaching related to school policy and staff. 

The comparison teachers with whom TFA study teachers were compared included both 

teachers from traditional routes to certification (TC routes) and those from less selective 

alternative routes to certification (AC routes)—59 percent of comparison teachers were from TC 

routes, while 41 percent were from less selective AC routes. With a few exceptions discussed 

below, these patterns of differences were present both among the subset of TFA teachers who 

were compared with teachers from TC routes and the subset who were compared with teachers 

from AC routes (Appendix D).
Effectiveness of TFA and Teaching Fellows Teachers 

42 

1. Demographic Characteristics

TFA teachers differed from comparison teachers in age, gender, and race/ethnicity 

(Table IV.2).15 Consistent with the fact that TFA primarily recruits recent college graduates and 

asks them to make only a two-year commitment to teaching (although some remain in teaching 

beyond this commitment), TFA study teachers were on average younger than comparison 

teachers (25 versus 38 years old). They were less likely to be female (61 versus 79 percent). TFA 

teachers were also less likely than comparison teachers to be members of racial or ethnic 

minorities. Eighty-nine percent of TFA study teachers were white, non-Hispanic, compared with 

30 percent of comparison teachers.16 Eight percent of TFA study teachers were black, nonHispanic, compared with 57 percent of comparison teachers. Comparison teachers in the study 

were closer in age to the average secondary teacher nationwide than were TFA study teachers, 

while TFA study teachers looked more like the average secondary teacher in terms of both 

gender and racial and ethnic distribution. 

2. Educational Background and Math Content Knowledge

TFA study teachers were more likely than comparison teachers to have graduated from a 

selective college or university (81 versus 23 percent) (Table IV.3).17

Patterns of differences in educational background were similar for the subset of TFA 

teachers who were compared with comparison teachers from TC routes and the subset who were 

compared with comparison teachers from AC routes, with one exception. Teachers from TC 

routes were significantly more likely to have majored or minored in education than the TFA 

teachers with whom they were compared, while none of the teachers from AC routes or the TFA 

teachers with whom they were compared had an education major or minor (Appendix 

Table D.2). 

However, they were also 

less likely to have completed a graduate degree (41 versus 70 percent). They were less likely 

than comparison teachers to have majored in math (8 versus 26 percent) or secondary math 

education (0 versus 16 percent), but more likely to have majored in some other math-related 

subject (statistics, engineering, computer science, finance, economics, physics, or astrophysics) 

(27 versus 12 percent). There was no significant difference in the percentage of TFA and 

comparison teachers who majored in any math-related subject (including math, secondary math 

education, and the other math-related subjects listed above).

 15 In this and all teacher-level analyses presented in this chapter, each teacher is counted only once, regardless 

of whether he or she taught multiple classes in the study. For teachers in both cohorts, the value of the variable as 

reported in cohort 1 is used if cohort 1 and cohort 2 reports differ. We also conducted analyses that weight each 

teacher according to the number of study classes taught, and findings were similar.

16 For comparison, among all TFA secondary math teachers who began teaching in fall 2010, 69 percent were 

white, non-Hispanic, according to data provided by TFA (not shown in table). We are not able to test the 

significance of the difference between this estimate and that for the study teachers.

17 College selectivity was defined based on Barron’s Profiles of American Colleges 2003. Highly selective 

colleges were defined as those ranked by Barron’s as most competitive, and selective colleges were defined as those 

ranked by Barron’s as very competitive, highly competitive, or most competitive.
Effectiveness of TFA and Teaching Fellows Teachers 

43 

Table IV.2. Demographic Characteristics of TFA and Comparison Teachers in the Study and All 

Secondary Teachers Nationwide (percentages unless otherwise indicated)

Secondary 

Teachers 

Nationwide

TFA 

Teachers

Comparison 

Teachers

Difference

Between 

TFA and 

Comparison 

Teachers p-Value

Age (Average Years) 42.7††^^ 24.5 37.9 -13.4** 0.000

Female 59.3^^ 60.9 79.4 -18.4* 0.023

Race/Ethnicitya

Asian, Non-Hispanic 1.3†^ 9.4 11.1 -1.7 0.749

Black, Non-Hispanic 6.9^^ 7.8 57.1 -49.3** 0.000

Hispanic 6.8 4.7 12.7 -8.0 0.111

White, Non-Hispanic 83.5^^ 89.1 30.2 58.9** 0.000

Sample Size 1,099,770 64 63

Source: Data for secondary teachers nationwide from the Schools and Staffing Survey Teacher 

Questionnaire, 2007–2008; data for study teachers from the Survey of Secondary Math Teachers.

a

Racial and ethnic categories for study teachers are not mutually exclusive, so percentages may sum to more 

than 100.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

 †Difference between secondary teachers nationwide and TFA teachers is statistically significant at the 0.05 

level, two-tailed test.

††Difference between secondary teachers nationwide and TFA teachers is statistically significant at the 0.01 

level, two-tailed test.

 ^Difference between secondary teachers nationwide and comparison teachers is statistically significant at the 

0.05 level, two-tailed test.

^^Difference between secondary teachers nationwide and comparison teachers is statistically significant at the 

0.01 level, two-tailed test.

TFA = Teach For America.

Consistent with the fact that they were less likely to have majored in math, TFA teachers 

had also completed fewer college-level math courses than comparison teachers (5 versus 8 

courses) (Table IV.4).18

 18 Teachers were asked to indicate the number of college or graduate-level math courses they had taken at a 

college or university, or high school courses for which they had received college credit, across various categories of 

courses. They were not expected to include high school courses for which they did not receive college credit.

TFA teachers had taken significantly fewer courses than comparison 

teachers in several topic areas, including advanced algebra, analysis, advanced 

geometry/topology, probability and statistics, and discreet mathematics; however, there was no 

significant difference in the number of calculus courses taken. TFA teachers took fewer collegelevel math courses on average than comparison teachers at both the middle and high school 

levels, although this difference was more pronounced at the high school level. 
Effectiveness of TFA and Teaching Fellows Teachers 

44 

Table IV.3. Educational Background of TFA and Comparison Teachers in the Study (percentages unless 

otherwise indicated)

TFA

Teachers

Comparison

Teachers Difference p-Value

Bachelor’s Degree

From a selective college or universitya 81.3 22.7 58.5** 0.000

Majorb

Math 7.8 25.6 -17.8* 0.020

Secondary math education 0.0 16.3 -16.3** 0.005

Other math-related subjectc 26.6 11.6 14.9* 0.047

Other subject 90.6 67.4 23.2** 0.005

Math, secondary math education, or other mathrelated subjectc 34.4 48.8 -14.5 0.141

Major or Minorb

Math 12.5 30.2 -17.7* 0.033

Secondary math education 0.0 20.9 -20.9** 0.001

Other math-related subjectc 28.1 14.0 14.2 0.072

Other subject 93.8 72.1 21.7** 0.005

Graduate Degree

Any graduate degree 40.6 69.8 -29.2** 0.001

Subjectb

Math 0.0 4.8 -4.8 0.081

Secondary math education 18.8 15.9 2.9 0.671

Other subject 21.9 54.0 -32.1** 0.000

Sample Size 64 63

Source: Survey of Secondary Math Teachers.

a

Selective colleges are those ranked by Barron’s Profiles of American Colleges 2003 as being very competitive, highly competitive, 

or most competitive.

b

Percentages might not sum to 100 if some sample members had a degree in more than one subject.

c

Includes statistics, engineering, computer science, finance, economics, and physics/astrophysics.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.

Despite the fact that the TFA teachers were less likely to have majored in math or a related 

subject than comparison teachers, the TFA teachers displayed greater math content knowledge, 

as measured by the Praxis II Mathematics Content Knowledge Test (taken primarily by the high 

school teachers in the sample, along with a few middle school teachers in states that allowed or 

required middle school teachers to take this test) or the Praxis II Middle School Mathematics 

Test (taken by the remaining middle school teachers in the sample) (Table IV.5).19

 19 Response rates on the Praxis II differed for TFA and comparison teachers—91 percent of the TFA teachers 

in the sample had Praxis II scores, compared with only 73 percent of comparison teachers (Appendix Table A.18). 

In the main analysis, we omitted teachers with missing scores. As a sensitivity test, in Appendix Table E.1 we 

examined differences in Praxis II scores when we imputed values that would be otherwise missing. Results were 

similar under the two approaches, although differences between the two groups were somewhat more pronounced, 

suggesting that teachers with missing Praxis data might have been those who would have scored lower had they 

taken the test.

TFA teachers 

who took the Mathematics Content Knowledge Test outperformed comparison teachers by 

22 points (or 0.93 standard deviations); those who took the Middle School Mathematics Test also 

outperformed comparison teachers by 22 points (or 1.19 standard deviations). Similar differences 

persisted among both teacher matches for whom the Praxis was “high stakes” (those in districts 

that required the exam for certification) and those for whom the Praxis was “low stakes” (not 

required for certification, and taken only at the request of the study team). 
Effectiveness of TFA and Teaching Fellows Teachers 

45 

Table IV.4. Average Number of College-Level Math Courses Taken by TFA and Comparison Teachers in the 

Study 

TFA 

Teachers

Comparison 

Teachers Difference p-Value

All Teachers

Total Number of College-Level Math Courses 4.9 8.3 -3.4** 0.001

Calculus 1.7 2.1 -0.4 0.179

Advanced Algebra 0.5 1.3 -0.8** 0.000

Analysis 0.3 0.8 -0.5** 0.008

Advanced Geometry/Topology 0.1 0.6 -0.5** 0.000

Probability and Statistics 1.2 1.5 -0.3 0.146

Discrete Mathematics 0.2 1.0 -0.8** 0.000

Applied Mathematics 0.8 1.0 -0.1 0.669

Sample Size 64 63

Middle School Teachers

Total Number of College-Level Math Courses 4.2 6.7 -2.5** 0.006

Sample Size 47 50

High School Teachers

Total Number of College-Level Math Courses 6.6 14.4 -7.7* 0.011

Sample Size 17 13

Source: Survey of Secondary Math Teachers.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.

Although it would be useful to compare average scores of study teachers to average scores 

of the full set of teachers who took the Praxis II mathematics tests nationwide, published data on 

national average scores are available only for test takers who passed the test. For comparison to 

these statistics, we also examined the average scores of the teachers in our sample who passed 

the test. On the Mathematics Content Knowledge Test, TFA teachers in the study who passed the 

test scored an average of 165 points, compared with an average of 155 for all test-takers 

nationwide who passed. Similarly, on the Middle School Mathematics Test, TFA teachers in the 

study who passed the test scored an average of 182 points, compared with an average of 169 for 

all test-takers nationwide who passed. 

3. Teaching and Nonteaching Work Experience

Previous research has shown that teacher effectiveness generally increases with years of 

teaching experience (Hanushek and Rivkin 2006; Kane et al. 2008). Because TFA only asks its 

teachers to make a two-year commitment to teaching (although they may choose to remain 

longer), critics of the program have claimed that TFA teachers are less effective than other 

teachers because they lack experience (Heilig and Jez 2010). TFA teachers in the study did have 

less teaching experience than comparison teachers (Table IV.6). The TFA teachers had been 

teaching an average of two years as of the end of the study school year, compared with an 

average of 10 years among comparison teachers. Eighty-three percent of the TFA teachers were 

in their first or second year of teaching, compared with 10 percent of comparison teachers. 

Seventy percent of the comparison teachers had been teaching more than five years, while none 

of the TFA teachers had been teaching this long. 
Effectiveness of TFA and Teaching Fellows Teachers 

46 

Table IV.5. Praxis II Scores of TFA and Comparison Teachers in the Study (percentages unless otherwise 

indicated)

Test-Takers 

Nationwide

TFA 

Teachers

Comparison 

Teachers

TFAComparison

Difference p-Value

Overall

Mathematics: Content Knowledge Test

Average score n.a. 162.0 140.1 21.9* 0.010

Average score of those who scored above the 

state’s passing thresholda 154.5† 164.6 152.7 11.9 0.074

Sample size 5,785 15 11

Middle School Mathematics Test

Average score n.a. 179.8 158.3 21.6** 0.000

Average score of those who scored above the 

state’s passing thresholda 169.0†† 181.7 166.8 14.9** 0.000

Sample size 9,532 45 40

High-Stakes Test-Takersb

Mathematics: Content Knowledge Test

Average score n.a. 159.9 140.1 19.8* 0.018

Sample size 14 11

Middle School Mathematics Test

Average score n.a. 179.3 163.0 16.3** 0.002

Sample size 20 16

Low-Stakes Test-Takersc

Middle School Mathematics Test

Average score n.a. 180.3 155.1 25.2** 0.000

Sample size 25 24

Source: Data on all test-takers nationwide are from Gitomer and Qi (2010), and include test-takers who did and did not 

eventually enter the teaching profession. Data for study teachers are from study-administered assessment or 

were provided by the Educational Testing Service. 

a

The Educational Testing Service does not report the average score of all test-takers, but only the average score of those 

who passed the test in their states. To compare the study sample with the national statistics from the Educational Testing 

Service, we computed the average scores of sample members who scored above their states’ passing thresholds using the 

Praxis passing thresholds from 2011. In states in which this test was not required, the score was compared with the 

average passing threshold across all states that did require this test.

b

High-stakes test-takers are those who are in districts that require secondary math teachers to pass the relevant Praxis II 

assessment for certification.

c

Low-stakes test-takers are those who are in districts that do not require secondary math teachers to pass the relevant 

Praxis II assessment for certification. Because fewer than three low-stakes test-takers in the TFA study sample took the 

Mathematics: Content Knowledge test, we do not present estimates for this group, to protect respondent confidentiality. 

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

 †Difference between secondary teachers nationwide and TFA teachers is statistically significant at the 0.05 level, twotailed test.

††Difference between secondary teachers nationwide and TFA teachers is statistically significant at the 0.01 level, two-tailed 

test.

 ^Difference between secondary teachers nationwide and comparison teachers is statistically significant at the 0.05 level, 

two-tailed test.

^^Difference between secondary teachers nationwide and comparison teachers is statistically significant at the 0.01 level, 

two-tailed test.

TFA = Teach For America.

n.a. = not available.
Effectiveness of TFA and Teaching Fellows Teachers 

47 

TFA teachers in the sample also had less nonteaching work experience than the comparison 

teachers (Table IV.6). Seventeen percent of the TFA teachers had held a nonteaching job after 

college, compared with 54 percent of comparison teachers. Nine percent of TFA teachers had 

used college-level math in a nonteaching job, compared with 37 percent of comparison teachers. 

Table IV.6. Nonteaching and Teaching Work Experience of TFA and Comparison Teachers in the Study 

(percentages unless otherwise indicated)

TFA 

Teachers

Comparison 

Teachers Difference p-Value

Nonteaching Work Experience

Had a nonteaching job after college 17.2 54.0 -36.8** 0.000

Years of experience in nonteaching job (average)a 0.4 2.7 -2.3** 0.000

Used college-level math in nonteaching joba 9.4 36.5 -27.1** 0.000

Teaching Experience (end of study year)

Years of teaching experience (average) 1.9 10.1 -8.3** 0.000

1 or 2 years of teaching experience 82.8 9.5 73.3** 0.000

3 to 5 years of teaching experience 17.2 20.6 -3.4 0.623

More than 5 years of teaching experience 0.0 69.8 -69.8** 0.000

Years of experience teaching math (average) 1.8 7.8 -6.0** 0.000

1 or 2 years of math teaching experience 85.9 9.5 76.4** 0.000

3 to 5 years of math teaching experience 14.1 28.6 -14.5* 0.047

More than 5 years of math teaching experience 0.0 61.9 -61.9** 0.000

Sample Size 64 63

Source: Survey of Secondary Math Teachers.

a

Calculations are based on all teachers, regardless of whether they had a nonteaching job after college.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.

4. Teacher Training, Professional Development, and Support 

Teacher training and professional development. TFA and comparison teachers reported 

completing similar amounts of math pedagogy instruction and student teaching in math as part of 

their teacher training programs (Table IV.7).20

Teachers from TC routes typically receive different teacher training than teachers from AC 

routes (Constantine et al. 2009), and so it is not surprising that there were some differences in 

teacher training and support in the subset of TFA teachers who were compared with teachers 

from TC routes relative to the subset who were compared with teachers from AC routes 

(Appendix Table D.6). For instance, TFA teachers completed significantly less student teaching 

Differences in average hours of math pedagogy 

instruction and average days of student teaching in math between TFA and comparison teachers 

were not statistically significant. However, the average days of student teaching in math mask 

some differences between the two groups—the TFA teachers were more likely than comparison 

teachers to have completed at least some student teaching in math and were more likely to have 

completed from 11 to 20 days. The TFA teachers also reported receiving less professional 

development in math during the study school year than comparison teachers (6 versus 11 hours). 

 20 Because questions about teacher training required more experienced teachers (predominantly comparison 

teachers) to recall experiences that occurred several years in the past, these data may be less reliable than data 

pertaining to the study year.
Effectiveness of TFA and Teaching Fellows Teachers 

48 

Table IV.7. Training and Professional Development of TFA and Comparison Teachers in the Study (percentages 

unless otherwise indicated)

TFA 

Teachers

Comparison 

Teachers Difference p-Value

Average Hours of Math Pedagogy Instruction as Part of 

Teacher Traininga 35.2 37.1 -1.9 0.755

Days of Student Teaching in Math as Part of Teacher 

Trainingb

No days 21.9 47.6 -25.7** 0.002

1 to 10 6.3 4.8 1.5 0.716

11 to 20 42.2 15.9 26.3** 0.001

More than 20 29.7 31.7 -2.1 0.803

Average Days of Student Teaching in Math 18.1 24.7 -6.6 0.141

Hours per Day Spent in Student Teaching in Math as Part of 

Teacher Training (average)c 1.3 3.3 -2.0** 0.000

Average Hours Spent in Math Pedagogy Professional 

Development During School Yeard 6.1 11.0 -4.9** 0.000

Sample Size 64 63

Source: Survey of Secondary Math Teachers.

a

Teachers were asked, “As part of your training to become a math teacher, did you receive any instruction in math pedagogy 

or strategies to teach math?” If so, “In total, how many hours of instruction in math pedagogy or strategies to teach math did 

you receive?” Possible responses were none, 1 to 4, 5 to 20, 21 to 40, 41 to 60, 61 to 80, 81 to 100, and more than 100. To 

construct average hours of math pedagogy training, we created a continuous variable equal to zero for teachers who 

completed no training, 100 for those who completed more than 100 hours, and the midpoint of the range for all other 

categories.

b

Teachers were asked, “Did your teacher education/preparation program require you to do any student teaching in which 

you went to an elementary or secondary school and taught one or more math lessons to a whole classroom of students?” If 

so, “On approximately how many days, in total, did you teach at least one full math lesson (at least one class period) to a 

whole classroom of students during your teacher education/preparation program?” Possible responses were none, 1 to 5, 6 

to 10, 11 to 15, 16 to 20, 21 to 40, 41 to 60, 61 to 80, and more than 80. To construct average days of student teaching in 

math, we created a continuous variable equal to zero for teachers who did not do any student teaching in math, 80 for 

those who did more than 80 days, and the midpoint of the range for all other categories.

c

Calculated only among those teachers who said they did some student teaching in math.

d

Teachers were asked, “During this school year, did you attend any professional development classes, workshops, or 

seminars provided by the school district in math pedagogy or strategies to teach math?” If so, “In total, how many hours did 

you spend attending these professional development classes, workshops, or seminars in math pedagogy or strategies to 

teach math?” Possible responses were none, 1 to 4, 5 to 10, 11 to 20, and more than 20. To construct average hours of 

professional development, we created a continuous variable equal to zero for teachers who did no professional 

development, 20 for those who did more than 20 hours, and the midpoint of the range for all other categories.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.

in math, on average, than comparison teachers from TC routes (20 versus 38 days), while the 

difference between TFA teachers and comparison teachers from AC routes (17 versus 8 days) 

was not statistically significant at the 5 percent level.

Coursework during study year. Most states require teachers from AC routes, including 

TFA, to take coursework in their first few years of teaching to fulfill state certification 

requirements (Feistritzer 2005). Consistent with the fact that they were more likely to be in their 

first or second year of teaching and thus likely still fulfilling coursework requirements for 

certification, TFA teachers were more likely than comparison teachers to have taken coursework 

during the study year (Table IV.8). Fifty percent of TFA teachers reported taking coursework

related to their teaching job during the study year, compared with 21 percent of comparison 
Effectiveness of TFA and Teaching Fellows Teachers 

49 

Table IV.8. Coursework Taken During the School Year by TFA and Comparison Teachers in the Study (percentages 

unless otherwise indicated)

TFA 

Teachers

Comparison 

Teachers Difference p-Value

All Teachers

Took Coursework Related to Teaching Job 50.0 20.6 29.4** 0.000

Total Hours Spent During School Year on Coursework 

(average) 89.4 49.9 39.5 0.095

Hours Spent in Class During School Year on Coursework 

(average) 41.8 22.8 19.1 0.089

Hours Spent Out of Class During School Year on Coursework 

(average) 47.5 27.1 20.4 0.137

Sample Size 64 63

Source: Survey of Secondary Math Teachers.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.

n.a = not applicable.

teachers. TFA teachers spent an average of 89 hours on coursework during the study year 

(roughly evenly divided between time in and out of class), compared with 50 hours among 

comparison teachers; this difference was not statistically significant at the 5 percent level.

Mentoring. Under federal guidelines, novice teachers from AC programs must participate in 

“a program of intensive supervision that consists of structured guidance and regular ongoing 

support for teachers or in a teacher mentoring program” to be considered “highly qualified” (U.S. 

Department of Education 2005). In keeping with the fact that they were more likely to be in their 

first or second year of teaching than comparison teachers, TFA teachers were more likely than 

comparison teachers to report having had a mentor during the study school year (Table IV.9). 

Sixty-seven percent of the TFA teachers reported having had a mentor, compared with 

29 percent of comparison teachers. TFA teachers were more likely than comparison teachers to 

have had a mentor assigned by their school as well as to have had a mentor assigned by their 

program. Among those who had mentors, TFA teachers and comparison teachers spent similar 

amounts of time both observing other teachers and being observed by their mentors. On average, 

TFA teachers spent 87 more minutes in formal meetings with their mentors than comparison 

teachers, a statistically significant difference; there was no statistically significant difference 

between the two groups in the amount of time spent in informal meeting with mentors. 
Effectiveness of TFA and Teaching Fellows Teachers 

50 

Table IV.9. Mentoring Received During the School Year by TFA and Comparison Teachers in the Study 

(percentages unless otherwise indicated)

TFA 

Teachers

Comparison 

Teachers Difference p-Value

Had a Mentor During School Year 67.2 28.6 38.6** 0.000

Mentor Assigned by School 62.5 27.0 35.5** 0.000

Mentor Assigned by Program 31.3 0.0 31.3** 0.000

Average Time Spent Observing Other Teachers (minutes) 92.6 92.7 -0.1 0.997

Average Time Spent Being Observed by Mentors (minutes) 16.8 15.1 1.7 0.842

Average Time Spent in Formal Meetings with Mentors (minutes) 147.9 61.4 86.5** 0.007

Average Time Spent in Informal Meetings with Mentors 

(minutes) 102.2 73.5 28.7 0.495

Number of Times Received Written Feedback on Teaching 

Performance 2.2 1.6 0.6 0.447

Felt that Mentoring Was Very Helpful 48.4 23.8 24.6** 0.004

Sample Size 64 63

Source: Survey of Secondary Math Teachers.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.

5. Views Toward Teaching

Because teachers’ levels of satisfaction with their jobs have the potential to influence how 

long they stay in teaching, we measured the job satisfaction of both TFA and comparison 

teachers. TFA teachers were less satisfied with some aspects of their job than comparison 

teachers, particularly those aspects related to school policies and staff (Table IV.10). Teachers 

were given a list of 10 aspects of their teaching job and asked whether they were “very 

dissatisfied,” “somewhat dissatisfied,” “somewhat satisfied,” or “very satisfied” with this aspect 

of their job. TFA and comparison teachers reported statistically similar levels of satisfaction with 

aspects of their jobs related to their own classrooms (autonomy and control over their own 

classrooms, students’ motivation to learn, students’ discipline and behavior, and availability of 

resources for the classroom). However, TFA teachers reported significantly lower levels of 

satisfaction for aspects of their jobs related to school policies and staff, including their influence 

over school policy, opportunities for professional development, procedures for performance 

evaluation, and the professional caliber of their colleagues.
Effectiveness of TFA and Teaching Fellows Teachers 

51 

Table IV.10. Job Satisfaction of TFA and Comparison Teachers in the Study (percentages unless otherwise 

indicated)

Percentage of Teachers Who Were Somewhat or 

Very Satisfied with this Aspect of Joba

Aspect of Job

TFA 

Teachers

Comparison 

Teachers Difference p-Value

Autonomy and Control Over Own Classroom 84.4 85.7 -1.3 0.834

Students’ Motivation to Learn 39.1 38.7 0.4 0.968

Students’ Discipline and Behavior 27.0 34.9 -7.9 0.339

Availability of Resources for Classroom 65.1 66.1 -1.0 0.903

Recognition/Support from Administration 59.4 67.7 -8.4 0.333

Influence Over School Policies and Practices 37.5 62.9 -25.4** 0.004

Opportunities for Professional Development 54.7 82.5 -27.9** 0.001

Principal’s Leadership and Vision 56.3 68.3 -12.0 0.165

Procedures for Performance Evaluation 50.0 73.0 -23.0** 0.007

Professional Caliber of Colleagues 57.8 76.2 -18.4* 0.028

Sample Size 64 63

Source: Survey of Secondary Math Teachers.

a

Teachers were asked about their satisfaction with each aspect of their job—possible responses were very 

dissatisfied, somewhat dissatisfied, somewhat satisfied, and very satisfied.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.

C. Students in the TFA Study Sample

Among students in the analysis sample (those for whom we have outcome test score data), 

those assigned to the TFA teachers (the treatment group) and those assigned to the comparison 

teachers (the control group) were statistically similar in terms of their baseline characteristics

(Table IV.11). This suggests that random assignment was properly implemented and that student 

attrition after random assignment (due to lack of outcome test score data) did not lead to 

differences in observable baseline characteristics between the two groups. Of the 23 differences 

in baseline characteristics examined, three were statistically significant at the 5 percent level, and 

these differences were small in magnitude. These same differences were present for the full 

sample of students who were randomly assigned (including those with missing outcome data), as 

shown in Appendix Table A.5—this indicates that the differences occurred at the time of random 

assignment and were not due to differential attrition between the treatment and control groups 

after random assignment.

Consistent with TFA’s goal of serving disadvantaged students, treatment and control group 

students in the analysis sample scored, on average, about half a standard deviation below average 

for their states in both reading and math in the years prior to the evaluation, as indicated by 

average z-scores for both groups of around -0.50. Both treatment and control group students were 

13.4 years old on average. The majority of students (around 62 percent) in both groups were 

black, non-Hispanic, while 28 percent in both groups were Hispanic, 7 percent were white, nonHispanic, and 2 percent were Asian. Thus a higher percentage of the study sample were members 

of racial and ethnic minority groups relative to public secondary school students nationwide, 
Effectiveness of TFA and Teaching Fellows Teachers 

52 

Table IV.11. Average Baseline Characteristics of Students in the Analysis Sample Who Were Assigned to TFA 

Teachers or Comparison Teachers (percentages unless otherwise indicated)

Characteristic

Secondary 

School 

Students 

Nationwide

Assigned 

to TFA 

Teachers

Assigned to

Comparison

Teachers

Difference

Between 

TFA and 

Comparison p-Value

Baseline Math Achievement

Baseline math score (average z-score) 0.00 -0.51 -0.50 -0.01 0.531

Score below 25th percentile of state 25.0 39.6 39.4 0.2 0.741

Score below 50th percentile of state 50.0 73.1 72.7 0.3 0.641

Baseline Reading Achievement

Baseline reading score (average z-score) 0.00 -0.51 -0.51 0.00 0.734

Score below 25th percentile of state 25.0 40.6 39.8 0.7 0.393

Score below 50th percentile of state 50.0 71.9 73.0 -1.1 0.163

Age (average years) n.a. 13.44 13.39 0.05** 0.002

Female 50.2 48.6 50.0 -1.5 0.102

Race and Ethnicity

Asian, non-Hispanic 4.7 2.1 1.8 0.2 0.391

Black, non-Hispanic 15.9 62.1 62.5 -0.4 0.656

Hispanic 18.2 28.3 27.7 0.5 0.471

White, non-Hispanic 60.1 6.5 6.6 -0.1 0.802

Other race/ethnicity 1.2 1.1 1.4 -0.3 0.319

Eligible for Free/Reduced-Price Lunch 35.0 89.9 90.5 -0.7 0.469

Limited English Proficient 6.5 8.0 8.4 -0.4 0.475

Individualized Education Plan 12.5 6.4 6.0 0.4 0.358

Grade Level in Study Year

6th grade 7.4 27.2 27.2 0.0 .

a

7th grade 7.5 28.6 28.7 -0.1 0.164

8th grade 7.6 19.5 19.5 0.1 0.164

9th grade 8.6 14.6 14.5 0.2 0.555

10th grade 7.9 7.3 7.8 -0.6* 0.012

11th grade 7.2 2.6 2.4 0.2 0.237

12th grade 6.6 0.2 0.0 0.2* 0.044

Number of Students 2,292 2,281

Number of Classroom Matches 111 111

Number of Teachers 66 70

Number of Schools 45 45

Source: Nationwide statistics on demographic characteristics from the 2007–2008 Schools and Staffing Survey, 

available at http://nces.ed.gov/pubs2009/2009321/. Data on nationwide grade distribution from the 

2006–2007 “Digest of Education Statistics: Enrollment in Public Elementary and Secondary Schools, by 

Grade,” available at http://nces.ed.gov/programs/digest/d08/tables/ dt08_037.asp. Data on study 

students from district administrative records.

Note: Means and percentages are weighted with sample weights and adjusted for classroom match fixed 

effects. P-values are based on a regression of the specified characteristic on a TFA indicator and 

classroom match indicators, accounting for sample weights and clustering at the teacher level.

a

p-value is not defined because there is no variation in this variable within classroom matches.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

53 

among whom 16 percent were black, 18 percent were Hispanic, and 60 percent were white, nonHispanic. Around 90 percent of students in both groups were eligible for free or reduced-price 

lunch, higher than the national average of 35 percent. In both groups, around 8 percent of 

students had limited English proficiency (similar to the national average of 7 percent) and around 

6 percent had an Individualized Education Plan (IEP) for a special education program or 

services. The percentage of students with an IEP in the TFA sample is lower than the national 

average of 13 percent, perhaps because students with more severe disabilities or restrictive IEPs 

were exempted from random assignment and excluded from the study sample. 
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

55 

V. TEACH FOR AMERICA: IMPACTS ON SECONDARY STUDENT 

MATH ACHIEVEMENT

A central goal of school administrators, policymakers, and parents is to select teachers who 

are most effective in increasing student achievement. In this chapter, we examine the impact of 

Teach For America (TFA) secondary math teachers on student achievement in math, relative to 

the comparison teachers who taught the same courses in the same schools. To estimate impacts, 

we compared the end-of-year math achievement of students assigned to TFA teachers and those 

assigned to comparison teachers. Random assignment ensured that these two groups of students 

had similar achievement levels and other characteristics at the start of the school year, so that 

differences in achievement between the two groups at the end of the school year could be 

reliably attributed to the effectiveness of the teachers. TFA and comparison teachers could differ 

in effectiveness as a result of two types of factors: (1) the characteristics they had before entering 

their preparation programs and (2) the training and support they received from their programs. 

The impact findings presented here are based on TFA and comparison teachers whose classes 

were fully comparable and whose schools and districts agreed to be in the study; the findings 

may not necessarily apply to TFA teachers in other types of schools, subjects, or demographic 

environments. 

For all impact analyses, the outcome of interest was a student’s end-of-year math score. We 

expressed the outcome as a z-score based on means and standard deviations of scores for the full 

student population in the same state and grade (in middle school grades) or the national norming 

sample of the student’s assessment (in high school grades). Therefore, differences in 

effectiveness between TFA and comparison teachers, expressed in student z-score units, can be 

regarded as effect sizes measured in standard deviation units within a statewide or national 

reference population. We estimated impacts within the full set of classroom matches in which 

TFA teachers were included (Section A) as well as within subgroups of matches defined by 

characteristics of the TFA or comparison teachers (Sections B and C). 

A. Impacts of TFA Teachers Relative to All Comparison Teachers 

1. Average Impact

On average, TFA teachers in the study were more effective than comparison teachers. 

Students assigned to TFA teachers scored 0.07 standard deviations higher on end-of-year math 

assessments than students assigned to comparison teachers (Table V.1). Although the average 

end-of-year math score in both groups was below the mean in the statewide or national reference 

populations (indicated by negative average z-scores), TFA teachers raised the average 

achievement of their students to a level that was closer to the population mean. 

The magnitude of the difference in effectiveness between TFA and comparison teachers can 

be interpreted in several ways. First, the effect size can be expressed as a change in percentiles of 

achievement within the reference populations used in the study. If assigned to a comparison 

teacher, the average student in the study would have had a z-score of -0.60, equivalent to the 27th 

percentile of achievement in his or her reference population based on a normal distribution for 

test scores. If assigned to a TFA teacher, this student would, instead, have had a z-score of 

-0.52—equivalent to the 30th percentile. Thus, the average student in the study would gain three 

percentile points from being assigned to a TFA teacher rather than a comparison teacher. A 

limitation of this interpretation, however, is that a given effect size equates to a different 
Effectiveness of TFA and Teaching Fellows Teachers 

56 

percentile gain at different points in the achievement distribution. Specifically, the effect size of 

0.07 translates to a 3 percentile point change for a student who, like the average student in the 

study, would have scored at the 27th percentile if assigned to a comparison teacher. However, 

the same effect size would imply a smaller percentile point change for lower-performing students 

and a larger percentile point change for students closer to the 50th percentile. 

Table V.1. Difference in Effectiveness Between TFA Teachers and All Comparison Teachers 

Mean Outcome

Difference in Outcomes 

Between Groups

Outcome Variable

Assigned 

to TFA 

Teachers 

Assigned to 

Comparison 

Teachers Estimate p-Value

Student Math Achievement (z-score) -0.52 -0.60 0.07** 0.000

Sample Sizes

Number of Students 2,292 2,281

Number of Classroom Matches 111 111

Number of Teachers 66 70

Number of Schools 45 45

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Note: The difference between groups is adjusted for classroom match fixed effects and all covariates in 

Appendix Table B.1. The mean outcome for students assigned to TFA teachers is calculated as the 

unadjusted mean outcome for students assigned to comparison teachers plus the adjusted difference in 

outcomes between the two groups.

 *Estimate is statistically significant at the 0.05 level based on a two-tailed test after adjusting for multiple hypothesis 

testing.

**Estimate is statistically significant at the 0.01 level based on a two-tailed test after adjusting for multiple hypothesis 

testing.

TFA = Teach For America.

Alternatively, the effect size can be compared with educationally relevant benchmarks. An 

illustrative benchmark is the average one-year gain in achievement exhibited by students on 

nationally normed assessments in grades 6 through 11, as tabulated by Hill et al. (2008). On the 

basis of this benchmark, the difference in achievement between students of TFA teachers and 

students of comparison teachers amounted to 26 percent of an average year of learning by 

students nationwide—that is, 2.6 months of learning in a 10-month school year. 

The finding that TFA teachers were more effective than comparison teachers is robust to 

multiple sensitivity analyses. We estimated models that (1) excluded covariates, (2) used 

alternative methods of handling missing data and invalid test scores, (3) used alternative 

approaches to weighting classroom matches, (4) dropped classroom matches with high rates of 

student mobility, (5) dropped matches with supplemental math classes, (6) used alternative ways 

of standardizing the outcome variable, and (7) accounted for students who switched to a different 

type of teacher than their originally assigned teacher (see Appendix Table F.1). Students of TFA 

teachers were estimated to outperform students of comparison teachers by a statistically 

significant degree in all models.

In supplemental analyses, we examined impacts on measures of student absences, a channel 

through which teachers could affect student math achievement. We found no statistically 

significant differences in the rate of absences during the study year between students of TFA 

teachers and students of comparison teachers (Appendix Table F.2). 
Effectiveness of TFA and Teaching Fellows Teachers 

57 

2. Variation in Impacts 

Although TFA teachers had a positive average impact on student math achievement relative 

to comparison teachers, impacts from individual classroom matches varied in both sign and 

magnitude (Figure V.1). Notably, not all TFA teachers were more effective than their 

counterparts; without regard to statistical significance, the estimated difference in effectiveness 

between TFA and comparison teachers was positive in 60 percent of classroom matches (67 out 

of 111) and negative in the remaining 40 percent. Because each match-specific estimate was 

based on a small number of students, random statistical error contributed to the variation in 

impact estimates across classroom matches. Nevertheless, on the basis of an F-test, we found 

that the observed variation in impact estimates across classroom matches exceeded the variation 

that would be expected from pure statistical chance. 

Therefore, although TFA teachers were more effective than comparison teachers on average, 

our findings suggest that an individual TFA teacher could be more or less effective than an 

individual comparison teacher. In other words, even after accounting for teachers' route to 

certification (TFA or comparison), teachers varied in effectiveness. Chapter IX explores 

additional factors that might account for this variation in effectiveness.

Figure V.1. Differences in Effectiveness Between TFA Teachers and Comparison Teachers from 

Individual Classroom Matches

-1.4

-1.2

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Classroom Match

Difference in Effectiveness

(student z-score units)

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) assessments.

Notes: Differences in effectiveness from individual classroom matches are estimated from a regression of students’ endof-year math scores on classroom match indicators, an indicator for being assigned to a TFA teacher fully 

interacted with all classroom match indicators, and all covariates in Appendix Table B.1. There are 111 

classroom matches represented in the figure. An F-test of the null hypothesis that differences in effectiveness 

between TFA teachers and comparison teachers are equal across classroom matches has a p-value of less than 

0.001. 

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

58 

Given that the difference in effectiveness between TFA and comparison teachers varied 

across matches, we examined whether differences were more or less pronounced when specific 

types of TFA and comparison teachers were compared. The subgroup analyses that address this 

question are discussed in the remainder of this chapter; detailed results are presented in 

Appendix Table F.3. 

B. Impacts of TFA Teachers Relative to Comparison Teachers from Traditional 

and Alternative Routes to Certification

The comparison teachers who were compared with TFA teachers consisted of a mix of 

teachers from two distinct routes to certification: traditional routes to certification (TC routes) 

and less selective alternative routes to certification (AC routes). As we discussed in Chapter IV, 

on a number of dimensions of academic background and training, patterns of differences 

between TFA and comparison teachers varied according to whether the comparison teachers 

entered teaching through TC or AC routes. Therefore, the average impact of TFA teachers might 

mask differences in how TFA teachers performed relative to each type of comparison teacher. In 

fact, one criticism of AC routes, such as TFA, is that teachers from those routes who have 

entered the classroom without completing all certification requirements have less pedagogical 

knowledge—and are therefore less effective—than counterparts from TC routes (DarlingHammond 1990, 2000; Darling-Hammond et al. 2005). To examine this possibility, we 

compared the effectiveness of TFA and comparison teachers within two separate subgroups of 

classroom matches: (1) those with TC comparison teachers and (2) those with AC comparison 

teachers.

On average, TFA teachers were more effective than comparison teachers from both TC and 

less selective AC routes. In classroom matches in which TFA teachers were compared with TC 

comparison teachers, students of TFA teachers outperformed those of TC comparison teachers 

by 0.06 standard deviations (Figure V.2). Likewise, students of TFA teachers scored 0.09 

standard deviations higher than students of AC comparison teachers in the same classroom 

match. These findings suggest that a strategy of hiring TFA teacher to teach the classes in the 

study would lead to higher student math achievement than would a strategy of hiring either TC 

or AC comparison teachers.

C. Impacts Within Other Teacher Subgroups

1. Subgroups Defined by Teaching Experience

Although the findings presented thus far shed light on the effectiveness of TFA teachers 

who are less experienced, on average, than their counterparts from other routes, school 

administrators might also want to know how student achievement at their school would differ in 

the short term as a result of hiring a new TFA teacher rather than some other new, inexperienced 

teacher. We gauged the short-term effects of choosing a new TFA teacher over a new non-TFA 

teacher by comparing TFA and comparison teachers who had recently entered teaching. 

Specifically, we classified all teachers into two experience categories: (1) novice teachers, 

defined as those in their first three years of teaching, and (2) experienced teachers, defined as 
Effectiveness of TFA and Teaching Fellows Teachers 

59 

Figure V.2. Differences in Effectiveness Between TFA Teachers and Comparison Teachers from 

Traditional and Alternative Routes to Certification

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

TFA versus

TC Comparison Teachers

TFA versus

AC Comparison Teachers

Difference in Effectiveness

(student z-score units)

0.06*

0.09**

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Note: Differences in effectiveness are adjusted for classroom match fixed effects and all covariates in 

Appendix Table B.1

*Estimate is statistically significant at the 0.05 level based on a two-tailed test after adjusting for multiple hypothesis 

testing.

**Estimate is statistically significant at the 0.01 level based on a two-tailed test after adjusting for multiple hypothesis 

testing.

AC = alternative route to certification; TC = traditional route to certification; TFA = Teach For America.

those in their fourth year of teaching or beyond. We examined impacts within the subgroup of 

classroom matches in which novice TFA teachers were compared with novice comparison 

teachers. We also examined impacts within other experience subgroups to determine whether the 

positive impact of TFA teachers was limited to particular types of comparisons or was observed 

more broadly. Because very few (4 of 66) TFA teachers were experienced, the remaining 

comparisons that included TFA teachers in the study were primarily those in which novice TFA 

teachers were compared with experienced comparison teachers.

Novice TFA teachers were more effective than novice comparison teachers in the study. 

Average math achievement was higher by 0.08 standard deviations for students of novice TFA 

teachers compared with students of novice comparison teachers (Figure V.3). The evidence 

implies that a net gain in student achievement from hiring a new TFA teacher rather than a new 

non-TFA teacher would be realized even in the short run. 

Novice TFA teachers also raised student math achievement by 0.07 standard deviations 

relative to experienced comparison teachers despite having 11 fewer years of experience, on 

average (Figure V.3). Taken together, our findings indicate that novice TFA teachers were more 

effective than comparison teachers irrespective of whether the comparison teachers were novice 

or experienced.
Effectiveness of TFA and Teaching Fellows Teachers 

60 

Figure V.3. Differences in Effectiveness Between Novice TFA Teachers and Comparison Teachers, by 

Experience Level of Comparison Teacher

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

Novice TFA versus 

Novice Comparison Teachers

Novice TFA versus 

Experienced Comparison Teachers

Difference in Effectiveness

(student z-score units)

0.08** 0.07**

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA)

assessments.

Note: Differences in effectiveness are adjusted for classroom match fixed effects and all covariates in 

Appendix Table B.1. Novice teachers are defined as teachers in their first three years of teaching. 

Experienced teachers are defined as teachers in their fourth or more year of teaching.

 *Estimate is statistically significant at the 0.05 level, two-tailed test. 

**Estimate is statistically significant at the 0.01 level, two-tailed test. 

TFA = Teach For America.

2. Subgroups Defined by Middle and High School

We examined differences in effectiveness between TFA and comparison teachers separately 

for middle school and high school teachers due to a number of differences between the two sets 

of grade levels. First, the state assessments taken by middle school students differed from the 

study-administered Northwest Evaluation Association (NWEA) assessments taken by high 

school students. For example, the state assessments were expected to be aligned more closely 

with state curriculum standards, but the NWEA assessments were expected to be less prone to 

floor and ceiling effects due to their computer-adaptive structure. Second, high school courses 

covered more advanced mathematics than did middle school courses. This difference could 

influence impact findings if the effective teaching of math at different levels required different 

sets of instructional skills. As Chapter IV shows, TFA teachers at both the middle and high 

school levels were more likely than comparison teachers to have graduated from a selective 

college or university, had higher average scores on the Praxis II, and were less likely to have 

majored in math. They also had taken fewer college-level math courses than comparison teachers 

at both the middle and high school levels, although this difference was more pronounced among 

high school teachers. 
Effectiveness of TFA and Teaching Fellows Teachers 

61 

At both the middle school and high school levels, TFA teachers had positive impacts relative 

to comparison teachers (Figure V.4). Students of TFA teachers outscored those of comparison 

teachers by 0.06 standard deviations in middle school and 0.13 standard deviations in high 

school. 

Figure V.4. Differences in Effectiveness Between TFA Teachers and Comparison Teachers Within 

Middle Schools and High Schools

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

Middle School High School

Difference in Effectiveness

(student z-score units)

0.06**

0.13**

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA)

assessments.

Note: Differences in effectiveness are adjusted for classroom match fixed effects and all covariates in 

Appendix Table B.1. 

 *Estimate is statistically significant at the 0.05 level, two-tailed test. 

**Estimate is statistically significant at the 0.01 level, two-tailed test. 

TFA = Teach For America.

