Repairing the Teacher Pipeline for People of Color- Three Essays

University of Connecticut OpenCommons@UConn Doctoral Dissertations University of Connecticut Graduate School 8-19-2020 Repairing the Teacher Pipeline for People of Color: Three Essays on Minority Teacher Scholarships Jeremy Landa University of Connecticut - Storrs, jeremy.landa@uconn.edu Follow this and additional works at: https://opencommons.uconn.edu/dissertations Recommended Citation Landa, Jeremy, "Repairing the Teacher Pipeline for People of Color: Three Essays on Minority Teacher Scholarships" (2020) Doctoral Dissertations 2633 https://opencommons.uconn.edu/dissertations/2633 Repairing the Teacher Pipeline for People of Color: Three Essays on Minority Teacher Scholarships Jeremy B Landa, Ph.D University of Connecticut, 2020 Despite near consensus agreement about the importance of increasing the presence of teachers of color in schools, there is limited research on how public policy can solve this problem Drawing on federal and one university’s teacher education data, this dissertation addresses whether a Minority Teacher Scholarship (MTS) can alter the labor supply of teachers of color The first essay evaluates whether five states implementing MTS programs increase the proportion of candidates of color earning teacher education bachelor’s degrees Using event study and difference-in-differences frameworks, I find that implementing states stabilized the share of Black candidates relative to non-implementing states, a result driven by changes in private institutions and states with the greatest financial value awards In the second essay, I estimate whether teacher candidates of color in the same program are more likely to complete a degree if receiving MTS aid Using linear probability and propensity score matching models, I find MTS receipt associated positively with bachelor’s and master’s degree completion for individuals who were observably similar on individual characteristics The third essay investigates whether teacher candidates of color in the same program university respond MTS awards differentially in the labor market Using linear probability and discrete-time survival analysis models, I find that MTS receipt associated positively with public school teaching employment within two years of graduation, and negatively with exiting teaching in a public school for individuals of color from the same program The three studies provide suggestive evidence that MTS programs benefit individuals and the largest group of people of color in states implementing MTS programs Repairing the Teacher Pipeline for People of Color: Three Essays on Minority Teacher Scholarships Jeremy B Landa B.A., Wayne State University, 2003 Ed.M., Harvard University, 2009 M.A University of Connecticut, 2017 A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy at the University of Connecticut 2020 ii Copyright by Jeremy Benjamin Landa 2020 iii Approval Page Doctor of Philosophy Dissertation Repairing the Teacher Pipeline for People of Color: Three Essays on Minority Teacher Scholarships Presented by Jeremy B Landa, B.A, Ed.M., M.A Dissertation Chair and Advisor _ Morgaen L Donaldson, Ed.D Dissertation Committee Shaun M Dougherty, Ed.D Dissertation Committee Eric J Brunner, Ph.D Dissertation Committee Ann Traynor, Ed.D Dissertation Committee H Kenny Nienhusser, Ed.D University of Connecticut 2020 iv Dedication For Shari, who made this possible For Oscar and George, who kept me grounded while completing work that is ostensibly maddening For my family, near and far, whose shoulders I stood on to achieve this feat And for Elise As the first-born, I thought you deserved to be the first doctor in our immediate family v Acknowledgements I am grateful to my committee whose efforts are the reason I produced a dissertation To Morgaen Donaldson, who made me a better writer, thinker, and was always willing to provide feedback and guidance despite her busy schedule To Shaun Dougherty, whose mentorship and investment in my career has persisted through his own job transition To Eric Brunner, who responded with patience and support to numerous stream of consciousness methodological questions To Ann Traynor, who has been an eager broker of data access and provider of practitioner insight for this work And to Kenny Nienhusser, whose detailed and organized feedback and orientation to criticality has always made me pause and think Thanks to my colleagues—in particular to Monique Golden, who helped me survive the first three years of classes, and Daron Cyr, who became a regular thought partner and