D. Conclusions

TFA aims to place high-quality teachers in schools that serve some of the most 

disadvantaged students in the United States. As we discuss in Chapter III, the program focuses 

its recruitment efforts primarily on recent college graduates and asks them to make a two-year

commitment to teaching. TFA is highly selective, with a multi-stage application process, and 

accepts only about 12 percent of applicants. The program attempts to identify applicants it 

believes will be most successful in the classroom based on both staff judgment and predictions of 

a mathematical selection model. It provides its newly selected teachers with an intense five-week 

summer training program as well as mentoring and support throughout the teachers’ two-year 

commitment to the program.

Consistent with TFA’s mission to place teachers in high-need schools, TFA teachers in the 

study were typically placed in urban schools that served economically disadvantaged students, 

largely from racial and ethnic minority groups. As we discuss in Chapter IV, the non-TFA study 

teachers in these schools were primarily nonwhite women, typically with more than five years of 

teaching experience. In contrast, the TFA teachers in the study were overwhelmingly white, less
Effectiveness of TFA and Teaching Fellows Teachers 

62 

likely to be female, and had significantly less teaching (and general work) experience. The TFA 

teachers were also far more likely to have attended a selective undergraduate university. 

Although the TFA teachers took fewer college-level math courses, they had significantly greater 

math content knowledge test scores than the typical math teachers in the schools in which they 

taught. 

The experimental analysis indicates that TFA teachers were more effective than comparison 

teachers. On average, students assigned to TFA teachers scored 0.07 standard deviations higher 

on end-of-year math assessments than students assigned to comparison teachers. The impact 

translated into an additional 2.6 months of learning for the average student nationwide. Findings 

were similar when we compared specific subgroups of TFA and comparison teachers: 

• TFA teachers were more effective than comparison teachers from both TC and 

less selective AC routes. Students of TFA teachers outperformed students of teachers 

from TC routes by 0.06 standard deviations and outperformed students of teachers 

from less selective AC routes by 0.09 standard deviations. 

• Novice TFA teachers were more effective than both novice and experienced 

comparison teachers. Students of novice TFA teachers—those in their first three 

years of teaching—outscored students of novice comparison teachers by 0.08 

standard deviations. Students of novice TFA teachers also outperformed students of 

more experienced comparison teachers (those with more than three years of 

experience) by 0.07 standard deviations. This latter finding is particularly important 

given the fact that TFA requires its teachers to make only a two-year commitment to 

teaching.

• TFA teachers were more effective than comparison teachers in both middle and 

high schools. Students of TFA teachers outscored those of comparison teachers by 

0.06 standard deviations in middle school and 0.13 standard deviations in high 

school.
Effectiveness of TFA and Teaching Fellows Teachers 

63 

VI. SELECTION, TRAINING, AND SUPPORT OF TEACHING FELLOWS

PROGRAM PARTICIPANTS

Like teachers who enter the profession through Teach For America (TFA), teachers who 

enter teaching through Teaching Fellows programs may differ from other teachers in their 

effectiveness in teaching mathematics. This may be because of their characteristics, knowledge, 

and experiences when they enter the program, and/or because of the training they receive from 

the program and the support they receive after they start teaching. This chapter presents details 

on how Teaching Fellows programs select, train, and support their participants. Appendix C 

presents some additional information on the programs and summarizes the features of both the 

Teaching Fellows programs and TFA.

A. Application and Selection

The Teaching Fellows application and selection process has two stages: (1) submission of an 

online application, and (2) an in-person assessment. Individuals apply to a specific Teaching 

Fellows program based on where they want to teach (Appendix Figure C.3 lists the 19 Teaching 

Fellows programs as of August 2011). Each program has its own application form and may have 

some different eligibility requirements, but all the programs follow a similar selection process, 

according to officials from TNTP, the national organization that oversees the Teaching Fellows 

programs. 

1. Application Form and Eligibility Rules

The online application form collects information on the colleges or universities applicants 

have attended, the highest degree they have earned, their fields of study, their overall 

undergraduate grade point average (GPA), any languages they speak in addition to English, and 

whether they are U.S. citizens. Applicants must also provide short written answers (200 to 

400 words) to three questions on such topics as (1) why they want to teach in high-need schools

and what experience they have in such settings, (2) what skills or abilities they have that will 

help them succeed in the classroom, and (3) what steps they have taken to overcome challenges 

they have faced. Responses to application form questions about personal demographic 

information—sex, age, race/ethnicity—are optional. Applicants can specify subject area 

preferences (for example, secondary math); however, those who reach the in-person assessment 

stage are informed what type of position they are being considered for, based on program 

officials’ reviews of their applications, transcripts, and districts’ needs. 

Applicants also must submit material at different points in the application and selection 

process. They must submit a resume with their application. Those who advance beyond the 

application stage must submit unofficial undergraduate and graduate school transcripts; if they 

reach the point of accepting a teaching position, they must submit official transcripts. At the 

hiring stage, candidates must provide proof of citizenship. Applications and related documents 

from all Teaching Fellows programs are reviewed online by a centrally overseen set of “prescreeners” who determine which candidates should be invited to the in-person assessment stage.

To be eligible for admission, all applicants to all Teaching Fellows programs must meet 

three basic, objective eligibility criteria: (1) hold a bachelor’s degree, (2) not have been certified 
Effectiveness of TFA and Teaching Fellows Teachers 

64 

to teach, and (3) be able to pass a background investigation. In addition, some eligibility criteria 

vary by state or program, or by teacher subject area or level: 

• Undergraduate institution. In some states, the bachelor’s degree must be from a 

U.S. institution. 

• GPA. Requirements for cumulative undergraduate GPA vary by program. Of the 

seven Teaching Fellows programs in this study still operating in 2011, two listed on 

their website an official GPA requirement of 3.0, and five listed a requirement of 

2.75. Four of the programs, however, allow some exceptions to these standards, 

giving applicants a chance to explain why their GPA was below the standard or to 

demonstrate academic achievement in other ways. One of the programs with a 

3.0 GPA requirement allowed such exceptions for applicants with a GPA of at least 

2.75, and one of the programs with a 2.75 GPA requirement allowed exceptions for 

applicants with a GPA of at least 2.5. 

• Coursework. Requirements may vary by state for teachers of certain subjects and 

grade levels. For example, some states require secondary math teacher candidates to 

have majored in math, to have earned a requisite GPA in math courses, to have taken 

a requisite number of college-level math courses, or to agree to take certain math 

courses while working toward initial certification.

• New-teacher tests. All candidates must meet applicable state policies for tests 

required of all new teachers to be deemed highly qualified to begin teaching. 

Teaching Fellows programs require candidates to meet the state-specified passing 

scores on all applicable examinations; they do not set higher thresholds. Candidates 

typically must have passed all applicable tests before the start of the school year, 

although some programs require candidates to pass tests before the start of the 

summer institute. 

State- and program-specific eligibility requirements are made clear to applicants at the start of 

the application process. 

2. Selection Process

The application and selection process used in every Teaching Fellows program is designed 

to highlight the degree to which each applicant embodies seven core competencies:

1. Critical thinking

2. Achieving ambitious goals

3. Personal responsibility and accountability 

4. Commitment to students in high-need schools 

5. Dedication to continuous improvement 

6. Communication skills

7. Respectful and positive in all situations 

In general, when TNTP pre-screeners decide which candidates for each local program 

should be invited to the second and final stage of the application and selection process, known as 
Effectiveness of TFA and Teaching Fellows Teachers 

65 

the “Interview Event,” they consider two factors: (1) the completeness and quality of the 

application, including the quality of responses to open-ended questions; and (2) the applicant’s 

experience, including academic and other accomplishments, and exposure to high-need schools 

and communities. Pre-screeners place applicants into one of five tiers, ranging from “concerns” 

to “strong.” In general, candidates must be in the upper tiers to be invited to the Interview Event, 

but exceptions may be made in response to district needs for certain types of teachers.

Each Teaching Fellows program conducts its own local Interview Event. The event, which 

lasts about six hours, consists of four activities:

1. Sample teaching lesson. Candidates take turns presenting a five-minute sample 

teaching lesson to one another as program staff observe and evaluate. Applicants may

target any subject and grade level for the lesson. The amount of time candidates have 

to prepare their sample lesson depends on how close to the Interview Event they 

receive their invitation; some applicants may have just four or five days’ notice, while 

others may know about the requirement weeks in advance. 

2. Writing exercise. Applicants have 20 minutes to describe in writing how they would 

handle a realistic, challenging classroom scenario. 

3. Group discussion. Groups of about 10 applicants spend 17 minutes discussing two 

questions posed by program staff, such as how they would respond to a particular, 

challenging classroom scenario. Participants are also instructed to draw on articles 

sent to them before the Interview Event. The articles, often taken from major 

newspapers, relate to current or recent education policy issues in low-income urban 

schools. Staff observe the discussion but do not participate in it. When the discussion 

time concludes, participants have three minutes to respond in writing to a summary 

question posed by the session organizer. 

4. One-on-one interview. Applicants participate in a one-on-one interview, lasting 

about 25 minutes. Following an interview guide developed by TNTP, staff may either 

use a standard set of questions or choose from a bank of questions, across three areas. 

They ask at least one question about preceding activities in the Interview Event and 

often a question about the applicant’s resume or answers to the written application 

questions. They ask several “scenario questions” about how the applicant would 

respond to a hypothetical classroom situation and several “targeted questions” to 

elicit more evidence of the applicant’s skills, accomplishments, and dedication and to 

round out a “holistic picture” of the applicant. Interviewers are encouraged to ask 

several follow-up questions to elicit complete, specific answers from applicants, and 

to gather robust, concrete evidence needed to assess applicants’ candidacy. 

After the Interview Event, local selectors (a different group than the pre-screeners) consider 

all available information and complete a final evaluation form on each candidate. The form 

includes a rating on each of the seven competencies listed above. The basic ratings are 

“exemplary,” “fully acceptable,” and “not fully acceptable”; a plus or minus sign may be 

attached to each rating when candidates appear to be slightly above or below the basic ratings. 

To be recommended for admission, applicants must earn “exemplary” on at least one of the first 

four competencies and no ratings of “not fully acceptable” on any competency.
Effectiveness of TFA and Teaching Fellows Teachers 

66 

In the three years preceding our interviews, according to TNTP officials, the application and 

selection process for Teaching Fellows programs changed in three important ways as officials

worked to refine and improve the process. First, they developed the five-tier system for screening 

applications. Second, they added “commitment to students in high-need schools” as a ranked 

competency. Third, they introduced the option to use pluses and minuses around each of the 

three basic ratings (exemplary, fully acceptable, not fully acceptable) applied to the seven core 

competencies. These changes, intended to help identify candidates who would be effective 

Teaching Fellows, provided additional information to help program officials make strategic 

decisions about who should receive an offer to join the program, and reportedly had the 

incidental effect of making it somewhat harder for applicants to gain admission. 

3. Program Selectivity and Application Yields

For an overall perspective on program selectivity, Figure VI.1 shows the flow of applicants 

through the selection process in the three years preceding our interviews. According to TNTP

officials, for every 100 applicants, on average, 63.3 advanced past the application stage to be 

invited to the Interview Event (about 55 percent of those attended), 12.6 were offered admission, 

and 9.7 enrolled. About 13 percent of applicants were given an offer to join a Teaching Fellows 

program, and, ultimately, 76.7 percent of those offered the opportunity chose to enroll in a

Teaching Fellows program. 

Figure VI.1. Teaching Fellows Selection Process and Applicant Flow

Source: TNTP officials.

TNTP officials noted that math teacher candidates were accepted at slightly lower rates than 

the overall rates shown above. One reason, they said, was that such candidates were less likely to 

be experienced in working in low-income communities or with underserved youth. They were 

also less likely to enroll when offered admission; officials thought that the refusals might
Effectiveness of TFA and Teaching Fellows Teachers 

67 

indicate that candidates were considering other teacher programs, including TFA, or nonteaching 

jobs. 

For another view on program selectivity, we asked TNTP officials how Teaching Fellows 

programs would respond if a district’s projected need for secondary math teachers were higher 

than usual or higher than expected, such that the district would likely face difficulty in meeting 

that need, given its applicant pool and typical process for making admission decisions. The 

officials indicated that programs may adjust their degree of selectivity but would never make 

admission offers to candidates not deemed “fully acceptable.” Officials also emphasized that 

rather than adjust selectivity, they would prefer to have programs encourage more candidates to 

apply, even extending the application deadline, if necessary, to attract potentially more qualified 

candidates. In addition, the hypothetical situation presented here may not apply to individual 

Teaching Fellows programs because placement goals are typically broad—for example, 

“50 teachers in the areas of math and science”—rather than stating a specific target for the 

number of secondary math teachers. 

B. Preservice Training for New Teaching Fellows

For new participants in Teaching Fellows programs, the main preservice training experience 

is a summer institute, but it is preceded by self-guided study and an orientation session. A few 

programs also provide a supplementary math immersion program, typically before the institute.

Figure VI.2 shows an overview of the timing of placement and all training and support activities 

before and after Teaching Fellows begin teaching.

1. Independent Study and Orientation

Teaching Fellows first complete assignments described in an Independent Study Guide, 

including a good deal of reading, classroom observations (either a full day or a series of shorter 

sessions), and written responses to questions. Altogether, independent study may take about 

25 hours. Next, Teaching Fellows participate in a 4-hour orientation session, either in person or 

via webinar, that provides information on district hiring and on future training and support and

includes an overview of the summer institute. 

2. Summer Institute

Each Teaching Fellows program hosts its own full-time summer institute. (Programs serving

several regions or districts may hold several institutes.) The summer institutes in nearly all 

Teaching Fellows programs reportedly last between five and six weeks, and Teaching Fellows 

attend every weekday. One program in the study runs a seven-week institute, and Teaching 

Fellows attend four days a week. The two primary activities Teaching Fellows engage in during 

the institute are fieldwork in public summer school classrooms and courses conducted in school 

buildings or a university. Institutes are customized for the districts they serve, but all follow the 

same training curriculum.

Training for Teaching Fellows is organized into what TNTP calls the Teaching for Student 

Achievement Framework. For general education teachers, the framework encompasses 

10 competencies across two domains, as shown in Table VI.1. 
Effectiveness of TFA and Teaching Fellows Teachers 

68 

Figure VI.2. Overview of Placement and Training of Teaching Fellows

Spring Summer Fall Winter Spring Summer Fall Winter Spring Summer

First School Year 

Teaching

Second School Year 

Teaching

Third School Year 

Teaching

Fellows Find School 

Placements

Independent Study and 

Orientation

Preservice Training and 

Support

Training and Support for 

Novice Fellows

Instruction/Training Provided 

by Local Alternative 

Certification Program

*

**

MI Institute

Source: TNTP officials.

Note: The shaded areas of this figure are meant to show that various activities generally do, or may, 

take place during a particular season; shading does not imply that any given activity takes up the 

full season. The text of this chapter provides information on the hours associated with various 

activities.

MI = Math Immersion Program; required of some Teaching Fellows in some programs, to help them meet 

requirements to teach secondary math courses.

*Although not typical, a modest amount of support may be provided, on an as-needed basis, to Teaching 

Fellows in their second year of teaching.

**Timing of required coursework varies; it may start as early as the summer before Teaching Fellows begin 

teaching and may last into their third year of teaching. When coursework extends beyond the first year of 

teaching, it may or may not take place during summer(s).

One major component of the institute is formal instruction. Teaching Fellows engage in

coursework nearly every day of the institute, an average of 27 days in all. On days when 

fieldwork is scheduled in the morning (described below), coursework takes place in the late 

afternoon. Formal instruction is led by Teaching Fellows program staff and district staff, many of 

whom are Teaching Fellows or TFA alumni. To help new general education teachers develop the 

10 competencies listed in Table VI.1, the curriculum is delivered in six “framework modules,” 

each spanning approximately three to five sessions covering theory and pedagogy: 

• Module 1—How can I use the Teaching for Student Achievement Framework to help 

me close the achievement gap in a “high-need” school? 

• Module 2—How do I prevent and handle disruptions to maximize the time I spend 

teaching?

• Module 3—How can I effectively teach a class with students whose readiness varies 

greatly?

• Module 4—How do I plan and deliver rigorous and engaging instruction? 

• Module 5—What does good literacy instruction look like? 

• Module 6—How can I establish credibility in the classroom and community? 
Effectiveness of TFA and Teaching Fellows Teachers 

69 

Table VI.1. Domains and Corresponding Competencies of TNTP’s Teaching for Student Achievement 

Framework

Instructional Design and Delivery Classroom Management and Culture

• Set rigorous academic goals

• Use appropriate assessments

• Create standards-based lessons and units

• Apply differentiated instruction

• Use high-impact teaching strategies

• Effect change as a newcomer

• Use diversity to promote achievement

• Address misbehavior effectively

• Develop rules, procedures, and consequences

• Create a “no excuses” classroom culture

Source: TNTP officials.

In addition to the standard Teaching Fellows curriculum delivered though the modules 

above, district officials (such as central administrators or curriculum and professional 

development staff) or school site leaders may schedule instructional workshops to cover districtor school-specific topics. Overall, counting both the framework modules and the additional 

district-specific sessions, Teaching Fellows reportedly spend an average of 2.5 hours per day 

receiving instruction, for an estimated average of 67.5 hours over 27 days. 

Another major component of the institute, and an important way for teachers to develop the 

10 competencies, is fieldwork, referred to as “practice teaching,” in a district’s summer school 

program. Program staff strive to maximize the time that Teaching Fellows spend in practice

teaching. The programs expect all Teaching Fellows to engage in practice teaching for a 

minimum of 15 days. The scheduling of fieldwork—whether it is all on consecutive days and 

how soon it starts after the beginning of the institute—varies by program and depends on the 

schedule of local summer school sessions. Program staff would like Teaching Fellows to spend 

5 hours a day on-site, but this is not possible if summer school operates for only 4 hours a day. 

National staff estimate that Teaching Fellows spend an average of 4 to 4.5 hours a day on-site on 

fieldwork days, or an estimated average of 64 hours in fieldwork over 15 days. Teaching Fellows 

are assigned in pairs to work with a regular summer school teacher (the “cooperating teacher”), 

and secondary math candidates typically are assigned to secondary math classrooms. Teaching 

Fellows may spend their first few days in the classroom mainly observing the teacher and 

students but are expected to assume increasing responsibility for leading instruction and other 

routine activities. They first work with small groups during sessions led by the cooperating 

teacher and move toward leading instruction for the whole class in back-to-back lessons as the 

fieldwork period progresses. 

The final component of the summer institute is assessment and intervention. Through 

formative and summative assessments, program staff evaluate a Teaching Fellow’s performance 

and provide feedback to help with his or her development. For example, staff observe each 

Teaching Fellow in practice teaching sessions three times and provide feedback after each 

session.

During the institute, Teaching Fellows are reportedly involved in training for 8.5 to 9 hours 

per day, including the activities described above, the commute to/from fieldwork sites, and

optional activities (such as visiting institute staff during their office hours and participating in 

other meetings). Even when instructional sessions and other scheduled activities conclude for the 

day, Teaching Fellows often remain busy into the evening, completing course assignments or 

lesson planning for practice teaching sessions.
Effectiveness of TFA and Teaching Fellows Teachers 

70 

Over the three years preceding the spring 2010 interviews, according to TNTP officials, 

94 percent of those who enrolled in a Teaching Fellows program, on average, completed the 

summer institute. Most (72 percent) of those who did not complete the institute left for personal 

reasons; others failed to meet eligibility requirements or exited from the program due to 

performance. Math teacher candidates were reportedly no more or less likely than other 

participants to complete the summer institute.

3. Post-Institute Activities

Three Teaching Fellows programs in the study offered “math immersion” programs during 

the summer. These programs involve an intensive review of mathematical concepts to help 

individuals otherwise ineligible to teach secondary math become qualified to do so and to 

achieve more success in the classroom. Table VI.2 lists key characteristics of the math 

immersion programs. The amount of instruction provided in the programs ranged from 30 to 

80 hours, with a mean of 62 hours. Respondents reported that each of the three math immersion 

programs had just one curriculum for all participants and that the curriculum did not include 

math pedagogy. They also reported that the math immersion programs were open only to 

Teaching Fellows for whom participation was mandatory; they were not an option for other 

Teaching Fellows. 

Table VI.2. Characteristics of Math Immersion Programs Offered by Three Teaching Fellows Programs

in the Study

Program 1 Program 2 Program 3

Candidates required to attend Anyone who did not 

have 24 college 

credits in math and 6 

related credits

Anyone who did not 

have 30 college 

credits in math or who 

did not major in math

Anyone who did not 

major in math as an 

undergraduate or 

graduate student

Estimated percentage of secondary 

math teacher candidates who 

participated in the program, 

past 3 years

61% 80% 80%

Amount of instruction provided 75 hours

(10 days, 7.5 hours 

per day)

80 hours

(10 days, 8 hours per 

day)

30 hours

(10 days, 3 hours 

per day)

College-level math subjects 

covered in program

Algebra, geometry, 

calculus, trigonometry, 

linear algebra

Algebra, geometry, 

calculus, trigonometry, 

linear algebra

Algebra, calculus

Source: Interviews with Teaching Fellows officials.

C. Placement and Retention of Teaching Fellows

After they accept an offer of admission to a Teaching Fellows program, Teaching Fellows 

must take an active role in finding a suitable, appropriate teaching position; they are not placed 

in schools by program or district staff. Candidates receive a list of local schools that, in the 

district’s assessment, have the greatest need for Teaching Fellows. Candidates are encouraged to 

apply to those schools, but they may also consider schools not on the list, if necessary, to find a 

suitable vacancy in the subject area and grade range in which they wish to teach. The timing of 

the process reportedly varies from program to program and year to year. Most hiring takes place 

during the summer institute; however, Teaching Fellows may receive job offers before the 
Effectiveness of TFA and Teaching Fellows Teachers 

71 

summer institute or not be hired until after the institute (in some cases, not until after the school 

year begins). Teaching Fellows programs do not place a priority on securing placements for their 

new Teaching Fellows in schools that already have teachers from the program.

In the three hiring cycles before our interviews, an average of 92 percent of all new 

candidates in the eight Teaching Fellows programs received a job offer before the start of the 

school year, and an additional 3 percent were hired after the school year started (Table VI.3). 

Hiring rates were 3 percentage points higher for secondary math candidates. TNTP officials 

noted that the averages were pulled down somewhat by the most recent year (placements for fall 

2009), which saw lower placement rates than in any previous year. According to TNTP officials,

many districts had fewer openings than expected because of layoffs and hiring freezes brought 

about by districts’ budget problems. They said that, in earlier years, the rates were always close 

to 100 percent. 

Table VI.3. Estimated Percentage of New Teaching Fellows Who Received Teaching Placements, on 

Average, Across the 2007–2008, 2008–2009, and 2009–2010 School Years

Hired Before Start 

of School Year

Hired After Start 

of School Year Total

All Candidates 92% 3% 95%

Secondary Math Candidates 95% 3% 98%

Source: Interview with TNTP officials.

In recent years, according to TNTP officials, an average of 75 percent of Teaching Fellows 

who received a teaching placement remained in teaching for more than two school years. Math 

teachers were reportedly less likely than others to complete two years of teaching (specific 

figures were not available). 

D. Instruction Provided to Teaching Fellows Through Local Teacher Certification 

Programs

All eight Teaching Fellows programs required new secondary math teachers to enroll in a 

state-authorized program that provided an alternative route to certification (AC program). To 

gain a general sense of the instruction that secondary math Teaching Fellows in our study might 

have received from local AC programs, we asked officials from each participating Teaching 

Fellows program to identify the one program that had enrolled the largest number, whether a 

majority or plurality, of their new secondary math teachers over the three most recent years 

before 2010. This was the time period, we believed, during which most study teachers would 

have enrolled in a local AC program. (The later addition of study teachers from Teaching 

Fellows programs’ summer 2010 entering cohort means that their AC program experiences may 

not be as well represented by the AC program information we collected.) In three of the 

Teaching Fellows programs we examined, the identified AC program reportedly served all the 

secondary math Teaching Fellows. In the remaining five Teaching Fellows programs, the 

identified AC program reportedly served 50 to 85 percent of secondary math Teaching Fellows. 

Hereafter, we refer to these as the “focal” AC programs, as they were the focus of our questions. 
Effectiveness of TFA and Teaching Fellows Teachers 

72 

A variety of institutions operated the eight focal AC programs. Five were operated by a 

nearby college or university, one by the local school district, and two by TNTP. As of 2011, 

TNTP operated six such programs, serving the District of Columbia, Louisiana, Maryland, 

Oakland (California), Rhode Island, and Texas. 

1. Preservice Instruction

Secondary math teachers (and other teachers) in three of the programs in the study were 

required to participate in some instruction for their AC program in the summer before they 

started teaching (in addition to the summer institute). All three programs were run by local 

colleges. One program met seven hours a day for four days, separate from the Teaching Fellows 

summer institute. The other two programs required participants to take their first course toward 

certification concurrent with the summer institute. One of these programs’ classes met for two 

hours, three nights a week, for six weeks. The other program’s summer classes met for 2.5 hours, 

one night a week, for eight weeks, with an additional 8-hour session on a Saturday. 

2. Instruction During and After the First Year of Teaching

In all eight Teaching Fellows programs in the study, secondary math teachers had to attend 

classes or other training activities toward their initial certification during their first year of 

teaching. The focal AC program with the most extensive first-year requirement involved an 

estimated 140 hours of instruction. The least extensive first-year requirement was 45 hours, with 

participants attending 3 hours a week for 15 weeks. Across the eight focal certification programs, 

the average amount of instruction required of first-year secondary math teachers was about 

86 hours. 

Just one of the focal AC programs featured an instruction component during the summer 

after teachers’ first year of teaching. Participants reportedly met for 2.5 hours a week for four 

weeks, for a total of 10 hours. 

In four Teaching Fellows programs in the study, secondary math teachers had to continue 

taking classes or other training activities toward their initial certification during their second year 

of teaching. The AC program with the most extensive second-year coursework requirement 

involved 4 hours a week for 30 weeks, for a total of 120 hours of instruction. The least extensive 

of the four programs involved 3 hours a week for 15 weeks, for a total of 45 hours. Across all 

eight programs, the average second-year instruction requirement for new secondary math 

teachers was about 38 hours. 

3. Total Amount of Instruction in Certification Programs

The total hours of instruction reportedly required by the certification programs that were the 

focus of our interviews—before and after secondary math Teaching Fellows started teaching—

ranged from about 61 to 250 hours, with a mean of about 137 hours. In Table VI.4, we present 

the average instruction hours required, overall and by time period. 
Effectiveness of TFA and Teaching Fellows Teachers 

73 

Table VI.4. Hours of Instruction Toward Certification Reportedly Required in Focal AC Programs for 

Secondary Math Teaching Fellows

Programs with This Instructional 

Component

Instruction Provided

Number of 

Programs Minimum Maximum Mean

Mean for All 

8 Programs

Before first year of teaching 3 28 36 30.7 11.5

During first year of teaching 8 45 140 86.2 86.2

During summer after first year of teaching 1 10 1.3

During second year of teaching 4 45 120 76.5 38.3

Total Hours, All Programs 8 60.8 250 137.2 137.2

Source: Interviews with Teaching Fellows programs and TNTP officials.

Notes: This table excludes training provided directly by Teaching Fellows programs.

The focal AC program for each participating Teaching Fellows program is the one that enrolled the 

largest number of its secondary math teachers from 2007 to 2009.

E. Training and Support for New Teaching Fellows After They Begin Teaching

Program staff continued to work with Teaching Fellows in a variety of ways after they 

began teaching.

1. Instruction, Training, and Professional Development 

Teaching Fellows programs reportedly deliver 10 hours of professional development to new 

participants in group sessions that take place on weeknights and weekends. Topics include 

classroom management, how to use data to inform instruction, and how to tailor instruction for 

different students. Staff also poll the participants or develop ideas for other professional 

development topics based on classroom observations (described below). TNTP staff described 

the material covered in the sessions as more practical and less theoretical than the instruction 

provided in the college-based AC programs that some participants attend while teaching. None 

of the professional development is uniquely designed for secondary math teachers. 

2. Other Support Services

In the standard model for Teaching Fellows programs, each new teacher is assigned to a 

staff member, known as a “training and resource manager” or a “training and instruction 

manager” (hereafter, “training manager”), who interacts one-on-one with the teachers in several

ways during their first year or two of teaching to monitor and foster their development. 

• Classroom observations. The training manager conducts at least two formal 

classroom observations of each new teacher, with the first taking place within the first 

six weeks of the school year. (When a program is too large for the training manager 

to conduct all the observations, additional staff, called “instructional specialists” or 

“field visitors,” are hired to conduct observations.) Some Teaching Fellows programs 

reportedly conduct considerably more classroom observations of new Teaching 

Fellows. The observer discusses the observation assessments mainly with the teacher 
Effectiveness of TFA and Teaching Fellows Teachers 

74 

but will speak to a teacher’s principal if he or she thinks the teacher might benefit 

from additional district- or school-based supports. 

• One-on-one meetings. Training managers schedule two meetings during the school 

year with each of their teachers to talk one-on-one, acting more or less as a mentor. 

The meetings last an average of 20 minutes. (New teachers in most Teaching Fellows

programs also have a formal mentor assigned to them by their district or school, 

according to information collected through our teacher surveys [Chapter VII]). 

• Informal discussions. Training managers may call or email their teachers 

occasionally for informal check-in discussions (for example, to determine whether the 

teachers need any information or resources that the training manager could provide). 

The average frequency and length of these casual, impromptu interactions is not 

systematically tracked.

Although the assignments of new Teaching Fellows to program staff typically remain in 

place only for a Teaching Fellow’s first year of teaching, a staff member might maintain contact 

with his or her teachers during the second year (for example, sending them newsletters or 

inviting them to optional professional development events). More generally, program staff 

provide both formal and informal support to any Teaching Fellows they believe need assistance.

F. Financial Support for Teaching Fellows

At the time of our interviews, participants in six of the eight Teaching Fellows programs 

reportedly could receive direct or indirect financial assistance to help cover training expenses. 

The percentage of eligible participants who received available financial assistance ranged from 

73 to 100 percent; the mean percentage receiving financial assistance was about 93 percent. 

Support ranged from a district covering the full cost of the AC program, estimated at $3,500, to a 

district covering about $14,000 of the cost of required coursework toward a master’s degree, 

which reportedly cost in total about $20,600. 
Effectiveness of TFA and Teaching Fellows Teachers 

75 

VII. TEACHING FELLOWS STUDY TEACHERS: THEIR CHARACTERISTICS, 

THE SCHOOLS THEY TEACH IN, AND THE STUDENTS THEY TEACH

The Teaching Fellows programs aim to recruit and train teachers to teach in low-income 

school districts, with recruitment efforts that focus on both recent college graduates and midcareer professionals. Given the particular application and hiring processes the Teaching Fellows 

programs use, Teaching Fellows may differ from their counterparts who entered the teaching 

profession through other routes. Because the programs aim to place their Teaching Fellows in 

high-poverty schools, the schools they work in and the students they serve are also likely to 

differ from typical schools and students nationwide. This chapter provides descriptive 

information on the schools (Section A), teachers (Section B), and students (Section C) in the 

Teaching Fellows study sample. 

To summarize the findings from this chapter, we found that Teaching Fellows in the study 

were typically placed in urban schools that served economically disadvantaged students, largely 

from racial and ethnic minority groups. The Teaching Fellows in the study were typically white, 

with an average of four years of teaching experience and five years of nonteaching work 

experience, and included roughly equal numbers of men and women. The other secondary math 

teachers in these same schools were primarily white or black women, with considerably more 

teaching experience (13 years) and three years nonteaching work experience, on average. 

Although the Teaching Fellows teachers were less likely to have majored in math than the 

teachers from other routes to certification, they were far more likely to have attended a selective 

undergraduate university and had significantly higher math content knowledge test scores. 

A. Schools in the Teaching Fellows Study Sample

Even though schools in the Teaching Fellows sample were not randomly selected from the 

full set of secondary schools with Teaching Fellows placements nationwide, the study schools 

were similar to secondary schools employing Teaching Fellows nationwide along many 

dimensions (Table VII.1). For example, most students at both sets of schools were members of 

racial and ethnic minority groups, although the study schools had more racial and ethnic 

minorities than did the full set of Teaching Fellows schools. On average, 6 percent of students in 

the study schools in the Teaching Fellows sample were white, non-Hispanic, compared with 

17 percent in Teaching Fellows secondary schools nationwide. About 46 percent of students at 

both study schools and all secondary schools with Teaching Fellows were black, non-Hispanic. 

Forty percent of students at the study schools and 35 percent of students in all secondary schools 

with Teaching Fellows placements nationwide were Hispanic. Teaching Fellows study schools 

had a large proportion of students eligible to receive free or reduced-price lunch—80 percent of 

study school students and 74 percent of all Teaching Fellows secondary school students. Eightytwo percent of the schools in the Teaching Fellows study sample and 85 percent of secondary 

schools with Teaching Fellows nationwide were eligible for Title I funds for schools with high 

percentages of low-income students. The grade distribution of study schools was also similar to 

the grade distribution of secondary schools with Teaching Fellows nationwide—about 48 percent 

of both sets of schools were middle schools (including at least one grade from 6 to 8), and 60 to 

70 percent were high schools (including at least one grade from 9 to 12). 

Consistent with the goal of the Teaching Fellows programs to serve low-income 

communities, schools in the study sample were, on average, more disadvantaged than the typical 
Effectiveness of TFA and Teaching Fellows Teachers 

76 

secondary school nationwide. For example, compared with students in the average secondary 

school nationwide, students in the average school in the Teaching Fellows study sample were 

more likely to be eligible for free or reduced-price lunch and to be from racial and ethnic 

minorities.

Table VII.1. Characteristics of Study Schools with Teaching Fellows Compared with All Secondary Schools 

with Teaching Fellows and All Secondary Schools Nationwide

Study 

Schools with 

Teaching 

Fellows

All Secondary Schools 

with Teaching Fellowsa All Secondary Schools 

Nationwide

Characteristic Mean Mean

p-Value of 

Difference 

from Study 

Schools Mean

p-Value of 

Difference 

from Study 

Schools

Racial/Ethnic Distribution of Students

Percentage Asian, non-Hispanic 6.6 4.2 0.227 3.5 0.099

Percentage Black, non-Hispanic 46.5 45.6 0.877 18.8** 0.000

Percentage Hispanic 40.2 35.0 0.333 20.2** 0.000

Percentage White, non-Hispanic 6.3 16.6** 0.000 59.4** 0.000

Percentage other race/ethnicity 0.5 2.7 0.059 9.8** 0.000

Student Socioeconomic Status

Percentage eligible for free/

reduced-price lunch 80.4 74.4 0.132 50.5** 0.000

Percentage Title I-eligible schools 81.8 86.6 0.476 60.0** 0.000

Enrollment and Staffing

Average total enrollment 1,211.0 989.3 0.288 551.2** 0.001

Average enrollment per grade 298.0 248.3 0.346 134.5** 0.001

Average student/teacher ratio 16.3 15.8 0.464 16.1 0.768

Grade Levelb

Percentage middle schools 47.7 47.1 0.939 66.1* 0.015

Percentage high schools 70.5 61.3 0.258 45.3** 0.000

School Type

Percentage magnet schools 6.8 5.9 0.832 2.3 0.237

Census Bureau Region

Percentage in Northeast 50.0 19.3** 0.000 14.3** 0.000

Percentage in Midwest 11.4 19.3 0.187 27.7** 0.001

Percentage in South 27.3 45.4* 0.025 30.8 0.601

Percentage in West 11.4 16.0 0.392 26.9** 0.001

Sample Size 44 119 63,148

Sources: TNTP placement data; Common Core of Data, Public Elementary/Secondary School Universe Survey, 

2009–2010.

Note: Secondary schools are defined as any schools that include at least one grade above 5th grade.

a

Estimates are based on schools in which new teaching fellows were placed in the 2009–2010 school year.

b

Middle schools are defined as schools with at least one grade from 6 to 8. High schools are defined as those 

with at least one grade from 9 to 12. Thus, the two categories are not mutually exclusive, as a given school 

could contain both middle and high school grades.

 *Difference between this group and study schools with Teaching Fellows (first column) is statistically significant at 

the 0.05 level, two-tailed test.

**Difference between this group and study schools with Teaching Fellows (first column) is statistically significant at 

the 0.01 level, two-tailed test.
Effectiveness of TFA and Teaching Fellows Teachers 

77 

Study schools and all Teaching Fellows secondary schools nationwide also differed on some 

dimensions, many of which may have been due to our recruitment strategies and study eligibility 

requirements. Nine percent of secondary schools employing Teaching Fellows nationwide were 

charter schools, compared with fewer than 5 percent of the study schools, a statistically 

significant difference (estimates not shown in table and exact percentage for study schools not 

reported to protect respondent confidentiality in accordance with National Center For Education 

Statistics statistical standards [National Center for Education Statistics 2000]). Charter schools 

typically were smaller than average and therefore less likely to have eligible classroom matches. 

Study schools also were significantly more likely to be in urban areas—more than 95 percent of 

study schools were in urban areas, versus 78 percent of Teaching Fellows secondary schools 

nationwide (also not shown in table and exact percentage for study schools not reported to 

protect respondent confidentiality), consistent with the fact that we concentrated on recruiting for 

the study districts with the greatest numbers of Teaching Fellows placements. Study schools 

were also more likely than the full set of Teaching Fellows secondary schools to be in the 

Northeast (50 versus 19 percent) and less likely to be in the South (27 versus 45 percent). 

B. Teaching Fellows in the Study Sample Compared with Comparison Teachers 

The Teaching Fellows programs aim to place effective teachers in low-income schools by 

selecting people with the qualities and attitudes they believe are predictive of successful 

teaching, providing these people with an intensive five- to seven-week training, and then 

supporting them through their first year of teaching. For these reasons, Teaching Fellows study 

teachers are likely to differ from the comparison teachers with whom they were compared—the 

non-Teaching Fellows teaching the same math course in the same school. In fact, we found that 

Teaching Fellows did differ from comparison teachers in important ways, with a few similarities, 

as described in the box below. 

Compared with comparison teachers, Teaching Fellows: 

• Were younger and less likely to be members of racial and ethnic minority groups 

• Were more likely to have graduated from a selective college or university 

• Had greater math content knowledge as measured by scores on the Praxis II math 

exams

• Were less likely to have majored in math or secondary math education

• Had fewer years of teaching experience, although they had more nonteaching work 

experience

• Completed similar amounts of math pedagogy instruction and math pedagogy 

professional development, but spent less time student teaching in math during their 

teacher training

• Were about as likely to have taken coursework during the study school year and to 

have had a mentor during that year 

• Were less satisfied in general with some aspects of teaching, including school 

administration.
Effectiveness of TFA and Teaching Fellows Teachers 

78 

The comparison teachers with whom Teaching Fellows were compared included teachers 

from traditional routes to certification (TC routes) and those from less selective alternative routes 

to certification (AC routes)—73 percent of comparison teachers were from TC routes, while 

27 percent were from less selective AC routes. With a few exceptions discussed below, patterns 

of differences between Teaching Fellows and comparison teachers were present both among the 

subset of Teaching Fellows who were compared with teachers from TC routes and the subset 

who were compared with teachers from AC routes (Appendix D). 

1. Demographic Characteristics

Teaching Fellows and comparison teachers differed along several demographic 

characteristics (Table VII.2).21 Teaching Fellows study teachers were younger than comparison 

teachers, on average (33 versus 41 years old), and were less likely to be members of racial and 

ethnic minority groups. Seventy-one percent of Teaching Fellows in the study were white, nonHispanic, compared with 43 percent of comparison teachers. Seventeen percent of the Teaching 

Fellows in the study were black, non-Hispanic, compared with 36 percent of comparison 

teachers. Comparison teachers in the study were closer in age and gender distribution to the 

average secondary teacher nationwide than were Teaching Fellows in the study, whereas

Teaching Fellows in the study more closely resembled the average secondary teacher in terms of 

racial and ethnic distribution. 

2. Educational Background and Content Knowledge 

Teaching Fellows in the study were more likely than comparison teachers to have graduated 

from a selective college or university (72 versus 34 percent, as well as from a highly selective 

college or university (21 versus 7 percent) (Table VII.3).22

Despite the fact that they were less likely to have majored in math, Teaching Fellows 

completed approximately the same number of college-level math courses as comparison teachers 

(Table VII.4). Both groups of teachers took about the same number of each type of college-level 

math course, including calculus, advanced algebra, analysis, advanced geometry/topology, 

probability and statistics, discrete math, and applied math. Differences in average number of 

college-level math courses were similar at both the middle and high school levels. 

They were about as likely as 

comparison teachers to have completed a graduate degree (83 versus 80 percent; difference not 

significant at the 5 percent level). They were less likely to have majored in math (25 versus 

43 percent), secondary math education (0 versus 13 percent), or any math-related subject, 

including math, secondary math education, statistics, engineering, computer science, finance, 

economics, physics, or astrophysics (56 versus 75 percent). 

 21 In this and all teacher-level analyses presented in this chapter, each teacher is counted only once, regardless 

of whether he or she taught multiple classes in the study. For teachers in both cohorts, the value of the variable as 

reported in cohort 1 is used if cohort 1 and cohort 2 reports differ. We also conducted analyses that weight each 

teacher according to the number of study classes taught, and findings were similar.

22 College selectivity was defined based on Barron’s Profiles of American Colleges 2003. Highly selective 

colleges were defined as those ranked by Barron’s as most competitive, and selective colleges were defined as those 

ranked by Barron’s as very competitive, highly competitive, or most competitive.
Effectiveness of TFA and Teaching Fellows Teachers 

79 

Table VII.2. Demographic Characteristics of Teaching Fellows and Comparison Teachers in the Study and All 

Secondary Teachers Nationwide (percentages unless otherwise indicated)

Secondary 

Teachers 

Nationwide

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

Age (Average Years) 42.7††^^ 33.3 41.0 -7.8** 0.000

Female 59.3 53.8 57.3 -3.5 0.681

Race/Ethnicitya

Asian, Non-Hispanic 1.3†^^ 9.1 18.7 -9.6 0.099

Black, Non-Hispanic 6.9†^^ 16.7 36.0 -19.3** 0.009

Hispanic 6.8 9.4 13.3 -4.0 0.464

White, Non-Hispanic 83.5†^^ 71.2 42.7 28.5** 0.001

Sample Size 1,099,770 66 75

Sources: Data for secondary teachers nationwide from the Schools and Staffing Survey Teacher Questionnaire, 

2007–2008; data for study teachers from the Survey of Secondary Math Teachers.

a

Racial and ethnic categories for study teachers are not mutually exclusive, so percentages may sum to more than 

100.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, twotailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, two-tailed 

test.

 †Difference between secondary teachers nationwide and Teaching Fellows is statistically significant at the 0.05 

level, two-tailed test.

††Difference between secondary teachers nationwide and Teaching Fellows is statistically significant at the 0.01 

level, two-tailed test.

 ^Difference between secondary teachers nationwide and comparison teachers is statistically significant at the 0.05 

level, two-tailed test.

^^Difference between secondary teachers nationwide and comparison teachers is statistically significant at the 0.01 

level, two-tailed test.

Moreover, although Teaching Fellows were less likely to have majored in math and reported 

taking roughly the same number of college-level math courses as comparison teachers, the 

Teaching Fellows demonstrated higher mathematics content knowledge (Table VII.5). This was 

measured by the Praxis II Mathematics Content Knowledge Test (taken primarily by the high 

school teachers in the sample, along with a few middle school teachers in states that allowed or 

required middle school teachers to take this test) or the Praxis II Middle School Mathematics

Test (taken by the remaining middle school teachers in the sample).23

 23 Response rates on the Praxis II differed for Teaching Fellows and comparison teachers—94 percent of the 

Teaching Fellows teachers in the sample had Praxis II scores, compared with only 81 percent of comparison 

teachers (Appendix Table A.18). In the main analysis, we omitted teachers with missing scores. As a sensitivity test, 

in Appendix Table E.2 we examined differences in Praxis II scores when we imputed values that would be otherwise 

missing. Results were similar under the two approaches, although differences between the two groups were even 

more pronounced, suggesting that teachers with missing Praxis data might have been those who would have scored 

lower had they taken the test.

On the Mathematics 

Content Knowledge Test, Teaching Fellows performed an average of 19 points higher than 

comparison teachers (or 0.80 standard deviations). Similarly, those teachers who took the Middle 

School Mathematics Test outperformed comparison teachers by 17 points (or 0.92 standard 

deviations). These patterns persisted both among teacher matches for which the Praxis was “high 
Effectiveness of TFA and Teaching Fellows Teachers 

80 

stakes” (those in districts that required the exam for certification) and those for whom the Praxis 

was “low stakes” (not required for certification, and taken only at the request of the study team). 

Table VII.3. Educational Background of Teaching Fellows and Comparison Teachers in the Study 

(percentages unless otherwise indicated)

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

Bachelor’s Degree

From a highly selective college or universitya 21.1 7.1 13.9* 0.033

From a selective college or universitya 71.9 33.9 38.0** 0.000

Majorb

Math 24.6 42.9 -18.3* 0.040

Secondary math education 0.0 12.5 -12.5** 0.006

Other math-related subjectc 33.3 23.2 10.1 0.236

Other subject 66.7 35.7 31.0** 0.001

Math, secondary math education, or other 

math-related subjectc 56.1 75.0 -18.9* 0.035

Major or minorb

Math 29.8 51.8 -22.0* 0.017

Secondary math education 0.0 25.0 -25.0** 0.000

Other math-related subjectc 38.6 30.4 8.2 0.361

Other subject 78.9 53.6 25.4** 0.004

Graduate Degree

Any graduate degree 83.3 80.0 3.3 0.612

Subjectb

Math or math-related subjectc 12.1 22.7 -10.5 0.098

Secondary math education 57.6 40.0 17.6* 0.037

In other education subject 19.7 24.0 -4.3 0.540

Other subject 12.1 9.3 2.8 0.598

Sample Size 66 75

Source: Survey of Secondary Math Teachers.

a

Highly selective colleges are those ranked by Barron’s Profiles of American Colleges 2003 as being most 

competitive. Selective colleges are those that are ranked by Barron’s as being very competitive, highly competitive, or 

most competitive.

b

Percentages might not sum to 100 if some sample members had a degree in more than one subject.

c

Math-related subjects include statistics, engineering, computer science, finance, economics, and 

physics/astrophysics.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, twotailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, twotailed test.
Effectiveness of TFA and Teaching Fellows Teachers 

81 

Table VII.4. Average Number of College-Level Math Courses Taken by Teaching Fellows and Comparison 

Teachers in the Study

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

All Teachers

Total Number of College-Level Math Courses 9.8 11.0 -1.2 0.320

Calculus 2.6 2.9 -0.4 0.192

Advanced Algebra 1.3 1.6 -0.3 0.190

Analysis 0.7 0.9 -0.2 0.295

Advanced Geometry/Topology 0.6 0.8 -0.2 0.155

Probability and Statistics 1.7 1.7 0.0 0.983

Discrete Mathematics 1.3 1.2 0.1 0.739

Applied Mathematics 1.5 1.8 -0.2 0.616

Sample Size 66 75

Middle School Teachers

Total Number of College-Level Math Courses 8.2 9.3 -1.1 0.648

Sample Size 26 22

High School Teachers

Total Number of College-Level Math Courses 10.8 11.7 -0.9 0.495

Sample Size 40 53

Source: Survey of Secondary Math Teachers.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

While it would be useful to compare average scores of study teachers to average scores of 

the full set of teachers who took the Praxis II mathematics tests nationwide, published data on 

national average scores are available only for test takers who passed the test. For comparison to 

these statistics, we also examined the average scores of the teachers in our sample who passed

the test. On the Mathematics Content Knowledge Test, Teaching Fellows in the study who 

passed the test scored an average of 164 points, compared with an average of 155 for all testtakers nationwide who passed. Similarly, on the Middle School Mathematics Test, Teaching 

Fellows in the study who passed the test scored an average of 187 points, compared with an

average of 169 for all test-takers nationwide who passed. 
Effectiveness of TFA and Teaching Fellows Teachers 

82 

Table VII.5. Praxis II Scores of Teaching Fellows and Comparison Teachers in the Study (percentages unless 

otherwise indicated)

Test-Takers 

Nationwide

Teaching 

Fellows

Comparison

Teachers

Teaching 

FellowsComparison

Difference p-Value

Overall

Mathematics: Content Knowledge Test

Average score n.a. 157.8 138.5 19.3** 0.000

Average score of those who scored above 

the state’s passing thresholda 154.5†† 163.8 154.1 9.7* 0.036

Sample size 5,785 39 47

Middle School Mathematics Test

Average score n.a. 186.7 170.1 16.5** 0.001

Average score of those who scored above 

the state’s passing thresholda 169.0†† 186.7 172.6 14.0** 0.002

Sample size 9,532 26 21

High-Stakes Test-Takersb

Mathematics: Content Knowledge Test

Average score n.a. 154.1 134.3 19.8* 0.040

Sample size 14 10

Low-Stakes Test-Takersc

Mathematics: Content Knowledge Test

Average score n.a. 159.8 139.6 20.2** 0.001

Sample size 25 37

Middle School Mathematics Test

Average score n.a. 186.7 170.1 16.5** 0.001

Sample size 26 21

Sources: Data on all test-takers nationwide are from Gitomer and Qi (2010), and include test-takers who did and did not 

eventually enter the teaching profession. Data for study teachers are from study-administered assessment or 

were provided by the Educational Testing Service. 

a

Educational Testing Service does not report the average score of all test-takers, but only the average score of those who 

passed the test in their states. To compare the study sample with the national statistics from the Educational Testing 

Service, we computed the average scores of sample members who scored above their states’ passing thresholds using the 

Praxis passing thresholds from 2011. In states that did not require this test, the score was compared with the average 

passing threshold across all states that did require this test.

b

High-stakes test-takers are those who are in districts that require secondary math teachers to pass the relevant Praxis II 

assessment for certification. Because no high-stakes test-takers in the Teaching Fellows study sample took the Middle 

School Mathematics test, we do not present estimates for this group.

c

Low-stakes test-takers are those who are in districts that do not require secondary math teachers to pass the relevant 

Praxis II assessment for certification.

*Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

 †Difference between secondary teachers nationwide and Teaching Fellows is statistically significant at the 0.05 level, twotailed test.

††Difference between secondary teachers nationwide and Teaching Fellows is statistically significant at the 0.01 level, twotailed test.

 ^Difference between secondary teachers nationwide and comparison teachers is statistically significant at the 0.05 level, 

two-tailed test.

^^Difference between secondary teachers nationwide and comparison teachers is statistically significant at the 0.01 level, 

two-tailed test.

n.a. = not available.
Effectiveness of TFA and Teaching Fellows Teachers 

83 

3. Teaching and Nonteaching Work Experience

Prior studies have found that, as teachers gain years of experience in the classroom, they 

become more effective teachers (Hanushek and Rivkin 2006; Kane et al. 2008). The Teaching 

Fellows in the study had, on average, 4 years of teaching experience at the end of the study 

school year, compared with an average of 13 years among comparison teachers (Table VII.6). 

Although the Teaching Fellows in the study did have less teaching experience on average than 

comparison teachers, most Teaching Fellows were not novice teachers, consistent with the 

program’s expectation that Teaching Fellows will remain in the teaching field for an extended 

period. In fact, the majority of Teaching Fellows in the study (56 percent) had between three and 

five years of teaching experience, compared with 25 percent of the comparison teachers. 

Twenty-three percent of the Teaching Fellows in the study were in their first or second year of 

teaching, compared with 7 percent of comparison teachers. Sixty-eight percent of the comparison 

teachers had been teaching for more than 5 years, compared with 21 percent of Teaching 

Fellows.

Table VII.6. Nonteaching and Teaching Work Experience of Teaching Fellows and Comparison Teachers in 

the Study (percentages unless otherwise indicated)

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

Nonteaching Work Experience

Had a nonteaching job after college 65.2 42.7 22.5** 0.007

Years of experience in nonteaching job 

(average)a 5.0 3.0 2.0 0.080

Used college-level math in nonteaching joba 40.9 28.0 12.9 0.110

Teaching Experience (End of Study Year)

Years of teaching experience (average) 4.0 13.0 -9.0** 0.000

1 or 2 years of teaching experience 22.7 6.7 16.1** 0.008

3 to 5 years of teaching experience 56.1 25.3 30.7** 0.000

More than 5 years of teaching experience 21.2 68.0 -46.8** 0.000

Years of experience teaching math (average) 3.6 10.8 -7.2** 0.000

Fewer than 3 years of math teaching 

experience 24.2 8.0 16.2** 0.010

3 to 5 years of math teaching experience 60.6 29.3 31.3** 0.000

More than 5 years of math teaching 

experience 15.2 62.7 -47.5** 0.000

Sample Size 66 75

Source: Survey of Secondary Math Teachers.

a

Calculations are based on all teachers, regardless of whether they had a nonteaching job after college.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, twotailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, twotailed test.

Consistent with the fact that the Teaching Fellows programs recruit experienced 

professionals to transition into the teaching field, the Teaching Fellows in the study generally 

had more nonteaching work experience than comparison teachers. Sixty-five percent of the 

Teaching Fellows held a nonteaching job after college, compared with 43 percent of comparison 

teachers (Table VII.6). This difference was driven entirely by the subset of Teaching Fellows 

who were compared with comparison teachers from TC routes—68 percent of these Teaching 

Fellows had held a nonteaching job, compared with 33 percent of TC comparison teachers, while 

there was no significant difference between comparison teachers from AC routes and the 
Effectiveness of TFA and Teaching Fellows Teachers 

84 

Teaching Fellows with whom they were compared (Appendix Table D.14). Forty-one percent of 

Teaching Fellows had used college-level math in a nonteaching job, as had 28 percent of 

comparison teachers; this difference was not significant at the 5 percent level.

4. Teacher Training, Professional Development, and Support

Teacher training and professional development. Teaching Fellows reported having 

received similar amounts of math pedagogy instruction as comparison teachers, but Teaching 

Fellows reported having fewer days of math student teaching as part of their teacher training 

(Table VII.7). 24

As discussed in Chapter VI, three of the eight Teaching Fellows programs in the study 

required Teaching Fellows who did not take enough math courses in college to complete a math 

immersion course in the summer before they began teaching. To determine the number of 

Teaching Fellows in the study who took math immersion, as well as whether any study teachers 

from other routes to certification completed a similar course, the teacher survey included the 

following question: “Some districts require prospective teachers without degrees in math to take 

an intensive math immersion program in order to become certified to teach secondary math. 

These programs typically cover the necessary content knowledge to teach secondary math. 

Before becoming a secondary math teacher, did you participate in this type of program?” Fifty 

percent of Teaching Fellows in the study reported completing a math immersion course, 

compared with 4 percent of comparison teachers. Across the three districts in the sample that 

offered math immersion, 43 percent of Teaching Fellows in the sample took math immersion in 

the first district, 68 percent took it in the second district, and all took it in the third.

Both Teaching Fellows study members and comparison teachers completed 

approximately 48 hours of math pedagogy instruction, on average. However, Teaching Fellows 

were less likely than comparison teachers to have student taught a math class for more than 

20 days during their teacher training (12 versus 61 percent). On average, Teaching Fellows 

reported that they taught at least one math class to a full classroom of students for 11 days during 

their teacher training programs, whereas comparison teachers taught a full math class during 

38 days on average. 

Some differences between Teaching Fellows and their comparison teachers depended on 

whether the comparison teachers were teachers from AC or TC routes (Appendix Table D.15). 

For example, Teaching Fellows completed less student teaching in math, on average, than 

comparison teachers from TC routes (10 versus 47 days), while Teaching Fellows and the 

AC teachers with whom they were compared completed similar amounts of student teaching. 

Similarly, Teaching Fellows received more professional development in math during the study 

year than comparison teachers from TC routes (9 versus 4 hours), while there was no significant 

difference in the amount of math professional development received by Teaching Fellows and 

comparison teachers from AC routes.

 24 Because questions about teacher training required more experienced teachers (predominantly comparison 

teachers) to recall experiences that occurred several years in the past, these data may be less reliable than data 

pertaining to the study year.
Effectiveness of TFA and Teaching Fellows Teachers 

85 

Table VII.7. Training and Professional Development of Teaching Fellows and Comparison Teachers in the 

Study (percentages unless otherwise indicated)

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

Average Hours of Math Pedagogy Instruction as Part of 

Teacher Traininga 48.7 47.5 1.2 0.843

Participated in Intensive “Math Immersion” Program as Part 

of Teacher Training 50.0 4.0 46.0** 0.000

Days of Student Teaching in Math as Part of Teacher 

Trainingb

No days 10.6 22.7 -12.1 0.053

1 to 10 53.0 6.7 46.4** 0.000

11 to 20 24.2 9.3 14.9* 0.019

More than 20 12.1 61.3 -49.2** 0.000

Average Days of Student Teaching in Math 10.8 37.8 -27.0** 0.000

Hours per Day Spent in Student Teaching in Math as Part of 

Teacher Training (Average)c 2.1 3.1 -1.0** 0.000

Average Hours Spent in Math Pedagogy Professional 

Development During School Yeard 7.8 5.7 2.2 0.078

Sample Size 66 75

Source: Survey of Secondary Math Teachers.

a

Teachers were asked, “As part of your training to become a math teacher, did you receive any instruction in math pedagogy 

or strategies to teach math?” If so, “In total, how many hours of instruction in math pedagogy or strategies to teach math did 

you receive?” Possible responses were none, 1 to 4, 5 to 20, 21 to 40, 41 to 60, 61 to 80, 81 to 100, and more than 100. To 

construct average hours of math pedagogy training, we created a continuous variable equal to zero for teachers who 

completed no training, 100 for those who completed more than 100 hours, and the midpoint of the range for all other 

categories.

b

Teachers were asked, “Did your teacher education/preparation program require you to do any student teaching in which 

you went to an elementary or secondary school and taught one or more math lessons to a whole classroom of students?” If 

so, “On approximately how many days, in total, did you teach at least one full math lesson (at least one class period) to a 

whole classroom of students during your teacher education/preparation program?” Possible responses were none, 1 to 5, 

6 to 10, 11 to 15, 16 to 20, 21 to 40, 41 to 60, 61 to 80, and more than 80. To construct average days of student teaching in 

math, we created a continuous variable equal to zero for teachers who did not do any student teaching in math, 80 for 

those who did more than 80 days, and the midpoint of the range for all other categories.

c

Calculated only among those teachers who said they did some student teaching in math.

d

Teachers were asked, “During this school year, did you attend any professional development classes, workshops, or 

seminars provided by the school district in math pedagogy or strategies to teach math?” If so, “In total, how many hours did 

you spend attending these professional development classes, workshops, or seminars in math pedagogy or strategies to 

teach math?” Possible responses were none, 1 to 4, 5 to 10, 11 to 20, and more than 20. To construct average hours of 

professional development, we created a continuous variable equal to zero for teachers who did no professional 

development, 20 for those who did more than 20 hours, and the midpoint of the range for all other categories.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

Coursework during study year. Many states require teachers from alternative routes, 

including Teaching Fellows, to take coursework in their first few years of teaching to meet 

certification requirements (Feistritzer 2005). Consistent with the fact that the majority of both 

Teaching Fellows and comparison teachers in the sample had more than two years of experience, 

there were no significant differences in the percentage who took coursework during the study 

year (Table VII.8). There was also no statistically significant difference between Teaching 

Fellows and comparison teachers in the average number of hours spent doing coursework. 
Effectiveness of TFA and Teaching Fellows Teachers 

86 

Table VII.8. Coursework Taken During the School Year by Teaching Fellows and Comparison Teachers in the 

Study (percentages unless otherwise indicated)

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

All Teachers

Took Coursework Related to Teaching Job 28.8 22.7 6.1 0.411

Total hours spent during school year on coursework 

(average) 59.9 36.6 23.3 0.240

Hours spent in class during school year on coursework 

(average) 27.6 15.9 11.7 0.174

Hours spent out of class during school year on 

coursework (average) 32.3 20.7 11.6 0.330

Sample Size 66 75

Middle School Teachers

Took Coursework Related to Teaching Job 34.6 9.1 25.5* 0.030

Sample Size 26 22

High School Teachers

Took Coursework Related to Teaching Job 25.0 28.3 -3.3 0.724

Sample Size 40 53

Source: Survey of Secondary Math Teachers.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

Mentoring. Teaching Fellows and comparison teachers received similar amounts of 

mentoring during the study year (Table VII.9). Less than 25 percent of both groups reported 

having a mentor during the school year, consistent with the fact that less than 5 percent of both 

groups were in their first years of teaching, when mentoring tends to be most common. 

5. Views Toward Teaching

Because teachers’ levels of satisfaction with their jobs have the potential to influence how 

long they stay in teaching, we measured the job satisfaction of both Teaching Fellows and 

comparison teachers. Teaching Fellows were less satisfied with some aspects of their job than 

comparison teachers, particularly those related to school policies and staff (Table VII.10). 

Teachers asked whether they were “very dissatisfied,” “somewhat dissatisfied,” “somewhat 

satisfied,” or “very satisfied” with 10 different aspects of their job. Teaching Fellows and 

comparison teachers reported statistically similar levels of satisfaction with aspects of their jobs 

related to their own classrooms (autonomy and control over their own classrooms, students’ 

motivation to learn, students’ discipline and behavior, and availability of resources for the 

classroom). However, Teaching Fellows reported significantly lower levels of satisfaction for 

three out of six aspects of their jobs related to school policies and staff, including their influence 

over school policy, recognition and support from the administration, and the principal’s 

leadership and vision. 
Effectiveness of TFA and Teaching Fellows Teachers 

87 

Table VII.9. Mentoring Received During the School Year by Teaching Fellows and Comparison Teachers in 

the Study (percentages unless otherwise indicated)

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

Had a Mentor During School Year 22.7 17.3 5.4 0.430

Average Time Spent Observing Other Teachers (minutes) 70.9 43.5 27.4 0.461

Average Time Spent Being Observed by Mentors (minutes) 4.0 6.5 -2.5 0.656

Average Time Spent in Formal Meetings with Mentors 

(minutes) 71.2 27.0 44.1 0.145

Average Time Spent in Informal Meetings with Mentors 

(minutes) 21.3 23.4 -2.1 0.897

Number of Times Received Written Feedback on Teaching 

Performance 1.0 0.2 0.8 0.067

Felt that Mentoring Was Very Helpful 18.2 14.7 3.5 0.578

Sample Size 66 75

Source: Survey of Secondary Math Teachers.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, twotailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, two-tailed 

test.

C. Students in the Teaching Fellows Study Sample

Among students in the impact analysis sample (those for whom we have outcome test score 

data), those assigned to the Teaching Fellows (the treatment group) and those assigned to the 

comparison teachers (the control group) were similar in most of their baseline characteristics

(Table VII.11). Of the 23 baseline characteristics examined, there were statistically significant 

differences in five, but these differences were all around 2 percent or less. This suggests that 

random assignment was properly implemented and that student attrition after random assignment

(due to lack of outcome test score data) did not lead to differences in observable baseline 

characteristics between the two groups. As shown in Appendix Table A.6, treatment and control 

group students in the full research sample (including both those with and without outcome test 

score data) were also balanced in terms of baseline characteristics.

Consistent with the Teaching Fellows programs’ goal of serving disadvantaged students, 

both treatment and control group students in the analysis sample scored, on average, about 0.10 

standard deviations below average for their states in math and about 0.05 standard deviations 

below average for their states in reading in the years before the evaluation, as indicated by 

average z-scores for both groups. Both treatment and control group students were about 14 years 

old, on average. Approximately half of the students in both groups were black, non-Hispanic, 

while around 35 percent in both groups were Hispanic, 5 percent were white, non-Hispanic, and 

8 percent were Asian. Thus, a higher percentage of the study sample were members of racial and 

ethnic minority groups relative to public secondary school students nationwide, among whom 
Effectiveness of TFA and Teaching Fellows Teachers 

88 

Table VII.10. Job Satisfaction of Teaching Fellows and Comparison Teachers in the Study (percentages 

unless otherwise indicated)

Percentage of Teachers Who Were Somewhat Satisfied 

or Very Satisfied with this Aspect of Joba

Aspect of Job

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

Autonomy and Control Over Own Classroom 95.5 89.3 6.1 0.169

Students’ Motivation to Learn 36.4 45.3 -9.0 0.282

Students’ Discipline and Behavior 39.4 48.0 -8.6 0.307

Availability of Resources for Classroom 66.7 69.3 -2.7 0.737

Recognition/Support from Administration 51.5 71.6 -20.1* 0.015

Influence Over School Policies and Practices 38.5 58.7 -20.2* 0.017

Opportunities for Professional Development 59.1 65.8 -6.7 0.422

Principal’s Leadership and Vision 57.6 76.0 -18.4* 0.021

Procedures for Performance Evaluation 56.1 64.0 -7.9 0.341

Professional Caliber of Colleagues 74.2 84.0 -9.8 0.159

Sample Size 66 75

Source: Survey of Secondary Math Teachers.

a

Teachers were asked about their satisfaction with each aspect of their job—possible responses were very 

dissatisfied, somewhat dissatisfied, somewhat satisfied, and very satisfied.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, 

two-tailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, 

two-tailed test.

16 percent were black, 18 percent were Hispanic, and 60 percent were white, non-Hispanic. 

Around 75 percent of students in both groups were eligible for free or reduced-price lunch, 

higher than the national average of 35 percent. In both groups, around 7 percent of students had 

limited English proficiency (similar to the national average of 7 percent), and around 6 percent 

had an Individualized Education Plan (IEP) for a special education program or services. The 

percentage of students with an IEP in the TFA sample is lower than the national average of 

13 percent, perhaps because students with more severe disabilities or restrictive IEPs were 

exempt from random assignment and excluded from the study sample.
Effectiveness of TFA and Teaching Fellows Teachers 

89 

Table VII.11. Average Baseline Characteristics of Students in the Analysis Sample Who Were Assigned to 

Teaching Fellows or Comparison Teachers (percentages unless otherwise indicated)

Characteristic

Secondary 

School 

Students 

Nationwide

Assigned to 

Teaching 

Fellows

Assigned to

Comparison 

Teachers

Difference

Between 

Teaching 

Fellows and 

Comparison p-Value

Baseline Math Achievement

Baseline math score (average z-score) 0.00 -0.11 -0.10 -0.01 0.636

Score below 25th percentile of state 25.0 26.0 25.3 0.7 0.453

Score below 50th percentile of state 50.0 56.4 57.1 -0.7 0.493

Baseline Reading Achievement

Baseline reading score (average z-score) 0.00 -0.06 -0.05 -0.02 0.418

Score below 25th percentile of state 25.0 22.8 22.3 0.5 0.619

Score below 50th percentile of state 50.0 57.1 57.6 -0.5 0.570

Age (average years) 14.31 14.27 0.04** 0.005

Female 50.2 53.1 54.1 -1.0 0.326

Race and Ethnicity

Asian, non-Hispanic 4.7 8.9 8.1 0.8 0.242

Black, non-Hispanic 15.9 50.4 48.8 1.6* 0.047

Hispanic 18.2 34.9 36.8 -1.9* 0.038

White, non-Hispanic 60.1 5.2 5.5 -0.3 0.580

Other race/ethnicity 1.2 0.6 0.8 -0.3 0.142

Eligible for Free/Reduced-Price Lunch 35.0 73.7 75.9 -2.1* 0.017

Limited English Proficient 6.5 7.7 7.2 0.5 0.332

Individualized Education Plan 12.5 6.7 6.1 0.6 0.233

Grade Level in Study Year

6th grade 7.4 8.1 8.1 0.0 a

7th grade 7.5 14.8 14.8 0.0 a

8th grade 7.6 17.6 17.6 0.0 a

9th grade 8.6 26.5 27.1 -0.6 0.140

10th grade 7.9 17.9 18.1 -0.1 0.766

11th grade 7.2 14.1 13.1 1.0* 0.040

12th grade 6.6 1.1 1.3 -0.2 0.541

Number of Students 2,127 1,989

Number of Classroom Matches 118 118

Number of Teachers 69 84

Number of Schools 44 44

Source: Nationwide statistics on demographic characteristics from the 2007–2008 Schools and Staffing Survey, 

available at http://nces.ed.gov/pubs2009/2009321/. Data on nationwide grade distribution from the 

2006–2007 “Digest of Education Statistics: Enrollment in Public Elementary and Secondary Schools, by 

Grade,” available at http://nces.ed.gov/programs/digest/d08/tables/ dt08_037.asp. Data on study 

students from district administrative records.

Note: Means and percentages are weighted with sample weights and adjusted for classroom match fixed 

effects. P-values are based on a regression of the specified characteristic on a Teaching Fellows 

indicator and classroom match indicators, accounting for sample weights and clustering at the teacher 

level.

a

p-value is not defined because there is no variation in this variable within classroom matches.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

91 

VIII. TEACHING FELLOWS: IMPACTS ON SECONDARY 

STUDENT MATH ACHIEVEMENT

In this chapter, we examine the impact of secondary math teachers from Teaching Fellows 

programs on student achievement in math, relative to the comparison teachers who taught the 

same courses in the same schools. Our analytic approach is identical to that used in estimating 

the impacts of Teach For America (TFA) teachers. To estimate the impacts of Teaching Fellows, 

we compared the end-of-year math achievement of students assigned to Teaching Fellows and 

those assigned to comparison teachers. Random assignment ensured that these two groups of 

students had similar achievement levels and other characteristics at the start of the school year, 

so that differences in achievement between the groups at the end of the school year could be 

reliably attributed to the effectiveness of the teachers. Teaching Fellows and comparison teachers 

could differ in effectiveness as a result of two types of factors: (1) the characteristics they had 

before entering their preparation programs and (2) the training and support they received from 

their programs. The impact findings presented here are based on Teaching Fellows and 

comparison teachers whose classes were fully comparable and whose schools and districts 

agreed to be in the study; the findings may not necessarily apply to Teaching Fellows in other 

types of schools, subjects, or demographic environments. 

As we did for the impacts of TFA teachers in Chapter V, we expressed the impacts of 

Teaching Fellows in terms of standard deviations of student achievement within a statewide or 

national reference population. We estimated impacts within both the full set of classroom 

matches in which Teaching Fellows were included (Section A) as well as within subgroups of 

matches defined by characteristics of the Teaching Fellows or comparison teachers (Sections B 

and C).

A. Impacts of Teaching Fellows Relative to All Comparison Teachers 

1. Average Impact

On average, Teaching Fellows in the study were no more or less effective than comparison 

teachers. Students assigned to Teaching Fellows and those assigned to comparison teachers both 

scored, on average, 0.39 standard deviations below the mean achievement in their statewide or 

national reference populations (Table VIII.1). 

The finding that Teaching Fellows were similar in effectiveness to comparison teachers is 

robust to a variety of sensitivity analyses. We estimated models that (1) excluded covariates, 

(2) used alternative methods of handling missing data and invalid test scores, (3) used alternative 

approaches to weighting classroom matches, (4) dropped classroom matches with high rates of 

student mobility, (5) dropped matches with supplemental math classes, (6) used alternative ways 

of standardizing the outcome variable, and (7) accounted for students who switched to a different 

type of teacher than their originally assigned teacher (Appendix Table F.4). In all models, there 

was no statistically significant difference in math achievement between students of Teaching 

Fellows and students of comparison teachers.

These findings suggest that student math achievement within the classes in the study would, 

on average, be no better or worse if the schools in the study were to hire Teaching Fellows rather 

than teachers from other certification routes to teach those classes. One important consideration 
Effectiveness of TFA and Teaching Fellows Teachers 

92 

Table VIII.1. Difference in Effectiveness Between Teaching Fellows and All Comparison Teachers

Outcome Variable

Mean Outcome

Difference in Outcomes 

Between Groups

Assigned to 

Teaching 

Fellows 

Assigned to 

Comparison 

Teachers Estimate p-Value

Student Math Achievement (z-score) -0.39 -0.39 0.00 0.956

Sample Sizes

Number of Students 2,127 1,989

Number of Classroom Matches 118 118

Number of Teachers 69 84

Number of Schools 44 44

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Note: The difference between groups is adjusted for classroom match fixed effects and all covariates in 

Appendix Table B.2. The mean outcome for students assigned to Teaching Fellows is calculated 

as the unadjusted mean outcome for students assigned to comparison teachers plus the adjusted 

difference in outcomes between the two groups.

 *Estimate is statistically significant at the 0.05 level based on a two-tailed test after adjusting for multiple 

hypothesis testing.

**Estimate is statistically significant at the 0.01 level based on a two-tailed test after adjusting for multiple 

hypothesis testing.

in interpreting these results, however, is that the Teaching Fellows in the study had, on average, 

nine fewer years of teaching experience than the comparison teachers. This experience 

differential could be due to a higher turnover rate among Teaching Fellows relative to 

comparison teachers. On the other hand, the experience gap could be due to the fact that many of 

the Teaching Fellows programs were still relatively new at the time of this study, and thus it was 

not possible for the Teaching Fellows in the sample to have accumulated as much experience as 

their comparison group counterparts. The findings from Table VIII.1 do not necessarily shed 

light on how effective Teaching Fellows would be if they were to have experience levels closer 

to those of their counterparts from other routes, a question we explore further below. 

In supplemental analyses, we examined impacts on measures of student absences, a potential 

channel through which teachers could affect student math achievement. Students assigned to 

Teaching Fellows were less likely to be chronically absent—defined as being absent more than 

25 percent of the time—from their math class during the study year than students assigned to 

comparison teachers (Appendix Table F.5). The difference in the rate of absences between these 

groups did not translate into differences in math achievement.

2. Variation in Impacts 

Although there was no average difference in effectiveness between Teaching Fellows and 

comparison teachers, impacts of Teaching Fellows relative to comparison teachers from 

individual classroom matches varied in both sign and magnitude (Figure VIII.1). Across the 

118 matches, the estimated difference in effectiveness between Teaching Fellows and 

comparison teachers, without regard to statistical significance, was positive in 46 percent of 

matches but negative in a similar proportion (54 percent) of matches. As with the TFA matches 

examined in Chapter V, each match-specific estimate for the impact of Teaching Fellows was 
Effectiveness of TFA and Teaching Fellows Teachers 

93 

based on a small number of students and, thus, had random statistical error that contributed to the 

variation in impact estimates across classroom matches. Nevertheless, on the basis of an F-test, 

we found that the observed variation in impact estimates across classroom matches exceeded the 

variation that would be expected from pure statistical chance.

Figure VIII.1. Differences in Effectiveness Between Teaching Fellows and Comparison Teachers from 

Individual Classroom Matches

-1.4

-1.2

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Classroom Match

Difference in Effectiveness

(student z-score units)

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Notes: Differences in effectiveness from individual classroom matches are estimated from a regression of 

students’ end-of-year math scores on classroom match indicators, an indicator for being assigned to a 

Teaching Fellow fully interacted with all classroom match indicators, and all covariates in Appendix 

Table B.2. There are 118 classroom matches represented in the figure. An F-test of the null hypothesis 

that differences in effectiveness between Teaching Fellows and comparison teachers are equal across 

classroom matches has a p-value of less than 0.001. 

Therefore, although Teaching Fellows and comparison teachers were similar in effectiveness 

on average, our findings suggest that an individual Teaching Fellow could be more or less 

effective than an individual comparison teacher. In other words, even after accounting for 

teachers' route to certification (Teaching Fellow or comparison), teachers varied in effectiveness. 

Chapter IX explores additional factors that might account for this variation in effectiveness.

Given that the difference in effectiveness between Teaching Fellows and comparison 

teachers varied across matches, we examined whether differences were more or less pronounced 

when specific types of Teaching Fellows and comparison teachers were compared. The subgroup 

analyses that address this question are discussed in the remainder of this chapter; detailed results 

are presented in Appendix Table F.6. 
Effectiveness of TFA and Teaching Fellows Teachers 

94 

B. Impacts of Teaching Fellows Relative to Comparison Teachers from 

Traditional and Alternative Routes to Certification

We compared the effectiveness of Teaching Fellows with that of comparison teachers in two 

separate subgroups of matches: (1) those whose comparison teachers were certified through 

traditional routes to certification (TC routes) and (2) those whose comparison teachers were 

certified through less selective alternative routes to certification (AC routes). As an AC route, 

Teaching Fellows programs are subject to the same criticisms mentioned in Chapter V regarding 

TFA—specifically, that they provide insufficient preparation for teaching relative to TC 

programs. Therefore, we explored whether the average similarity in effectiveness between 

Teaching Fellows and comparison teachers masked differences in how Teaching Fellows 

performed relative to TC and AC teachers separately.

While we found no statistically significant difference in achievement between students 

of Teaching Fellows and students of comparison teachers from TC routes, students of Teaching 

Fellows outperformed students of comparison teachers from less selective AC routes by 0.13 

standard deviations (Figure VIII.2). This finding has two distinct implications. First, for study 

schools whose main choice is between Teaching Fellows and TC teachers, math achievement in 

the classes examined by the study would be no different if they filled vacancies with one type of 

teacher rather than another. Second, for study schools whose main choice is between Teaching 

Fellows and AC teachers, relying on Teaching Fellows instead of the AC teachers to teach the 

secondary math classes in the study would, on average, lead to higher student math achievement. 

Figure VIII.2. Differences in Effectiveness Between Teaching Fellows and Comparison Teachers from 

Traditional and Alternative Routes to Certification

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

Teaching Fellows versus 

TC Comparison Teachers

Teaching Fellows versus 

AC Comparison Teachers

Difference in Effectiveness

(student z-score units)

-0.03

0.13*

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Note: Differences in effectiveness are adjusted for classroom match fixed effects and all covariates in Appendix 

Table B.2.

 *Estimate is statistically significant at the 0.05 level based on a two-tailed test after adjusting for multiple hypothesis testing.

**Estimate is statistically significant at the 0.01 level based on a two-tailed test after adjusting for multiple hypothesis testing.

AC = alternative route to certification; TC = traditional route to certification. 
Effectiveness of TFA and Teaching Fellows Teachers 

95 

C. Impacts Within Other Teacher Subgroups

1. Subgroups Defined by Specific Levels of Teaching Experience

School administrators might want to know how student achievement in their school would 

differ as a result of hiring a new Teaching Fellow rather than some other new, inexperienced 

teacher. We gauged the effects of choosing a new Teaching Fellow over a new teacher from 

another certification route by comparing Teaching Fellows and comparison teachers who had 

recently entered teaching. As in Chapter V, we classified all teachers into two experience 

categories: (1) novice teachers, defined as those in their first three years of teaching, and (2) 

experienced teachers, defined as those in their fourth year of teaching or beyond. We then 

examined impacts within the subgroup of classroom matches in which novice Teaching Fellows

were compared with novice comparison teachers. We also examined impacts within other 

experience subgroups to determine how each type of comparison contributed to the overall 

similarity in effectiveness between Teaching Fellows and comparison teachers.

Among teachers in the study, novice Teaching Fellows demonstrated greater effectiveness 

than novice comparison teachers. Students of novice Teaching Fellows scored 0.13 standard 

deviations higher than students of novice comparison teachers (Figure VIII.3).

Figure VIII.3. Differences in Effectiveness Between Novice Teaching Fellows and Comparison Teachers, by 

Experience Level of Comparison Teacher

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

Novice Teaching Fellows versus 

Novice Comparison Teachers

Novice Teaching Fellows versus 

Experienced Comparison Teachers

Difference in Effectiveness

(student z-score units)

0.13**

-0.10**

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Note: Differences in effectiveness are adjusted for classroom match fixed effects and all covariates in 

Appendix Table B.2. Novice teachers are defined as teachers in their first three years of teaching. 

Experienced teachers are defined as teachers in their fourth or more year of teaching.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.
Effectiveness of TFA and Teaching Fellows Teachers 

96 

Novice Teaching Fellows were less effective than experienced comparison teachers. Novice 

Teaching Fellows lowered student math achievement by 0.10 standard deviations relative to 

experienced comparison teachers (Figure VIII.3)—a difference that could reflect both the 

imbalance in experience and other differences in teacher characteristics. As experienced 

Teaching Fellows were rarely matched (in only 11 classroom matches) with novice comparison 

teachers, we did not estimate differences in the effectiveness of those teacher groups. In the 

65 classroom matches in which experienced Teaching Fellows were compared with experienced 

comparison teachers, the two groups did not statistically differ in effectiveness (Figure VIII.4). 

Figure VIII.4. Differences in Effectiveness Between Experienced Teaching Fellows and Comparison Teachers, 

by Experience Level of Comparison Teacher

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

Experienced Teaching Fellows versus 

Novice Comparison Teachers

Experienced Teaching Fellows versus 

Experienced Comparison Teachers

Difference in Effectiveness

(student z-score units)

Suppresseda

0.03

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Note: Differences in effectiveness are adjusted for classroom match fixed effects and all covariates in 

Appendix Table B.2. Novice teachers are defined as teachers in their first three years of teaching. 

Experienced teachers are defined as teachers in their fourth or more year of teaching.

a

Due to small sample sizes, this estimate did not meet the minimum level of precision required to present a subgroup 

estimate in this report.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

2. Subgroup of Teaching Fellows and Comparison Teachers with Similar Levels of 

Teaching Experience

As discussed earlier, the average difference in effectiveness between all Teaching Fellows 

and all comparison teachers includes any difference reflecting the gap in teaching experience 

between these groups. However, it is possible that the experience gap could narrow over time as 

the program matures and earlier cohorts of Teaching Fellows have more time to gain experience. 

We explored this scenario by considering the impacts that Teaching Fellows would have if their 

experience levels were similar to those of their counterparts in the same schools.
Effectiveness of TFA and Teaching Fellows Teachers 

97 

To assess the relative effectiveness of Teaching Fellows and comparison teachers in the 

absence of an experience gap, we estimated impacts based only on Teaching Fellows in the study 

who were compared with comparison teachers with similar levels of teaching experience (an 

absolute difference in experience of no more than two years). Within this subgroup of 

46 teachers, the average experience levels of Teaching Fellows (3.6 years) and comparison 

teachers (3.9 years) were similar.

We found no statistically significant difference in effectiveness between Teaching Fellows 

and comparison teachers who had similar levels of teaching experience (Table VIII.2). 

Therefore, our main conclusion from the average impacts presented earlier—that Teaching 

Fellows and comparison teachers in the study were indistinguishable in effectiveness—also held 

true for comparisons in which the two groups had equivalent amounts of teaching experience. 

Table VIII.2. Difference in Effectiveness Between Teaching Fellows and Comparison Teachers with 

Similar Levels of Teaching Experience

Mean Outcome

Difference in Outcomes 

Between Groups

Outcome Variable

Assigned to 

Teaching 

Fellows 

Assigned to

Comparison 

Teachers Estimate p-Value

Student Math Achievement (z-score) -0.17 -0.20 0.03 0.399

Sample Sizes

Number of Students 661 622

Number of Classroom Matches 33 33

Number of Teachers 22 24

Number of Schools 17 17

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Note: A Teaching Fellow and comparison teacher in the same classroom match are classified as having 

similar levels of teaching experience if those levels differ in absolute value by no more than two 

years. The difference in outcomes between groups is adjusted for classroom match fixed effects 

and all covariates in Appendix Table B.2. The mean outcome for students assigned to Teaching 

Fellows is calculated as the unadjusted mean outcome for students assigned to comparison 

teachers plus the adjusted difference in outcomes between the two groups.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

3. Subgroups Defined by Middle and High School

We examined differences in effectiveness between Teaching Fellows and comparison 

teachers separately for middle and high school teachers due to the different types of math courses 

and student assessments associated with the two grade spans, as discussed in Chapter V. At both 

the middle and high school levels, the effectiveness of Teaching Fellows was statistically 

indistinguishable from that of comparison teachers (Figure VIII.5).
Effectiveness of TFA and Teaching Fellows Teachers 

98 

Figure VIII.5. Differences in Effectiveness Between Teaching Fellows and Comparison Teachers Within 

Middle Schools and High Schools

-0.16

-0.12

-0.08

-0.04

0

0.04

0.08

0.12

0.16

Middle School High School

Difference in Effectiveness

(student z-score units)

0.04

-0.02

Sources: District administrative records and study-administered Northwest Evaluation Association (NWEA) 

assessments.

Note: Differences in effectiveness are adjusted for classroom match fixed effects and all covariates in 

Appendix Table B.2.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

D. Conclusions

The Teaching Fellows programs aim to recruit and train teachers to teach in low-income 

school districts. As discussed in Chapter VI, the programs focus their recruitment efforts on both 

recent college graduates and midcareer professionals and seek applicants who are willing to 

make a long-term commitment to teaching. The programs are highly selective, with multi-stage 

application processes, and accept only 13 percent of applicants nationwide. They provide their 

newly selected teachers with intense five- to seven-week summer training programs as well as 

mentoring and support after they begin teaching. 

Consistent with the Teaching Fellows programs’ mission to place teachers in high-need 

schools, Teaching Fellows in the study were typically placed in urban schools that served 

economically disadvantaged students, largely from racial and ethnic minority groups. As 

discussed in Chapter VII, the Teaching Fellows in the study were typically white, with an 

average of four years of teaching experience and five years of nonteaching work experience, and 

included roughly equal numbers of men and women. The other secondary math teachers in these 

same schools were primarily white or black women, with considerably more teaching experience 

(13 years) and three years of nonteaching work experience, on average. Although the Teaching 

Fellows teachers took similar numbers of college-level math courses as the teachers from other 

routes to certification, they were far more likely to have attended a selective undergraduate 

university and had significantly higher math content knowledge test scores. 
Effectiveness of TFA and Teaching Fellows Teachers 

99 

The experimental analysis suggests that Teaching Fellows teaching secondary math were 

neither more nor less effective than comparison teachers. However, this comparison of average 

effectiveness masked several differences in effectiveness between specific subgroups of teachers: 

• Teaching Fellows were more effective than comparison teachers from less 

selective AC routes. Students of Teaching Fellows outperformed students of 

comparison teachers from less selective AC routes by 0.13 standard deviations. 

• Teaching Fellows were neither more nor less effective than comparison teachers 

from TC routes. Students of Teaching Fellows did not perform significantly better or 

worse than students of comparison teachers from TC routes.

• Novice Teaching Fellows were more effective than novice comparison teachers. 

Students of novice Teaching Fellows (those in their first three years of teaching) 

outscored students of novice comparison teachers by 0.13 standard deviations. 

However, on average across all levels of experience, Teaching Fellows were neither 

more nor less effective than comparison teachers who had similar levels of teaching 

experience.

• Teaching Fellows were neither more nor less effective than comparison teachers 

in both middle and high schools. Math achievement did not differ significantly 

between students of Teaching Fellows and students of comparison teachers in either 

middle or high schools. 
This page has been left blank for double–sided copying. 
Effectiveness of TFA and Teaching Fellows Teachers 

101 

IX. RELATIONSHIPS BETWEEN TEACHER CHARACTERISTICS 

AND TEACHER EFFECTIVENESS

When making hiring decisions, school administrators take into account a variety of applicant 

characteristics other than route to certification that provide information on applicants’ likely 

effectiveness in the classroom. Using nonexperimental analyses, this chapter explores the extent 

to which various teacher characteristics—including measures of the teachers’ academic ability, 

math knowledge, professional experience, and instructional training—are predictive of teacher 

effectiveness. This evidence can, in turn, suggest the degree to which differences in effectiveness 

between teachers from distinct certification routes are related to differences in the types of 

teachers who were recruited and selected into those routes versus differences in the training and 

support they received. The findings presented here are correlational relationships between 

teacher characteristics and student achievement; as such, they can generate hypotheses about—

but do not provide conclusive evidence for—the causal effects of these characteristics.

Because each teacher’s effectiveness is defined as his or her contributions to student 

achievement relative to other teachers, our analyses are focused on examining differences in 

effectiveness across teachers and identifying how they are related to differences in the teachers’ 

characteristics. In previous chapters, we found wide variation across classroom matches in the 

relative effectiveness of the teachers who were compared even after taking into account the 

teachers’ certification routes (see Figures V.1 and VIII.1). This variation suggests that there were 

other teacher characteristics that were correlated with effectiveness among teachers in the study. 

In the remainder of this chapter, we identify characteristics associated with variation in 

teacher effectiveness (Section A), using the combined sample of all Teach For America (TFA) 

teachers, Teaching Fellows, and comparison teachers in the study. We then explore whether 

these characteristics could account for the observed difference in effectiveness between TFA and 

comparison teachers (Section B). Because Teaching Fellows and comparison teachers did not 

differ in effectiveness on average, we did not seek to decompose differences in effectiveness 

between these groups. 

A. Analysis of Characteristics That Predict Teacher Effectiveness

We explored the relationships between teacher characteristics and teacher effectiveness by 

including teacher characteristics in the model of student math achievement used in the 

experimental analysis from Chapters V and VIII. Because the model controlled for classroom 

match indicators, only differences in characteristics between teachers in the same match were 

used to predict differences in achievement between students of matched classes. Achievement 

differences between matched classes were solely driven by differences in teacher effectiveness, 

so this regression model was, in effect, an analysis of the association between teacher 

characteristics and teacher effectiveness.

This analysis examined three broad categories of teacher characteristics: (1) general 

academic ability; (2) exposure to and knowledge of mathematics; and (3) instructional training 

and experience. Variables that measured teacher characteristics in the main analysis, along with 

their sample means and standard deviations, are listed in Appendix Table G.1 (see also 

Table II.7).
Effectiveness of TFA and Teaching Fellows Teachers 

102 

We estimated the association between each teacher characteristic and student math 

achievement both without and with controls for the other teacher characteristics in the analysis. 

While findings that were consistent across these two estimation methods were considered to be 

more reliable, we used findings from models that controlled for other teacher characteristics to 

assess and interpret the magnitudes of the estimated relationships. From the estimation models, 

each regression coefficient on a teacher characteristic can be interpreted as the difference in 

student math achievement that would be predicted from a specified difference in that 

characteristic between two teachers. Table IX.1 shows these regression coefficients, expressed as 

predicted differences in achievement between the students of two illustrative teachers; complete 

results from these models are provided in Appendix Tables G.2 and G.3. 