a provider of feedback on my dissertation writings Thanks to Sam Kamin, whose presence ensured that I know something about statistics and can use Stata fluently Thanks to Michael Correl, Chelsea Connery, Alex Lamb, Shannon Holder, Britney Jones, Patricia Virella, and Dave Alexandro whose feedback, cheerleading, and camaraderie sustained me when the requirements felt overwhelming And to Shari, who took on the bulk of the childcare during the pandemic so that I could reach the finish line in this doctoral journey I can’t imagine having done any of this without you, and cannot wait for what the future holds vi Table of Contents Acknowledgements v Table of Contents vi List of Tables ix List of Figures x Chapter Repairing the Teacher Pipeline for People of Color: Evidence from States Adopting Minority Teacher Scholarships Background The Dysfunctional Teacher Pipeline for Individuals of Color Preparation Pathways State Scholarships, Public Service, and Teacher Scholarships States’ Approaches to Scholarships State Merit Scholarships State Financial Need Scholarships Public Service and Scholarships The Outcomes of Teaching Scholarships 10 Conceptual Framework 11 Methods 12 Program Description and Context 13 Type 17 Eligibility Criteria 17 Generosity 19 Data Source 19 Summary Statistics 20 Outcomes 29 Controls 29 Empirical Strategy 32 Results 34 Event Study 35 Difference-in-Differences Estimates 38 Tests of Robustness 42 Heterogeneous Effects 46 Greatest Financial Value Scholarships 46 Private Higher Education Institutions 50 Placebo Test 53 Discussion and Implications 57 Limitations 58 Financial Incentives are not Large Enough 59 Programs are not Scaled Properly 60 Programs are Substitutes of State Level Financial Aid Based on Merit or Need 61 Programs are Adopted in States with Specific Racial-Ethnic Structures 62 Implications 63 References 66 Appendix 1-A Procedures for Identifying “Minority Teacher Scholarship” Program States 71 vii Appendix 1-B Classification of Instructional Programs (CIP) Code selection for Teachers and Nursing 72 Chapter Do Minority Teacher Scholarships Lessen Leaks in the Teacher Pipeline? Evidence Flagship University’s Traditional Teacher Education Program 74 Background 76 Teachers of Color Matter for Schooling 78 Entry into the Teacher Pipeline for Individuals of Color 79 The Challenges of Unobserved Selection for Identifying Causal Impacts 81 Theoretical Framework 83 Methods 84 Program Description 84 University Context 85 Data 86 Measures 86 Outcomes 86 Independent Variables 87 Summary Statistics 88 Empirical Strategy 92 Coefficient Stability 92 Propensity Score Matching 93 Alternative Matching Strategies 95 Findings 95 OLS Estimates 96 Propensity Score Matching Estimates 99 Sensitivity Analysis 100 Remove GPA Cut-Off Years 100 Tests of Differential Associations 102 Differential Results by Cohort 102 Differential Results by Pre-Teaching Major or Financial Aid Based on Need 104 Discussion and Implications 106 Limitations 107 Discussion 108 Implications 109 References 113 Appendix 2-A Procedures for identifying “Minority Teacher Scholarship” Program States 118 Appendix 2-B Common Support and Covariate Balance 119 Chapter Minority Teacher Scholarships and Employment: A Case Study of Labor Market Outcomes from Flagship University’s Traditional Teacher Education Program 122 Background 124 Financial Aid Incentives for Teaching Service 126 Differential Access to Teacher Labor Markets by Race/Ethnicity 128 Employment 129 viii Turnover 130 Theoretical Framework 132 Research Questions 133 Methods 133 Program Description 133 University Context 135 Data Sources and Sample 136 Outcomes 136 Employment 137 Exit 137 Educators or Students of Color 137 Predictors 138 Predictor of Interest 138 Covariates 138 Empirical Strategy 140 Employment 140 Exit 141 Students or Educators of Color 141 Findings 143 Summary Statistics 143 Inferential Statistics 147 Employment 147 Exit 149 Discrete Time Survival Analysis Models 149 Kaplan-Meier Survival Curves 151 Racial and Ethnic Match in Schools and MTS Status 153 Students of Color 153 Educators of Color 157 Limitations, Discussion, and Implications 160 References 166 Appendix A 172 160 Limitations, Discussion, and Implications This paper presents new evidence exploring the relationship between an MTS award and employment for teacher candidates of color in the same teacher education program I find suggestive evidence of a positive relationship between MTS awards and probability of employment within two years of graduating from a master’s program and a negative relationship between MTS awards and the probability of exit from teaching Notably, I find evidence that MTS recipients exited less than individuals who did not receive an MTS while loan stipends were available (four years) and evidence of increased exit of MTS recipients in the year that loan stipends conclude Finally, I found a statistically significant and positive associations between receipt of an MTS award and the proportion of people of color in the same school building for the first seven years of employment Teachers of color who received an MTS award gained employment and remained in schools with more students of color relative to peers who did not receive an MTS award Teachers of color who received MTS awards also began and continued working with more Black educators than teachers of color who did not In sum, I interpret this evidence to suggest that MTS aid relates to employment outcomes and sorting to schools serving different amounts of students or colleagues of color Despite the promise of this evidence, there are limitations related to selection, right censoring, and omitted variables bias that threaten the internal validity of the estimates First, I not observe MTS selection directly and thus cannot rule out that unobserved selection criteria into MTS This is problematic if the unobserved selection criteria are applied systematically within the university’s teacher education program and would result in an over-estimate of the relationship Second, right censoring bias is a problem because the time frame of the data ensures that most individuals are observed for less than the entire time frame and many individuals will 161 never experience the event of interest This threatens inferences from this work because it is possible that teachers revealed behaviors are obscured resulting in either over- or underestimates Third, there are several omitted variables that potentially correlate with MTS awards and the outcomes, such as other financial aid received, family income, personal motivation and dedication to teaching, or first-generation higher education student These variables could bias estimation in either direction since it is feasible that they covary with treatment and outcome This study also has an important limitation to the generalizability across settings Since this case study uses data from a single flagship university, it remains uncertain if the results would replicate in other university’s or other states that have implemented differently designed programs or contextual features No evidence here should be interpreted as conclusive that MTS programs work the same way in all university’s or certification pathways Future studies should aim to collect all data from across a state implementing a program in order to estimate intent-totreat and treatment-on-the-treated effects of programs Despite the limitations, the evidence here bodes well for MTS programs as an important public policy that states can use as part of a broader set of strategies to increase the racial and ethnic diversity of their teacher workforce Notably, the findings align with prior evidence showing that (a) individuals with strong academic credentials enter teaching more frequently when receiving scholarships (Henry et al., 2012), (b) teachers respond to service scholarships or loan forgiveness by working in hard-to-staff schools or subjects more (Feng & Sass, 2018; Steele et al, 2011), and (c) individuals enter public service jobs when potential student loans are reduced (Field, 2009; Rouse & Rothstein, 2011) If the policies cause increases in representation of teachers of color in the workforce, prior studies suggest this could lead to important benefits 162 for students of color (Bristol & Martin-Fernandez, 2019; Dee, 2004; 2005; Gershenson et al., 2018; Redding, 2019) There is strongly suggestive evidence from this study that some teachers responded to the incentives of this program A small, but particularly relevant, body of work suggests that financial aid incentives may increase sorting into public service careers when they lower tuition because they (a) reduce or (b) eliminate potential student loans (Field, 2009; Rouse & Rothstein, 2011), thereby addressing racial or ethnic differences in aversion to loans (Boatman et al., 2017) or sensitivity to loan sizes (Baker et al., 2018) This study, when synthesized with the evidence from Landa (2020a), affirms that several teachers of color responded, as theory would predict, to reductions in the costs of schooling and acquired student loans This information, while not conclusive, should challenge public