We found that two types of factors were consistently associated with teacher effectiveness, 

with suggestive evidence for a third factor (Table IX.1):

1. Teacher effectiveness increased with teacher experience. Students assigned to a 

second-year teacher were predicted to score 0.08 standard deviations higher on math 

assessments than students assigned to a first-year teacher. Among teachers with at 

least five years of teaching experience, each additional year of teaching experience 

was associated with an increase of 0.005 standard deviations in student achievement. 

2. Teacher effectiveness declined with increasing amounts of teacher coursework 

during the school year. For each additional 10 hours of coursework that teachers 

took during the school year, the math achievement of their students was predicted to 

drop by 0.002 standard deviations. These findings imply that a teacher who took an 

average amount of coursework during the school year, whether for initial 

certification or any other certification or degree, decreased student math achievement 

by 0.04 standard deviations relative to a teacher who took no coursework while 

teaching.

3. Some evidence suggests that greater math content knowledge was positively 

associated with teacher effectiveness in high schools, but not in middle schools. In

high schools, we found that teachers’ math content knowledge, as measured by their 

scores on the Praxis II math assessments, was positively associated with student 

achievement in some, but not all, analyses. Our main analysis indicates that a one 

standard deviation increase in a high school teacher’s Praxis II score—equivalent to 

rising from the 50th to the 84th percentile of Praxis II scores—was associated with an 

increase in student math achievement of 0.04 standard deviations (p-value = 0.051). 

In middle schools, we found no association between teachers’ scores on the Praxis II 

and student achievement.

No other characteristics in the analysis predicted teacher effectiveness to a statistically 

significant degree.

We discuss next, in greater detail, the specific characteristics that were and were not 

predictive of teacher effectiveness.

1. General Academic Ability

We measured teachers’ general academic ability based on the selectivity of the college or 

university from which they received their bachelor’s degree. There was no statistically 
Effectiveness of TFA and Teaching Fellows Teachers 

103 

significant difference in effectiveness between teachers from selective colleges or universities 

and those from all other educational institutions (Table IX.1). Likewise, in sensitivity analyses, 

we found that teachers from highly selective colleges or universities did not differ in 

effectiveness from teachers whose colleges or universities had lower levels of selectivity 

(Appendix Table G.5). 

Table IX.1. Differences in Student Math Achievement Associated with Differences in Teacher Characteristics

Difference in Teacher Characteristic

Without Controlling for Other 

Teacher Characteristics

Controlling for Other Teacher 

Characteristics

Predicted Difference 

in Student Math 

Achievement 

(student z-score 

units) P-value

Predicted Difference 

in Student Math 

Achievement 

(student z-score 

units) P-value

Teacher Who Graduated from Selective College or 

University, Compared with Teacher Who 

Graduated from Other Institutiona 0.017 0.543 0.003 0.913

Teacher Who Took More than the Median Number 

of College-Level Math Courses, Compared with 

Teacher Who Did Notb -0.022 0.381 -0.027 0.281

Teacher Who Used College-Level Math in a 

Nonteaching Job, Compared with Teacher Who 

Did Not -0.045 0.134 -0.038 0.190

Teacher Whose Score on the Specified Praxis II 

Test Was Higher by One z-Score Unit Than the 

Score of Another Teacher

Praxis II Test in Math Content Knowledge 0.017 0.293 0.035 0.051

Praxis II Test in Middle School Math 0.002 0.907 -0.001 0.955

Teacher Who Had More than the Median Number 

of Hours of Math Pedagogy Instruction During 

Training, Compared with Teacher Who Did Notc -0.011 0.668 -0.014 0.592

Teacher Who Had More than the Median Number of 

Days of Student Teaching in Math During Training, 

Compared with Teacher Who Did Notd -0.001 0.977 -0.003 0.895

Teacher Who Took 10 More Total Hours of 

Coursework During the School Year than Another 

Teacher -0.002* 0.028 -0.002* 0.041

Teacher Who Had One More Year of Teaching 

Experience Compared with a Teacher in the: 

First Year of Teaching 0.069* 0.038 0.080* 0.016

Second to Fourth Years of Teaching 0.000 0.991 -0.004 0.755

Fifth Year of Teaching or Beyond 0.004* 0.040 0.005* 0.017

Sources: District administrative records, study-administered Northwest Evaluation Association (NWEA) 

assessments, and Survey of Secondary Math Teachers.

Note: The table shows coefficients on teacher characteristics and corresponding p-values from regression 

models in which student end-of-year math scores are the dependent variable and the set of 

independent variables consists of an indicator for TFA teachers, an indicator for Teaching Fellows, one 

or more teacher characteristics, classroom match fixed effects, and all covariates in Appendix 

Table B.1. Coefficients in the first column of results come from separate models, each of which includes 

only a single teacher characteristic (or a group of variables representing a single teacher characteristic). 

Coefficients in the third column of results come from a single model that includes all displayed teacher 

characteristics simultaneously. Complete model results, including p-values, are in Appendix Tables G.2 

and G.3.
Effectiveness of TFA and Teaching Fellows Teachers 

104 

Table IX.1. (continued)

a

Selective colleges are those ranked by Barron’s as being very competitive, highly competitive, or most competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

2. Exposure to and Knowledge of Math 

We did not find strong support for the notion that teachers’ familiarity with math—as 

reflected in the amount of math coursework completed, experience in a math-related nonteaching 

job, or scores on math knowledge assessments—was related to their effectiveness at teaching 

math. Across a variety of measures of teachers’ exposure to and knowledge of math, no measure 

predicted teacher effectiveness in a manner that consistently reached statistical significance in 

multiple estimation approaches.

We found no statistically significant relationships between teacher effectiveness and the 

amount of college-level math coursework completed. Teachers who had completed more than 

the median number of math courses—7.5 courses—were statistically indistinguishable in their 

effectiveness from teachers who had completed less than the median number of courses 

(Table IX.1). Findings were similar when we measured exposure to math coursework on the 

basis of teachers’ completion of minors, majors, or advanced degrees in math-related subjects 

(Appendix Table G.6). 

The use of math in a nonteaching job is another type of experience through which an 

individual can acquire greater familiarity with math and its applications. However, among 

teachers in the study, this type of experience was not associated with effectiveness in the 

classroom; there was no statistically significant difference in effectiveness between teachers who 

had used college-level math in a prior nonteaching job and those who had not (Table IX.1). 

The most direct measure of the study teachers’ knowledge of math was their score from the 

Praxis II assessment in either Middle School Mathematics (taken primarily by middle school 

teachers in the study) or Mathematics Content Knowledge (taken primarily by high school 

teachers in the study). At the middle school level, we found no relationship between teachers’ 

Praxis scores and their effectiveness. At the high school level, we found suggestive evidence that 

students’ achievement was higher when their teachers performed better on the Mathematics 

Content Knowledge assessment. Our main analysis indicates that a one standard deviation 

increase in a high school teacher’s Praxis II score—equivalent to rising from the 50th to the 84th 

percentile of Praxis II scores—was associated with an increase in student math achievement of 

0.04 standard deviations (Table IX.1; p-value = 0.051 in a model controlling for other teacher 

characteristics). Across a variety of sensitivity analyses (see Appendix G), the relationship 

between Praxis scores and high school teachers’ effectiveness was statistically significant in 

some, but not all, analyses. In particular, high school teachers with Praxis II scores in the top half 

of the score distribution were more effective than those with scores in the bottom half by a 

statistically significant margin (Appendix Table G.7). Taken together, these findings suggest the 

possibility that high school math teachers with higher Praxis scores were more effective, but the 

findings are sensitive to the way in which the analysis is specified. 
Effectiveness of TFA and Teaching Fellows Teachers 

105 

3. Instructional Training and Experience

Both the formal training that teachers receive and the experience they acquire on the job 

have the potential to shape their instructional skills. We found no evidence that the measured 

features of formal training were associated with greater teacher effectiveness; one feature of 

training—coursework during the school year—predicted lower teacher effectiveness. In contrast, 

various measures of on-the-job teaching experience were positively associated with teacher 

effectiveness.

Two specific elements of formal training—instruction in math pedagogy and student 

teaching in math—had no statistically significant relationship with teacher effectiveness 

(Table IX.1). These results should be interpreted cautiously, as teachers for whom more time 

had elapsed since their training might have had more difficulty in recollecting the amount of 

training they received. 

Enrollment in coursework—not necessarily limited to math pedagogy—is a broad form of 

training in which teachers might participate for a variety of reasons, such as to obtain full 

certification, maintain current certification, or obtain an advanced degree. We found that teachers 

who took more coursework during the school year were less effective by a statistically 

significant margin. The estimated relationship implied that, for each additional 10 hours of 

coursework that teachers took during the school year, the math achievement of their students was 

predicted to drop by 0.002 standard deviations (Table IX.1). Therefore, a teacher who took the 

average amount of coursework among teachers who took any coursework at all during the school 

year—about 219 hours—was predicted to lower student math achievement by 0.04 standard 

deviations relative to a teacher who took no concurrent coursework. The direction of this 

estimated relationship is consistent with prior correlational evidence for a negative association 

between coursework taken during the school year and teacher effectiveness (Constantine et al. 

2009). 

Beyond formal training, on-the-job teaching experience represents a different means of 

developing instructional skills: learning by doing. We found evidence that additional teaching 

experience predicted greater effectiveness among two groups of teachers: (1) those who had just 

started their teaching career, and (2) those who had already accumulated five or more years of 

teaching experience. First, we considered teachers in their first year of teaching and assessed the 

extent to which teachers with an additional year of experience—second-year teachers—were 

predicted to have greater effectiveness. Controlling for other teacher characteristics, students 

assigned to a second-year teacher were predicted to score 0.08 standard deviations higher on 

math assessments than students assigned to a first-year teacher (Table IX.1). Second, among 

teachers in their second, third, or fourth year of teaching, an additional year of experience was 

associated with neither greater nor lower effectiveness. In other words, a teacher with four years 

of experience was predicted to be no more or less effective than a teacher with three years of 

experience. Third, among teachers with at least five years of teaching experience, those with 

more experience were more effective after controlling for other teacher characteristics; each 

additional year of teaching experience was associated with an increase of 0.005 standard 

deviations in student achievement. 

To interpret properly the estimated relationships between teacher experience and 

effectiveness, it is important to recognize that these estimates are based on differences in 

effectiveness across different teachers—not the evolution of effectiveness for the same teachers 
Effectiveness of TFA and Teaching Fellows Teachers 

106 

over time. Comparisons of effectiveness between more- and less-experienced teachers capture 

both the true effects of experience and unobserved differences between the broader group of 

people who enter teaching and the self-selected group that remains in teaching.

Nevertheless, our estimates accord with the general pattern of experience effects found by 

prior studies that have used longitudinal data on teachers and students. In particular, our findings 

are consistent with previous evidence that the largest gain in effectiveness from experience 

occurs between the first and second years of teaching (Hanushek et al. 2005; Boyd et al. 2006; 

Kane et al. 2008). Beyond the second year of teaching, gains in effectiveness from additional 

experience have not been consistently found by previous research. Compared with their own 

effectiveness in their second year of teaching, teachers in their fifth year or beyond of teaching 

were no different in effectiveness based on data from an anonymous Texas district (Hanushek et 

al. 2005) but were more effective based on data from New York City (Kane et al. 2008). Our 

findings on gains in effectiveness from additional experience beyond the second year of 

teaching—which showed gains at some experience levels but not at others—share the 

inconsistency present in previous research. 

B. Accounting for the Impact of TFA Teachers

Given that some teacher characteristics were associated with effectiveness, differences in 

effectiveness between TFA and comparison teachers could potentially be accounted for—that is, 

predicted—by differences in those characteristics. In our experimental analysis, we found that 

TFA teachers in the study were, on average, more effective than comparison teachers 

(Chapter V). Using our estimates for the relationship between teacher characteristics and 

effectiveness, this section examines the extent to which differences in characteristics between 

TFA and comparison teachers can account for their difference in effectiveness. Given that this 

analysis relies on the nonexperimental estimates from Section A, it can produce suggestive, but 

not conclusive, evidence for the reasons TFA teachers were more effective than comparison 

teachers. Because we found no average difference in effectiveness between Teaching Fellows 

and comparison teachers (Chapter VIII), we did not conduct a similar analysis for these teacher 

groups. 

As discussed in Chapter II, two factors were necessary for a characteristic to account for part 

of the difference in effectiveness between TFA and comparison teachers: (1) the characteristic 

was associated with teacher effectiveness, and (2) TFA and comparison teachers differed on this 

characteristic. Based on the magnitude and direction of these two factors, we calculated a 

predicted difference in effectiveness between TFA and comparison teachers and compared it to 

the groups’ actual difference in effectiveness from Chapter V.

For each characteristic in the analysis, Table IX.2 shows the difference in effectiveness 

between TFA and comparison teachers, in student z-score units, that would have been predicted 

based only on that characteristic; Appendix Table G.4 contains detailed findings. Although we 

show results for all characteristics, we primarily considered the characteristics that had a 

statistically significant association with effectiveness from the findings in Section A of this 

chapter. 

Our central finding is that the observed characteristics, when considered collectively, did not 

account for any positive portion of the difference in effectiveness between TFA and comparison 

teachers. On the basis of these characteristics, TFA teachers would have been predicted to be less 
Effectiveness of TFA and Teaching Fellows Teachers 

107 

effective than comparison teachers, suggesting that these characteristics could not account for 

why TFA teachers were, in fact, more effective than their counterparts. We discuss these

findings in greater detail next.

Table IX.2. Predicted Differences in Effectiveness Between TFA Teachers and Comparison Teachers 

Based on Observed Teacher Characteristics

Teacher Characteristic

Predicted Difference in Effectiveness 

Between TFA Teachers and 

Comparison Teachers Based on the 

Specified Characteristic 

(student z-score units)

Graduated from Selective College or Universitya 0.001

Number of College-Level Math Courses Taken Is Above Medianb 0.006

Used College-Level Math in a Nonteaching Job 0.011

Score on Praxis II Test in Math Content Knowledge 0.012

Score on Praxis II Test in Middle School Math -0.001

Number of Hours of Math Pedagogy Instruction During Training Is Above 

Medianc 0.000

Number of Days of Student Teaching in Math During Training Is Above 

Mediand 0.000

Hours of Coursework During the Study Year (divided by 10) -0.005

Has More than One Year of Teaching Experience -0.026

Number of Additional Years of Teaching Experience Beyond Two Total 

Years (until teacher has five total years of experience) 0.010

Number of Additional Years of Teaching Experience Beyond Five Total 

Years -0.036

Total Predicted Difference in Effectiveness Between TFA Teachers 

and Comparison Teachers Based on All Measured Characteristics -0.028

Total Observed Difference in Effectiveness Between TFA Teachers 

and Comparison Teachers 0.075

Sources: District administrative records, study-administered Northwest Evaluation Association (NWEA) 

assessments, and Survey of Secondary Math Teachers. 

Note: For a given characteristic, the entry in the final column is equal to the product of two estimates: (1) the 

estimated association between the characteristic and student math achievement after controlling for 

other teacher characteristics and (2) the average difference in the characteristic between TFA teachers 

and comparison teachers. Complete results are in Appendix Table G.4.

a

Selective colleges are those ranked by Barron’s as being very competitive, highly competitive, or most competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching.

TFA = Teach For America. 

1. Predictions Based on Each Individual Characteristic

First, we considered whether each characteristic separately could have predicted that TFA 

teachers would be more effective than comparison teachers. A characteristic could account for 

part of the positive impact of TFA teachers relative to comparison teachers only under one of 

two scenarios:
Effectiveness of TFA and Teaching Fellows Teachers 

108 

1. If the characteristic had a positive association with teacher effectiveness based on the 

analyses in Section A, then TFA teachers needed to show more of the characteristic 

than comparison teachers. 

2. If the characteristic had a negative association with teacher effectiveness based on 

the analyses in Section A, then TFA teachers needed to show less of the 

characteristic than comparison teachers.

The analyses in Section A identified three characteristics for which there was either tentative 

or consistent evidence of an association with teacher effectiveness: (1) teachers’ scores on the 

Praxis II Mathematics Content Knowledge assessment, (2) amount of coursework taken during 

the school year, and (3) teaching experience. For each of the three characteristics, we examined 

how TFA and comparison teachers differed on the characteristic to calculate a predicted 

difference in effectiveness based on that characteristic alone.

Math content knowledge. Scores on the Praxis II Mathematics Content Knowledge 

assessment accounted for a positive portion of the difference in effectiveness between TFA and 

comparison teachers. This is because (1) these Praxis scores were positively associated with 

teacher effectiveness (Table IX.1) and (2) TFA teachers had higher Praxis scores than 

comparison teachers (see Chapter IV). Based on this characteristic alone, students of TFA 

teachers would be predicted to outscore students of comparison teachers by 0.012 standard 

deviations (Table IX.2). In comparison, the actual, experimentally estimated difference in 

student math achievement between these groups was 0.075 standard deviations. Therefore, our 

estimates suggest that the difference in Praxis performance between TFA and comparison 

teachers accounted for 16 percent of their actual difference in effectiveness.

Coursework during the school year. Patterns of coursework during the school year did not 

predict a positive impact of TFA teachers relative to comparison teachers (Table IX.2). Although 

findings from Table IX.1 indicate that coursework during the school year was associated with 

lower effectiveness, TFA teachers took more coursework during the school year. Based on these 

patterns, TFA teachers would have been predicted to be less effective than comparison teachers, 

when in fact they were more effective.

Teaching experience. On the basis of teaching experience alone, TFA teachers would have 

been predicted to be less effective than comparison teachers because (1) experience was 

positively associated with effectiveness and (2) TFA teachers had relatively less experience.

Earlier, our findings had indicated that teachers who acquired a second year of teaching 

experience were more effective than those who had not yet done so (Table IX.1). TFA teachers 

in our study were less likely than comparison teachers to have acquired a second year of teaching 

experience. This gap implied that TFA teachers would be predicted to lower student math 

achievement by 0.026 standard deviations relative to comparison teachers (Table IX.2). 

Likewise, TFA teachers had, on average, fewer additional years of teaching experience beyond 

the fifth year, implying a further predicted drop of 0.036 standard deviations in their students’ 

math achievement relative to the students of comparison teachers (Table IX.2). In short, patterns 

of teaching experience predicted a negative impact of TFA teachers relative to comparison 

teachers—the opposite of what actually occurred. 
Effectiveness of TFA and Teaching Fellows Teachers 

109 

2. Predictions Based on All Observed Characteristics

Overall, the observed characteristics could not account for why TFA teachers were actually 

more effective than comparison teachers. TFA teachers’ lower experience levels suggested that 

they would be less effective than comparison teachers to an extent that would more than offset 

the other observed characteristics, such as Praxis scores, on which they had an advantage. On 

net, based on all teacher characteristics in the analysis, students of TFA teachers would have 

been predicted to score 0.028 standard deviations lower than students of comparison teachers. In 

fact, students of TFA teachers actually scored 0.075 standard deviations higher than students of 

comparison teachers.

A potential reason why the characteristics in the analysis did not predict TFA teachers’ 

impact relative to comparison teachers is that the attributes enabling TFA teachers to be more 

effective might have been different than the ones we measured in the study. For instance, it is 

possible that TFA’s intensive method of screening and evaluating applicants effectively 

identifies attributes that predict teachers’ effectiveness in the classroom but that are difficult for 

outside researchers to measure. However, given the wide variation in effectiveness among 

teachers from the same certification route, there are likely to be other teacher characteristics—

beyond those considered during the selection of applicants into each route—that are also 

associated with effectiveness in the classroom and that we did not observe in our study. 
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

111 

REFERENCES

Aaronson, Daniel, Lisa Barrow, and William Sander. “Teachers and Student Achievement in the 

Chicago Public High Schools.” Journal of Labor Economics, vol. 25, no. 1, 2007, pp. 95-

135. 

Angrist, Joshua D., and Jorn-Steffen Pischke. Mostly Harmless Econometrics: An Empiricist’s 

Companion. Princeton, NJ: Princeton University Press, 2009. 

Angrist, Joshua D., Guido W. Imbens, and Donald B. Rubin. “Identification of Causal Effects 

Using Instrumental Variables.” Journal of the American Statistical Association, vol. 91, 

no. 434, 1996, pp. 444–455. 

Barron’s Profiles of American Colleges 2003. 25th ed. New York: Barron’s Educational Series, 

2002. 

Benjamini, Yoav, and Yosef Hochberg. “Controlling for the False Discovery Rate: A Practical 

and Powerful Approach to Multiple Hypothesis Testing.” Journal of the Royal Statistical 

Society. Series B (Methodological), vol. 57, no. 1, 1995, pp. 289–300. 

Bloom, Howard S., Lashawn Richburg-Hayes, and Alison Rebeck Black. “Using Covariates to 

Improve Precision for Studies that Randomize Schools to Evaluate Educational 

Interventions.” Educational Evaluation and Policy Analysis, vol. 29, no. 1, March 2007, 

pp. 30–59. 

Boyd, Donald, Pamela Grossman, Hamilton Lankford, Susanna Loeb, and James Wyckoff. 

“How Changes in Entry Requirements Alter the Teacher Workforce and Affect Student 

Achievement.” Education Finance and Policy, vol. 1, no. 2, 2006, pp. 176–216. 

Carroll, Stephen, Robert Reichardt, and Cassandra Guarino. “The Distribution of Teachers 

Among California’s Districts and Schools.” Santa Monica, CA: RAND, October 2000. 

Chetty, Raj, John N. Friedman, and Jonah E. Rockoff. “The Long-Term Impacts of Teachers: 

Teacher Value-Added and Student Outcomes in Adulthood.” NBER Working Paper 

No. 17699. Cambridge, MA: National Bureau of Economic Research, December 2011. 

Clark, Melissa A., Eric Isenberg, and Marykate Zukiewicz. “The Evaluation of the Teach For 

America Investing in Innovation (i3) Scale–Up: Design Report.” Princeton, NJ: 

Mathematica Policy Research, 2012.

Clark, Melissa A., Daniel W. Player, Alison Wellington, and Sheena McConnell. “An Evaluation 

of Secondary Math Teachers from Two Highly Selective Alternative Routes to Certification: 

Design Report.” Princeton, NJ: Mathematica Policy Research, December 22, 2009.

Clark, Melissa, Sheena McConnell, Kristin Hallgren, Daniel Player, and Alison Wellington. 

“Evaluating Highly Selective Programs That Provide Alternative Routes to Teacher 

Certification: Feasibility and Design Issues.” Princeton, NJ: Mathematica Policy Research, 

March 28, 2008. 
Effectiveness of TFA and Teaching Fellows Teachers 

112 

Clotfelter, Charles, Helen F. Ladd, Jacob Vigdor, and Justin Wheeler. “High-Poverty Schools 

and the Distribution of Teachers and Principals.” North Carolina Law Review, vol. 85, 2007, 

pp. 1345-79. 

Constantine, Jill, Daniel Player, Tim Silva, Kristin Hallgren, Mary Grider, and John Deke. “An 

Evaluation of Teachers Trained Through Different Routes to Certification. Final Report.” 

Princeton, NJ: Mathematica Policy Research, 2009. 

Darling-Hammond, Linda. “Teaching and Knowledge: Policy Issues Posed by Alternate 

Certification for Teachers.” Peabody Journal of Education, vol. 67, no. 3, Spring 1990, 

pp. 123-154. 

Darling-Hammond, Linda. “How Teacher Education Matters.” Journal of Teacher Education, 

vol. 51, no. 3, May/June 2000, pp. 166-73. 

Darling-Hammond, Linda, Deborah J. Holtzman, Su Jin Gatlin, and Julian Vasquez Heilig. 

“Does Teacher Preparation Matter? Evidence About Teacher Certification, Teach For 

America, and Teacher Effectiveness.” Education Policy Analysis Archives, vol. 13, no. 42, 

October 2005, pp. 1068–2341. 

Decker, Paul T., Daniel P. Mayer, and Steven Glazerman. “The Effect of Teach For America on 

Students: Findings from a National Evaluation.” Princeton, NJ: Mathematica Policy 

Research, 2004. 

Donald, Stephen G., and Kevin Lang. “Inference with Difference-in-Differences and Other Panel 

Data.” Review of Economics and Statistics, vol. 89, 2007, pp. 221–233. 

Donaldson, Morgaen L., and Susan Moore Johnson. “Teach For America Teachers: How Long 

Do They Teach? Why Do They Leave?” Phi Delta Kappan, vol. 93, no. 2, 2011, pp. 47–51. 

Editorial Projects in Education. “Education Counts.” Available at http://www.edweek.org/rc/

2007/06/07/edcounts.html. Accessed July 18, 2012. 

Feistritzer, C.E. “State Policy Trends for Alternative Routes to Teacher Certification: A Moving 

Target.” Presented at the Conference on Alternative Certification: A Forum for Highlighting 

Rigorous Research, hosted by Learning Point Associates and supported by the Institute of 

Education Sciences, Washington, DC, 2005. 

Gaskill, Peggy E. “Progress in the Certification of Middle Level Personnel.” Middle School 

Journal, vol. 33, no. 5, 2002, pp. 33–40. 

Gitomer, Drew H., and Yi Qi. “Recent Trends in Mean Scores and Characteristics of TestTakers on Praxis II Licensure Tests.” Washington, DC: U.S. Department of Education, 

Office of Planning, Evaluation, and Policy Development, Policy and Program Studies 

Service, April 2010. 

Glazerman, Steven, and Jeffrey Max. “Do Low-Income Students Have Equal Access to the 

Highest-Performing Teachers?” NCEE Evaluation Brief. Washington, DC: U.S. Department 

of Education, Institute of Education Sciences, National Center for Education Evaluation and

Regional Assistance. Document No. PP11-23a, 2011. 
Effectiveness of TFA and Teaching Fellows Teachers 

113 

Hanushek, Eric A., and Steven Rivkin. “Teacher Quality.” In Handbook of the Economics of 

Education, edited by Eric A. Hanushek and Finis Welch. Vol. 2. Amsterdam: NorthHolland, 2006. 

Hanushek, Eric A., John F. Kain, Daniel M. O’Brien, and Steven Rivkin. “The Market for 

Teacher Quality.” NBER Working Paper 11154. Cambridge, MA: National Bureau of 

Economic Research, February 2005. 

Heilig, Julian Vasquez, and Su Jin Jez. “Teach For America: A Review of the Evidence.” East 

Lansing, MI: The Great Lakes Center for Education Research and Practice, June 2010. 

Hill, Carolyn J., Howard S. Bloom, Alison Rebeck Black, and Mark W. Lipsey. “Empirical 

Benchmarks for Interpreting Effect Sizes in Research.” Child Development Perspectives, 

vol. 2, no. 3, 2008, pp. 172–177. 

Hill, Heather C., Brian Rowan, and Deborah Loewenberg Ball. “Effects of Teachers’ 

Mathematical Knowledge for Teaching on Student Achievement.” American Educational 

Research Journal, vol. 42, no. 2, Summer 2005, pp. 371-406. 

Ingersoll, Richard M., and David Perda. “The Mathematics and Science Teacher Shortage: Fact 

and Myth.” CPRE Research Report #RR-62. Philadelphia, PA: University of Pennsylvania, 

Consortium for Policy Research in Education, 2009. 

Ingersoll, Richard M., and Henry May. “The Magnitude, Destinations, and Determinants of 

Mathematics and Science Teacher Turnover.” Educational Evaluation and Policy Analysis, 

forthcoming, 2012. 

Jacob, Brian A. “The Challenges of Staffing Urban Schools with Effective Teachers.” The 

Future of Children, vol. 17, no. 1, 2007, pp. 129–153. 

Kane, Thomas, Jonah E. Rockoff, and Douglas Staiger. “What Does Certification Tell Us About 

Teacher Effectiveness? Evidence from New York City.” Economics of Education Review, 

vol. 27, 2008, pp. 615–631. 

Lankford, Hamilton, Susanna Loeb, and James Wyckoff. “Teacher Sorting and the Plight of 

Urban Schools: A Descriptive Analysis.” Educational Evaluation and Policy Analysis, 

vol. 24, no. 1, 2002, pp. 37-62. 

Liang, Kung-Yee, and Scott L. Zeger. “Longitudinal Data Analysis Using Generalized Linear 

Models.” Biometrika, vol. 73, pp. 13–22. 

Mayer, Daniel P., Paul T. Decker, Steven Glazerman, and Timothy W. Silva. “Identifying 

Alternative Certification Programs for an Impact Evaluation of Teacher Preparation.” 

Cambridge, MA: Mathematica Policy Research, April 2003. 

Monk, David H. “Recruiting and Retaining High-Quality Teachers in Rural Areas.” The Future 

of Children, vol. 17, no. 1, 2007, pp. 155–174. 
Effectiveness of TFA and Teaching Fellows Teachers 

114 

National Center for Education Statistics. “Statistical Standards.” U.S. Department of Education, 

Office of Educational Research and Improvement, National Center for Education Statistics. 

Washington DC: U.S. Government Printing Office, 2000. Available at 

[http://nces.ed.gov/statprog/2002/std4_2.asp]. Accessed July 9, 2013. 

Provasnik, Stephen, Patrick Gonzales, and David Miller. U.S. Performance Across International 

Assessments of Student Achievement: Special Supplement to The Condition of Education 

2009. Washington, DC: U.S. Department of Education, National Center for Education 

Statistics, Institute of Education Sciences, 2009. 

Puma, Michael J., Robert B. Olsen, Stephen H. Bell, and Cristofer Price. “What to Do When 

Data Are Missing in Group Randomized Controlled Trials.” Washington, DC: U.S. 

Department of Education, Institute of Education Sciences, National Center for Education 

Evaluation and Regional Assistance, October 2009. 

Rivkin, Steven G., Eric A. Hanushek, and John F. Kain. “Teachers, Schools, and Academic 

Achievement.” Econometrica, vol. 73, no. 2, March 2005, pp. 417–458. 

Rockoff, Jonah. “The Impact of Individual Teachers on Student Achievement: Evidence from 

Panel Data.” American Economic Review: AEA Papers and Proceedings, vol. 94, no. 2, 

2004, pp. 247-252. 

Royston, Patrick. “Multiple Imputation of Missing Values: Update of ice.” Stata Journal, vol. 5, 

2005, pp. 527–536. 

Royston, Patrick. “Multiple Imputation of Missing Values.” Stata Journal, vol. 4, 2004, pp. 227–

241. 

Rubin, Donald B. Multiple Imputation for Nonresponse in Surveys. New York: Wiley, 1987. 

Samejima, Fumiko. “A Use of the Information Function in Tailored Testing.” Applied 

Psychological Measurement, vol. 1, no. 3, 1977, pp. 233–247. 

Samejima, Fumiko. “Estimation of Reliability Coefficients Using the Test Information Function 

and its Modifications.” Applied Psychological Measurement, vol. 18, no. 3, 1994, pp. 229-

244. 

Sass, Tim, Jane Hannaway, Zeyu Xu, David Figlio, and Li Feng. “Value Added of Teachers in 

High-Poverty Schools and Lower-Poverty Schools.” CALDER Working Paper no. 52, 

National Center for Analysis of Longitudinal Data in Education Research. Washington, DC: 

Urban Institute, 2010. 

Schafer, Joseph L., and John W. Graham. “Missing Data: Our View of the State of the Art.” 

Psychological Methods, vol. 7, no. 2, 2002, pp. 147–177. 

U.S. Department of Education, Office of Elementary and Secondary Education. Highly Qualified 

Teachers / Improving Teacher Quality State Grants: ESEA, Title II, Part A: Non-Regulatory 

Guidance. August 3, 2005. 
Effectiveness of TFA and Teaching Fellows Teachers 

115 

U.S. Department of Education, Office of Postsecondary Education. Preparing and Credentialing 

the Nation’s Teachers: The Secretary’s Eighth Report on Teacher Quality Based on Data 

Provided for 2008, 2009, and 2010. Washington, DC, 2011. 

U.S. Department of Education, Office of Postsecondary Education, Office of Policy Planning 

and Innovation. Meeting the Highly Qualified Teachers Challenge: The Secretary’s Annual 

Report on Teacher Quality. Washington, DC, 2002. 

van Buuren, S., H.C. Boshuizen, and D.L. Knook. “Multiple Imputation of Missing Blood 

Pressure Covariates in Survival Analysis. Statistics in Medicine, vol. 18, 1999, pp. 681–694. 

Walsh, Kate, and Sandi Jacobs. “Alternative Certification Isn’t Alternative.” Washington, DC: 

Thomas B. Fordham Institute, September 2007. 

Xu, Zeyu, Jane Hannaway, and Colin Taylor. “Making a Difference? The Effects of Teach For 

America in High School.” Washington, DC: Urban Institute, March 2008. 
This page has been left blank for double–sided copying.
APPENDIX A

SUPPLEMENTARY TECHNICAL INFORMATION 

ON STUDY DESIGN AND DATA COLLECTION
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

A.3 

In Appendix A, we provide additional information on the study’s experimental design, 

random assignment, district and school recruiting, and data collection and response rates, as a 

supplement to the information presented in Chapter II. 

A. Experimental Design

As discussed in Chapter II, the study’s experimental design relied on the random assignment 

of students within schools to a math class taught by a Teach For America (TFA) or Teaching 

Fellows teacher or to a comparable class taught by a comparison teacher. The classes between 

which students were randomly assigned are referred to as a classroom match. For classes to

match and be eligible for the study, the classes must have covered an eligible math course and 

been fully comparable, random assignment must not have interfered with the school’s scheduling 

process, and any supplemental math instruction must not have interfered with the study design, 

as discussed further below. 

1. Eligible Math Courses

All middle school math courses were eligible, as were general high school math (such as 

pre-algebra or remedial math), Algebra I, Geometry, and Algebra II. The study did not include 

more advanced courses, such as trigonometry or calculus, because appropriate assessments for 

these subjects were not available.

2. Comparability of Classes

To be eligible for inclusion in a classroom match, classes must have been taught at the same 

level (for instance, honors or regular). In addition, they must have been taught under similar 

circumstances, including similar class sizes, same roles for teacher’s aides, and same 

arrangements for inclusion of English language learners and special education students. These 

restrictions helped to ensure that any differences in student achievement between classes in a 

match could be attributed to the effectiveness of the teachers rather than to other differences 

between the classes.

3. No Interference with Scheduling

Secondary school scheduling is a complex process, typically beginning in the middle of the 

preceding school year and encompassing multiple iterations to determine the number and 

schedule of courses to be offered, as well as the schedules of individual students. To avoid 

disrupting the school’s normal scheduling process, we allowed matches only if either (1) all 

classrooms in the match were taught during the same period of the school day or (2) students 

were assigned to groups with which they took all their classes (sometimes called teams, families, 

academies, pathways, or schools within schools) and the TFA/Teaching Fellows and comparison 

teachers in the match taught in separate groups. In the latter case, after we randomly assigned 

students to groups (and by association, teachers), we allowed schools to determine which period 

during the school day each student attended math class. The overwhelming majority (95 percent) 

of students in the study were assigned to concurrent classes, and the remaining 5 percent were 

assigned to teams.
Effectiveness of TFA and Teaching Fellows Teachers 

A.4 

4. Supplemental Math Did Not Interfere with Study Design

In many schools, students attended supplemental math classes aimed at reinforcing the 

instruction given in the main math classes that constituted the study sample. In 10 percent of 

classroom matches in the study, all students enrolled in the study classes were also required to 

take supplemental math classes; in another 23 percent of matches, specific subsets of students—

usually those with low achievement in the prior year—were assigned to supplemental math 

instruction (Table A.1).

Table A.1. Percentage of Classroom Matches in Which Students Receive Supplemental Math

Percentage of 

Matches

No Students Receive Supplemental Math 53

Some Students Receive Some Supplemental Math 23

Regular and supplemental math teacher are of the same type 3

Regular and supplemental math teacher are not necessarily of the same type 21

All Students Receive Supplemental Math 10

Regular and supplemental math teacher are of the same type 2

Regular and supplemental math teacher are not necessarily of the same type 8

No Information on Supplemental Math Available 14

Total Number of Classroom Matches 228

Note: Teacher types are Teach For America teachers, Teaching Fellows, and comparison teachers.

Supplemental math instruction had the potential to either reinforce or dilute the contrast 

between matched classes in the types of teachers to whom students were exposed. The contrast 

was reinforced within matches in which students received all supplemental math instruction from 

the same type of teacher (TFA, Teaching Fellow, or comparison) who taught their regular math 

classes; this arrangement occurred in 5 percent of matches. In the remaining 29 percent of 

matches with students enrolled in supplemental math instruction, the contrast from the matched 

classes was diluted because students’ supplemental instruction was not necessarily delivered by 

the same type of teacher who delivered their regular instruction. Examples of the latter scenario 

included arrangements in which a single math teacher was responsible for all supplemental math 

instruction, as well as arrangements in which schools had assigned students to supplemental 

classes before the study team randomly assigned them to the study classes. Notably, in these 

scenarios, the mix of teachers from whom students received supplemental instruction was still 

equivalent between the matched study classes. Therefore, any differences in achievement 

between matched classes were the result of differences in effectiveness between the teachers of 

those classes.

Before random assignment, we excluded from the study any matches in which arrangements 

for supplemental math instruction would have prevented us from attributing differences in 

achievement between matched classes to differences in the types of teachers responsible for 

those classes. Accordingly, we did not admit matches in which students received all 

supplemental math instruction from the opposite type of teacher as the one responsible for their 

regular classes. We also did not admit matches in which assignment to supplemental classes was 

determined after random assignment (for instance, if lower-performing students were assigned to 
Effectiveness of TFA and Teaching Fellows Teachers 

A.5 

a supplemental class midyear), because assignment to supplemental instruction after random 

assignment could have been correlated with the teacher to whom the students were randomly 

assigned.

B. Recruitment of Districts, Schools, and Classroom Matches

As discussed in Chapter II, we focused recruitment efforts on districts with large 

concentrations of secondary math teachers from TFA or a Teaching Fellows program. Figure A.1 

illustrates the recruitment of districts and schools into the sample.

Within the 15 districts that agreed to participate in the study, we conducted random 

assignment for at least one classroom match in each of 109 schools, with a total of 321 matches.

Eighty-two of these 109 schools (75 percent, comprising 228 classroom matches) properly 

implemented random assignment, maintained viable classroom matches, and cooperated with 

data collection activities—these schools and matches formed the study’s research sample. The 

remaining 27 schools (25 percent) were dropped from the study sample. Twenty-one of these 

schools (comprising 67 matches) were dropped because they failed to implement random 

assignment—the rosters they sent to the study team after random assignment did not correspond 

to the assignments we had given them, and they refused to make the requested changes. An 

additional 6 schools (26 matches) were dropped after random assignment because: (1) students 

needed to be completely reassigned during the school year (for instance, the school had failed to 

inform us that it had to reassign all students to different classes at the end of the first semester); 

(2) a teacher we thought was from TFA or a Teaching Fellows program had actually entered 

through some other route; (3) classrooms were consolidated due to lower than expected 

enrollments; (4) a study teacher left the school for administrative reasons unrelated to 

performance; or (5) the school was unwilling to distribute parental consent forms. 

Recruitment of the study sample occurred prior to each of the two school years in which the 

study was conducted. Table A.2 shows the number of sample members in each year of the study. 

In both the TFA and Teaching Fellows study samples, the vast majority of classroom 

matches consisted of one class taught by a TFA or Teaching Fellows teacher and one class taught 

by a comparison teacher. In the TFA study sample, 103 of the 111 matches (93 percent) 

consisted of one class taught by a TFA teacher and one taught by a comparison teacher

(Table A.3). The remaining matches included additional classes, taught by either TFA or 

comparison teachers, with the largest matches including six classes taught by TFA teachers and 

six taught by comparison teachers. In the Teaching Fellows study sample, 98 of the 118 matches 

(83 percent) consisted of one class taught by a Teaching Fellow and one taught by a comparison 

teacher (Table A.4). The largest matches included four Teaching Fellow classes and two 

comparison classes. 
Effectiveness of TFA and Teaching Fellows Teachers 

A.6 

Figure A.1. District and School Recruiting

Nonparticipating schools

N = 683

Districts unresponsive or 

unwilling to participate

N = 27

Schools in which random 

assignment occurred

N = 109

(# of classroom matches = 321)

Schools contacted

N = 792

Secondary schools identified as 

potentially employing TFA teachers 

or Teaching Fellows

N = 890

Contacted districts

N = 42

Participating districts

N = 15

All districts known to have secondary 

math teachers from TFA or Teaching 

Fellows programs

N = 86

Schools did not implement 

random assignment

N = 21

(# of classroom matches = 67)

Schools dropped after 

random assignment

N = 6

(# of classroom matches = 26)

Schools that implemented 

random assignment

N = 88

(# of classroom matches = 254)

Schools in research sample

N = 82

(# of classroom matches = 228)
Effectiveness of TFA and Teaching Fellows Teachers 

A.7 

Table A.2. Number of Districts, Schools, Classroom Matches, Teachers, and Classes in the Study, by 

School Year

Number of Sample Members

2009–2010 

School Year

2010–2011 

School Year

Both Years 

Combined

Districts 15 12 15

With TFA teachers in the study 10 8 11

With Teaching Fellows in the study 9 6 9

Schools 65 43 82

With TFA teachers in the study 30 25 45

With Teaching Fellows in the study 40 19 44

Classroom Matchesa 140 88 228

TFA teachers versus comparison teachers 60 51 111

Teaching Fellows versus comparison teachers 81 37 118

Teachersa, b 199 122 287

TFA teachers 36 34 66

Teaching Fellows 55 25 69

Comparison teachers 108 63 152

Compared with TFA teachers 42 36 70

Compared with Teaching Fellows 68 27 84

Classes 329 188 517

Taught by TFA teachers 70 53 123

Taught by Teaching Fellows 93 42 135

Taught by comparison teachers 166 93 259

Compared with TFA teachers 72 53 125

Compared with Teaching Fellows 95 40 135

a

Counts of classroom matches with TFA teachers and those with Teaching Fellows sum to more than the total 

number of matches because some matches contained both TFA and Teaching Fellows teachers. Likewise, 

counts of comparison teachers who were compared with TFA teachers and those who were compared with 

Teaching Fellows sum to more than the total number of comparison teachers because some comparison 

teachers were compared with both TFA and Teaching Fellows teachers.

b

Counts of teachers from the 2009–2010 and 2010–2011 school years sum to more than the total number of 

teachers in the study because 34 teachers were in both years of the study. 

TFA = Teach For America.

Table A.3. Structure of Classroom Matches in the TFA Study Sample

Number of TFA and Comparison Classes 

in the Classroom Match Number of Classroom Matches

1 TFA Class, 1 Comparison Class 103

1 TFA Class, 2 Comparison Classes 3 

Other Structuresa 5 

Total Number of Classroom Matches 111

TFA = Teach For America. 

a

Other structures include matches with 2 TFA classes and 1 comparison class; 3 TFA classes and 3 

comparison classes; and 6 TFA classes and 6 comparison classes.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

A.8 

Table A.4. Structure of Classroom Matches in the Teaching Fellows Study Sample

Number of Teaching Fellow and Comparison Classes 

in the Classroom Match Number of Classroom Matches

1 Teaching Fellow Class, 1 Comparison Class 98

1 Teaching Fellow Class, 2 Comparison Classes 9 

2 Teaching Fellow Classes, 1 Comparison Class 3 

2 Teaching Fellow Classes, 3 Comparison Classes 3 

Other Structuresa 5 

Total Number of Classroom Matches 118

a

Other structures include matches with 2 Teaching Fellow classes and 2 comparison classes; 4 Teaching 

Fellow classes and 1 comparison class; and 4 Teaching Fellow classes and 2 comparison classes.

C. Selection and Assignment of Students

All students who enrolled in a study class before the start of the school year or in the first 

month of school were potentially eligible for random assignment and inclusion in the study 

sample. Initial random assignment occurred in the summers (2009 and 2010) preceding the study 

school years, as soon as schools were able to provide student lists for assignment. After this 

initial random assignment, the study team assigned additional students who needed to enroll in a 

study class through a process referred to as rolling random assignment. Ninety-one percent of 

students in the study were assigned via initial random assignment and 9 percent via rolling 

random assignment.25 Next, we describe the two random assignment procedures, the process for 

verifying that random assignments were properly implemented, and the final student sample. 

1. Initial Random Assignment 

Initial random assignment was conducted in the study’s Sample Management System via an 

embedded Visual Basic program. We allowed schools to specify up to three categorical variables 

on which to stratify the assignments—if the school did not request any stratifiers, we stratified on 

gender. We gave schools the opportunity to choose the variables used in stratification, rather than 

imposing specific stratifiers or requiring schools to choose from a pre-specified list, because 

different schools had different priorities for the types of student characteristics that had to be 

balanced between classes. The range of variables on which schools requested stratification 

included gender, race, ethnicity, academic ability, special education status, English language 

learner status, feeder school, grade level, age, behavior classification, and whether the student 

was retained in grade from the previous year. The exact characteristics used to define strata did 

not have any bearing on the randomization process. Regardless of how the strata were defined, 

the randomization process sought to equalize, within each stratum, the number of students 

assigned to the different classes in a classroom match, as described in more detail shortly.

 25 Because assignment probabilities to the treatment and control groups in a given match might have varied for 

students assigned via either procedure, we developed sample weights to adjust for differential assignment 

probabilities in the analysis, as discussed in Appendix B.
Effectiveness of TFA and Teaching Fellows Teachers 

A.9 

We also accommodated a limited number of special requests from the school, including

grouping students together, assigning students to separate classes, and placing students in a 

particular class. Students who had to be grouped together or separated could be and were 

randomly assigned; students who had to be placed in a particular class (or “forced to” that class) 

were exempted from random assignment and excluded from the research sample. Of the 

12,675 students in the study who were randomly assigned, 12 had to be grouped with a peer and 

18 had to be separated from a peer. In addition, 46 students were forced to a particular class and 

exempted from random assignment. 

If there were no exemptions from random assignment within a match, students assigned 

during initial random assignment had equal probabilities of assignment to each class in a match. 

The probability of assignment to a particular group (treatment or control) was thus equal to the 

number of classes in that group divided by the total number of classes in the match. For example, 

in a match with one class taught by a TFA teacher and two classes taught by comparison 

teachers, a given student would have a 1/3 = 0.33 probability of being assigned to the TFA 

teacher (the treatment group) and a 2/3 = 0.67 probability of being assigned to the comparison 

teachers (the control group). 

The only exceptions to the simple scenario described here occurred when a school required 

that a particular student or students be placed with a particular teacher. In these cases, the 

excluded students were placed in the required classes and then the remaining students in each 

stratum were randomly assigned to the remaining slots in the match. Within a given stratum, 

randomly assigned students’ probabilities of assignment to a given group (treatment or control) 

were equal to the number of available slots for that stratum in that group (after the excluded 

students had been placed) divided by the total number of slots for that stratum in the match 

(again after the excluded students had been placed). For example, if a given match had one 

treatment and two control classes and no stratification, with a total of 60 students to be assigned 

to the classes, two of whom had to be placed in the treatment class, the probability of assignment 

to the treatment group for randomly assigned students would have been (20-2)/(60-2) = 0.31, and 

the probability of assignment to the control group would have been (40)/(60-2) = 0.69. 

The probability of assignment to the treatment group in a given match and stratum is 

summarized by the following formula, with the probability of assignment to the control group 

determined in a parallel manner:

(A.1) ( ) ( ,, , ) 1 * * t

s s ts cs ts

s

N pr T n f f f N n

       

= ++ −                

where pr(Ts) is the probability of assignment to the treatment group for a student in stratum s, Nt

is the number of treatment group classes in the match, N in the total number of classes in the 

match, ns is the number of students in the stratum to be randomly assigned in that match, ft,s is 

the number of students in the stratum forced to the treatment group, and fc,s is the number of 

students in the stratum forced to the control group. In the simple case in which no students are 

forced to a particular class, the formula reduces to the number of treatment classes divided by the 

total number of classes in the match.
Effectiveness of TFA and Teaching Fellows Teachers 

A.10 

2. Rolling Random Assignment 

After initial random assignment was conducted, late enrolling students were assigned, 

individually or in small batches, in a process we referred to as rolling random assignment. 

School staff were provided with a toll-free hotline number to call for each new student’s class 

assignment. Study staff entered information on newly enrolling students into an Excel form;

students were then randomly assigned via an embedded Visual Basic program. Assignments 

were not stratified. Rolling random assignment occurred through the first month of classes; after 

that time, schools were free to assign students to classes as they chose. Students who enrolled 

after the first month of school were not included in the study sample. 

Because rolling random assignment typically occurred in the first few weeks of school, at a 

time when there was movement into and out of classes, class sizes were often not perfectly equal. 

To correct for any class size imbalances that existed at the time of rolling random assignment, 

the rolling random assignment program was constructed so that students would have a greater 

probability of being assigned to smaller classes. Our approach was as follows: 

• If the number of students to be assigned was greater than or equal to the number 

needed to equalize class sizes, all classes with fewer than the maximum number of 

students would be given the number of slots required to bring the class size to the 

maximum class size in the match, plus one. The largest class(es) in the match would 

(each) be given one slot. If the number of students to be assigned exceeded this 

number of slots, additional slots would be evenly distributed between all matches 

until there were enough slots for all students. The students would then be randomly 

assigned between these slots. For example, if a match had three classes—Teaching 

Fellows class A with 20 students, control class B with 22 students, and control class 

C with 25 students, and there were 8 students to be assigned, class A would be given 

6 slots, class B would be given 4 slots, and class C would be given one slot. The 

newly enrolling student or students would be randomly assigned between the 

available slots with equal probability of being assigned to a given slot (because there 

were fewer students than slots in this example, not all slots would be filled). Thus, the 

probability of assignment to the Teaching fellows class (class A) would be 6/(6+4+1) 

= 6/11 = 0.55, and the probability of assignment to the control group (class B or C) 

would be 4/11 +1/11 = 5/11= 0.45. 

• If the number of students to be assigned was less than the number needed to equalize 

class sizes, we increased the probability of assignment to the smaller classes. 

Specifically, all classes with fewer than the maximum number of students would be 

given the number of slots required to bring the class size to the maximum class size in 

the match, plus one, and then this number would be multiplied by three (a factor that 

was chosen arbitrarily to increase the probability of assignment to the smaller 

classes). The largest class(es) in the match would (each) be given one slot. Then 

students would be randomly assigned between these slots. For example, if a match 

had three classes—Teaching Fellows class A with 20 students, control class B with 

22 students, and control class C with 25 students, and there were two students to be 

assigned, class A would be given 6*3 = 18 slots, class B would be given 4*3 = 12 

slots, and class C would be given one slot. The newly enrolling student or students 

would be randomly assigned between the available slots with equal probability of 

being assigned to a given slot. Thus, the probability of assignment to the Teaching 
Effectiveness of TFA and Teaching Fellows Teachers 

A.11 

Fellows class (class A) would be 18/(18+12+1) = 18/31 = 0.58, and the probability of 

assignment to the control group (class B or C) would be 12/31 +1/31 = 13/31= 0.42. 

3. Roster Verification

Immediately after random assignment was conducted, schools were asked to send the study 

team updated rosters so we could verify that the assignments were properly implemented. If we 

could not verify assignments or identified students who had been placed with a type of teacher 

opposite to that of their assigned treatment status, we followed up with the school to resolve any 

issues—for instance, to request that particular students be placed in accordance with the random 

assignment results. In some cases, schools agreed to move misplaced students to their correctly 

assigned classes (and confirmed this move with an updated roster); in other cases, they refused to 

move these students. We considered random assignment to have been implemented in a match if 

at least 75 percent of randomly assigned students were in their assigned classes at the time of the 

initial roster verification. If more than 25 percent of students were not in their assigned classes at 

the time of initial verification, we classified the match as having refused to implement the 

randomly assigned rosters and dropped it from the study sample. After the initial roster 

verification, we requested updated rosters at three other points during the study school years—in 

the fall, in the first week of classes in the spring, and then toward the end of the spring semester. 

These rosters were used to monitor the integrity of random assignment and the extent to which 

students left or were added to classes, as well as to help locate study students for assessment.

4. Student Sample

In the 228 matches in the study sample, 13,488 students were on the rosters schools sent 

during either initial or rolling random assignment (Figure A.2). Forty-six of these students 

(0.3 percent) were exempted from random assignment and forced to a particular classroom. Of 

the remaining students, approximately half were assigned to a TFA or Teaching Fellows teacher 

and half to a comparison teacher. In both treatment and control groups, 6 percent of students who 

were randomly assigned left the school before the start of the school year and were excluded 

from the study sample. The remaining 12,675 students (6,350 treatment and 6,325 control) 

formed the study’s research sample. Of these students, 5,790 belonged to the TFA study sample 

and 6,909 belonged to the Teaching Fellows study sample; twenty-four control group students 

were in both samples because their class was compared with the classes of both TFA and 

Teaching Fellows teachers (see Chapter II, Table II.4).

As expected due to random assignment, treatment and control group students in the 

research sample were balanced in terms of most observed baseline characteristics. The treatment 

and control groups differed by a statistically significant margin on 4 (out of 23) characteristics in 

the TFA study sample and 5 (out of 23) characteristics in the Teaching Fellows study sample 

(Tables A.5 and A.6). The largest of these treatment-control differences consisted of a 

2 percentage point difference in the percentage female within the TFA study sample, and a 

2 percentage point difference in the percentage eligible for free or reduced-price lunch in the 

Teaching Fellows study sample.
Effectiveness of TFA and Teaching Fellows Teachers 

A.12 

Figure A.2. Number of Students Involved in Each Stage of Random Assignment and Data Collection

Left school 

before school 

started

N = 383

Randomly assigned

N = 13,442

In school at school

start

N = 6,325

No parental 

consent

N = 978

Test score not 

available = 

1,042

Test score not 

valid = 55

Parental consent 

obtained

N = 5,347

Outcome data 

available

N = 4,250

Left school 

before school 

started

N = 384

In school at school 

start

N = 6,350

No parental 

consent

N = 943

Parental consent 

obtained

N = 5,407

Test score not 

available = 925

Test score not 

valid = 63

Outcome data 

available

N = 4,419

Research 

Sample

Analysis 

Sample

Students on class 

rosters

N = 13,488

(# of classroom 

matches = 228)

Assigned to TFA

teachers or 

Teaching Fellows

N = 6,734

Assigned to 

comparison teachers

N = 6,708

Exempted from 

random assignment

N = 46
Effectiveness of TFA and Teaching Fellows Teachers 

A.13 

Table A.5. Average Baseline Characteristics of Students Assigned to TFA Teachers or Comparison Teachers 

(percentages unless otherwise indicated)

Assigned 

to TFA Comparison 

Characteristic Teachers Teachers Difference p-Value

Assigned to 

Baseline Math Achievement

Baseline math score (average z-score) -0.53 -0.53 -0.01 0.606

Score below 25th percentile of state 40.8 41.0 -0.2 0.775

Score below 50th percentile of state 73.4 73.6 -0.2 0.817

Baseline Reading Achievement

Baseline reading score (average z-score) -0.53 -0.53 0.00 0.851

Score below 25th percentile of state 41.3 40.6 0.7 0.352

Score below 50th percentile of state 72.6 73.7 -1.1 0.124

Age (average years) 13.62 13.56 0.06** 0.001

Female 48.4 50.3 -1.9** 0.007

Race and Ethnicity

Asian, non-Hispanic 2.3 1.9 0.4 0.147

Black, non-Hispanic 62.3 63.2 -0.9 0.285

Hispanic 27.6 26.8 0.7 0.262

White, non-Hispanic 6.7 6.7 0.0 0.984

Other race/ethnicity 1.1 1.4 -0.2 0.442

Eligible for Free/Reduced-Price Lunch 88.2 88.7 -0.6 0.473

Limited English Proficient 8.1 8.6 -0.5 0.291

Individualized Education Plan 7.2 6.6 0.6 0.153

Grade Level in Study Year

6th grade 25.0 25.2 -0.2 0.125

7th grade 27.0 26.5 0.4* 0.024

8th grade 18.8 19.0 -0.2 0.210

9th grade 17.4 17.0 0.5 0.123

10th grade 7.9 8.6 -0.7* 0.027

11th grade 3.4 3.3 0.1 0.655

12th grade 0.3 0.2 0.1 0.243

Number of Students 2,725 2,737

Number of Classroom Matches 111 111

Number of Teachers 66 70

Number of Schools 45 45

Source: District administrative records.

Note: Table is based on students in the research sample with parental consent. Means and percentages are 

weighted with sample weights and adjusted for classroom match fixed effects. P-values are based on a 

regression of the specified characteristic on a TFA indicator and classroom match indicators, accounting for 

sample weights and clustering at the teacher level.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

A.14 

Table A.6. Average Baseline Characteristics of Students Assigned to Teaching Fellows or Comparison 

Teachers (percentages unless otherwise indicated)

Characteristic

Assigned to 

Teaching 

Fellows

Assigned to

Comparison 

Teachers Difference p-Value

Baseline Math Achievement

Baseline math score (average z-score) -0.17 -0.17 0.00 0.994

Score below 25th percentile of state 28.7 28.3 0.3 0.679

Score below 50th percentile of state 59.3 59.5 -0.2 0.853

Baseline Reading Achievement

Baseline reading score (average z-score) -0.11 -0.09 -0.02 0.305

Score below 25th percentile of state 24.7 24.1 0.5 0.591

Score below 50th percentile of state 58.6 59.0 -0.3 0.664

Age (average years) 14.62 14.60 0.02 0.123

Female 52.6 52.1 0.4 0.601

Race and Ethnicity

Asian, non-Hispanic 8.5 7.6 0.8 0.161

Black, non-Hispanic 53.3 51.8 1.4* 0.034

Hispanic 32.4 34.2 -1.8* 0.014

White, non-Hispanic 5.3 5.5 -0.2 0.646

Other race/ethnicity 0.6 0.8 -0.2 0.145

Eligible for Free/Reduced-Price Lunch 73.5 75.7 -2.1* 0.011

Limited English Proficient 7.2 7.4 -0.2 0.714

Individualized Education Plan 7.1 7.1 0.1 0.901

Grade Level in Study Year

6th grade 6.6 6.6 0.0 0.958

7th grade 12.0 12.1 -0.1* 0.050

8th grade 14.2 14.1 0.1 0.302

9th grade 29.7 30.0 -0.3 0.571

10th grade 19.4 20.0 -0.6 0.215

11th grade 16.3 15.1 1.2** 0.003

12th grade 1.8 2.1 -0.3 0.217

Number of Students 2,682 2,631

Number of Classroom Matches 118 118

Number of Teachers 69 84

Number of Schools 44 44

Source: District administrative records.

Note: Table is based on students in the research sample with parental consent. Means and percentages 

are weighted with sample weights and adjusted for classroom match fixed effects. P-values are 

based on a regression of the specified characteristic on a Teaching Fellows indicator and 

classroom match indicators, accounting for sample weights and clustering at the teacher level.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
Effectiveness of TFA and Teaching Fellows Teachers 

A.15 

Parental consent was obtained for 85 percent of research sample students in both the 

treatment and control groups (Figure A.2). Valid outcome test score data were obtained for 

82 percent of consenting students in the treatment group and 79 percent of consenting students in 

the control group. The 8,669 students with parental consent and valid outcome test score data 

(4,419 treatment and 4,250 control group members) formed the study’s analysis sample on 

which impact estimates were based. As discussed in Chapter II, the treatment and control groups 

in the analysis samples were also balanced in terms of most baseline characteristics.

The mobility of research sample members determined their level of exposure to the type of 

teacher to which they were originally assigned. Overall, most students in the research sample 

(77.2 percent) stayed in their originally assigned class for the full study year (Table A.7). The 

remaining students moved out of the class. The most common reason for leaving the class was

departure from the study school, which occurred for 11.7 percent of research sample members. 

Table A.7. Movement of Members of Research Sample During the School Year (percentages unless 

otherwise indicated)

Mobility Status

All Students 

in Research 

Sample

Assigned 

to TFA 

Teachers or 

Teaching 

Fellows

Assigned to

Comparison

Teachers

Crossed Over to Study Class with Opposite Teacher Typea 2.8 2.9 2.7

Never Crossed Over to Study Class with Opposite Teacher Typea 97.2 97.1 97.3

Left study school before end of year 11.7 11.8 11.5

Switched to nonstudy class in same school before end of year 6.7 6.2 7.1*

Switched to another study class with same teacher type before 

end of yearb 1.6 1.6 1.7

Stayed in originally assigned class through end of year 77.2 77.4 77.0

Number of Students 12,675 6,350 6,325

Note: Teacher types are TFA teachers, Teaching Fellows, and comparison teachers. Data include both 

consenting and nonconsenting students. Calculations are unweighted. Tests of differences 

between TFA or Teaching Fellows classes and comparison classes are based on independentsample t-tests with unequal variances.

a

Crossovers consist only of cases in which students transferred to another study class with the opposite 

teacher type (a student in a TFA or Teaching Fellows study class transferring to a comparison class in the 

study, or vice versa). Transfers to classes or schools outside of the study sample are not classified as cases of 

crossover because the teacher type of the destination classroom is unknown.

b

Includes only students who stayed in study classes through the end of the year.

 *Difference between TFA or Teaching Fellows classes and comparison classes is statistically significant at the 

0.05 level, two-tailed test.

**Difference between TFA or Teaching Fellows classes and comparison classes is statistically significant at the 

0.01 level, two-tailed test.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

A.16 

Not all students in study classes were randomly assigned. Those who were not randomly 

assigned were excluded from the study sample, but their presence could theoretically have 

affected the achievement of randomly assigned students. We requested that schools contact us to 

randomly assign all students who enrolled in study classes up through the first month of school; 

however, some students were exempted from random assignment by school request, and schools 

might have failed to request assignments for other late-enrolling students. After the first month 

of school, schools were free to place newly enrolling students without random assignment. As of 

the end of the school year, the percentage of students in study classes who had not been

randomly assigned was 14 percent in both treatment and control classes. 

We examined the baseline characteristics of nonrandomly assigned students on class rosters 

at the end of the study year for the TFA and Teaching Fellows study samples, to determine 

whether particular types of students appeared to be systematically placed with TFA/Teaching 

Fellows or comparison teachers. In the TFA study sample, students nonrandomly assigned to 

TFA teachers had lower baseline math scores, were more likely to have baseline reading scores 

below the 25th percentile in their state, were more likely to be female, and were less likely to be 

in 9th grade than students nonrandomly assigned to comparison teachers (Table A.8). In the 

Teaching Fellows study sample, students nonrandomly assigned to Teaching Fellows were more 

likely to be white and were distributed differently across high school grade levels than students 

nonrandomly assigned to comparison teachers (Table A.9). There were no other significant 

differences between treatment and control classes in the characteristics of nonrandomly assigned 

students. 

D. Statistical Power

With an analysis sample of 136 teachers and 4,573 students in the TFA study sample and 

153 teachers and 4,116 students in the Teaching Fellows study sample, the study had 

considerable precision for estimating the average impacts of TFA and Teaching Fellows teachers

relative to the comparison teachers with whom they were compared. The minimum detectable 

effect (MDE) is the smallest true impact for which there would be an 80 percent probability of 

obtaining a statistically significant estimate. We computed MDEs based on the realized values of 

key parameters determining the study’s precision for the six impact estimates deemed to be of 

primary policy interest, as discussed in Chapter II—impacts for the full sample of TFA teachers, 

the subsample compared with TC teachers, and the subsample compared with less-selective AC 

teachers, as well as the full sample of Teaching Fellows, the subsample compared with TC 

teachers, and the subsample compared with less-selective AC teachers. The impact of the full 

sample of TFA teachers relative to comparison teachers was 0.07 standard deviations 

(Table A.10). That is, if students truly scored at least 0.07 standard deviations higher by being 

assigned to TFA teachers rather than comparison teachers, then any study with the same design 

on the same population of teachers would have at least an 80 percent probability of obtaining a 

statistically significant impact estimate. Similarly, the MDE for the impact of the full sample of 

Teaching Fellows relative to comparison teachers was 0.09 standard deviations. Given prior 

tabulations for the average year-to-year gain in math achievement on nationally standardized 

assessments (Hill et al. 2008), these minimum detectable effect sizes were equivalent to 2.6 to 

3.3 months of learning out of a 10-month school year. MDEs for impacts within subgroups 

defined by the certification route of the comparison teachers ranged from 0.10 to 0.16 standard 

deviations.
Effectiveness of TFA and Teaching Fellows Teachers 

A.17 

Table A.8. Characteristics of Nonstudy Students on End-of-Year Rosters of Classrooms in the TFA 

Study Sample (percentages unless otherwise indicated)

Characteristic

In Classes 

of TFA 

Teachers

In Classes of 

Comparison 

Teachers Difference p-Value

Baseline Math Achievement

Baseline math score (average z-score) -0.84 -0.72 -0.12* 0.035

Score below 25th percentile of state 55.4 52.4 3.0 0.435

Score below 50th percentile of state 81.7 80.2 1.6 0.609

Baseline Reading Achievement

Baseline reading score (average z-score) -0.82 -0.72 -0.10 0.229

Score below 25th percentile of state 58.4 49.1 9.3* 0.018

Score below 50th percentile of state 76.9 77.0 -0.1 0.986

Age (average years) 13.6 13.67 -0.04 0.373

Female 50.0 38.5 11.5** 0.001

Race and Ethnicity

Asian, non-Hispanic 1.3 1.4 -0.1 0.885

Black, non-Hispanic 70.9 73.0 -2.0 0.367

Hispanic 21.7 20.8 0.9 0.677

White, non-Hispanic 5.2 4.1 1.1 0.379

Other race/ethnicity 1.0 0.8 0.2 0.786

Eligible for Free/Reduced-Price Lunch 87.9 87.7 0.2 0.910

Limited English Proficient 16.1 16.7 -0.6 0.868

Individualized Education Plan 8.6 9.6 -0.9 0.579

Grade Level in Study Year

6th grade 21.1 21.4 -0.2 0.675

7th grade 36.5 35.0 1.4 0.080

8th grade 21.8 22.5 -0.7 0.163

9th grade 8.7 10.8 -2.2* 0.025

10th grade 8.1 6.8 1.3 0.065

11th grade 2.4 2.3 0.1 0.856

12th grade 1.4 1.1 0.3 0.665

Number of Nonstudy Students with 

Parental Consent and Any Baseline Data 343 366

Percentage of Nonstudy Students with 

Parental Consent and Any Baseline Data 85.1 85.3

Sources: District administrative records and study-administered Northwest Evaluation Association 

assessments.

Note: Numbers are based on consenting students who do not belong to the research sample but are 

listed on end-of-year rosters of study classes. Means and percentages are unweighted and 

adjusted for classroom match fixed effects. p-values are based on a regression of the specified 

characteristic on an indicator for TFA classes and classroom match indicators, accounting for 

clustering at the teacher level.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

A.18 

Table A.9. Characteristics of Nonstudy Students on End-of-Year Rosters of Classrooms in the Teaching 

Fellows Study Sample (percentages unless otherwise indicated)

Characteristic

In Classes 

of Teaching 

Fellows

In Classes of

Comparison

Teachers Difference p-Value

Baseline Math Achievement

Baseline math score (average z-score) -0.42 -0.48 0.06 0.394

Score below 25th percentile of state 40.8 38.2 2.6 0.637

Score below 50th percentile of state 76.9 74.7 2.2 0.602

Baseline Reading Achievement

Baseline reading score (average z-score) -0.45 -0.55 0.09 0.207

Score below 25th percentile of state 38.0 47.4 -9.4 0.052

Score below 50th percentile of state 75.2 72.5 2.7 0.585

Age (average years) 14.3 14.23 0.10 0.412

Female 47.5 47.1 0.4 0.904

Race and Ethnicity

Asian, non-Hispanic 5.2 6.1 -0.9 0.629

Black, non-Hispanic 42.0 41.4 0.6 0.869

Hispanic 41.9 47.8 -6.0 0.063

White, non-Hispanic 9.5 4.7 4.8* 0.026

Other race/ethnicity 1.5 0.0 1.5 0.065

Eligible for Free/Reduced-Price Lunch 77.6 74.1 3.5 0.295

Limited English Proficient 22.0 20.9 1.2 0.800

Individualized Education Plan 9.1 9.4 -0.3 0.924

Grade Level in Study Year

6th grade 17.0 17.8 -0.8 0.238

7th grade 12.7 13.3 -0.6 0.179

8th grade 8.2 7.6 0.7 0.264

9th grade 40.6 43.2 -2.5 0.050

10th grade 13.1 9.5 3.6* 0.016

11th grade 2.9 7.6 -4.7* 0.025

12th grade 5.5 1.1 4.3* 0.023

Number of Nonstudy Students with 

Parental Consent and Any Baseline Data 263 278

Percentage of Nonstudy Students with 

Parental Consent and Any Baseline Data 60.0 63.9

Sources: District administrative records and study-administered Northwest Evaluation Association 

assessments.

Note: Numbers are based on consenting students who do not belong to the research sample but are 

listed on end-of-year rosters of study classes. Means and percentages are unweighted and 

adjusted for classroom match fixed effects. p-values are based on a regression of the specified 

characteristic on an indicator for classes of Teaching Fellows and classroom match indicators, 

accounting for clustering at the teacher level.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
Effectiveness of TFA and Teaching Fellows Teachers 

A.19 

Table A.10. Realized Values for Key Precision Parameters

Parameter

Value in 

TFA Study 

Sample

Value in 

Teaching 

Fellows Study 

Sample

Sample Sizes

Number of schools 45 44

Number of teachers per school 3.0 3.5

Number of classes per teacher 1.8 1.8

Number of randomly assigned students per class 23.3 25.6

Student Response Rate 0.79 0.60

Teacher-Level Intraclass Correlation Coefficient 0.24 0.52

Teacher-Level R-squared 0.94 0.96

Student-level R-squared 0.41 0.36

Sample Standard Deviation of End-of-Year Math Scores (expressed 

in standard deviations within the reference population) 0.93 1.08

Minimum Detectable Effect for:

Full study sample 0.07 0.09

Subsample for comparisons with TC teachersa 0.10 0.10

Subsample for comparisons with less-selective AC teachersb 0.11 0.16

Note: Minimum detectable effects are expressed in standard deviations of outcome scores within the 

reference population of the student’s assessment.

a

Within the TFA study sample, calculations are based on a 60 percent subsample of teachers; within the 

Teaching Fellows sample, calculations are based on a 74 percent subsample of teachers. All other parameters 

are fixed at their full-sample values.

b

Within the TFA study sample, calculations are based on a 43 percent subsample of teachers; within the 

Teaching Fellows sample, calculations are based on a 30 percent subsample of teachers. All other parameters 

are fixed at their full-sample values.

TFA = Teach for America.

E. Data Reliability and Response Rates

Below we discuss the psychometric properties of the Northwest Evaluation Association 

(NWEA) assessments administered to high school students in the study and the state assessments 

taken by middle school students in the study, as well as response rates for students (test score 

data) and teachers (survey and Praxis data).

1. Psychometric Properties of NWEA Assessments

To measure the math achievement of students in grades 9 to 12 in the study, we 

administered end-of-course math assessments developed by the NWEA. Based on the content of 

their math course, students took computer-adaptive assessments in either general high school 

math, Algebra I, Geometry, or Algebra II. Departing from standard NWEA procedures, which do 

not time-limit the tests, we imposed a 35-minute time limit on the assessments so they could be 

administered in a single class period. Although NWEA typically does not score incomplete tests, 

it provided us with Rasch Unit (RIT) scores and standard errors of measurement (SEMs) on all 

students, regardless of whether they completed all 50 items. Although imposing a time limit and 
Effectiveness of TFA and Teaching Fellows Teachers 

A.20 

accepting incomplete tests were expected to lower the reliability of the test scores, the actual 

reliability of NWEA scores in the analysis sample remained high. Marginal reliability 

coefficients—measuring the internal consistency of the assessments (Samejima 1977, 1994)—for

all four of the NWEA assessments used in the study were greater than 0.90 in the analysis 

sample (Table A.11). 

Table A.11. Reliability of the NWEA Assessments, by Subject

Subject

Marginal Reliability Coefficient

Published by NWEA In Analysis Sample

General High School Math 0.974a 0.927

Algebra I 0.964a 0.957

Geometry 0.962b 0.969

Algebra II 0.949b 0.968

Source: Published reliability coefficients are from NWEA technical documentation; reliability coefficients for 

analysis sample are from authors’ calculations.

a

Value is the NWEA’s published marginal reliability coefficient for test scores taken in 9th grade in the indicated 

subject.

b

Value is the NWEA’s published marginal reliability coefficient for test scores taken in 10th grade in the 

indicated subject.

NWEA = Northwest Evaluation Association.

To improve the reliability of the NWEA data, we designated scores as invalid, and treated 

them as missing in the analysis, for one or more of the following reasons:

1. The standard error of measurement of the test was greater than 5.5, or the 

student completed the test in fewer than six minutes. This rule was recommended 

by NWEA for assessing test score validity. Four percent or less of each group had 

scores designated as invalid for this reason (Table A.12).

2. Students took the wrong assessment. This may occur when students moved from 

one study class to another. For example, a student assigned to an Algebra II class may 

have moved to Algebra I in the middle of the year. In the Algebra I class, this student 

may have been erroneously administered the Algebra I test. This occurred for less 

than 2 percent of all tested students in the treatment or control groups. 

Overall, approximately 4 percent of NWEA scores were designated as invalid in the treatment or 

control groups in either the TFA or Teaching Fellows samples for one of these three reasons. 

Table A.13 shows statistics on NWEA scores by exam for the analysis sample of students 

with valid scores. Across all four assessments, the average standard error of measurement ranged 

from 3.4 to 3.7, the average number of items completed (out of 50) ranged from 37.4 to 43.8, and 

the average test completion time ranged from 27.6 to 30.6 minutes. 
Effectiveness of TFA and Teaching Fellows Teachers 

A.21 

Table A.12. Invalid NWEA Scores, by Treatment Status

Reason Score Was Categorized Invalid

Percentage with Invalid NWEA Scores

Assigned to 

TFA Teachers 

or Teaching 

Fellows

Assigned to

Comparison 

Teachers Difference p-Value

TFA Study Sample

Test was in a different subject than the most 

commonly administered test in the classroom 

match 0.5 0.6 -0.2 0.673

Standard error of measurement > 5.5 RIT, or test 

was completed in fewer than 6 minutes 3.9 3.4 0.5 0.628

Any of the specified reasons 4.4 4.1 0.3 0.767

Teaching Fellows Study Sample

Test was in a different subject than the most 

commonly administered test in the classroom 

match 0.8 1.4 -0.6 0.120

Standard error of measurement > 5.5 RIT, or test 

was completed in fewer than 6 minutes 3.0 2.5 0.4 0.489

Any of the specified reasons 3.8 4.0 -0.2 0.801

Sample Sizes: TFA Study Sample

Students 637 616

Classroom Matches 28 28

Teachers 17 16

Schools 14 14

Sample Sizes: Teaching Fellows Study Sample

Students 1,271 1,336

Classroom Matches 81 81

Teachers 41 60

Schools 29 29

Source: Study-administered NWEA assessments. Numbers are based on students in the research sample 

who took an NWEA assessment. 

Note: p-values are based on independent-sample t-tests with unequal variances.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

NWEA = Northwest Evaluation Association; RIT = Rasch Units; TFA = Teach for America.
Effectiveness of TFA and Teaching Fellows Teachers 

A.22 

Table A.13. NWEA Test Statistics in Analysis Sample

Mean

Standard 

Deviation

Percentile

5th 25th 50th 75th 95th

General High School Math

RIT score 217.3 12.7 197.3 206.8 216.1 226.6 240.2

Standard error of measurement 3.4 0.5 2.9 3.0 3.2 3.6 4.4

Number of items completed 43.8 9.5 24.0 35.5 50.0 50.0 50.0

Test completion time (minutes) 27.6 5.8 17.5 22.2 30.4 32.4 34.0

Number of Students in Analysis 

Sample with Valid NWEA Scores

in General High School Math 38

Algebra I

RIT score 229.7 18.1 197.0 219.6 231.2 241.2 258.3

Standard error of measurement 3.7 0.6 2.9 3.1 3.5 4.1 5.0

Number of items completed 37.4 11.2 19.0 28.0 38.0 50.0 50.0

Test completion time (minutes) 30.6 4.5 20.3 29.6 32.3 33.5 34.4

Number of Students in Analysis 

Sample with Valid NWEA Scores

in Algebra I 1,488

Geometry

RIT score 238.1 20.2 201.5 226.1 240.3 253.1 268.1

Standard error of measurement 3.5 0.6 2.9 3.0 3.3 3.9 4.8

Number of items completed 40.4 10.1 22.0 32.0 43.0 50.0 50.0

Test completion time (minutes) 29.9 5.2 19.3 28.1 32.1 33.4 34.3

Number of Students in Analysis 

Sample with Valid NWEA Scores

in Geometry 1,287

Algebra II

RIT score 240.5 20.7 204.1 227.6 240.2 255.0 274.4

Standard error of measurement 3.6 0.6 2.9 3.1 3.5 4.1 4.9

Number of items completed 38.4 10.7 20.0 29.0 39.0 50.0 50.0

Test completion time (minutes) 30.3 4.3 21.5 28.2 31.9 33.4 34.2

Number of Students in Analysis 

Sample with Valid NWEA Scores

in Algebra II 893

Source: Study-administered NWEA assessments.

NWEA = Northwest Evaluation Association; RIT = Rasch Unit.
Effectiveness of TFA and Teaching Fellows Teachers 

A.23 

2. Psychometric Properties of State Math Assessments

To measure the end-of-year math achievement of students in grades 6 through 8 in the study, 

we obtained their scores on state math assessments. All of these math assessments were 

criterion-referenced tests—those that measured students’ mastery of state-specific curriculum 

standards. Each state in the study administered a different assessment. Among the districts in the 

study, the dates on which state math assessments were administered ranged from early March to 

late May in the spring of the school year. 

All state math assessments used in the study had high reliability based on measures of 

internal consistency calculated from coefficient alpha (Table A.14). Across the eight states 

represented in the study (labeled A through H in Table A.14 to preserve confidentiality), 

reliability values ranged from 0.89 to 0.94. These reliability values were close to, but slightly 

lower than, the reliability values for the NWEA assessment presented in Table A.11; this was 

expected because of the adaptive nature of the NWEA assessment.

In each state assessment, the precision of the test scores varied across the range of the 

achievement scale. Test scores were less precise (had higher SEMs) at the low and high ends of 

the achievement scale compared with scores in the middle of the scale. Given that a key 

objective of the state assessments was to differentiate students who were proficient on the states’ 

standards from those who were not, larger shares of the test items had a level of difficulty 

appropriate for differentiating these groups. Therefore, precision was generally highest for scores 

at or near the proficiency cut point (the point on the achievement scale that divided the 

nonproficient and proficient scores). As Table A.14 shows, the SEMs at the proficiency cut 

points were at or near the minimum value for the range of SEMs in each state assessment.

Consequently, the average precision of math scores among middle school students in the 

study was determined by the distribution of these scores relative to the proficiency cut point. 

About half (49 percent) of students in the TFA study sample and slightly more than half 

(56 percent) of students in the Teaching Fellows study sample scored above the proficiency cut 

point (Table A.15). Therefore, in each sample, the average score of the sample members was no 

more than 0.12 standard deviations away from the proficiency cut point. This result implies that 

test scores among middle school students in the analysis sample were centered near the parts of 

the achievement scale at which the scores were most precise.
Effectiveness of TFA and Teaching Fellows Teachers 

A.24 

Table A.14. Characteristics of State Math Assessments from which End-of-Year Scores Were Used in 

the Study

State Grade Reliability

Conditional Standard Error of Measurement

Vertical 

Lowest Highest Scale?

At Proficiency 

Cut Point

A 6 0.94 N/A N/A 16 No

B 6 0.94 14 81 15 Yes

B 7 0.93 12 106 14 Yes

B 8 0.94 11 100 12 Yes

C 6 N/A N/A N/A N/A Noa 

C 7 N/A N/A N/A N/A Noa 

C 8 N/A N/A N/A N/A Noa 

D 6 0.89 N/A N/A N/A No

D 7 0.90 N/A N/A N/A No

E 6 0.92b N/A N/A 9 Yes

E 7 0.92b N/A N/A 8 Yes

F 6 0.92c 2 6 3 Yes

F 7 0.92c 2 6 3 Yes

F 8 0.92c 2 6 3 Yes

G 6 0.93 6 125 6 No

G 7 0.92 6 129 6 No

G 8 0.93 5 162 5 No

H 6 0.91 22 70 22 Yes

H 7 0.90 21 69 21 Yes

H 8 0.91 21 69 21 Yes

Source: State assessment technical reports.

Note: All statistics pertain to the Spring 2011 administration of the test unless otherwise noted. Reliability 

values are measures of internal consistency based on coefficient alpha.

a

The state assessment also produces vertically scaled scores, but those scores were not used in the study.

b

Statistics are based on the Spring 2010 administration because the state was not included in the study in the 

2010–2011 school year.

c

Statistics are based on the first administration—in Spring 2006—of the test edition used in the study. 

N/A = not available from state assessment technical reports.
Effectiveness of TFA and Teaching Fellows Teachers 

A.25 

Table A.15. State Math Assessment Scores of Middle School Students in the Analysis Sample Relative 

to Proficiency Cut Points

Subsample

Average Difference between 

End-of-Year Test Score and 

Proficiency Cut Point 

(z-score units)

Percentage of Students 

Scoring At or Above 

Proficiency Cut Point

Teach For America Study Sample -0.12 49.0

Teaching Fellows Study Sample 0.10 56.3

Source: Test scores from district administrative records; proficiency cutoffs from state education agencies.

3. Response Rates for Students

On average, we had valid outcome test score data (from either state assessments or the 

NWEA) for 79 percent of students in TFA matches and 60 percent of students in Teaching 

Fellows matches (Table A.16). In TFA matches, average response rates for the treatment and 

control groups were similar—they did not differ by more than 2 percentage points for all TFA 

matches or for the subsets of matches with comparison teachers from a traditional route to 

certification (TC route) and an alternative route to certification (AC route). In Teaching Fellows 

matches, average response rates for the treatment and control groups differed by up to 

5 percentage points, with higher response rates for students in the treatment group. In the full set 

of Teaching Fellows matches, the response rate was 61 percent for Teaching Fellows classes and 

58 percent for control classes. In matches in which Teaching Fellows and TC teachers were 

compared, the response rate was 63 percent for Teaching Fellows classes and 58 percent for 

control classes. In matches in which Teaching Fellows and AC teachers were compared, the 

response rate was 56 percent for Teaching Fellows classes and 58 percent for control classes. For 

both TFA and Teaching Fellows matches, response rates were higher at the middle school level 

than at the high school level. 

As shown earlier in Figure A.2, overall student response rates depended on parental consent 

rates as well as test score availability among consenting students. Overall, on average, we 

obtained parental consent for 85 percent of students in the research sample, for both the 

treatment and control groups. We obtained parental consent and valid outcome test score data for 

68 percent of the research sample (70 percent of the treatment group and 67 percent of the 

control group). On average, both consent rates (88 versus 82 percent) and rates of valid outcome 

test score data (80 versus 57 percent) were higher at the middle school level than at the high 

school level. 
Effectiveness of TFA and Teaching Fellows Teachers 

A.26 

Table A.16. Student Response Rates, by Type of Impact Estimate to Which the Student’s Classroom 

Contributes

Type of Impact Estimate to Which the Student’s Classroom 

Contributes

Percentage of Research Sample Students

with Valid End-of-Year Math Scores

Assigned to 

TFA Teachers 

or Teaching 

Fellows

Assigned to

Comparison 

Teachers Total

TFA Teachers Versus All Comparison Teachers 79.5 78.5 79.0

TFA teachers versus TC teachers 75.8 75.4 75.6

TFA teachers versus other AC teachers 84.1 82.6 83.4

Teaching Fellows Versus All Comparison Teachers 61.4 57.8 59.6

Teaching Fellows versus TC teachers 62.9 57.8 60.4

Teaching Fellows versus other AC teachers 55.9 57.8 56.8

Number of Students

TFA teachers versus all comparison teachers 2,884 2,906 5,790

TFA teachers versus TC teachers 1,610 1,667 3,277

TFA teachers versus other AC teachers 1,274 1,239 2,513

Teaching Fellows versus all comparison teachers 3,466 3,443 6,909

Teaching Fellows versus TC teachers 2,762 2,650 5,412

Teaching Fellows versus other AC teachers 794 793 1,587

Sources: District administrative records and study-administered Northwest Evaluation Association 

assessments.

Note: Calculations are unweighted. 

AC = alternative route to certification; TC = traditional route to certification; TFA = Teach For America.

Compared with students with valid outcome data, students without valid outcome data had 

much higher rates of absenteeism and differed on some characteristics (Table A.17). On average, 

for both treatment and control group students, those with valid outcome data had higher baseline 

test scores (statistically significant only for control group math scores) and were younger, more 

likely to be eligible for free or reduced-price lunch, and less likely to have an individualized 

education plan (IEP) (statistically significant only for the control group). Consistent with the fact 

that students who were frequently absent were less likely to be present for testing (whether for 

state testing or the study assessment), for both the treatment and control groups, those with valid 

outcome data had, on average, 11 fewer days of absence than those without valid outcome data 

and were only about one-fourth as likely (11 versus 44 percent for the treatment group; 10 versus 

46 percent for the control group) to have been absent from math class more than 25 percent of 

the time.
Effectiveness of TFA and Teaching Fellows Teachers 

A.27 

Table A.17. Characteristics of Students With and Without Valid Outcome Data (percentages unless otherwise indicated)

Characteristic

Assigned to TFA Teachers 

or Teaching Fellows

Assigned to

Comparison Teachers

Valid 

Outcome 

Data

No Valid 

Outcome 

Data 

Valid 

Outcome 

Data

No Valid 

Outcome 

Data

Baseline Math Score (average z-score) -0.34 -0.39 -0.33 -0.42**

Baseline Reading Score (average z-score) -0.31 -0.34 -0.30 -0.35 

Age (average years) 13.86 14.01** 13.81 13.97**

Female 50.8 49.9 52.2 47.9

Race and Ethnicity

Asian, non-Hispanic 5.3 5.7 4.8 5.0

Black, non-Hispanic 56.5 53.9 55.9 55.5 

Hispanic 31.4 33.0 32.0 31.9

White, non-Hispanic 6.0 6.3 6.2 6.4

Other race/ethnicity 0.9 1.1 1.1 1.3

Eligible for Free/Reduced-Price Lunch 80.4 75.4* 81.9 75.4**

Limited English Proficient 8.0 6.4 7.9 9.6 

Individualized Education Plan 6.6 9.7 6.1 9.2* 

Grade Level in Study Year

6th Grade 18.5 17.2 18.5 18.3

7th Grade 21.0 22.4 21.1 20.4

8th Grade 18.9 17.9 18.9 19.0 

9th Grade 20.5 24.4* 20.7 22.2

10th Grade 12.4 10.2 12.8 11.4

11th Grade 8.1 5.2 7.5 5.9

12th Grade 0.6 1.9 0.6 2.4*

Number of Days Absent (average days) 11.6 22.7** 11.4 22.1**

Percentage of Days Absent from Math Class

No more than 25 percent 89.3 56.2** 89.7 54.5**

More than 25 percent 10.7 43.8** 10.3 45.5**

Number of Studentsa

(district administrative records) 4,390 937 4,220 1,040

Number of Students 

(teacher-reported attendance data) 2,952 391 2,762 390

Sources: Demographic characteristics, baseline test scores, and number of days absent are from district administrative records. 

Percentage of days absent from math class is from teacher reports.

Note: Numbers are based on students in the research sample with parental consent. Means and percentages are weighted 

with sample weights and adjusted for classroom match fixed effects. Within each research group (students of TFA or 

Teaching Fellows teachers and students of comparison teachers), tests of differences between those with and without 

valid outcome data are based on a regression of the specified characteristic on an indicator for having valid outcome 

data and classroom match indicators, accounting for sample weights and clustering at the teacher level.

a

Sample sizes pertain to research sample members with information on any of the listed baseline characteristics from districts’ 

administrative records. Students with end-of-year scores but with no information on any of the listed baseline characteristics are not 

counted in the sample sizes for this table.

 *Difference between those with and without valid outcome data is statistically significant at the 0.05 level, two-tailed test.

**Difference between those with and without valid outcome data is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America. 
Effectiveness of TFA and Teaching Fellows Teachers 

A.28 

4. Response Rates for Teachers

Response rates for the teacher survey and Praxis assessment were higher for TFA and 

Teaching Fellows teachers than for comparison teachers, and response rates for the teacher 

survey were generally higher than those for the Praxis (Table A.18). An overwhelming majority 

(97 percent) of TFA teachers and 90 percent of comparison teachers in the same matches 

completed the teacher survey, as did 96 percent of Teaching Fellows and 89 percent of 

comparison teachers in the same matches. Ninety-one percent of TFA teachers and 73 percent of 

comparison teachers in the same matches had Praxis II math assessment data, as did 94 percent 

of Teaching Fellows and 81 percent of comparison teachers in the same matches. 

Table A.18. Teacher Response Rates and Sample Sizes

Percentage of Research Sample Teachers

with Specified Type of Data

TFA Study Sample TFA Comparison Total

Percentage of Teachers Responding to Teacher Survey 97.0 90.0 92.7

Percentage of Teachers with Scores on Teacher 

Assessment (Praxis) 90.9 72.9 84.3

Number of Teachers 66 70 287

Teaching Fellows Study Sample

Teaching 

Fellows Comparison Total

Percentage of Teachers Responding to Teacher Survey 95.7 89.3 92.7

Percentage of Teachers with Scores on Teacher 

Assessment (Praxis) 94.2 81.0 84.3

Number of Teachers 69 84 287

Note: Calculations are unweighted. 

TFA = Teach For America.