policymakers to think carefully about the optimal design features of teacher scholarships broadly and MTS aid specifically I pose two questions of import for consideration: (1) Is a program more effective with frontloaded tuition reductions or backloaded student loan debt forgiveness? Existing evidence suggests the former, but there is evidence that the later also works in Florida (Sass & Feng, 2018) This is a fertile area for future experimentation to gain a deeper understanding of how different financial aid approaches Field (2009) offers an experimental approach to test hypothesis that individuals who receive money upfront rather than on the backend of schooling take up educational opportunity and public service occupations more Researchers moving forward on this work would be able address issues related to selection bias found in this paper since random assignment is a possibility A second question worth answering is: (2) What are the costs and benefits of changing the length of the incentive (e.g., loan stipend program) for practicing teachers? If the loan stipend 163 program extends the length that a teacher of color remains, this would potentially improve several average conditions of education First, students of color may gain (Bristol & MartinFernandez, 2019; Dee, 2004; 2005; Gershenson et al., 2018; Redding, 2019) since teachers of color would be better represented amongst teachers, and this change may reduce harsh disciplinary, and biased grading or gatekeeping practices Second, inequitable sorting of new teachers into schools with large proportions of novice teachers may be reduced, a labor market condition that differential affects students by race and ethnicity (Goldhaber et al., 2015; Lankford et al., 2002) This change could yield important benefits for students of color since returns to teacher experiences are quite large in the first few years of teaching (Atteberry et al., 2015; Kraft & Papay, 2014) Answering this question also helps spell out the contributions of an MTS program If these contributions confirm my studies of a single university’s teacher education program, they may demonstrate how spending money in this manner is a worthy investment of taxpayer dollars Finally, I also found that financial aid incentives from the MTS related to recipients working in schools with more students of color and Black colleagues I consider this a curious result that requires more investigation Is this result an artifact of scholarship recipients’ differential commitments to schooling than individuals who never received scholarships? Given the differences begin at entry as a teacher and persist over time, to some extent this result is likely some combination of access related to social networks (Cannata, 2011; Jabbar et al., 2019), humanistic commitments to students (Irizarry & Donaldson, 2012), and hiring processes (Goings et al., 2019; 2020; Ingle et al., 2011) The evidence here supports the contention of some researchers that one policy solution to inadequate labor supply across schools that are hard-tostaff would be to increase the proportion of teacher candidates of color (Achinstein et al., 2010) 164 Moving forward, this work also highlights a key challenge that researchers and policymakers need to jointly take on Data in this area is extremely limited because higher education and teacher employment data typically requires cross agency collaboration, which is often dependent on the goals of individual employees within government Researchers should aim to collaborate with state policymakers so that each state has a comprehensive and linked teacher education and teacher labor market database The maintenance of a longitudinal database would increase opportunities to externally evaluate programs like MTS or describe changes to the workforce on the state level It would also increase opportunities for individual teacher education programs to evaluate their curriculums, mentorship, and clinical aspects of their work with data sharing between state education agencies On this note though, the administrative data available currently may have important information missing In this study, I draw on a crude proxy variable (Delisle, 2017), financial need aid awarded during college, to detect whether there are differences in employment outcomes However, there are several other factors that might be more productive for statistical models These include but are not limited to parent’s income, educational attainment levels, and occupation if a mother is a teacher (Jacinto & Gershenson, 2019) and student loan size at time of