For both the teacher survey and the Praxis, nonresponding comparison teachers had 

significantly more years of teaching experience than responding comparison teachers (Tables 

A.19 and A.20). There were no significant differences in years of teaching experience between 

responding and nonresponding TFA teachers and Teaching Fellows. There were also no 

significant differences between respondents and nonrespondents in route to certification and the 

level (middle or high) of their school, among both the TFA/Teaching Fellows teachers and 

comparison teachers.
Effectiveness of TFA and Teaching Fellows Teachers 

A.29 

Table A.19. Characteristics of Teachers, by Response to Teacher Survey (percentages unless otherwise 

indicated)

Characteristic

TFA or Teaching Fellows 

Teachers

Comparison 

Teachers

Responded

Did Not 

Respond Responded

Did Not 

Respond

Route to Certification

TFA 49.2 40.0 n.a. n.a.

Teaching Fellows 50.8 60.0 n.a. n.a.

Traditional n.a. n.a. 64.7 75.0

Alternative n.a. n.a. 35.3 25.0

Years of Teaching Experience 2.9 3.0 11.8 16.9*

School Levela 

Middle school 56.2 80.0 51.5 43.8

High school 43.8 20.0 49.3 56.3

Number of Teachers 130 5 136 16

Source: Teacher background form. a

Percentages of teachers in middle school and high school grades can sum to more than 100 percent because some 

teachers taught in both levels.

 *Difference between respondents and nonrespondents is statistically significant at the 0.05 level, two-tailed test.

**Difference between respondents and nonrespondents is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America; n.a = not applicable.

Table A.20. Characteristics of Teachers, by Availability of Praxis II Scores (percentages unless otherwise 

indicated)

Characteristic

TFA or Teaching Fellows 

Teachers

Comparison 

Teachers

Scores 

Available

Scores 

Unavailable 

Scores 

Available

Scores 

Unavailable

Route to Certification

TFA 48.0 60.0 n.a. n.a.

Teaching Fellows 52.0 40.0 n.a. n.a.

Traditional n.a. n.a. 62.4 77.1

Alternative n.a. n.a. 37.6 22.9

Years of Teaching Experience 3.0 2.4 11.0 16.9**

School levela 

Middle school 59.2 30.0 52.1 45.7

High school 40.8 70.0 47.9 57.1

Number of Teachers 125 10 117 35

Source: Teacher background form. a

Percentages of teachers in middle and high school grades can sum to more than 100 percent because some 

teachers taught in both levels.

 *Difference between those with and without scores is statistically significant at the 0.05 level, two-tailed test.

**Difference between those with and without scores is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America; n.a. = not applicable. 
This page has been left blank for double–sided copying.
APPENDIX B

SUPPLEMENTARY INFORMATION ON ANALYTIC METHODS
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

B.3 

In Appendix B, we describe the analytic methods used in this report. We first discuss the 

construction of sample weights (Section A) and the specification of baseline achievement scores 

(Section B). We then describe the methods used in the contextual analyses (Section C), 

experimental analyses (Section D), and nonexperimental analyses (Section E).

A. Sample Weights

In the analyses of student data, sample weights were used to account for differences in 

probabilities of assignment to the treatment group (classes of Teach For America [TFA] or 

Teaching Fellows teachers) or the control group (classes of comparison teachers) among students 

in the same classroom match. Random assignment procedures and associated assignment 

probabilities are described in more detail in Appendix A. Sample weights ensured that even if 

certain types of students (for instance, late enrollees) had a higher or lower probability of 

assignment to the treatment group than other types of students, the weighted treatment and 

control groups within a classroom match were both fully representative of all randomly assigned 

students in the match. 

We constructed sample weights for all students in the research sample—that is, randomly 

assigned students who did not leave the school before the start of the school year. To calculate 

these weights, we first constructed a raw weight, equal to the inverse of the probability of 

assignment to the group (treatment or control) to which each student was actually assigned: 

 (B.1) 1

igk

igk

raw_weight

p = , 

where igk raw_weight is the raw weight for student i in group (treatment or control) g and match 

k, and igk p is the student’s ex ante probability of being assigned to the group g to which he or she 

was actually assigned.

We then normalized the raw weights so that the sum of the normalized weights within a 

match equaled the total number of research sample students in the match, with the sum of the 

weights among treatment group students equal to the sum of the weights among control group 

students. Specifically, we used the following formula: 

 (B.2) 

1

2 gk

igk k

igk N

igk i

raw_weight N sample_weight

raw_weight =

    =  ∗      ∑

where igk sample_weight is the final sample weight for student i in group g and match k, Ngk is 

the total number of research sample students assigned to group g in match k, and Nk is the total 

number of research sample students in match k. 

B. Specification of Baseline Achievement Scores

Baseline achievement scores—that is, math and reading scores that students earned before 

being assigned to a study class—were key covariates in the experimental and nonexperimental 

analyses. All baseline scores were expressed as z-scores based on the statewide mean and 
Effectiveness of TFA and Teaching Fellows Teachers 

B.4 

standard deviation of scores in the grade level and year in which the assessment was 

administered. This section describes our rules for selecting the grade level from which we 

obtained each student’s baseline scores.

Even within the same classroom match, students differed in the grade level at which they 

had most recently been assessed by end-of-grade state assessments. For example, in middle 

school, the grade level that students attended in the immediate prior year differed between grade 

repeaters and nonrepeaters in the same classroom match. Among high school students, although 

their last end-of-grade state assessment had typically occurred in 8th grade, several states in the 

study administered end-of-grade exams in selected high school grades. In those states, high 

school students in the same classroom match who differed in their current grade level could 

thereby also differ in the grade level in which they last took an end-of-grade assessment.

Our basic approach to specifying students’ baseline scores was to require that baseline 

scores for all students in the same classroom match be taken from the same grade level. We 

focused on making the grade level of the baseline scores consistent within classroom matches 

because only scores within the same matches were compared. The advantage of our approach 

was that the z-scores being compared were thereby based on similar distributions of 

achievement—distributions pertaining to the same grade level.

Separately for each classroom match, we used the following two steps to identify the grade 

level from which baseline scores were taken:

1. We calculated the 10th percentile of current grade level within the classroom match. 

This represented the highest grade level that nearly all (at least 90 percent of) students 

in the match had reached. We chose not to identify the minimum grade level in the 

match because this value would have been more vulnerable to data errors, especially 

those in which a student’s recorded grade level was much lower than his or her actual 

grade level.

2. We identified the highest grade level that was less than the grade level calculated in 

step 1 and was a grade level at which end-of-grade state exams were administered. 

Baseline scores for all students in the classroom match were taken from this identified 

grade level.

We then identified each student’s most recent reading and math scores from the grade level 

specified in step 2 above. These two scores served as the student’s baseline scores in the 

analysis. Cases in which students did not have a score from the specified baseline grade level 

were treated as missing data. Notably, students differed—even within the same match—in the 

number of years elapsed since they earned their baseline scores. Therefore, in the impact 

analyses, we controlled for a set of binary indicators representing different numbers of years 

elapsed since students earned their baseline scores (see Section D).

We did not control for students’ scores from additional grades before the baseline grade 

level specified in the preceding discussion. Findings by Bloom et al. (2007) indicate that 

controlling for scores from multiple prior grades would have yielded little to no improvement in 

precision beyond controlling for scores from a single prior grade. Moreover, higher rates of 

missing data in scores from additional earlier grades—especially among high school students—

would have further limited the precision gains from including these additional variables. Instead, 

our approach of controlling for scores from multiple subjects—rather than multiple grades—
Effectiveness of TFA and Teaching Fellows Teachers 

B.5 

enabled the use of baseline achievement variables from a single recent baseline grade with lower 

rates of missing data.

C. Analytic Methods in the Contextual Analyses

We conducted several types of descriptive analyses to develop a fuller understanding of the 

characteristics, experiences, and institutional environment of the study participants. As discussed 

next, we focused these analyses on describing the TFA and Teaching Fellows programs, 

teachers, schools, and students in the study. 

1. Descriptive Analyses of TFA and Teaching Fellows Programs 

We documented the strategies and methods by which TFA and the Teaching Fellows 

programs screened and selected candidates, trained and placed their teachers, and supported their 

teachers during the school year, using data from interviews with program officials. We also 

examined similarities and differences between TFA and the Teaching Fellows programs as a 

whole, as well as differences between the individual Teaching Fellows programs in the study.

The information that we collected from program officials included numeric data for several 

types of program features (for example, how often program staff observed new teachers). When 

respondents gave a range in response to a question seeking a numeric value, we used the 

midpoint of the range as the value in the analysis. When respondents reported only a minimum 

value—for example, that program staff observed new teachers at least once per semester—we 

used the minimum reported value in the analysis. We gave equal weight to each regional or local 

program when reporting average characteristics across these programs.

2. Descriptive Analyses of Teacher Characteristics

Documenting the characteristics of each group of study teachers was a key to identifying 

potential reasons for differences in effectiveness across these groups. On several measures of 

teachers’ professional background and characteristics, we compared (1) TFA teachers with the 

comparison teachers in the same classroom matches and (2) Teaching Fellows with the 

comparison teachers in the same classroom matches. For each comparison, we calculated 

unweighted differences between the groups being compared and tested the statistical significance 

of the differences.

We also conducted supplemental descriptive analyses in which teachers were weighted so 

that the TFA/Teaching Fellows and comparison teachers were equally represented in every 

classroom match. Specifically, for a teacher j belonging to group g (either TFA/Teaching 

Fellows or comparison), the weight assigned to this teacher, Wj , was

(B.3) (1/ )

j

j gk

k M

W n ∈= ∑ , 

where M j denotes the set of matches to which teacher j belonged, and ngk is the number of 

teachers from group g in match k. For example, if a particular TFA teacher was the only TFA or 

Teaching Fellows teacher in each of three different matches, then he or she received a weight of 

3.0 in this supplemental analysis. If another teacher was one of two comparison teachers in a 

single match, he or she received a weight of 0.5. 
Effectiveness of TFA and Teaching Fellows Teachers 

B.6 

3. Descriptive Analyses of Schools and Students in the Study

We tabulated the average characteristics of schools and students in the study for two main 

purposes. First, the tabulations characterized the demographic context in which the study was 

implemented. Second, they helped assess the integrity of random assignment. If random

assignment was implemented properly, then there should be few differences in baseline

characteristics between students assigned to the treatment group and those assigned to the control 

group in the same classroom match.

To check the integrity of random assignment, we estimated treatment-control differences on 

several baseline student characteristics and tested the statistical significance of the differences. 

These estimates were based on a regression model that controlled for classroom match indicators 

to ensure that we compared only treatment and control students in the same classroom match. 

For a given characteristic, zijk , of student i assigned to teacher j in match k, we used the 

following ordinary least squares (OLS) regression model: 

(B.4) ijk k jk ijk 1 z T =+ + αβ ε , 

where αk is a classroom match fixed effect; Tjk is a binary indicator for being assigned to a TFA 

or Teaching Fellows teacher (rather than a comparison teacher); and ε ijk is a random error term. 

The parameter of interest that we estimated, β1 , measures the within-match difference in the

specified characteristic between treatment and control group students.

The methods used to estimate Equation (B.4) were identical to those used to estimate the 

main impacts, discussed later in Section D. In particular, we applied sample weights and 

calculated standard errors based on the Huber-White sandwich variance estimator, taking into 

account the clustering of student characteristics at the teacher level (Liang and Zeger 1986). For 

each characteristic, we used a two-sided t-test to assess the statistical significance of the 

difference between the treatment and control groups. 

D. Analytic Methods in the Experimental Analyses

1. Main Estimation Model 

In the experimental analyses, we estimated separately the impacts of TFA and Teaching 

Fellows teachers relative to the comparison teachers with whom they were compared. We used 

separate samples but identical regression models to estimate the two impacts. We modeled the 

end-of-year math achievement score, ijk y , of student i who was randomly assigned to teacher j

in classroom match k as follows:

 (B.5) y T ijk k jk ijk ijk =+ + + αβ βε 1 2 X , 

where αk is a classroom match fixed effect; Tjk is a binary indicator for being assigned to a TFA 

or Teaching Fellows teacher (rather than a comparison teacher); Xijk is a set of baseline student 
Effectiveness of TFA and Teaching Fellows Teachers 

B.7 

characteristics specified below; β1 and 2 β are parameters that we estimated; and ijk ε is a random 

error term.

The parameter of interest, , is the average difference in effectiveness between TFA or 

Teaching Fellows teachers and the comparison teachers with whom they were compared. As we 

did for estimates of treatment-control baseline differences, we conducted the impact estimates in 

Equation (B.5) using OLS with sample weights, and we calculated sandwich standard errors that 

accounted for the clustering of student outcomes at the teacher level. By accounting for 

clustering at the teacher level, we effectively modeled teachers’ effects on student achievement 

as random effects; therefore, the model accommodated the possibility that true differences in 

effectiveness between TFA/Teaching Fellows teachers and comparison teachers could vary 

across classroom matches. Moreover, because the sandwich standard errors were robust to any 

type of correlation in outcomes among students assigned to the same teacher, these standard 

errors automatically accounted for common influences—for instance, common sets of peers—

among students who were assigned to the same classroom as well as scenarios in which students 

were grouped together in the random assignment process (see Appendix A). 

β1

2. Covariates 

In the impact estimation, we controlled for several baseline student characteristics. 

Tables B.1 and B.2 show summary statistics of the covariates in the TFA and Teaching Fellows 

study samples, respectively.

3. Degrees of Freedom for Hypothesis Tests

We used a two-sided t-test to test the null hypothesis, 1 β = 0. Because sandwich standard 

errors in finite samples have the potential to lead to overrejection of null hypotheses, we 

conducted hypothesis tests in the impact analyses based on a t-distribution that guarded against 

overrejection. Following Donald and Lang (2007) and Angrist and Pischke (2009), we used a 

t-distribution with degrees of freedom equal to the number of teachers minus the number of 

independent variables that varied only at the teacher level, with the teacher-level variables 

consisting of the treatment status indicator and the classroom match indicators. For these 

degrees-of-freedom calculations only, we amalgamated classroom matches that shared the same 

teacher so that the resulting classroom match indicators truly varied only at the teacher level.

4. Handling Missing Data: Main Approach 

Our main estimation approach included only students who had valid outcome scores in the 

analysis sample for the experimental analyses. For randomized controlled trials, simulations in a 

recent study suggest that impact estimates based only on cases with observed outcome data may 

have only a small amount of bias (0.05 standard deviations or less) when the outcome data are 

missing at random among students with the same baseline covariate values (Puma et al. 2009). 

Missing covariate data were imputed. For each covariate, we replaced missing values with 

the mean of the covariate based on research sample students in the same classroom match who 

had nonmissing values of that covariate. If data on the covariate were missing for all students in 

a classroom match, missing values were replaced with the covariate mean in the full research 

sample. In the impact estimation, we controlled for binary indicators that denoted whether a 
Effectiveness of TFA and Teaching Fellows Teachers 

B.8 

student had an imputed value for a specified covariate (see Tables B.1 and B.2). Consequently, 

the impact estimates were unaffected by our choice for the exact numeric values used to replace 

missing covariate data, so long as these imputed values were constant within classroom matches. 

Simulations by Puma et al. (2009) have shown that this approach to handling missing covariate 

data is likely to keep estimation bias at less than 0.05 standard deviations. 

Table B.1. Means and Standard Deviations of Covariates Included in Models for Estimating the Impacts of TFA Teachers

Assigned to TFA 

Teachers

Assigned to Comparison 

Teachers

Mean

Standard 

Deviation N Mean

Standard 

Deviation N 

Difference 

in Means

p-Value of 

Difference

Baseline Achievement

Baseline math score (z-score) -0.512 0.870 2,073 -0.504 0.853 2,080 -0.008 0.531

Baseline reading score (z-score) -0.514 0.908 2,078 -0.510 0.893 2,090 -0.005 0.734

Demographic Characteristics

Old for grade 0.073 0.261 2,252 0.064 0.245 2,253 0.009 0.098

Grade is below modal grade in 

classroom match 0.011 0.113 2,252 0.014 0.117 2,254 -0.003 0.084

Grade is above modal grade in 

classroom match 0.021 0.143 2,252 0.016 0.127 2,254 0.005 0.160

Retained in same grade between 

previous and current year 0.022 0.146 2,132 0.024 0.154 2,130 -0.002 0.551

Female 0.486 0.500 2,284 0.500 0.500 2,273 -0.015 0.102

Black, non-Hispanic 0.621 0.487 2,274 0.625 0.484 2,262 -0.004 0.656

Hispanic 0.283 0.452 2,274 0.277 0.448 2,262 0.005 0.471

Non-black, non-Hispanica 0.096 0.300 2,274 0.098 0.297 2,262 -0.002 0.774

Eligible for free/reduced-price lunch 0.899 0.305 1,417 0.905 0.293 1,399 -0.007 0.469

Limited English proficient 0.080 0.276 2,284 0.084 0.277 2,273 -0.004 0.475

Individualized education plan 0.064 0.245 2,284 0.060 0.237 2,273 0.004 0.358

Time Since Baseline Math Test

1 yeara 0.814 0.396 2,292 0.808 0.394 2,281 0.005 0.385

2 years 0.072 0.260 2,292 0.082 0.274 2,281 -0.010** 0.006

3 years 0.023 0.161 2,292 0.021 0.143 2,281 0.002 0.470

4 or 5 years 0.001 0.035 2,292 0.000 0.021 2,281 0.001 0.316

Imputation Indicators

Baseline math score 0.091 0.291 2,292 0.089 0.284 2,281 0.003 0.659

Baseline reading score 0.089 0.288 2,292 0.084 0.278 2,281 0.004 0.400

Old for grade 0.016 0.131 2,292 0.012 0.110 2,281 0.004* 0.018

Current grade 0.016 0.131 2,292 0.012 0.108 2,281 0.004** 0.006

Retained in same grade 0.063 0.252 2,292 0.066 0.249 2,281 -0.003 0.373

Gender 0.003 0.059 2,292 0.003 0.059 2,281 0.000 0.673

Race/ethnicity 0.007 0.086 2,292 0.009 0.094 2,281 -0.002 0.073

Eligible for free/reduced-price lunch 0.377 0.487 2,292 0.377 0.485 2,281 0.000 0.703

Limited English proficient 0.003 0.059 2,292 0.003 0.059 2,281 0.000 0.703

Individualized education plan 0.003 0.059 2,292 0.003 0.059 2,281 0.000 0.703

Total Number of Students in the 

Analysis Sample 2,292 2,281

Source: District administrative records.

Note: Means and differences are adjusted for classroom match fixed effects. P-values are based on a regression of the 

specified variable on a TFA indicator and classroom match indicators, accounting for sample weights and clustering 

at the teacher level.

a

Omitted category in regression models.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

N = number of observations, excluding imputed values; TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

B.9 

Table B.2. Means and Standard Deviations of Covariates Included in Models for Estimating the Impacts of Teaching 

Fellows

Assigned to Teaching 

Fellows

Assigned to Comparison 

Teachers

Mean

Standard 

Deviation N Mean

Standard 

Deviation N 

Difference 

in Means

p-Value of 

Difference

Baseline Achievement

Baseline math score (z-score) -0.111 0.913 1,930 -0.104 0.891 1,795 -0.007 0.636

Baseline reading score (z-score) -0.064 0.984 1,924 -0.048 0.990 1,789 -0.016 0.418

Demographic Characteristics

Old for grade 0.035 0.174 1,981 0.030 0.172 1,838 0.004 0.175

Grade is below modal grade in 

classroom match 0.047 0.207 2,106 0.049 0.216 1,964 -0.002 0.581

Grade is above modal grade in 

classroom match 0.052 0.221 2,106 0.046 0.209 1,964 0.006 0.195

Retained in same grade between 

previous and current year 0.017 0.124 2,024 0.021 0.144 1,893 -0.004 0.300

Female 0.531 0.499 2,106 0.541 0.498 1,964 -0.010 0.326

Black, non-Hispanic 0.504 0.500 2,106 0.488 0.500 1,964 0.016* 0.047

Hispanic 0.349 0.475 2,106 0.368 0.482 1,964 -0.019* 0.038

Non-black, non-Hispanica 0.147 0.368 2,106 0.144 0.352 1,964 0.002 0.810

Eligible for free/reduced-price lunch 0.737 0.441 2,105 0.759 0.428 1,963 -0.021* 0.017

Limited English proficient 0.077 0.262 2,106 0.072 0.258 1,965 0.005 0.332

Individualized education plan 0.067 0.247 2,106 0.061 0.240 1,964 0.006 0.233

Time Since Baseline Math Test

1 yeara 0.607 0.490 2,127 0.614 0.487 1,989 -0.007 0.304

2 years 0.159 0.367 2,127 0.163 0.369 1,989 -0.003 0.425

3 years 0.125 0.339 2,127 0.115 0.319 1,989 0.010** 0.008

4 or 5 years 0.011 0.101 2,127 0.015 0.123 1,989 -0.004 0.116

Imputation Indicators

Baseline math score 0.098 0.297 2,127 0.094 0.291 1,989 0.004 0.605

Baseline reading score 0.099 0.301 2,127 0.097 0.296 1,989 0.003 0.733

Old for grade 0.067 0.269 2,127 0.065 0.247 1,989 0.002 0.397

Current grade 0.013 0.109 2,127 0.011 0.102 1,989 0.002 0.434

Retained in same grade 0.050 0.221 2,127 0.046 0.209 1,989 0.004 0.417

Gender 0.013 0.109 2,127 0.011 0.102 1,989 0.002 0.434

Race/ethnicity 0.013 0.109 2,127 0.011 0.102 1,989 0.002 0.434

Eligible for free/reduced-price lunch 0.013 0.111 2,127 0.011 0.105 1,989 0.002 0.466

Limited English proficient 0.013 0.109 2,127 0.010 0.100 1,989 0.003 0.312

Individualized education plan 0.013 0.109 2,127 0.011 0.102 1,989 0.002 0.434

Total Number of Students in the 

Analysis Sample 2,127 1,989

Source: District administrative records.

Note: Means and differences are adjusted for classroom match fixed effects. P-values are based on a regression of the 

specified variable on a Teaching Fellows indicator and classroom match indicators, accounting for sample weights 

and clustering at the teacher level.

a

Omitted category in regression models.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

N = number of observations, excluding imputed values.
Effectiveness of TFA and Teaching Fellows Teachers 

B.10 

5. Handling Missing Data: Alternative Approach 

In sensitivity analyses reported in Appendix F, we used multiple imputation (Rubin 1987) to 

replace missing values of the outcome variable and/or covariates in the estimation of 

Equation (B.5). To generate the imputed data, we conducted multiple imputation by chained 

equations (MICE) (van Buuren et al. 1999) using data on all research sample students with 

parental consent. In particular, we specified imputation models in which each variable to be 

imputed—referred to as a variable of interest—was modeled as a function of predictor variables. 

The imputation model was linear except when imputing race/ethnicity, an unordered categorical 

variable, which was imputed with a multinomial logit specification.

The estimated coefficients and standard errors from each imputation model were used to 

form a posterior distribution for the true coefficients of the imputation model. We made a 

random draw from this posterior distribution and then used the resulting draw to generate 

predictions of the variable of interest for all students. For each student with a missing value for 

the variable of interest, we assigned an imputed value equal to the observed value of the student 

who had the nearest prediction, in a process known as predictive mean matching. We repeatedly 

applied this procedure to generate 10 stochastically imputed values for each missing value. 

We conducted MICE separately on each of four subsamples: (1) students assigned to TFA 

teachers, (2) students assigned to comparison teachers who were compared with TFA teachers, 

(3) students assigned to Teaching Fellows, and (4) students assigned to comparison teachers who 

were compared with Teaching Fellows. Following standard practice (see, for example, Puma et 

al. 2009), the imputation model for a given variable of interest used all other variables from 

Equation (B.5) as predictors. That is, we generated imputed values for the outcome variable 

based on all covariates, and we generated imputed values for a given covariate based on all other 

covariates and the outcome variable.

We then estimated Equation (B.5) by using multiply imputed data to replace missing values 

of (1) covariates only, (2) the outcome variable only, or (3) both the outcome variable and the 

covariates (see Appendix F). Estimates that used multiply imputed outcome data were no longer 

limited to analysis sample members; instead, we used all research sample members with parental 

consent.26

6. Estimation Models for Subgroup Analyses 

Several of the subgroup analyses assessed the impact of a specified type of TFA/Teaching 

Fellows teacher compared with two different types of comparison teachers separately. In these 

cases, we modified Equation (B.5) so that impacts could differ according to the type of 

comparison teacher. For example, to estimate the impacts of TFA or Teaching Fellows teachers 

relative to comparison teachers from traditional and alternative certification routes (TC and AC 

teachers, respectively) separately, we used an estimation model of the form

 26 With Stata, we used the “ice” command (Royston 2004, 2005) to generate multiply imputed data, and we 

used the “mi estimate” command to produce impact estimates and standard errors with the multiply imputed data 

based on Rubin’s (1987) formulas.
Effectiveness of TFA and Teaching Fellows Teachers 

B.11 

 (B.6) y TC AC ijk k =+ + + + α δ δ βε 1 2 jk jk ijk ijk X , 

where TCjk is an indicator for TC teachers, ACjk is an indicator for AC teachers, and all other 

variables are defined as in Equation (B.5). The negative of 1 δ and the negative of 2 δ represent 

the impacts of TFA/Teaching Fellows teachers relative to comparison teachers from, 

respectively, traditional and alternative routes. We used estimation models of a similar structure 

when assessing the impacts of TFA/Teaching Fellows teachers with a specified experience level 

relative to novice and experienced comparison teachers separately.

In other subgroup analyses, we estimated the impacts of TFA/Teaching Fellows teachers 

relative to comparison teachers separately within middle and high schools. These estimates were 

based on a variant of Equation (B.5) in which the indicator for TFA/Teaching Fellows teachers 

was interacted with an indicator for middle schools. 

7. Adjustments for Multiple Hypothesis Testing

Because the study tested the statistical significance of several impact estimates—including 

overall and subgroup-specific impact estimates—the likelihood of finding a difference that was 

significant at the 5 percent level for any given outcome or subgroup simply due to chance would 

have been greater than 5 percent if no corrections were made to account for these multiple 

hypothesis tests. However, adjusting for all hypothesis tests conducted in the study would have 

severely limited the study’s power to detect any impacts at all. To balance these competing 

factors, we designated the following six impact estimates to be of primary interest, and adjusted 

significance tests for these estimates to account for multiple hypothesis testing using the 

approach formulated by Benjamini and Hochberg (1995): 

• Impacts of TFA teachers relative to all comparison teachers

• Impacts of TFA teachers relative to TC comparison teachers

• Impacts of TFA teachers relative to AC comparison teachers

• Impacts of Teaching Fellows relative to all comparison teachers

• Impacts of Teaching Fellows relative to TC comparison teachers

• Impacts of Teaching Fellows relative to AC comparison teachers

Across these six impact estimates, our adjustment controlled the false discovery rate—the 

expected proportion of statistically significant findings that were spurious—at five percent. 

Because we did not adjust statistical tests in any of the remaining subgroup analyses, there was a 

greater likelihood that significant findings from these remaining analyses were spurious. 

E. Analytic Methods in the Nonexperimental Analyses

1. Model for Estimating Relationships between Teacher Characteristics and Student 

Achievement

We estimated the relationships between teacher characteristics and student math 

achievement by augmenting the experimental impact model with measures of teacher 

characteristics as additional independent variables. The resulting regression model, which we 
Effectiveness of TFA and Teaching Fellows Teachers 

B.12 

estimated on the pooled set of observations from the TFA and Teaching Fellows study samples, 

had the following specification: 

 (B.7) 12 3

4 5

C

 (X ) (X ) ,

ijk k jk jk jk

ijk ijk ijk ijk ijk

y TFA Fellow

TFASam FellowSam

αγ γ γ

γ γ ε

=+ + +

+ × +× +

where TFAjk and Fellowjk are binary indicators for being assigned to TFA teachers and 

Teaching Fellows, respectively; Cjk is a set of teacher characteristics with coefficients 3 γ ; 

TFASamijk and FellowSamijk are binary indicators for the TFA and Teaching Fellows study 

samples, respectively; and all other variables are defined as in Equation (B.5). The teacher 

characteristics included in Cjk are those listed in Table II.7 of Chapter II, and the student-level 

covariates ( Xijk ) are the same ones used in the experimental impact models (see Tables B.1 and 

B.2). Without teacher characteristics in Equation (B.7), estimates of 1 γ and 2 γ would exactly 

replicate the experimentally estimated impacts of TFA and Teaching Fellows teachers, 

respectively. As a result, this specification permitted a direct analysis of the extent to which the 

measured teacher characteristics accounted for the experimental impacts, as discussed later.

The parameters of primary interest were the coefficients in 3 γ , which captured the 

association between teacher characteristics and student math achievement. We estimated variants 

of Equation (B.7) that included either all teacher characteristics simultaneously or only a single 

teacher characteristic. In all estimates, we applied sample weights and clustered standard errors 

at the teacher level.

2. Handling Missing Data in the Measures of Teacher Characteristics

The nonexperimental analyses required more complex methods for handling missing data 

than the experimental analyses. In the experimental analyses, the independent variable of 

interest—treatment status—was nonmissing for all students. The other covariates, which had 

some missing data, were expected to be uncorrelated with the variable of interest due to random 

assignment, so a relatively simple method—mean imputation along with the inclusion of 

imputation indicators—could account for missing data in a manner that kept bias low. 

In the nonexperimental analyses, the variables of interest—those that measured teacher 

characteristics—had some missing values. It was therefore important to handle missing data in a 

manner that preserved the observed distributions of the teacher characteristics and the observed 

relationships between each characteristic and the other variables in the analysis. Because 

multiple imputation met these objectives (Schafer and Graham 2002), we applied this procedure 

to account for missing data in the measures of teacher characteristics.

We imputed missing data in the teacher-level variables through MICE. We used the same 

general approach to implementing MICE as that used in the sensitivity analyses of the 

experimental estimates (described in Section D). The procedure generated 10 imputed values for 

each missing value of a teacher characteristic. Because middle and high school teachers differed 

in the type of Praxis assessment for which data were needed, we applied MICE separately to four 

groups of teachers, defined based on state, grade, and entry route: (1) TFA and Teaching Fellows 

teachers who were supposed to have Praxis II Mathematics Content Knowledge scores; 
Effectiveness of TFA and Teaching Fellows Teachers 

B.13 

(2) comparison teachers who were supposed to have Praxis II Mathematics Content Knowledge 

scores; (3) TFA and Teaching Fellows teachers who were supposed to have Praxis II Middle 

School Mathematics scores; and (4) comparison teachers who were supposed to have Praxis II 

Middle School Mathematics scores.

The imputation model for a specified teacher characteristic included all other teacher 

characteristics as predictors. Every imputation model also included the student outcome variable 

(y) and the student covariates (X). Because teacher characteristics did not vary within classes, we 

averaged all student-level variables to the classroom level and estimated the imputation models 

at the classroom level. However, some teachers in the study taught more than one class; initial 

imputed values of a particular teacher characteristic could therefore differ across classes taught 

by the same teacher. To eliminate differences in imputed values for the same teacher within the 

same imputation round, we took either the mode (for binary variables), median (for ordinal 

variables), or mean (for continuous variables) of the initial imputed values across classes taught 

by the same teacher.

3. Specification of Praxis Score Variables

As discussed in Chapter II, the study used two different assessments to measure teachers’ 

knowledge of math concepts: (1) the Praxis II Mathematics Content Knowledge test for high 

school teachers, and (2) the Praxis II Middle School Mathematics test for middle school teachers. 

In our main specification, we expressed a teacher’s score from a given Praxis II assessment as a 

z-score based on the mean and standard deviation of scores among comparison teachers who 

took the same assessment.

To account for the possibility that the relationship between teachers’ Praxis II scores and 

student math achievement could differ by the type of Praxis II assessment that teachers took, we 

included into Equation (B.7) separate variables for scores from the two Praxis II assessments. 

The two variables were constructed as interactions between a teacher’s z-score and (1) an 

indicator for whether a teacher was supposed to have taken the Mathematics Content Knowledge 

assessment, and (2) indicator for whether a teacher was supposed to have taken the Middle 

School Mathematics assessment. The coefficient on each interaction term captured the 

relationship between Praxis II scores from the specified assessment and students’ math 

achievement. Because the Praxis type indicators did not vary within classroom matches, there 

was need to control for these indicators in addition to the classroom match indicators in 

Equation (B.7).

4. Accounting for the Impacts of TFA Teachers

Based on the estimates of Equation (B.7), we assessed the extent to which differences in 

effectiveness between TFA and comparison teachers, reported in Chapter V, could be accounted 

for by the groups’ difference in characteristics.27

 27 We did not conduct a parallel analysis for the Teaching Fellows sample because we did not find a 

statistically significant impact of Teaching Fellows teachers relative to comparison teachers.

Specifically, we calculated the difference in 

effectiveness between these groups that would be predicted based on each teacher characteristic. 

This predicted difference was the product of two quantities: (1) the association between the 
Effectiveness of TFA and Teaching Fellows Teachers 

B.14 

characteristic and student achievement and (2) the difference between TFA and comparison 

teachers with regard to this characteristic.

Formally, for each of the teacher characteristics listed in Table II.7, we calculated the 

predicted TFA-comparison difference in effectiveness based on that teacher characteristic, as 

follows. Let ( )r Cjk be the measure of the rth characteristic for teacher j. First, from the estimates of 

Equation (B.7) that controlled for all teacher characteristics, we obtained the estimated 

coefficient, ( )

3

ˆ r γ , on ( )r Cjk . Second, to calculate the difference between TFA and comparison 

teachers on the rth characteristic, we estimated a student-level regression of the form 

 (B.8) 

( ) ( ) ( )

1 2

( ) ( )

3 4 (X ) (X )

rr r

jk k jk jk

r r

ijk ijk ijk ijk ijk

C TFA Fellow

TFASam FellowSam

απ π

π π ε

=+ +

+× +× +

where all variables are defined as in Equation (B.7). The estimated coefficient on the TFA 

indicator, ( )

1ˆ r π , represents the difference in the rth characteristic between TFA and comparison 

teachers. Estimates of Equation (B.8) were based on student-level data rather than teacher-level 

data in order to provide an exact decomposition of the total TFA impact into explained and 

unexplained portions, as discussed next.

From the two preceding steps, the predicted difference in effectiveness between TFA and 

comparison teachers based on the rth characteristic was the product, () ()

3 1 ˆ ˆ r r γ π . Mathematically, the

predicted TFA-comparison differences in effectiveness based on all measured characteristics, 

along with the unexplained difference in effectiveness ( 1 γˆ ) from Equation (B.7), summed to the 

total TFA-comparison difference in effectiveness from the experimental analyses.
APPENDIX C

SUPPLEMENTARY INFORMATION ON TEACH FOR AMERICA 

AND TEACHING FELLOWS PROGRAMS
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

C.3 

This appendix presents supplementary information on Teach For America (TFA) and the 

Teaching Fellows programs. Figure C.1 lists the 43 TFA regions as of August 2011. Figure C.2 

lists TFA’s Teaching As Leadership rubric, which includes six principles of leadership, each 

with specific teacher actions intended to improve student achievement. Figure C.3 lists the 

19 Teaching Fellows programs and similar programs affiliated with TNTP as of August 2011. 

Finally, in support of Chapters III and VI, Table C.1 summarizes how participants in TFA and 

the Teaching Fellows programs in the study sample were selected, trained, and supported. 

Figure C.1. Teach For America Regions, as of August 2011

Connecticut

New England

Greater Boston

Rhode Island

Baltimore

East

D.C. Region

Delaware

Greater Newark

Greater Philadelphia

New York

Alabama

Southeast

Appalachia

Charlotte

Eastern North Carolina

Greater Nashville

Greater New Orleans

Jacksonville

Memphis

Metro Atlanta

Miami-Dade

Mississippi Delta

South Carolina

South Louisiana

Chicago

Midwest

Detroit

Indianapolis

Kansas City

Milwaukee

South Dakota

St. Louis

Twin Cities

Dallas-Fort Worth

Southwest

Houston

New Mexico

Oklahoma

Phoenix

Rio Grande Valley

San Antonio

Bay Area

West

Colorado

Hawai’i

Las Vegas Valley

Los Angeles

Seattle-Tacoma

Source: http://www.teachforamerica.org/where-we-work. 
Effectiveness of TFA and Teaching Fellows Teachers 

C.4 

Figure C.2. Teach For America’s Teaching as Leadership Rubric

Set Big Goals

• Set ambitious goals for student achievement

Invest Students and Their Families/Influencers in Working Hard to Reach the Big Goals

• Instill “I can” in students

• Instill “I want” in students

• Use role models

• Reinforce academic efforts

• Create a welcoming environment

• Mobilize families and influencers

Plan Purposefully

• Develop assessments

• Create long-term and unit plans (backward design)

• Lesson plan

• Differentiate

• Develop behavioral management plans

• Classroom procedures

Execute Effectively

• Clearly present academic content

• Manage student practice

• Check for understanding

• Reinforce rules and consequences

• Implement time-saving procedures

• Track student performance

Continuously Increase Effectiveness

• Gauge progress and gaps

• Identify contributing student actions

• Identify teacher actions

• Identify underlying factors

• Access learning experiences

• Adjust course

Work Relentlessly

• Persist in the face of challenges

• Expand time and resources

• Sustain energy

Source: http://www.teachingasleadership.org/. 
Effectiveness of TFA and Teaching Fellows Teachers 

C.5 

Figure C.3. TNTP’s Teaching Fellows Programs, as of August 2011

Baltimore City Teaching Residency

East Coast

DC Teaching Fellows

Delaware Teaching Fellows

New York City Teaching Fellows

Philadelphia Teaching Fellows

Rhode Island Teaching Fellows

The Teacher Academy Residency (Pittsburgh)

Chicago Teaching Fellows

Midwest

Denver Teaching Fellows

Indianapolis Teaching Fellows

Milwaukee Teaching Fellows

Arizona Teaching Fellows

South/Southwest

Georgia Teaching Fellows

Memphis Teaching Fellows

Nashville Teaching Fellows

TeachNOLA (New Orleans)

TEACH Charlotte

Texas Teaching Fellows

Oakland Teaching Fellows

West Coast

Source: http://tntp.org/become-a-teacher/. 
Effectiveness of TFA and Teaching Fellows Teachers 

C.6 

Table C.1. Similarities and Differences in TFA and the Teaching Fellows Programs

TFA Teaching Fellows Programs

Program Administration 

and Location

National program; it serves numerous regions 

around the country

TNTP has set up Teaching Fellows programs 

in numerous locations around the country; 

programs have distinct identities, but TNTP 

oversees them all.

Application Forms and 

Locality Requests

One form submitted to national program 

office; applicants may express their interest in 

being assigned to particular regions; no 

guarantee that preferences will be met

Each program has its own application form; 

applicants to programs serving a region with 

several districts specify locality of interest.

Participant Commitment 2 years No commitment

Writing Requirements of 

the Application

Applicants submit a letter of intent explaining, 

in 500 words or fewer, why they want to join 

TFA, what they hope to accomplish in the 

program, and how they would determine their 

success in the program

Applicants answer three questions 

(concerning, for example, their interest in the 

program and their qualifications); each 

answer should be 200 to 400 words.

Steps in the Application 

and Selection Processes

as of Spring 2010

Online application, telephone interview,a inperson assessment

Online application, in-person assessment

Activities in the In-Person 

Assessment as of Spring 

2010

Sample teaching lesson, group discussion, 

problem-solving activity,b one-on-one 

interview

Sample teaching lesson, writing exercise, 

group discussion, one-on-one interview

Core Competencies 

Sought in the Application 

and Selection Processes

1. Demonstrated leadership and achievement 

in academic, professional, extracurricular, 

or volunteer arenas

2. Perseverance and sustained focus in the 

face of challenges

3. Critical thinking skills

4. Organizational ability

5. Respect for individuals’ diverse 

experiences and ability to work effectively

with people from a variety of backgrounds

6. Interpersonal skills to motivate and lead 

others

7. An understanding of and desire to work 

relentlessly in pursuit of the organization’s 

vision

1. Critical thinking

2. Achieving ambitious goals

3. Personal responsibility and accountability

4. Commitment to students in high-need 

schools

5. Dedication to continuous improvement

6. Communication skills

7. Respectful and positive in all situations

Objective Eligibility 

Criteria for Program 

Admission and/or District 

Hiring

1. Hold a bachelor’s degree

2. Have a cumulative undergraduate GPA of 

at least 2.5

3. Meet all applicable state-specified 

coursework requirements

4. Pass all state-required tests for new 

teachers

5. Not have been involved in certain criminal 

proceedings

6. Be a U.S. citizen or national or legal 

permanent resident

1. Hold a bachelor’s degree

2. Not be or have been in process of earning 

a degree in education or a teaching 

certificate

3. Meet minimum cumulative undergraduate 

GPA requirement (varies by program; 

minimum allowed across programs in the 

study: 2.5)

4. Meet all applicable state requirements for 

subject area coursework

5. Pass all state-required tests for new 

teachers

6. Pass a background check

7. Meet citizenship or residency requirements

Application Review and 

Selection Process for 

Deciding Which 

Candidates to Consider 

Further and Admit to the 

Program

Combination of staff judgment and a 

computerized algorithm

Staff judgment
Effectiveness of TFA and Teaching Fellows Teachers 

C.7 

TFA Teaching Fellows Programs

Program Admission and 

Yield Rates (programestimated averages over 

3 recent years)

50% of all applicants invited to in-person 

assessment

12% of all applicants offered admission

80% of admitted applicants enrolled

63% of all applicants invited to in-person 

assessment

13% of all applicants offered admission

77% of admitted applicants enrolled

Pre-Institute Activities 30 to 40 hours of independent study and 

regional induction of up to one week

25 hours of independent study and a 4-hour 

orientation meeting

Summer Institute 

Location

Eight locations around the country; each 

serves several regional programs

Each program has its own institute(s)

Institute Curriculum Uniform across locations Uniform across programs

Other Types of 

Instructional Activities 

and Meetings

Uniform across locations; exceptions for new 

components under development

Variable; adapted to district(s) served

Estimated Hours Spent 

Receiving Instruction 

During Institute

109 68

Institute Fieldwork 

(“practice teaching”)

Corps members assigned in groups of 3 to 4 

to summer school classrooms, spend 

estimated 20 hours tutoring small groups, 

20 hours leading instruction for whole class

Goal is minimum 15 days in summer school 

classroom, 5 hours a day; Teaching Fellows

are assigned in pairs, take increasing 

responsibility for instruction, building up to 2 

consecutive full days; estimated average total 

fieldwork: 64 hours

Math Immersion 

Programs for Individuals 

Who Might Not Otherwise 

Qualify to Teach 

Secondary Math

None at present, but one summer institute 

offers an online training course to help 

qualified secondary math teacher candidates 

hone their math knowledge and skills

Mandatory for certain candidates in three of 

the Teaching Fellows programs in the study

Removal of 

Underperforming 

Participants

Officials do dismiss participants viewed as not 

well suited for teaching, but reported that data 

on dismissal rates were not sufficiently 

reliable (for example, could not definitively 

distinguish dismissals from departures for 

other reasons), and would not be made public

Officials do “out-place” participants viewed as 

not well suited for teaching, but reported it as 

rarely necessary. Of the approximately 6 

percent of Teaching Fellows who did not 

complete summer institute, fewer than onefourth were out-placed. Out-placement also 

occurs during the first year of teaching, but 

data on frequency were not readily available.

Placement/Hiring for 

Specific Teaching Jobs

Corps members typically interview with 

potential hiring principals, but often decisions 

about where to interview and where corps 

members will teach are not made by the 

corps members, but instead made by district, 

school, or regional program officials

Teaching Fellows typically select, on their

own, the schools at which to interview and 

which hiring offer to accept.

Percentage of 

Candidates Placed 

Before Start of School 

Year (program-estimated 

averages over 3 recent 

years)

98% of all candidates

100% of secondary math candidates

92% of all candidates

95% of secondary math candidates

Post-Placement 

Instruction/Training and 

Support

Staff provide training on topics such as 

classroom management, lesson planning, 

goal setting, student assessment, and 

pedagogy, guided by corps member’s needs. 

The average amount of training reported 

across regions was 42 hours. Staff observe 

corps members in their classrooms; 4 to 5 

times over a 2-year period is a commonly 

reported frequency for these observations. 

Staff also provide individualized support as 

needed.

Staff deliver 10 hours of training on practical 

topics such as classroom management, the 

use of data to inform instruction, and tailoring 

instruction for different students. Staff also 

conduct at least 2 classroom observations of 

each Teaching Fellow, have at least 2 checkin meetings, and may have additional 

meetings as needed.
Effectiveness of TFA and Teaching Fellows Teachers 

C.8 

TFA Teaching Fellows Programs

Enrollment in Local 

Alternative Certification 

Program Required for 

Secondary Math 

Teachers

Yes, if state or district requires enrollment for 

all new teachersc

Yes

Operators of Alternative 

Certification Programs 

Attended by Participants

Universities, districts, TNTP, TFA Universities, districts, TNTP

Estimated Total Hours of 

Instruction that 

Secondary Math 

Teachers Received in 

Focal Alternative 

Certification Program

Varies by program; among focal programs in 

the study, range was 54 to more than 315d

Varies by program; among focal programs 

examined in the study, range was 61 to 250

Financial Support for 

Participants

All participants receive as many AmeriCorps 

education awards (up to 2) as they are 

eligible for; TFA covers all institute and 

orientation costs; need-based no-interest 

loans and grants can be used to cover certain 

other costs associated with joining TFA; in 

some regions, other sources help cover 

certification program costs.

Varies by program; some arrange for 

AmeriCorps education awards, some 

leverage other sources to help cover 

certification program costs.

a

Some applicants were allowed to bypass the telephone interview.

b

Starting in 2011, this component was moved from the in-person assessment to before the telephone interview or before the 

in-person assessment.

c

This was not required for all new secondary math teachers in one of the 10 regional programs in the study.

d

This was reportedly the amount of instruction in the first two years of a three-year program.

GPA = grade point average; TFA = Teach For America.
APPENDIX D

TEACH FOR AMERICA AND TEACHING FELLOWS TEACHERS 

COMPARED WITH COMPARISON TEACHERS BY ENTRY ROUTE 

(ALTERNATIVE OR TRADITIONAL)
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

D.3 

In Chapters IV and VII of this report, we compared Teach For America (TFA) and Teaching 

Fellows teachers, respectively, with the full set of comparison teachers with whom they were 

matched. However, the study’s comparison teachers included teachers from both traditional (TC) 

and alternative (AC) routes to certification, two very different pathways into teaching, and we 

are interested in the impacts of TFA and Teaching Fellows teachers relative to teachers from TC 

and AC routes separately as well as combined. To provide context for these impact estimates, in 

this appendix we separately examine the characteristics of TFA and Teaching Fellows teachers 

relative to the AC and TC comparison teachers with whom they were matched. 

A. TFA Teachers and the Comparison Teachers with Whom They Were Matched

As discussed in Chapter IV, for most of the characteristics we examined, patterns of 

differences between TFA and the comparison teachers with whom they were matched were 

similar for comparison teachers from both TC and AC routes. This included demographic 

characteristics (Table D.1), average number of college-level math courses (Table D.3), Praxis II 

scores (Table D.4), teaching experience (Table D.5), teacher support during the school year 

(Table D.8), and teacher satisfaction with teaching at his or her school (Table D.9). 

However, there were also some differences in TFA comparisons to teachers from AC and 

TC routes: 

• Although patterns related to educational background were generally similar when 

comparing TFA teachers with comparison teachers from TC and AC routes, TFA 

teachers were much less likely to have majored or minored in education than TC 

comparison teachers, whereas none of the AC teachers in the sample or the TFA 

teachers to whom they were matched had an education major or minor (Table D.2).

• Although TFA teachers had less nonteaching work experience than comparison 

teachers from both AC and TC routes, the differences were smaller and not 

consistently statistically significant when comparing TFA teachers with TC 

comparison teachers (Table D.5).

• TFA teachers generally reported having received less training and support than TC 

comparison teachers but received similar or larger amounts of training and support 

than AC comparison teachers (Table D.6). 

• Although TFA teachers were more likely to have taken coursework during the school 

year compared with comparison teachers from both AC and TC routes, differences 

between TFA teachers and AC comparison teachers were smaller and were not 

statistically significant (Table D.7). 

B. Teaching Fellows and the Comparison Teachers with Whom They Were 

Matched

Patterns of differences between Teaching Fellows and the comparison teachers with whom 

they were matched were also similar for comparison teachers from both TC and AC routes for 

many characteristics, as discussed in Chapter VII. This included average number of college-level 

math courses (Table D.12), Praxis II scores (Table D.13), teaching experience (Table D.14), and 

teacher satisfaction with teaching at his or her school (Table D.17). 
Effectiveness of TFA and Teaching Fellows Teachers 

D.4 

There were also some differences in Teaching Fellows comparisons with teachers from AC 

and TC routes: 

• Comparison teachers from AC routes were much more likely to be nonwhite or 

Hispanic than the Teaching Fellows with whom they were matched, whereas the 

difference between teachers from TC routes and the Teaching Fellows with whom 

they were matched was smaller, although still statistically significant (Table D.10).

• Teaching Fellows were more likely to have a degree from a selective college or 

university than TC comparison teachers, whereas the difference between Teaching 

Fellows and AC comparison teachers was smaller and not statistically significant

(Table D.11). 

• Teachers from TC routes were significantly more likely to have majored or minored 

in secondary math education than the Teaching Fellows with whom they were 

matched, whereas none of the teachers from AC routes or the Teaching Fellows with 

whom they were matched had a secondary math education major or minor (Table 

D.11). 

• The amount of nonteaching work experience of Teaching Fellows in the study 

exceeded that of TC comparison teachers but was statistically indistinguishable from 

that of AC comparison teachers (Table D.14). 

• Although neither difference was statistically significant at the 5 percent level, 

Teaching Fellows matched to TC comparison teachers reported receiving fewer hours 

of math pedagogy instruction than the comparison teachers, whereas Teaching 

Fellows matched to AC comparison teachers reported receiving more hours than the 

comparison teachers (Table D.15).

• Teaching Fellows completed less student teaching in math, on average, than 

comparison teachers from TC routes, whereas Teaching Fellows completed more 

days of student teaching in math than comparison teachers from AC routes, although 

the latter difference was not statistically significant (Table D.15). 
D.5 

Table D.1. Demographic Characteristics of Teachers in the TFA Study Sample, by Entry Route (percentages unless otherwise indicated)

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

Characteristic

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Age (average years) 24.2 38.3 -14.1** 0.000 24.7 37.3 -12.6** 0.000

Female 59.0 80.0 -21.0* 0.049 58.6 78.6 -20.0 0.108

Race/Ethnicity

White, Non-Hispanic 79.5 25.7 53.8** 0.000 72.4 17.9 54.6** 0.000

Nonwhite or Hispanic 20.5 74.3 -53.8** 0.000 27.6 82.1 -54.6** 0.000

Sample Size 39 35 29 28

Source: Survey of Secondary Math Teachers.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.6 

Table D.2. Educational Background of Teachers in the TFA Study Sample, by Entry Route (percentages unless otherwise indicated)

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Bachelor’s Degree

From a highly selective college or universitya 28.2 8.3 19.9* 0.037 31.0 0.0 31.0** 0.001

From a selective college or universitya 76.9 29.2 47.8** 0.000 86.2 15.0 71.2** 0.000

Majorb

Math 12.8 26.1 -13.3 0.223 0.0 25.0 -25.0* 0.015

Secondary math education 0.0 30.4 -30.4** 0.003 0.0 0.0 0.0 n.a.

Other subject 94.9 65.2 29.7** 0.007 100.0 75.0 25.0* 0.015

Major or minorb

Math 12.8 34.8 -22.0 0.060 10.3 25.0 -14.7 0.207

Secondary math education 0.0 39.1 -39.1** 0.000 0.0 0.0 0.0 n.a.

Other subject 97.4 69.6 27.9** 0.008 100.0 80.0 20.0* 0.033

Graduate Degree 43.6 74.3 -30.7** 0.007 34.5 64.3 -29.8* 0.024

Sample Size 39 35 29 28

Source: Survey of Secondary Math Teachers.

a

Highly selective colleges are those ranked by Barron’s as most competitive. Selective colleges are those that are ranked by Barron’s as very competitive, highly 

competitive, or most competitive.

b

Percentages might not sum to 100 if some sample members had a degree in more than one subject or had a degree in math education, which counts as both a 

math-related major and an education major.

c

Includes statistics, engineering, computer science, finance, economics, and physics/astrophysics. 

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.7 

Table D.3. Average Number of College-Level Math Courses Taken by Teachers in the TFA Study Sample, by Entry Route

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Total Number of College-Level Math Courses 4.4 8.8 -4.4** 0.003 5.1 7.7 -2.6 0.066

Calculus 1.6 2.2 -0.6 0.166 1.7 1.9 -0.2 0.533

Advanced Algebra 0.5 1.5 -1.0** 0.002 0.4 1.1 -0.8** 0.000

Analysis 0.3 1.0 -0.7** 0.001 0.4 0.5 -0.2 0.544

Advanced Geometry/Topology 0.1 0.7 -0.7** 0.000 0.1 0.5 -0.3 0.061

Probability and Statistics 1.2 1.4 -0.2 0.353 1.1 1.6 -0.5 0.171

Discrete Mathematics 0.2 1.2 -1.0** 0.000 0.2 0.9 -0.7** 0.000

Applied Mathematics 0.5 0.8 -0.3 0.275 1.2 1.2 0.1 0.922

Sample Size 39 35 29 28

Source: Survey of Secondary Math Teachers.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.8 

Table D.4. Praxis II Scores of Teachers in the TFA Study Sample, by Entry Route (percentages unless otherwise indicated)

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Mathematics: Content Knowledge Test

Average score 161.3 138.8 22.5 0.124 163.0 141.2 21.8* 0.033

Average score of those who passeda 165.8 155.0 10.8 0.328 163.0 150.3 12.7 0.130

Sample size 9 5 6 6

Middle School Mathematics Test

Average score 181.3 160.7 20.7** 0.000 177.3 155.6 21.7** 0.000

Average score of those who passeda 181.3 168.8 12.5** 0.005 181.0 164.3 16.7** 0.007

Sample size 26 21 22 19

Source: Praxis II scores from study-administered assessment or provided by the Educational Testing Service.

a

Praxis passing thresholds from 2011. In states in which this test is not required, score is compared against the average passing threshold across all states that 

require this test.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.9 

Table D.5. Nonteaching and Teaching Work Experience of Teachers in the TFA Study Sample, by Entry Route (percentages unless otherwise indicated)

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Nonteaching Work Experience

Had a nonteaching job after college 15.4 37.1 -21.8* 0.035 20.7 75.0 -54.3** 0.000

Years of experience in nonteaching job 

(average)a 0.2 1.4 -1.2 0.053 0.6 4.3 -3.7** 0.001

Used college-level math in nonteaching joba 7.7 20.0 -12.3 0.133 13.8 57.1 -43.3** 0.000

Teaching Experience

Years of teaching experience (average) 1.9 10.9 -9.1** 0.000 1.7 9.1 -7.3** 0.000

1 or 2 years of teaching experience 79.5 8.6 70.9** 0.000 89.7 10.7 78.9** 0.000

3 to 5 years of teaching experience 20.5 17.1 3.4 0.715 10.3 25.0 -14.7 0.153

More than 5 years of teaching experience 0.0 74.3 -74.3** 0.000 0.0 64.3 -64.3** 0.000

Years of experience teaching math (average) 1.8 8.0 -6.2** 0.000 1.7 7.5 -5.8** 0.000

Fewer than 3 years of math teaching 

experience 84.6 8.6 76.0** 0.000 89.7 10.7 78.9** 0.000

3 to 5 years of math teaching experience 15.4 28.6 -13.2 0.179 10.3 28.6 -18.2 0.086

More than 5 years of math teaching 

experience 0.0 62.9 -62.9** 0.000 0.0 60.7 -60.7** 0.000

Sample Size 39 35 29 28

Source: Survey of Secondary Math Teachers. 

a

Calculations are based on all teachers, regardless of whether they had a nonteaching job after college.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.10 

Table D.6. Training and Professional Development of Teachers in the TFA Study Sample, by Entry Route (percentages unless otherwise indicated)

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Average Hours of Math Pedagogy Instruction as Part 

of Teacher Traininga 39.0 46.3 -7.4 0.367 36.7 25.6 11.1 0.224

Days of Student Teaching in Math as Part of 

Teacher Trainingb

No days 15.4 22.9 -7.5 0.423 27.6 78.6 -51.0** 0.000

1 to 20 46.2 28.6 17.6 0.121 48.3 10.7 37.6** 0.001

More than 20 38.5 48.6 -10.1 0.388 24.1 10.7 13.4 0.187

Average days of student teaching in math 20.0 37.7 -17.7** 0.004 16.6 8.4 8.2 0.124

Hours per Day Spent in Student Teaching in Math as 

Part of Teacher Training (average)c 1.3 3.2 -1.9** 0.000 1.3 3.7 -2.4* 0.036

Average Hours Spent in Math Pedagogy Professional 

Development During School Yeard

4.6 11.4 -6.9** 0.000 7.8 10.4 -2.6 0.194

Sample Size 39 35 29 28

Source: Survey of Secondary Math Teachers.

a

Teachers were asked, “As part of your training to become a math teacher, did you receive any instruction in math pedagogy or strategies to teach math?” If so, “In total, 

how many hours of instruction in math pedagogy or strategies to teach math did you receive?” Possible responses were none, 1 to 4, 5 to 20, 21 to 40, 41 to 60, 61 to 80, 

81 to 100, and more than 100. To construct average hours of math pedagogy training, we created a continuous variable equal to zero for teachers who completed no 

training, 100 for those who completed more than 100 hours, and the midpoint of the range for all other categories.

b

Teachers were asked, “Did your teacher education/preparation program require you to do any student teaching in which you went to an elementary or secondary school 

and taught one or more math lessons to a whole classroom of students?” If so, “On approximately how many days, in total, did you teach at least one full math lesson (at 

least one class period) to a whole classroom of students during your teacher education/preparation program?” Possible responses were none, 1 to 5, 6 to 10, 11 to 15, 

16 to 20, 21 to 40, 41 to 60, 61 to 80, and more than 80. To construct average days of student teaching in math, we created a continuous variable equal to zero for teachers 

who did not do any student teaching in math, 80 for those who did more than 80 days, and the midpoint of the range for all other categories.

c

Calculated only among those teachers who said they did some student teaching in math.

d

Teachers were asked, “During this school year, did you attend any professional development classes, workshops, or seminars provided by the school district in math 

pedagogy or strategies to teach math?” If so, “In total, how many hours did you spend attending these professional development classes, workshops, or seminars in math 

pedagogy or strategies to teach math?” Possible responses were none, 1 to 4, 5 to 10, 11 to 20, and more than 20. To construct average hours of professional 

development, we created a continuous variable equal to zero for teachers who did no professional development, 20 for those who did more than 20 hours, and the midpoint 

of the range for all other categories.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.11 

Table D.7. Coursework Taken During the School Year by Teachers in the TFA Study Sample, by Entry Route (percentages unless otherwise indicated)

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Overall

Took Coursework Related to Teaching Job 53.8 11.4 42.4** 0.000 41.4 32.1 9.2 0.478

Total Hours Spent During School Year on 

Coursework (average) 95.3 22.8 72.5** 0.006 71.2 83.8 -12.6 0.751

Hours spent in class during school year on 

coursework (average) 43.3 12.3 31.0* 0.010 35.1 35.9 -0.8 0.969

Hours spent out of class during school year on 

coursework (average) 51.9 10.5 41.5* 0.010 36.1 47.9 -11.8 0.590

Sample Size 39 35 29 28

Source: Survey of Secondary Math Teachers. 

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.12 

Table D.8. Mentoring Received During the School Year by Teachers in the TFA Study Sample, by Entry Route (percentages unless otherwise indicated)

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Had a Mentor During School Year 56.4 28.6 27.8* 0.015 79.3 28.6 50.7** 0.000

Mentor Assigned by School 51.3 25.7 25.6* 0.023 75.9 28.6 47.3** 0.000

Mentor Assigned by Program 30.8 0.0 30.8** 0.000 34.5 0.0 34.5** 0.000

Average Time Spent Observing Other Teachers 

(minutes) 84.4 83.7 0.6 0.989 104.3 103.9 0.4 0.994

Average Time Spent Being Observed by Mentor 

(minutes) 10.2 20.3 -10.1 0.418 26.7 8.6 18.1 0.114

Average Time Spent in Formal Meetings with 

Mentors (minutes) 143.2 45.5 97.7* 0.017 167.1 81.4 85.6 0.090

Average Time Spent in Informal Meetings with 

Mentors (minutes) 114.0 90.9 23.1 0.727 85.7 51.8 33.9 0.431

Number of Times Received Written Feedback on 

Teaching Performance 2.0 0.6 1.4* 0.027 2.4 2.9 -0.4 0.767

Felt that Mentoring Was Very Helpful 43.6 22.9 20.7 0.059 55.2 25.0 30.2* 0.020

Sample Size 39 35 29 28

Source: Survey of Secondary Math Teachers.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.13 

Table D.9. Job Satisfaction of Teachers in the TFA Study Sample, by Entry Route (percentages unless otherwise indicated)

TFA Teachers Matched with Teachers from 

Traditional Routes to Certification

TFA Teachers Matched with Teachers from 

Alternative Routes to Certification

Aspect of Job

TFA 

Teachers

Teachers from 

Traditional 

Routes Difference p-Value

TFA 

Teachers

Teachers from 

Alternative 

Routes Difference p-Value

Autonomy and Control Over Own Classroom 82.1 82.9 -0.8 0.929 89.7 89.3 0.4 0.965

Students’ Motivation to Learn 43.6 38.2 5.4 0.648 37.9 39.3 -1.4 0.918

Students’ Discipline and Behavior 34.2 31.4 2.8 0.804 17.2 39.3 -22.0 0.067

Availability of Resources for Classroom 66.7 73.5 -6.9 0.529 60.7 57.1 3.6 0.791

Recognition/Support from Administration 56.4 70.6 -14.2 0.214 62.1 64.3 -2.2 0.865

Influence Over School Policies and Practices 35.9 61.8 -25.9* 0.027 37.9 64.3 -26.4* 0.047

Opportunities for Professional Development 51.3 85.7 -34.4** 0.001 55.2 78.6 -23.4 0.062

Principal’s Leadership and Vision 51.3 68.6 -17.3 0.132 58.6 67.9 -9.2 0.478

Procedures for Performance Evaluation 46.2 71.4 -25.3* 0.027 55.2 75.0 -19.8 0.120

Professional Caliber of Colleagues 61.5 80.0 -18.5 0.082 55.2 71.4 -16.3 0.209

Sample Size 39 35 29 28

Source: Survey of Secondary Math Teachers.

Note: Teachers were asked about their satisfaction with each aspect of their job—possible responses were very dissatisfied, somewhat dissatisfied, 

somewhat satisfied, and very satisfied. Table shows the percentages of teachers who were somewhat or very satisfied with each aspect of their job.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
D.14 

Table D.10. Demographic Characteristics of Teachers in the Teaching Fellows Study Sample, by Entry Route (percentages unless otherwise indicated)

Teaching Fellows Matched with Teachers 

from Traditional Routes to Certification

Teaching Fellows Matched with Teachers 

from Alternative Routes to Certification

Characteristic

Teaching 

Fellows

Teachers from 

Traditional 

Routes Difference p-Value

Teaching 

Fellows

Teachers from 

Alternative 

Routes Difference p-Value

Age (average years) 33.6 40.1 -6.5** 0.008 32.3 43.3 -11.1** 0.001

Female 52.0 60.0 -8.0 0.415 50.0 50.0 0.0 1.000

Race/Ethnicity

White, Non-Hispanic 63.3 36.4 26.9** 0.006 73.7 20.0 53.7** 0.000

Nonwhite or Hispanic 36.7 63.6 -26.9** 0.006 26.3 80.0 -53.7** 0.000

Sample Size 50 55 21 20

Source: Survey of Secondary Math Teachers.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
D.15 

Table D.11. Educational Background of Teachers in the Teaching Fellows Study Sample, by Entry Route (percentages unless otherwise indicated)

Teaching Fellows Matched with Teachers 

from Traditional Routes to Certification

Teaching Fellows Matched with Teachers 

from Alternative Routes to Certification

Teaching 

Fellows

Teachers from 

Traditional 

Routes Difference p-Value

Teaching 

Fellows

Teachers from 

Alternative 

Routes Difference p-Value

Bachelor’s Degree

From a selective college or universitya 71.4 31.7 39.7** 0.000 73.7 40.0 33.7 0.052

Majorb

Math 28.6 48.8 -20.2 0.060 15.8 26.7 -10.9 0.461

Secondary math education 0.0 17.1 -17.1** 0.005 0.0 0.0 0.0 n.a.

Math-related subjectc 33.3 14.6 18.7* 0.046 36.8 46.7 -9.8 0.578

Other subject 66.7 31.7 35.0** 0.001 68.4 46.7 21.8 0.216

Major or minorb

Math 33.3 58.5 -25.2* 0.021 26.3 33.3 -7.0 0.670

Secondary math education 0.0 34.1 -34.1** 0.000 0.0 0.0 0.0 n.a.

Math-related subjectc 40.5 22.0 18.5 0.070 36.8 53.3 -16.5 0.353

Other subject 81.0 56.1 24.9* 0.015 73.7 46.7 27.0 0.119

Graduate Degree 80.0 78.2 1.8 0.821 90.5 85.0 5.5 0.605

Sample Size 50 55 21 20

Source: Survey of Secondary Math Teachers.

a

Highly selective colleges are those ranked by Barron’s as most competitive. Selective colleges are those ranked by Barron’s as very competitive, highly 

competitive, or most competitive.

b

Percentages might not sum to 100 if some sample members had a degree in more than one subject or had a degree in math education, which counts as both a 

math-related major and an education major.

c

Includes mathematics, secondary mathematics education, statistics, engineering, computer science, finance, economics, and physics/astrophysics.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
D.16 

Table D.12. Average Number of College-Level Math Courses Taken by Teachers in the Teaching Fellows Study Sample, by Entry Route

Teaching Fellows Matched with Teachers from 

Traditional Routes to Certification

Teaching Fellows Matched with Teachers from 

Alternative Routes to Certification

Teaching 

Fellows

Teachers from 

Traditional 

Routes Difference p-Value

Teaching 

Fellows 

Teachers from 

Alternative 

Routes Difference p-Value

Total Number of College-Level Math Courses 9.6 11.1 -1.5 0.332 10.6 10.8 -0.2 0.907

Calculus 2.6 3.1 -0.5 0.089 2.6 2.4 0.2 0.635

Advanced Algebra 1.4 1.7 -0.3 0.261 1.2 1.5 -0.3 0.441

Analysis 0.6 0.9 -0.3 0.192 1.0 1.0 0.0 0.996

Advanced Geometry/Topology 0.6 0.9 -0.2 0.219 0.5 0.7 -0.2 0.506

Probability and Statistics 1.7 1.8 -0.1 0.745 2.0 1.5 0.5 0.284

Discrete Mathematics 1.2 1.2 0.0 0.934 1.4 1.2 0.2 0.572

Applied Mathematics 1.5 1.5 0.0 0.957 1.8 2.5 -0.7 0.460

Sample Size 50 55 21 20

Source: Survey of Secondary Math Teachers.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, two-tailed test.
D.17 

Table D.13. Praxis II Scores of Teachers in the Teaching Fellows Study Sample, by Entry Route (percentages unless otherwise indicated)

Teaching Fellows Matched with Teachers 

from Traditional Routes to Certification

Teaching Fellows Matched with Teachers 

from Alternative Routes to Certification

Teaching 

Fellows

Teachers from 

Traditional 

Routes Difference p-Value

Teaching 

Fellows

Teachers from 

Alternative 

Routes Difference p-Value

Mathematics: Content Knowledge Test

Average score 157.2 140.9 16.3** 0.007 157.9 132.0 25.9** 0.002

Average score of those who passeda 163.9 155.0 9.0 0.100 163.8 150.6 13.1 0.149

Sample size 29 34 14 13

Middle School Mathematics Test

Average score 187.6 175.7 11.9* 0.024 183.7 156.3 27.3** 0.002

Average score of those who passeda 187.6 177.9 9.6* 0.047 183.7 157.8 25.9** 0.005

Sample size 20 15 6 6

Source: Praxis II scores from study-administered assessment or provided by the Educational Testing Service.

a

Praxis passing thresholds from 2011. In states in which this test is not required, score is compared against the average passing threshold across all states that 

require this test.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
D.18 

Table D.14. Nonteaching and Teaching Work Experience of Teachers in the Teaching Fellows Study Sample, by Entry Route (percentages unless 

otherwise indicated)

Teaching Fellows Matched with Teachers 

from Traditional Routes to Certification

Teaching Fellows Matched with Teachers 

from Alternative Routes to Certification

Teaching 

Fellows

Teachers from 

Traditional 

Routes Difference p-Value

Teaching 

Fellows

Teachers from 

Alternative 

Routes Difference p-Value

Nonteaching Work Experience

Had a nonteaching job after college 68.0 32.7 35.3** 0.000 61.9 70.0 -8.1 0.595

Years of experience in nonteaching job 

(average)a 5.2 1.9 3.3* 0.012 4.8 5.9 -1.1 0.610

Used college-level math in nonteaching joba 40.0 20.0 20.0* 0.026 52.4 50.0 2.4 0.883

Teaching Experience

Years of teaching experience (average) 3.7 12.6 -8.9** 0.000 4.6 14.0 -9.4** 0.000

Years of experience teaching math (average) 3.5 11.2 -7.8** 0.000 3.9 9.8 -5.9** 0.000

Sample Size 50 55 21 20

Source: Survey of Secondary Math Teachers.

a

Calculations are based on all teachers, regardless of whether they had a nonteaching job after college.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
D.19 

Table D.15. Training and Professional Development of Teachers in the Teaching Fellows Study Sample, by Entry Route (percentages unless otherwise 

indicated)

Teaching Fellows Matched with Teachers 

from Traditional Routes to Certification

Teaching Fellows Matched with Teachers 

from Alternative Routes to Certification

Teaching 

Fellows

Teachers from 

Traditional 

Routes Difference p-Value

Teaching 

Fellows

Teachers from 

Alternative 

Routes Difference p-Value

Average Hours of Math Pedagogy Instruction as Part 

of Teacher Traininga 47.8 50.4 -2.6 0.727 57.5 39.5 17.9 0.127

Participated in Intensive Math Immersion Program 

as Part of Teacher Training 46.0 5.5 40.5** 0.000 52.4 0.0 52.4** 0.000

Average Days of Student Teaching in Math as Part 

of Teacher Trainingb

No days 8.0 9.1 -1.1 0.843 14.3 60.0 -45.7** 0.002

1 to 20 82.0 14.5 67.5** 0.000 66.7 20.0 46.7** 0.002

More than 20 10.0 76.4 -66.4** 0.000 19.0 20.0 -1.0 0.941

Average days of student teaching in math 10.1 46.7 -36.6** 0.000 14.7 13.4 1.3 0.840

Hours per Day Spent in Student Teaching in Math as 

Part of Teacher Training (average)c 2.0 3.1 -1.1** 0.000 2.7 3.3 -0.6 0.397

Average Hours Spent in Math Pedagogy Professional 

Development During School Yeard 8.6 4.4 4.2** 0.003 7.9 9.1 -1.2 0.625

Sample Size 50 55 21 20

Source: Survey of Secondary Math Teachers.

a

Teachers were asked, “As part of your training to become a math teacher, did you receive any instruction in math pedagogy or strategies to teach math?” If so, “In total, 

how many hours of instruction in math pedagogy or strategies to teach math did you receive?” Possible responses were none, 1 to 4, 5 to 20, 21 to 40, 41 to 60, 61 to 80, 

81 to 100, and more than 100. To construct average hours of math pedagogy training, we created a continuous variable equal to zero for teachers who completed no 

training, 100 for those who completed more than 100 hours, and the midpoint of the range for all other categories.

b

Teachers were asked, “Did your teacher education/preparation program require you to do any student teaching in which you went to an elementary or secondary school 

and taught one or more math lessons to a whole classroom of students?” If so, “On approximately how many days, in total, did you teach at least one full math lesson (at 

least one class period) to a whole classroom of students during your teacher education/preparation program?” Possible responses were none, 1 to 5, 6 to 10, 11 to 15, 

16 to 20, 21 to 40, 41 to 60, 61 to 80, and more than 80. To construct average days of student teaching in math, we created a continuous variable equal to zero for teachers 

who did not do any student teaching in math, 80 for those who did more than 80 days, and the midpoint of the range for all other categories.

c

Calculated only among those teachers who said they did some student teaching in math.

d

Teachers were asked, “During this school year, did you attend any professional development classes, workshops, or seminars provided by the school district in math 

pedagogy or strategies to teach math?” If so, “In total, how many hours did you spend attending these professional development classes, workshops, or seminars in math 

pedagogy or strategies to teach math?” Possible responses were none, 1 to 4, 5 to 10, 11 to 20, and more than 20. To construct average hours of professional 

development, we created a continuous variable equal to zero for teachers who did no professional development, 20 for those who did more than 20 hours, and the midpoint 

of the range for all other categories.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
D.20 

Table D.16. Coursework Taken During the School Year by Teachers in the Teaching Fellows Study Sample, by Entry Route (percentages unless 

otherwise indicated)

Teaching Fellows Matched with Teachers 

from Traditional Routes to Certification

Teaching Fellows Matched with Teachers 

from Alternative Routes to Certification

Teaching 

Fellows

Teachers from 

Traditional 

Routes Difference p-Value

Teaching 

Fellows

Teachers from 

Alternative 

Routes Difference p-Value

Overall

Took Coursework Related to Teaching Job 30.0 23.6 6.4 0.468 28.6 20.0 8.6 0.534

Total hours spent during school year on 

coursework (average) 65.6 32.1 33.5 0.155 55.3 48.8 6.4 0.865

Hours spent in class during school year on 

coursework (average) 28.8 14.6 14.2 0.154 25.2 19.5 5.7 0.724

Hours spent out of class during school year on 

coursework (average) 36.8 17.6 19.2 0.176 30.1 29.3 0.8 0.974

Sample Size 50 55 21 20

Source: Survey of Secondary Math Teachers. 

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
D.21 

Table D.17. Job Satisfaction of Teachers in the Teaching Fellows Study Sample, by Entry Route (percentages unless otherwise indicated)

Teaching Fellows Matched with Teachers 

from Traditional Routes to Certification

Teaching Fellows Matched with Teachers 

from Alternative Routes to Certification

Aspect of Job

Teaching 

Fellows

Teachers from 

Traditional 

Routes Difference p-Value

Teaching 

Fellows

Teachers from 

Alternative 

Routes Difference p-Value

Autonomy and Control Over Own Classroom 96.0 89.1 6.9 0.177 95.2 90.0 5.2 0.535

Students’ Motivation to Learn 38.0 47.3 -9.3 0.342 28.6 40.0 -11.4 0.454

Students’ Discipline and Behavior 36.0 52.7 -16.7 0.086 47.6 35.0 12.6 0.424

Availability of Resources for Classroom 66.0 67.3 -1.3 0.891 66.7 75.0 -8.3 0.568

Recognition/Support from Administration 52.0 70.4 -18.4 0.056 52.4 75.0 -22.6 0.138

Influence Over School Policies and Practices 42.0 56.4 -14.4 0.144 35.0 65.0 -30.0 0.060

Opportunities for Professional Development 62.0 64.8 -2.8 0.769 61.9 68.4 -6.5 0.675

Principal’s Leadership and Vision 60.0 76.4 -16.4 0.074 52.4 75.0 -22.6 0.138

Procedures for Performance Evaluation 54.0 61.8 -7.8 0.423 66.7 70.0 -3.3 0.824

Professional Caliber of Colleagues 70.0 83.6 -13.6 0.102 81.0 85.0 -4.0 0.738

Sample Size 50 55 21 20

Source: Survey of Secondary Math Teachers.

Note: Teachers were asked about their satisfaction with each aspect of their job—possible responses were very dissatisfied, somewhat dissatisfied, 

somewhat satisfied, and very satisfied. Table shows the percentages of teachers who were somewhat or very satisfied with each aspect of their job.

 *Difference is statistically significant at the 0.05 level, two-tailed test.

**Difference is statistically significant at the 0.01 level, two-tailed test.
This page has been left blank for double–sided copying.
APPENDIX E

SUPPLEMENTARY INFORMATION ON TEACH FOR AMERICA AND 

TEACHING FELLOWS TEACHERS COMPARED 

WITH COMPARISON TEACHERS 
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

E.3 

In this appendix, we examine the sensitivity of our analysis of study teachers’ scores on the 

Praxis II math assessments. As discussed in the main text of the report, response rates on the 

Praxis II differed between TFA and comparison teachers (Chapter IV) and between Teaching 

Fellows and comparison teachers (Chapter VII). Ninety-one percent of the TFA teachers in the 

sample had Praxis II scores, compared with only 73 percent of comparison teachers. Similarly, 

94 percent of the Teaching Fellows teachers in the sample had Praxis II scores, compared with 

only 81 percent of comparison teachers (Appendix Table A.18). In our main analyses, we 

omitted teachers with missing scores. However, these analyses could be misleading if teachers 

who did not take the assessment would have systematically scored lower (or higher) than their 

counterparts who did take the assessment. To examine the sensitivity of our findings, we 

examined differences in Praxis II scores when we imputed values that would otherwise be 

missing. We used the same imputed values as those that we used in the nonexperimental analysis 

of Chapter IX, based on the multiple imputation procedure described in Appendix B. 

• Table E.1 presents the sensitivity analysis of estimated differences in Praxis II scores 

between TFA and comparison teachers. 

• Table E.2 presents the sensitivity analysis of estimated differences in Praxis II scores 

between Teaching Fellows and comparison teachers. 

For both the TFA and Teaching Fellows samples, results were similar under the two 

approaches, although differences between the two groups were somewhat more pronounced. 

This suggests that teachers with missing Praxis data might have been those who would have 

scored lower had they taken the test. 
Effectiveness of TFA and Teaching Fellows Teachers 

E.4 

Table E.1. Sensitivity of Differences in Praxis II Scores Between TFA and Comparison Teachers in the 

Study

TFA 

Teachers

Comparison 

Teachers Difference p-Value

Main Estimates

Mathematics: Content Knowledge Test

Average score 162.0 140.1 21.9* 0.010

Sample size 15 11

Middle School Mathematics Test

Average score 179.8 158.3 21.6** 0.000

Sample size 45 40

Multiple Imputation of Missing Scores

Mathematics: Content Knowledge Test

Average score 178.9 152.3 26.6* 0.002

Sample size 20 20

Middle School Mathematics Test

Average score 174.6 152.3 22.3* 0.000

Sample size 50 58

Source: Praxis II scores from study-administered assessment or provided by the Educational Testing 

Service.

a

Praxis passing thresholds from 2011. In states in which this test is not required, the score is compared against 

the average passing threshold across all states that require this test.

 *Difference between TFA and comparison teachers is statistically significant at the 0.05 level, two-tailed test.

**Difference between TFA and comparison teachers is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

E.5 

Table E.2. Sensitivity of Differences in Praxis II Scores Between Teaching Fellows and Comparison 

Teachers in the Study

Teaching 

Fellows

Comparison 

Teachers Difference p-Value

Main Estimates

Mathematics: Content Knowledge Test

Average score 157.8 138.5 19.3** 0.000

Sample size 39 47

Middle School Mathematics Test

Average score 186.7 170.1 16.5** 0.001

Sample size 26 21

Multiple Imputation of Missing Scores

Mathematics: Content Knowledge Test

Average score 168.1 145.9 22.3* 0.000

Sample size 52 70

Middle School Mathematics Test

Average score 163.1 145.9 17.3* 0.001

Sample size 28 25

Source: Praxis II scores from study-administered assessment or provided by the Educational Testing 

Service.

a

Praxis passing thresholds from 2011. In states in which this test is not required, the score is compared against 

the average passing threshold across all states that require this test.

 *Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.05 level, 

two-tailed test.

**Difference between Teaching Fellows and comparison teachers is statistically significant at the 0.01 level, 

two-tailed test.
This page has been left blank for double–sided copying.
APPENDIX F

SUPPLEMENTARY ANALYSES OF THE IMPACTS OF TEACH FOR AMERICA 

AND TEACHING FELLOWS TEACHERS
This page has been left blank for double–sided copying.
Effectiveness of TFA and Teaching Fellows Teachers 

F.3 

In Appendix F, we present three types of supplemental findings on the impacts of Teach For 

America (TFA) and Teaching Fellows teachers relative to comparison teachers: (1) sensitivity 

analyses that assess the robustness of the main impact estimates, (2) analyses of impacts on 

student attendance, and (3) subgroup analyses that assess differences in effectiveness between 

specific types of teachers.

A. Supplemental Findings on the Impacts of TFA Teachers

1. Sensitivity Analyses 

We explored various changes, described below, to the estimation sample or regression 

model for estimating the impacts of TFA teachers relative to comparison teachers. Findings from 

all specifications were similar to the main findings; estimated impacts of TFA teachers ranged 

from 0.06 to 0.11 standard deviations and were always statistically significant. 

Excluding covariates. Our main estimation model controlled for classroom match 

indicators and all covariates in Appendix Table B.1. Findings were similar when only classroom 

match indicators, but no other covariates, were included in the estimation model (Table F.1, 

model 1). 

Averaging impacts across classroom matches. In our main specification, sample weights 

were normalized so that the weights within each match summed to the number of research 

sample students in the match. Therefore, matches with more students received more weight in 

the main impact estimates. An alternative normalization for the sample weights in which every 

match had the same total weight in the final analysis sample produced similar findings 

(Table F.1, model 2). 

Accounting for missing data and nonresponse. For our main impact estimates, we used an 

analysis sample that excluded students with missing outcome data; we imputed missing covariate 

data with match-specific or full-sample variable means and included binary indicators for 

imputed covariate data in the estimation model. In sensitivity analyses, we produced alternative 

impact estimates based on (1) all research sample students with parental consent, with missing 

outcome data replaced by multiply imputed values; (2) the main analysis sample, with missing 

covariate data replaced by multiply imputed values; and (3) all research sample students with 

parental consent, with missing data for both outcomes and covariates replaced by multiply 

imputed values (see Appendix B). All findings from these analyses were similar to the main 

findings (Table F.1, models 3 through 5). 

The main analysis sample also excluded high school students whose scores on the Northwest 

Evaluation Association (NWEA) assessment were deemed invalid due to an unreasonably short 

testing duration (fewer than six minutes) or an excessively high standard error of measurement 

(greater than 5.5 Rasch units). However, findings were similar when these invalid scores were 

included in the analysis (Table F.1, model 6). 

Dropping classroom matches. Our main analysis used all classroom matches for which the 

participating schools sent class rosters verifying that students had been placed into their 

randomly assigned classes shortly after random assignment occurred at the beginning of the 

school year. All matches were retained in the main analysis regardless of how many students 

switched into or out of the matched classes after the beginning of the school year. In a sensitivity 
Effectiveness of TFA and Teaching Fellows Teachers 

F.4 

analysis, we dropped matches in which students who entered the study classes through a method 

other than random assignment constituted more than 10 percent of students enrolling before the 

end of the first month of school or more than 25 percent of students on end-of-year class rosters; 

findings from this analysis were similar to the main findings (Table F.1, model 7). 

In another sensitivity analysis, we excluded classroom matches in which any students 

received supplemental math instruction outside of the classes that constituted the match. As 

discussed in Appendix A, supplemental math classes had the potential to either reinforce or 

dilute the impacts that students experienced from the classes in the study. After dropping 

matches with supplemental math classes, the estimated impact of TFA teachers remained 

positive and statistically significant, with a slightly larger magnitude (0.11 standard deviations) 

than the main impact estimate (Table F.1, model 8).

Standardizing test scores. For the main analysis, we standardized outcome and baseline 

scores into z-scores based on means and standard deviations in a statewide or national reference 

population. The reference population was either the statewide student population at the same 

grade level during the year of the test (if the test was a state assessment) or the national norming 

sample of the test (if the test was an NWEA assessment). Impact findings were similar when the 

z-scores were standardized based on control group members in the same state and grade during 

the year of the test (for state assessments) or control group members in the same state who took 

the same math course (for NWEA assessments) (Table F.1, model 9).

Adjusting for noncompliance. Our main model estimated the intent-to-treat (ITT) 

impact—the impact of being randomly assigned to a TFA teacher rather than a comparison 

teacher. However, some students did not stay with the type of teacher to which they were 

originally assigned, and outcomes for these students did not reflect the effectiveness of their 

assigned teachers. Only for compliers—those who would have stayed with their assigned type of 

teacher in any assignment scenario—did the impact of assignment to TFA teachers represent the 

actual impact of being taught by TFA teachers. In a sensitivity analysis, we isolated the ITT 

impact pertaining only to compliers, referred to as the complier average causal effect (CACE), 

capturing the full difference in effectiveness between TFA and comparison teachers for this 

subset of students. 

To estimate the CACE, we used instrumental variables estimation (Angrist et al. 1996). We 

estimated a regression for end-of-year math scores in which the independent variable of interest 

was a binary variable for being enrolled in a TFA teacher’s class (rather than a non-TFA 

teacher’s class) based on spring rosters, near the time of testing. An indicator for having been 

randomly assigned to a TFA teacher served as the instrumental variable for being enrolled in a 

TFA teacher’s class.28

 

We controlled for classroom match indicators and all covariates in 

Appendix Table B.1. 

28 The causal validity of the CACE estimate depends on the validity of the exclusion restriction—the 

assumption that a student’s original assignment could affect his or her outcomes only by influencing the type of 

teacher (TFA or comparison) whom the student had at the time of testing. The exclusion restriction might not hold 

for students who crossed over to the opposite type of teacher but who spent a significant amount of time with their 

originally assigned teacher before crossing over. These students could be affected by both their originally assigned 

teacher and the teacher they had at the time of testing. We do not know the magnitude of this potential bias because 
Effectiveness of TFA and Teaching Fellows Teachers 

F.5 

For students who left the entire set of study classes before we collected spring rosters, we 

did not know the type of teacher that they had at the time of testing. Therefore, we made two 

alternative sets of assumptions that led to lower- and upper-bound estimates for the CACE. First, 

we assumed that all students who left the study classes moved to a class taught by the same type 

of teacher with which they were last observed before they left. Second, we assumed that all 

students who left the study classes were subsequently taught by the opposite type of teacher to 

their original assignment.

Consistent with the main results, TFA teachers were more effective than comparison 

teachers at teaching math to students who complied with their original assignment. Compliers 

taught by TFA teachers scored 0.08 to 0.10 standard deviations higher than those taught by 

comparison teachers (Table F.1, models 10 and 11). 

2. Analyses of Impacts on Student Absences

A potential channel through which teachers could influence student achievement is by 

affecting their students’ rate of absences. To explore this possibility, we estimated the impact on 

student absences of TFA teachers relative to comparison teachers. We examined two measures of 

absences: (1) whether a student had been absent from his or her math class more than 25 percent 

of the time, as reported by the student’s teacher, and (2) the number of days a student was absent 

from school, as recorded in district administrative records. In the full TFA study sample as well 

as in middle schools and high schools separately, there was no statistically significant difference 

between students of TFA teachers and students of comparison teachers in either of the two 

measures of student absences (Table F.2).

3. Subgroup Analyses

Table F.3 presents detailed results for the subgroup analyses discussed in Chapter V. We 

show estimates of differences in effectiveness between TFA and comparison teachers within 

subgroups of matches defined by the certification route of the comparison teacher, the experience 

level of the TFA and/or comparison teacher, and the level of the school (middle or high) in 

which the teachers taught. We found positive impacts of TFA teachers within each subgroup 

examined, ranging from 0.06 to 0.13 standard deviations. 

 

(continued) 

we do not have precise information on the exact time when students crossed over. Nevertheless, the magnitude of 

the potential bias depends on the percentage of students who crossed over. This percentage ranges from 2.5 to 13.0 

percent in the TFA study sample, depending on our assumptions for whether students who left the study classes 

were taught by the same or opposite type of teacher to their originally assigned teacher. The corresponding 

percentages in the Teaching Fellows study sample range from 2.4 to 5.4 percent.
Effectiveness of TFA and Teaching Fellows Teachers 

F.6 

B. Supplemental Findings on the Impacts of Teaching Fellows

1. Sensitivity Analyses 

We explored various changes to the estimation sample or regression model for estimating 

the impacts of Teaching Fellows relative to comparison teachers. Findings from all specifications 

were similar to the main findings; across all specifications, estimated impacts of Teaching 

Fellows were never statistically significant and ranged from -0.03 to 0.03. 

The types of sensitivity analyses that we conducted for estimating impacts of Teaching 

Fellows were identical to the analyses we described in Section A for estimating impacts of TFA 

teachers. As shown in Table F.4, our basic finding—that Teaching Fellows were statistically 

indistinguishable from comparison teachers in their effectiveness—held in all sensitivity 

analyses, including the following: 

• A regression model that excluded all covariates except classroom match indicators

• Sample weights that gave equal total weight in the analysis sample to each classroom 

match

• Use of multiply imputed data to replace missing values of the outcome variable 

and/or covariates 

• Inclusion of NWEA scores that were deemed invalid 

• Exclusion of classroom matches with high rates of nonrandom student entry into the 

study classes

• Exclusion of classroom matches with supplemental math instruction

• Use of achievement z-scores based on means and standard deviations in the control 

group sample 

• Adjustment for noncompliance with original random assignment 

2. Analyses of Impacts on Student Absences

As in the analysis of TFA teachers’ impacts, we estimated impacts on student absences of 

Teaching Fellows relative to comparison teachers. Students of Teaching Fellows and those of 

comparison teachers were statistically indistinguishable in the average number of days absent 

from school, as recorded in district administrative records (Table F.5). However, students of 

Teaching Fellows were, on average, two percentage points less likely than students of 

comparison teachers to be chronically absent—absent more than one-fourth of the time—from 

their math class, as reported by the students’ math teachers. The reduction in chronic 

absenteeism for students of Teaching Fellows was observed in high school but not in middle 

school. 

3. Subgroup Analyses

Table F.6 presents detailed results for the subgroup analyses discussed in Chapter VIII. We 

show estimates of differences in effectiveness between Teaching Fellows and comparison 

teachers within subgroups of matches defined by the certification route of the comparison 

teacher, the experience level of the Teaching Fellow and/or comparison teacher, and the level of 
Effectiveness of TFA and Teaching Fellows Teachers 

F.7 

the school (middle or high) in which the teachers taught. Impacts were not statistically 

significant for the subgroup of Teaching Fellows compared with teachers from traditional routes 

to certification but were positive and significant for the subgroup compared with teachers from 

alternative routes to certification (impact = 0.13). Within subgroups defined by whether teachers 

were novice (in their first three years of teaching) or experienced (in their fourth or more year of 

teaching), impacts were positive and significant for novice Teaching Fellows compared with 

novice comparison teachers (impact = 0.13) but were negative and significant for novice

Teaching Fellows compared with experienced comparison teachers (impact = -0.10). There was 

no significant impact of experienced Teaching Fellows compared with experienced comparison 

teachers, and no significant impact of Teaching Fellows compared with comparison teachers 

whose teaching experience differed by no more than two years. Moreover, there were no 

significant impacts among subgroups at the middle and high school levels. 
F.8 

Table F.1. Differences in Effectiveness Between TFA Teachers and Comparison Teachers, Sensitivity Analyses

Mean Student 

Math Achievement 

(z-scores)

Difference in Math 

Achievement 

Between Groups 

(z-scores) Sample Sizes

Model

Assigned 

to TFA 

Teachers

Assigned to

Comparison

Teachers Estimate p-Value Students

Classroom 

Matches Teachers Schools

Main Modela -0.52 -0.60 0.07** 0.000 4,573 111 136 45

Alternative Specifications

Covariates

(1) No covariates except classroom match indicators -0.53 -0.60 0.07** 0.001 4,573 111 136 45

Method of Averaging Impacts Across Classroom Matches

(2) Weight each classroom match equally -0.56 -0.64 0.08** 0.000 4,573 111 136 45

Accounting for Missing Data and Nonresponse

(3) Missing outcome test scores imputed with multiple 

imputation -0.57 -0.66 0.09** 0.000 5,462 111 136 45

(4) Missing covariate values imputed with multiple 

imputation -0.52 -0.60 0.08** 0.000 4,573 111 136 45

(5) Missing outcome test scores and covariate values 

imputed with multiple imputation -0.58 -0.66 0.08** 0.000 5,462 111 136 45

(6) Include NWEA scores that were deemed invalid due to 

high standard error of measurement or short testing 

duration -0.52 -0.60 0.07** 0.000 4,619 111 136 45

Rule for Dropping Classroom Matches

(7) Drop classroom matches in which percentage assigned 

nonrandomly in first month > 10% or percentage on 

final roster who had entered nonrandomly > 25% -0.43 -0.49 0.06* 0.012 3,434 78 112 39

(8) Drop classroom matches with supplemental math 

classesb -0.53 -0.63 0.11** 0.000 2,460 58 72 30
F.9 

Table F.1 (continued)

Difference in Math 

Mean Student Achievement 

Math Achievement Between Groups 

(z-scores) (z-scores) Sample Sizes

Model

Assigned Assigned to

to TFA Comparison

Teachers Teachers Estimate p-Value Students

Classroom 

Matches Teachers Schools

Standardization of Test Scores

(9) Compute z-scores based on control group mean and 

standard deviation within each state and subject 0.08 -0.01 0.09** 0.000 4,573 111 136 45

Adjustment for Students who Switched to a Different Type of 

Teacher than their Originally Assigned Teacher

(10) Complier average causal effect, assuming that all 

students who left study classes stayed with the type of 

teacher with which they were last observed -0.51 -0.59 0.08** 0.000 4,573 111 136 45

(11) Complier average causal effect, assuming that all 

students who left study classes switched to the 

opposite teacher type -0.43 -0.53 0.10** 0.000 4,573 111 136 45

Sources: District administrative records and study-administered NWEA assessments.

Note: The difference between groups is adjusted for classroom match fixed effects and all covariates in the specified model. The mean outcome for 

students assigned to TFA teachers is calculated as the unadjusted mean outcome for students assigned to comparison teachers plus the adjusted 

difference in outcomes between the two groups.

a

The main model adjusts for the baseline student characteristics shown in Appendix Table B.1. Missing values of covariates are imputed with sample means in the 

same classroom match; if the sample mean of a covariate in a particular classroom match is missing, then missing values are imputed with the sample mean in the 

full research sample. Covariate imputation indicators are included in the regression model. Outcome data are not imputed—students with missing values of 

outcome data are excluded from the analysis. Weights are scaled so that the weights for research sample members in each classroom match sum to the number 

of research sample members in the match. Students with missing outcome test scores or invalid NWEA scores are excluded. All classroom matches in which 

random assignment was implemented are included. Z-scores are computed using state means and standard deviations by grade level for middle school students 

(who took state assessments) and national means and standard deviations by subject for high school students (who took the study-administered NWEA 

assessments). The main model does not adjust for students who switched to a different type of teacher than their originally assigned teacher. 

b

This model also retains classroom matches for which there is no information on participation in supplemental math classes.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

NWEA = Northwest Evaluation Association; TFA = Teach For America.
F.10 

Table F.2. Impact on Student Absences of TFA Teachers Relative to Comparison Teachers

Rate of Student Absences

Difference Between 

Groups Sample Sizes

Measure of Student Absences

Assigned 

to TFA 

Teachers

Assigned 

to Comparison 

Teachers Estimate p-Value Students

Classroom 

Matches Teachers Schools

All Students

Absent from Math Class More Than 25 Percent of 

the Time (percentage) 13.1 12.3 0.8 0.528 3,149 87 111 41

Number of Days Absent from School (average) 10.8 11.0 -0.1 0.658 4,601 103 124 39

Middle School Students

Absent from Math Class More Than 25 Percent of 

the Time (percentage) 9.3 9.3 0.1 0.964 2,184 67 85 28

Number of Days Absent from School (average) 9.6 9.3 0.3 0.197 3,352 80 99 29

High School Students

Absent from Math Class More Than 25 Percent of 

the Time (percentage) 21.3 18.9 2.4 0.477 965 20 26 13

Number of Days Absent from School (average) 14.6 15.6 -1.0 0.283 1,249 23 25 10

Sources: Percentage of days absent from math class is based on teacher reports; days absent from school are based on district administrative 

records.

Note: Means and differences are adjusted for classroom match fixed effects and all covariates listed in Appendix Table B.1. 

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America. 
F.11 

Table F.3. Differences in Effectiveness Between TFA Teachers and Comparison Teachers, by Subgroup

Mean Student 

Math Achievement 

(z-scores)

Difference in Math 

Achievement 

Between Groups 

(z-scores) Sample Sizes

Type of Comparison

Assigned 

to TFA 

Teachers

Assigned to

Comparison

Teachers Estimate p-Value Students

Classroom 

Matches Teachers Schools

Subgroups Defined by Certification Route of Comparison 

Teacher

TFA versus TC comparison teachers -0.52 -0.58 0.06* 0.025 2,477 58 82 34

TFA versus AC comparison teachers -0.52 -0.62 0.09** 0.001 2,096 53 58 17

Difference between subgroups -0.03 0.351 4,573 111 136 45

Subgroups with Novice TFA Teachers

Novice TFA versus novice comparison teachers -0.24 -0.32 0.08** 0.006 710 18 23 10

Novice TFA versus experienced comparison teachers -0.59 -0.66 0.07** 0.001 3,642 85 107 36

Difference between subgroups 0.01 0.728 4,352 103 127 43

Subgroups with Experienced TFA Teachers (suppresseda)

Subgroups Defined by School Level

Middle school -0.47 -0.52 0.06** 0.007 3,373 83 103 31

High school -0.69 -0.82 0.13** 0.002 1,200 28 33 14

Difference between subgroups -0.07 0.090 4,573 111 136 45

Sources: District administrative records and study-administered Northwest Evaluation Association assessments.

Note: The difference between groups is adjusted for classroom match fixed effects and all covariates in Appendix Table B.1. The mean outcome for 

students assigned to TFA teachers is calculated as the unadjusted mean outcome for students assigned to comparison teachers plus the adjusted 

difference in outcomes between the two groups. Hypothesis tests within subgroups defined by the certification route of the comparison teacher were 

adjusted for multiple hypothesis testing, as described in Appendix B; the remaining hypothesis tests in this table were not adjusted for multiple 

hypothesis testing.

a

Due to small sample sizes, estimates did not meet the minimum level of precision required for a subgroup estimate to be presented in this report.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

AC = alternative route to certification; TC = traditional route to certification; TFA = Teach For America.
F.12 

Table F.4. Differences in Effectiveness Between Teaching Fellows and Comparison Teachers, Sensitivity Analyses

Mean Student 

Math Achievement 

(z-scores)

Difference in Math 

Achievement 

Between Groups 

(z-scores) Sample Sizes

Model

Assigned to 

Teaching 

Fellows

Assigned to

Comparison

Teachers Estimate p-Value Students

Classroom 

Matches Teachers Schools

Main Modela -0.39 -0.39 0.00 0.956 4,116 118 153 44

Alternative Specifications

Covariates

(1) No covariates except classroom match indicators -0.40 -0.39 -0.01 0.820 4,116 118 153 44

Method of Averaging Impacts Across Classroom Matches

(2) Weight each classroom match equally -0.55 -0.52 -0.03 0.147 4,116 118 153 44

Accounting for Missing Data and Nonresponse

(3) Missing outcome test scores imputed with multiple 

imputation -0.51 -0.50 -0.01 0.815 5,313 118 153 44

(4) Missing covariate values imputed with multiple 

imputation -0.39 -0.39 0.01 0.800 4,116 118 153 44

(5) Missing outcome test scores and covariate values 

imputed with multiple imputation -0.51 -0.50 0.00 0.963 5,313 118 153 44

(6) Include NWEA scores that were deemed invalid due to 

high standard error of measurement or short testing 

duration -0.38 -0.39 0.01 0.736 4,188 118 153 44

Rule for Dropping Classroom Matches

(7) Drop classroom matches in which percentage assigned 

nonrandomly in first month > 10% or percentage on 

final roster who had entered nonrandomly > 25% -0.26 -0.28 0.03 0.390 3,246 91 113 32

(8) Drop classroom matches with supplemental math 

classesb -0.38 -0.37 -0.01 0.751 3,208 95 125 37
F.13 

Table F.4 (continued)

Difference in Math 

Mean Student Achievement 

Math Achievement Between Groups 

(z-scores) (z-scores) Sample Sizes

Model

Assigned to Assigned to

Teaching Comparison

Fellows Teachers Estimate p-Value Students

Classroom 

Matches Teachers Schools

Standardization of Test Scores

(9) Compute z-scores based on control group mean and 

standard deviation within each state and subject 0.02 0.02 0.00 0.884 4,116 118 153 44

Adjustment for Students who Switched to a Different Type of 

Teacher than their Originally Assigned Teacher

(10) Complier average causal effect, assuming that all 

students who left study classes stayed with the type of 

teacher with which they were last observed -0.38 -0.38 0.00 0.955 4,116 118 153 44

(11) Complier average causal effect, assuming that all 

students who left study classes switched to the 

opposite teacher type -0.34 -0.34 0.00 0.955 4,116 118 153 44

Sources: District administrative records and study-administered NWEA assessments.

Note: The difference between groups is adjusted for classroom match fixed effects and all covariates in the specified model. The mean outcome for 

students assigned to Teaching Fellows is calculated as the unadjusted mean outcome for students assigned to comparison teachers plus the 

adjusted difference in outcomes between the two groups.

a

The main model adjusts for the baseline student characteristics shown in Appendix Table B.2. Missing values of covariates are imputed with sample means in the 

same classroom match; if the sample mean of a covariate in a particular classroom match is missing, then missing values are imputed with the sample mean in the 

full research sample. Imputation indicators are included in the regression model. Weights are scaled so that the weights for research sample members in each 

classroom match sum to the number of research sample members in the match. Students with missing outcome test scores or invalid NWEA scores are excluded. 

All classroom matches in which random assignment was implemented are included. Z-scores are computed using state means and standard deviations by grade 

level for middle school students (who took state assessments) and national means and standard deviations by subject for high school students (who took the 

study-administered NWEA assessments). The main model does not adjust for students who switched to a different type of teacher than their originally assigned 

teacher. 

b

This model also retains classroom matches for which there is no information on participation in supplemental math classes.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

NWEA = Northwest Evaluation Association.
F.14 

Table F.5. Impact on Student Absences of Teaching Fellows Relative to Comparison Teachers

Rate of Student Absences

Difference 

Between Groups Sample Sizes

Measure of Student Absences

Assigned to 

Teaching 

Fellows

Assigned to 

Comparison 

Teachers Estimate p-Value Students

Classroom 

Matches Teachers Schools

All Students

Absent from Math Class More Than 25 Percent of the 

Time (percentage) 17.2 19.7 -2.4* 0.047 3,346 96 124 38

Number of Days Absent from School (average) 18.0 17.7 0.3 0.405 5,061 115 149 43

Middle School Students

Absent from Math Class More Than 25 Percent of the 

Time (percentage) 5.1 3.9 1.1 0.288 968 25 36 12

Number of Days Absent from School (average) 12.0 11.7 0.3 0.551 1,627 37 53 17

High School Students

Absent from Math Class More Than 25 Percent of the 

Time (percentage) 22.6 26.5 -3.9* 0.020 2,378 71 89 28

Number of Days Absent from School (average) 20.9 20.7 0.2 0.557 3,434 78 97 28

Sources: Percentage of days absent from math class is based on teacher reports; days absent from school are based on district administrative 

records.

Note: Means and differences are adjusted for classroom match fixed effects and all covariates listed in Appendix Table B.2. 

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.
F.15 

Table F.6. Differences in Effectiveness Between Teaching Fellows and Comparison Teachers, by Subgroup

Mean Student 

Math Achievement 

(z-scores)

Difference in Math 

Achievement 

Between Groups 

(z-scores) Sample Sizes

Type of Comparison

Assigned 

to 

Teaching 

Fellows

Assigned to

Comparison

Teachers Estimate p-Value Students

Classroom 

Matches Teachers Schools

Subgroups Defined by Certification Route of Comparison 

Teacher

Teaching Fellows versus TC comparison teachers -0.36 -0.32 -0.03 0.248 3,268 92 113 33

Teaching Fellows versus AC comparison teachers -0.50 -0.63 0.13* 0.014 902 30 46 19

Difference between subgroups -0.17** 0.005 4,116 118 153 44

Subgroups with Novice Teaching Fellows

Novice Teaching Fellows versus novice comparison teachers -0.40 -0.53 0.13** 0.004 354 12 17 7

Novice Teaching Fellows versus experienced comparison 

teachers -0.63 -0.53 -0.10** 0.002 1,153 38 53 19

Difference between subgroups 0.24** 0.000 1,475 47 68 23

Subgroups with Experienced Teaching Fellows

Experienced Teaching Fellows versus novice comparison 

teachers (suppresseda)

Experienced Teaching Fellows versus experienced 

comparison teachers -0.27 -0.30 0.03 0.446 2,408 65 80 26

Teaching Fellows Versus Comparison Teachers Whose Levels 

of Teaching Experience Differ by No More than Two Years -0.17 -0.20 0.03 0.399 1,283 33 46 17

Subgroups Defined by School Level

Middle school -0.35 -0.39 0.04 0.377 1,610 37 53 17

High school -0.41 -0.39 -0.02 0.472 2,506 81 101 29

Difference between subgroups 0.06 0.253 4,116 118 153 44

Sources: District administrative records and study-administered Northwest Evaluation Association assessments.

Note: The difference between groups is adjusted for classroom match fixed effects and all covariates in Appendix Table B.2. The mean outcome for 

students assigned to Teaching Fellows is calculated as the unadjusted mean outcome for students assigned to comparison teachers plus the 

adjusted difference in outcomes between the two groups. Hypothesis tests within subgroups defined by the certification route of the comparison 

teacher were adjusted for multiple hypothesis testing, as described in Appendix B; the remaining hypothesis tests in this table were not adjusted for 

multiple hypothesis testing.
F.16 

Table F.6. (continued)

a

Due to small sample sizes, estimate did not meet the minimum level of precision required for a subgroup estimate to be presented in this report.

*Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

AC = alternative route to certification; TC = traditional route to certification.
APPENDIX G

SUPPLEMENTARY FINDINGS ON FACTORS ASSOCIATED 

WITH TEACHER EFFECTIVENESS
This page has been left blank for double–sided copying. 
Effectiveness of TFA and Teaching Fellows Teachers 

G.3 

In Appendix G, we present supplemental tables that document the relationships between 

teacher characteristics and student math achievement from the nonexperimental analyses. The 

tables in Section A contain detailed results that form the basis for the nonexperimental findings 

reported in Chapter IX. The tables in Section B contain sensitivity analyses that assess the 

robustness of the main nonexperimental findings. 

A. Detailed Results from the Main Nonexperimental Analyses

1. Teacher Characteristics in the Analysis

Table G.1 lists the measures of teachers’ academic ability, exposure to and knowledge of 

math, instructional training, and teaching experience that constituted the main set of teacher-level 

variables included in the analysis. Means and standard deviations are provided for each 

characteristic.

2. Estimates of Relationships Between Teacher Characteristics and Student Achievement

To assess the relationships between teacher characteristics and student math achievement, 

we estimated a student-level regression for students’ end-of-year math scores. Independent 

variables consisted of classroom match indicators, separate indicators for Teach For America 

(TFA) and Teaching Fellows teachers, all student-level baseline covariates, and measures of 

teacher characteristics (see Appendix B).

Earlier in the report, in Chapter IX, Table IX.1 reported coefficients on the teacher 

characteristics from the regression estimates. In this appendix, Tables G.2 and G.3 display these 

coefficients again but also report their corresponding p-values as well as additional coefficients 

and p-values pertaining to the TFA and Teaching Fellows indicators. Each of the models in 

Table G.2 included a single teacher characteristic (or a group of variables measuring a single 

teacher characteristic, such as teaching experience). The single model shown in Table G.3 

included all of the main teacher-level variables.

The estimated coefficients on the teacher characteristics in these models represented

associations rather than causal effects. For instance, if any of the teacher characteristics included 

in the models were correlated with some other teacher characteristics that also affected student 

math achievement but were omitted from the models (for instance, teacher enthusiasm), the true 

causal effect of that omitted variable on the outcome would be attributed to the included 

characteristics, leading to biased estimates of the causal effects of each included characteristic. 

Nonetheless, these estimates could provide useful descriptive information on the association 

between each included teacher characteristic and student math achievement. 

As discussed in Chapter IX, evidence from both Tables G.2 and G.3 indicated that students’ 

math achievement was negatively associated with the amount of coursework that their teachers 

took during the school year and positively associated with two of three measures of teacher 

experience. We found no other statistically significant relationships between teacher 

characteristics and student achievement.
Effectiveness of TFA and Teaching Fellows Teachers 

G.4 

3. Accounting for the Difference in Effectiveness Between TFA and Comparison 

Teachers

We used the estimated relationships between teacher characteristics and student math 

achievement from Table G.3 to ascertain the difference in effectiveness between TFA and 

comparison teachers that could be predicted based on each characteristic. These predicted 

differences in effectiveness represented the portion of the groups’ actual difference in 

effectiveness that could be accounted for by the observed characteristics.29

Table G.4 shows results from all steps in this analysis. The first column of entries repeats 

the coefficients from Table G.3. The second and third columns show the estimate and p-value for 

the difference in each characteristic between TFA and comparison teachers. The final column 

provides the predicted difference in effectiveness between TFA and comparison teachers based 

on each characteristic, calculated as the product of the first and second columns.

As we discussed in Chapter IX, the observed characteristics collectively did not account for 

any positive portion of the difference in effectiveness between TFA and comparison teachers. 

After summing the predicted TFA-comparison differences in effectiveness based on all observed 

characteristics, students of TFA teachers were predicted to score 0.028 standard deviations below 

students of comparison teachers. In fact, however, the experimental estimates from Chapter V 

found that students of TFA teachers actually scored 0.075 standard deviations higher than 

students of comparison teachers. 

B. Sensitivity Analyses of the Relationships Between Teacher Characteristics 

and Student Achievement

Starting from the main nonexperimental regression model (Table G.3) that included all 

teacher characteristics, we explored several modifications to this model to determine the 

robustness of the main findings. We used alternative measures of particular characteristics, 

modeled the relationships between teacher characteristics and student achievement with different 

functional forms, and included additional characteristics in the regression model. 

1. Alternative Measures of College Selectivity

Our main measure of college selectivity was a binary indicator for whether a teacher had 

received a bachelor’s degree from a selective college or university. In alternative models, we 

replaced this variable with an indicator for bachelor’s degrees from highly selective colleges or 

universities, either alone or in conjunction with another indicator for bachelor’s degrees from 

selective but not highly selective colleges or universities (Table G.5). Consistent with the main 

findings, no measures of college selectivity were associated with student math achievement.

 29 We did not conduct a parallel analysis for the Teaching Fellows sample because we did not find a 

statistically significant average difference in effectiveness between Teaching Fellows and comparison teachers. 
Effectiveness of TFA and Teaching Fellows Teachers 

G.5 

2. Alternative Measures of Exposure to Math Coursework

In the main model, we measured exposure to math coursework with a binary indicator for 

whether a teacher was in the top half of the study teachers in terms of the number of collegelevel math courses completed. We conducted sensitivity analyses that explored whether teacher 

effectiveness was associated with having college minors, college majors, or advanced degrees in 

math or math-related subjects, with math-related subjects defined as either including (Table G.6, 

models 1 and 2) or excluding (Table G.6, models 3 and 4) secondary math education. As in the 

main analyses, we found no statistically significant relationships between teachers’ exposure to 

math coursework and the achievement of their students in these sensitivity analyses. 

3. Alternative Measures of Praxis Achievement

Our main specification modeled a linear relationship between teachers’ Praxis II scores, 

expressed as z-scores, and student math achievement. In sensitivity analyses, we replaced the 

continuous Praxis variables with either (1) indicators for whether teachers’ Praxis II scores were 

above the median for study teachers who took the same assessment (Table G.7, model 1); or 

(2) indicators for whether teachers’ Praxis II scores met the passing thresholds for certification in 

their states (Table G.7, model 2).30

Like the main analyses, the sensitivity analyses did not find any association between the 

Praxis II scores of middle school teachers and their students’ achievement. However, high school 

teachers whose Praxis II scores (on the Mathematics Content Knowledge assessment) exceeded 

the median were more effective, by a statistically significant degree, than those whose scores 

were below the median. Earning a passing score on the Mathematics Content Knowledge 

assessment was not statistically related to teacher effectiveness.

4. Inclusion of Teacher Demographic Characteristics

The main nonexperimental model did not include teacher demographic characteristics 

because these variables were not central to assessing whether teachers’ academic ability and 

professional background were predictive of teacher effectiveness. In a sensitivity analysis, we 

augmented the main nonexperimental model with additional variables that measured teachers’ 

demographic characteristics, including their gender, age, and race, as well as a variable 

indicating whether the teacher and student were of the same race (black or non-black) 

(Table G.8). This alternative specification yielded similar conclusions to the main findings—

namely, that students’ achievement was positively associated with some measures of their 

teachers’ experience and negatively associated with the amount of concurrent coursework in 

which their teachers were enrolled. In addition, the relationship between teachers’ scores on the 

Praxis II Mathematics Content Knowledge assessment and student math achievement reached 

statistical significance, with higher Praxis scores predicting higher student achievement. We also

found that female teachers were more effective than their male counterparts, but no other teacher 

demographic characteristics were predictive of student math achievement.

 30 If the teacher’s state did not require the specified Praxis test, the passing threshold was specified as the 

average threshold across all states that required the test.
Effectiveness of TFA and Teaching Fellows Teachers 

G.6

Table G.1. Summary Statistics of Teacher Characteristics Examined in the Nonexperimental Analysis

Teacher Characteristic

Variable 

Structure Mean

Standard 

Deviation

Graduated from Selective College or Universitya Dichotomous 0.542 0.498

Number of College-Level Math Courses Taken Is Above 

Medianb Dichotomous 0.477 0.499

Used College-Level Math in Nonteaching Job Dichotomous 0.315 0.464

Score on Praxis II Test in Math Content Knowledge (z-score) Continuous 0.176 0.707

Score on Praxis II Test in Middle School Math (z-score) Continuous 0.287 0.917

Number of Hours of Math Pedagogy Instruction During 

Training Is Above Medianc Dichotomous 0.467 0.499

Number of Days of Student Teaching in Math During 

Training Is Above Mediand Dichotomous 0.343 0.475

Hours of Coursework During the School Year (divided by 10) Continuous 5.728 11.964

Has More Than One Year of Teaching Experience Dichotomous 0.876 0.330

Number of Additional Years of Teaching Experience Beyond 

Two Total Years (until teacher has five total years of 

experience) Continuous 1.770 1.292

Number of Additional Years of Teaching Experience Beyond 

Five Total Years Continuous 3.824 7.053

Number of Students 8,669

Number of Classroom Matches 228

Number of Teachers 287

Number of Schools 82

Sources: District administrative records, study-administered Northwest Evaluation Association

assessments, and Survey of Secondary Math Teachers.

Note: Missing values of teacher-level variables are imputed with multiple imputation.

a

Selective colleges are those ranked by Barron’s as very competitive, highly competitive, or most competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching. 
Effectiveness of TFA and Teaching Fellows Teachers 

G.7

Table G.2. Estimated Associations Between Teacher Characteristics and Student Math Achievement in 

Models that Include Only a Single Teacher Characteristic

Teacher Characteristic

Regression 

Coefficient p-Value

Model 1

Entered teaching through TFA 0.075** 0.000

Entered teaching through Teaching Fellows program 0.001 0.956

Model 2

Entered teaching through TFA 0.067** 0.004

Entered teaching through Teaching Fellows program -0.004 0.880

Graduated from selective college or universitya 0.017 0.543

Model 3

Entered teaching through TFA 0.070** 0.000

Entered teaching through Teaching Fellows program -0.003 0.924

Number of college-level math courses taken is above medianb -0.022 0.381

Model 4

Entered teaching through TFA 0.062** 0.004

Entered teaching through Teaching Fellows program 0.014 0.616

Used college-level math in nonteaching job -0.045 0.134

Model 5

Entered teaching through TFA 0.068** 0.004

Entered teaching through Teaching Fellows program -0.007 0.798

Score on Praxis II test in Math Content Knowledge (z-score) 0.017 0.293

Score on Praxis II test in Middle School Math (z-score) 0.002 0.907

Model 6

Entered teaching through TFA 0.075** 0.000

Entered teaching through Teaching Fellows program 0.001 0.967

Number of hours of math pedagogy instruction during training is above 

medianc -0.011 0.668

Model 7

Entered teaching through TFA 0.075** 0.000

Entered teaching through Teaching Fellows program 0.001 0.970

Number of days of student teaching in math during training is above mediand -0.001 0.977

Model 8

Entered teaching through TFA 0.080** 0.000

Entered teaching through Teaching Fellows program 0.001 0.983

Hours of coursework during the school year (divided by 10) -0.002* 0.028

Model 9

Entered teaching through TFA 0.126** 0.000

Entered teaching through Teaching Fellows program 0.029 0.359

Has more than one year of teaching experience 0.069* 0.038

Number of additional years of teaching experience beyond two total years 

(until teacher has five total years of experience) 0.000 0.991

Number of additional years of teaching experience beyond five total years 0.004* 0.040

Number of Students 8,669

Number of Classroom Matches 228

Number of Teachers 287

Number of Schools 82
Effectiveness of TFA and Teaching Fellows Teachers 

Table G.2 (continued)

G.8 

Sources: District administrative records, study-administered Northwest Evaluation Association assessments, and 

Survey of Secondary Math Teachers.

Note: Each model represents a separate regression in which student end-of-year math scores are the 

dependent variable and the displayed variables are the independent variables. All models also include 

classroom match fixed effects and all covariates in Appendix Table B.1. Missing values of teacher-level 

variables are imputed with multiple imputation.

a

Selective colleges are those ranked by Barron’s as very competitive, highly competitive, or most competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching. 

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

G.9

Table G.3. Estimated Associations Between Teacher Characteristics and Student Math Achievement in 

a Model that Includes Multiple Teacher Characteristics: Main Specification

Teacher Characteristic

Regression 

Coefficient p-Value

Entered Teaching Through TFA 0.102* 0.014

Entered Teaching Through Teaching Fellows Program 0.019 0.609

Graduated from Selective College or Universitya 0.003 0.913

Number of College-Level Math Courses Taken Is Above Medianb 

-0.027 0.281

Used College-Level Math in Nonteaching Job -0.038 0.190

Score on Praxis II Test in Math Content Knowledge (z-score) 0.035 0.051

Score on Praxis II Test in Middle School Math (z-score) -0.001 0.955

Number of Hours of Math Pedagogy Instruction During Training Is Above 

Medianc 

-0.014 0.592

Number of Days of Student Teaching in Math During Training Is Above 

Mediand 

-0.003 0.895

Hours of Coursework During the School Year (divided by 10) -0.002* 0.041

Has More Than One Year of Teaching Experience 0.080* 0.016

Number of Additional Years of Teaching Experience Beyond Two Total 

Years (until teacher has five total years of experience) -0.004 0.755

Number of Additional Years of Teaching Experience Beyond Five Total 

Years 0.005* 0.017

Number of Students 8,669

Number of Classroom Matches 228

Number of Teachers 287

Number of Schools 82

Sources: District administrative records, study-administered Northwest Evaluation Association 

assessments, and Survey of Secondary Math Teachers. 

Note: The model in the table represents a single regression in which student end-of-year math scores 

are the dependent variable and the displayed variables are the independent variables. The model

also includes classroom match fixed effects and all covariates in Appendix Table B.1. Missing 

values of teacher-level variables are imputed with multiple imputation.

a

Selective colleges are those ranked by Barron’s as very competitive, highly competitive, or most competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
G.10 

Table G.4. Extent to Which Teacher Characteristics Explain the Difference in Effectiveness Between TFA Teachers and Comparison Teachers 

Teacher Characteristic

Regression Coefficient 

from Model that 

Includes Multiple 

Teacher Characteristics 

(Table G.3) 

Average Difference in Characteristic 

between TFA Teachers and 

Comparison Teachers

Predicted Difference in 

Effectiveness Between 

TFA Teachers and 

Comparison Teachers 

Estimate p-Value (z-score units)

Graduated from Selective College or Universitya 0.003 0.450** 0.000 0.001

Number of College-Level Math Courses Taken Is Above 

Medianb -0.027 -0.233** 0.001 0.006

Used College-Level Math in a Nonteaching Job -0.038 -0.289** 0.000 0.011

Score on Praxis II Test in Math Content Knowledge (z-score) 0.035 0.354** 0.001 0.012

Score on Praxis II Test in Middle School Math (z-score) -0.001 0.780** 0.000 -0.001

Number of Hours of Math Pedagogy Instruction During 

Training Is Above Medianc -0.014 0.012 0.884 0.000

Number of Days of Student Teaching in Math During Training 

Is Above Mediand -0.003 -0.046 0.538 0.000

Hours of Coursework During the School Year (divided by 10) -0.002* 2.641 0.160 -0.005

Has More Than One Year of Teaching Experience 0.080* -0.327** 0.000 -0.026

Number of Additional Years of Teaching Experience Beyond 

Two Total Years (until teacher has five total years of 

experience) -0.004 -2.301** 0.000 0.010

Number of Additional Years of Teaching Experience Beyond 

Five Total Years 0.005* -7.324** 0.000 -0.036

Total Predicted Difference in Effectiveness Between TFA 

Teachers and Comparison Teachers Based on All 

Characteristics -0.028

Total Observed Difference in Effectiveness Between TFA 

Teachers and Comparison Teachers 0.075

Number of Students 8,669

Number of Classroom Matches 228

Number of Teachers 287

Number of Schools 82
Table G.4 (continued)

G.11 

Source: District administrative records, study-administered Northwest Evaluation Association assessments, and Survey of Secondary Math Teachers. 

Note: Differences in characteristics between TFA and comparison teachers are estimated from a student-level regression of the indicated teacher 

characteristic on a TFA indicator, classroom match fixed effects, and all covariates in Appendix Table B.1. Therefore, estimated differences might not 

be identical to those calculated from teacher-level data in Chapter IV. Missing values of teacher-level variables are imputed with multiple imputation.

a

Selective colleges are those ranked by Barron’s as very competitive, highly competitive, or most competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching. 

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America. 
Effectiveness of TFA and Teaching Fellows Teachers 

G.12 

Table G.5. Estimated Associations Between Teacher Characteristics and Student Math Achievement in 

Models that Include Multiple Teacher Characteristics: Specifications with Alternative Measures of College 

Selectivity

 Model 1 Model 2

Teacher Characteristic

Regression 

Coefficient p-Value

Regression 

Coefficient p-Value

Entered Teaching Through TFA 0.111** 0.004 0.104* 0.012

Entered Teaching Through Teaching Fellows Program 0.021 0.546 0.017 0.635

Graduated from Highly Selective College or Universitya 

-0.042 0.338 -0.034 0.511

Graduated from Selective but Not Highly Selective College or 

Universitya 0.013 0.648

Number of College-Level Math Courses Taken Is Above 

Medianb 

-0.027 0.266 -0.027 0.276

Used College-Level Math in Nonteaching Job -0.037 0.192 -0.037 0.188

Score on Praxis II Test in Math Content Knowledge (z-score) 0.038* 0.025 0.037* 0.035

Score on Praxis II Test in Middle School Math (z-score) 0.002 0.909 0.002 0.904

Number of Hours of Math Pedagogy Instruction During 

Training Is Above Medianc 

-0.017 0.488 -0.017 0.495

Number of Days of Student Teaching in Math During Training 

Is Above Mediand 0.003 0.916 0.002 0.933

Hours of Coursework During the School Year (divided by 10) -0.002* 0.027 -0.002* 0.030

Has More Than One Year of Teaching Experience 0.080* 0.016 0.081* 0.015

Number of Additional Years of Teaching Experience Beyond 

Two Total Years (until teacher has five total years of 

experience) -0.002 0.863 -0.003 0.844

Number of Additional Years of Teaching Experience Beyond 

Five Total Years 0.005* 0.016 0.005* 0.019

Number of Students 8,669 8,669

Number of Classroom Matches 228 228

Number of Teachers 287 287

Number of Schools 82 82

Sources: District administrative records, study-administered Northwest Evaluation Association assessments, and 

Survey of Secondary Math Teachers. 

Note: Each model represents a separate regression in which student end-of-year math scores are the 

dependent variable and the displayed variables are the independent variables. All models also include 

classroom match fixed effects and all covariates in Appendix Table B.1. Missing values of teacher-level 

variables are imputed with multiple imputation.

a

Highly selective colleges are those ranked by Barron’s as most competitive. Selective but not highly selective 

colleges are those ranked by Barron’s as very competitive or highly competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching. 

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America. 
G.13 

Table G.6. Estimated Associations Between Teacher Characteristics and Student Math Achievement in Models that Include Multiple Teacher 

Characteristics: Specifications with Measures of Academic Degrees in Math or Math-Related Subjects

 

Model 1:

Broader Definition of 

Math-Related Subject 

Model 2:

Broader Definition of 

Math-Related Subject 

Model 3:

Narrower Definition of 

Math-Related Subject

Model 4:

Narrower Definition of 

Math-Related Subject

Teacher Characteristic

Regression 

Coefficient p-Value

Regression 

Coefficient p-Value

Regression 

Coefficient p-Value

Regression 

Coefficient p-Value

Entered Teaching Through TFA 0.096* 0.020 0.089* 0.038 0.110** 0.005 0.105* 0.011

Entered Teaching Through Teaching Fellows 

Program 0.008 0.812 0.005 0.879 0.023 0.517 0.019 0.614

Graduated from Selective College or Universitya 

-0.004 0.899 0.007 0.851 -0.003 0.931 0.005 0.883

Has College Minor in Math or Math-Related 

Subjectb 

-0.044 0.320 -0.024 0.631 -0.037 0.370 -0.021 0.717

Has College Major in Math or Math-Related 

Subjectb

-0.038 0.243 -0.035 0.429 -0.015 0.627 -0.009 0.826

Has Advanced Degree in Math or Math-Related 

Subjectb 0.001 0.984 0.002 0.955 -0.068 0.147 -0.068 0.156

Has College Minor in Math or Math-Related 

Subject from Selective College or Universitya, b 

-0.053 0.455 -0.032 0.748

Has College Major in Math or Math-Related 

Subject from Selective College or Universitya, b 

-0.008 0.892 -0.009 0.868

Used College-Level Math in Nonteaching Job -0.031 0.293 -0.033 0.257 -0.029 0.310 -0.028 0.320

Score on Praxis II Test in Math Content 

Knowledge (z-score) 0.034 0.056 0.034 0.061 0.029 0.143 0.029 0.158

Score on Praxis II Test in Middle School Math (zscore) 0.003 0.812 0.004 0.777 -0.001 0.944 0.000 0.979

Number of Hours of Math Pedagogy Instruction 

During Training Is Above Medianc 

-0.017 0.521 -0.016 0.539 -0.005 0.840 -0.005 0.830

Number of Days of Student Teaching in Math

During Training Is Above Mediand 0.002 0.951 -0.002 0.934 -0.004 0.891 -0.006 0.829

Hours of Coursework During the School Year 

(divided by 10) -0.002* 0.041 -0.002* 0.035 -0.002* 0.039 -0.002* 0.039

Has More Than One Year of Teaching 

Experience 0.076* 0.024 0.077* 0.023 0.079* 0.017 0.083* 0.015

Number of Additional Years of Teaching 

Experience Beyond Two Total Years (until 

teacher has five total years of experience) -0.001 0.911 -0.003 0.829 -0.004 0.789 -0.005 0.719
Table G.6 (continued)

G.14 

 

Model 1:

Broader Definition of 

Math-Related Subject 

Model 2:

Broader Definition of 

Math-Related Subject 

Model 3:

Narrower Definition of 

Math-Related Subject 

Model 4:

Narrower Definition of 

Math-Related Subject

Teacher Characteristic

Regression 

Coefficient p-Value

Regression 

Coefficient p-Value

Regression 

Coefficient p-Value

Regression 

Coefficient p-Value

Number of Additional Years of Teaching 

Experience Beyond Five Total Years 0.005* 0.025 0.005* 0.032 0.005* 0.013 0.005* 0.020

Number of Students 8,669 8,669 8,669 8,669 

Number of Classroom Matches 228 228 228 228 

Number of Teachers 287 287 287 287 

Number of Schools 82 82 82 82 

Sources: District administrative records, study-administered Northwest Evaluation Association assessments, and Survey of Secondary Math Teachers.

Note: Each model represents a separate regression in which student end-of-year math scores are the dependent variable and the displayed variables are 

the independent variables. All models also include classroom match fixed effects and all covariates in Appendix Table B.1. Missing values of teacherlevel variables are imputed with multiple imputation.

a

Selective colleges are those ranked by Barron’s as very competitive, highly competitive, or most competitive.

b

In the broader definition, math-related subjects include mathematics, secondary mathematics education, statistics, engineering, computer science, finance, 

economics, and physics/astrophysics. The narrower definition includes all of the aforementioned subjects except secondary math education.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching. 

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America. 
Effectiveness of TFA and Teaching Fellows Teachers 

G.15 

Table G.7. Estimated Associations Between Teacher Characteristics and Student Math Achievement in 

Models that Include Multiple Teacher Characteristics: Specifications with Alternative Measures of Praxis 

Achievement

 Model 1 Model 2

Teacher Characteristic

Regression 

Coefficient p-Value

Regression 

Coefficient p-Value

Entered Teaching Through TFA 0.102** 0.010 0.109** 0.006

Entered Teaching Through Teaching Fellows Program 0.009 0.796 0.026 0.448

Graduated from Selective College or Universitya 0.000 0.990 0.004 0.885

Number of College-Level Math Courses Taken Is Above 

Medianb 

-0.035 0.160 -0.023 0.357

Used College-Level Math in Nonteaching job -0.038 0.179 -0.044 0.136

Score on Praxis II Test in Math Content Knowledge Is Above 

Median 0.114** 0.001

Score on Praxis II Test in Middle School Math Is Above Median 0.008 0.784

Score on Praxis II Test in Math Content Knowledge Is at Least 

as High as State’s Passing Thresholdc 0.050 0.258

Score on Praxis II Test in Middle School Math Is at Least as 

High as State’s Passing Thresholdc 

-0.030 0.466

Number of Hours of Math Pedagogy Instruction During Training 

Is Above Mediand 

-0.007 0.774 -0.008 0.752

Number of Days of Student Teaching in Math During Training 

Is Above Mediane 

-0.010 0.683 -0.006 0.834

Hours of Coursework During the School Year (divided by 10) -0.002 0.055 -0.002* 0.035

Has More Than One Year of Teaching Experience 0.088** 0.007 0.079* 0.020

Number of Additional Years of Teaching Experience Beyond 

Two Total Years (until teacher has five total years of 

experience) -0.002 0.873 -0.002 0.859

Number of Additional Years of Teaching Experience Beyond 

Five Total Years 0.005** 0.006 0.004* 0.040

Number of Students 8,669 8,669

Number of Classroom Matches 228 228

Number of Teachers 287 287

Number of Schools 82 82

Sources: District administrative records, study-administered Northwest Evaluation Association assessments, and 

Survey of Secondary Math Teachers.

Note: Each model represents a separate regression in which student end-of-year math scores are the 

dependent variable and the displayed variables are the independent variables. All models also include 

classroom match fixed effects and all covariates in Appendix Table B.1. Missing values of teacher-level 

variables are imputed with multiple imputation. a

Selective colleges are those ranked by Barron’s as very competitive, highly competitive, or most competitive. b

Teacher at the median took 7.5 college-level math courses. c

If the teacher’s state does not require the indicated Praxis test, then the passing threshold is specified as the 

average threshold across all states that require this test.

d

Teacher at the median had 21 to 40 hours of math pedagogy instruction. e

Teacher at the median had 16 to 20 days of student teaching. 

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
Effectiveness of TFA and Teaching Fellows Teachers 

G.16 

Table G.8. Estimated Associations Between Teacher Characteristics and Student Math Achievement in 

a Model that Includes Multiple Teacher Characteristics: Specification with Teacher Demographic 

Characteristics

Teacher Characteristic

Regression 

Coefficient p-Value

Entered Teaching Through TFA 0.107* 0.017

Entered Teaching Through Teaching Fellows Program 0.016 0.630

Graduated from Selective College or Universitya 0.001 0.969

Number of College-Level Math Courses Taken Is Above Medianb 

-0.033 0.186

Used College-Level Math in Nonteaching Job -0.035 0.230

Score on Praxis II Test in Math Content Knowledge (z-score) 0.042* 0.019

Score on Praxis II Test in Middle School Math (z-score) 0.010 0.515

Number of Hours of Math Pedagogy Instruction During Training Is Above 

Medianc 

-0.016 0.509

Number of Days of Student Teaching in Math During Training Is Above 

Mediand 

-0.003 0.903

Hours of Coursework During the School Year (divided by 10) -0.002* 0.044

Has More Than One Year of Teaching Experience 0.084* 0.015

Number of Additional Years of Teaching Experience Beyond Two Total 

Years (until teacher has five total years of experience) -0.008 0.543

Number of Additional Years of Teaching Experience Beyond Five Total 

Years 0.005* 0.036

Teacher is Female 0.061* 0.014

Teacher’s Age (in years) -0.001 0.705

Teacher is Black 0.032 0.369

Teacher Has Same Black/Nonblack Status as Student -0.021 0.322

Number of Students 8,669

Number of Classroom Matches 228

Number of Teachers 287

Number of Schools 82

Sources: District administrative records, study-administered Northwest Evaluation Association 

assessments, and Survey of Secondary Math Teachers. 

Note: The model in the table represents a single regression in which student end-of-year math scores 

are the dependent variable and the displayed variables are the independent variables. The model

includes classroom match fixed effects and all covariates in Appendix Table B.1. Missing values of 

teacher-level variables are imputed with multiple imputation.

a

Selective colleges are those ranked by Barron’s as very competitive, highly competitive, or most competitive.

b

Teacher at the median took 7.5 college-level math courses.

c

Teacher at the median had 21 to 40 hours of math pedagogy instruction.

d

Teacher at the median had 16 to 20 days of student teaching.

 *Estimate is statistically significant at the 0.05 level, two-tailed test.

**Estimate is statistically significant at the 0.01 level, two-tailed test.

TFA = Teach For America.
This page has been left blank for double–sided copying.