graduation (Baker et al., 2018) Ultimately, these more granular variables may address selection even if it is weakly identified In conclusion, recruiting, training, hiring, and retaining quality teachers of color with financial aid programs holds great potential to improve the experiences and outcomes of students of color in American public schools This study aimed to uncover the evidence about whether teachers of color differed on employment outcomes conditional upon receiving an MTS The evidence here suggests that financial incentives relate to teacher’s entry and retention in the 165 workforce Financial incentives should be part of a broader set of policies to increase the proportion of teachers of color in the workforce I call for further quantitative inquiry into MTS programs and qualitative inquiry to better understand the perceptions of which mechanisms support them on their journey to teaching 166 References Achinstein, B., Ogawa, R T., Sexton, D., & Freitas, C (2010) Retaining teachers of color: A pressing problem and a potential strategy for “hard-to-staff” schools Review of Educational Research, 80(1), 71-107 Allegretto, S., & Mishel, L (2018) The teacher pay penalty has hit a new high Economic Policy Institute https://www.epi.org/files/pdf/153196.pdf Atteberry, A., Loeb, S., & Wyckoff, J (2015) Do first impressions matter? 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The impact of the Brown v Board of Education decision on the employment status of Black educators Education and urban society, 36(3), 280-303 U.S Department of Education (2016) The state of racial diversity in the educator workforce Washington, DC: U.S Department of Education, Office of Planning, Evaluation and Policy Development, Policy and Program Studies Service Villegas, A M., Strom, K., & Lucas, T (2012) Closing the racial/ethnic gap between students of color and their teachers: An elusive goal Equity & Excellence in Education, 45(2), 283301 172 Appendix A Table A.1 State Level Financial Incentives for Pre- and In-service Teachers State Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Program Titles Alabama Teacher Recruitment Incentive Scholarship; Technology Scholarship for Alabama Teachers Alaska Teacher Scholarship Program Arizona Teacher Student Loan Program (ATSLP); Math, Science, & Special Education Teacher Loan Forgiveness Program (MSSE) Arkansas Geographical Critical Needs Program; Arkansas Minority Teacher Scholarship; Minority Masters Fellows Program; State Teacher Assistance Resource Program; State Teacher Education Program; Teacher Opportunity Program; APLE for Credentialed Teachers (K-12); Assumption Program of Loans for Education (APLE); Child Development Teacher & Supervisor Grant Program; State Work Study & Teacher Intern Program None Minority Teacher Incentive Program Grant Christa McAuliffe Teacher Incentive Program; Critical Need Scholarship; Delaware Teacher Corps MTS program Teacher Practice Scholarship Critical Needs Teacher Scholarship 1996 2006; 2010 2005 2003 2003 1990; 2004 2003 1990 1992 Teacher Scholarship Program Grow Your Own Program 2009; 1994 1995 2017; 2012 1995; 2001 1998 None Florida Fund for Minority Teachers; Chappie James Promising Teacher Loan; Critical Teacher Shortage Tuition Reimbursement Promise II Teacher None Grow Your Own Teacher Scholarship; Idaho Student Education Incentive Loan Forgiveness Contract Golden Apple; Illinois Future Teacher Corp Scholarship Program; Minority Teacher Scholarship MTI; Teacher Shortage Scholarships; Teacher and Child Care Provider Loan Repayment Program Minority Teacher Scholarship I Indiana; Minority Teacher Stipend Iowa Teacher Shortage Loan Forgiveness Program; Teach Iowa Scholar Kansas Special Education Teacher Service Scholarship; Kansas Teacher Education Scholarship; Kansas Teacher Service Scholarship 2003 2002 1991 1993 2002 2002; 2003 2005 2003 1990; 2014 2002; 2015 2007; 2007; 1991 2013 173 Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska New Hampshire New Jersey New Mexico New York Nevada North Carolina North Dakota Ohio Oregon Pennsylvania Rhode Island South Carolina South Dakota Kentucky Teacher Scholarship/Loan; Minority Educator Recruitment and Retention Scholarship TOPS Teacher Scholarship Program Educators For Maine Distinguished Scholar Teacher Education Award; Maryland Teacher Scholarship Tomorrow's Teachers Scholarship None Indian Teacher Education Scholarship Graduate Teacher; Teacher Education Scholars; William Winter Teaching Program Missouri Minority Teaching Scholarship; Missouri Teacher Education None None 2003 1990 2003 2003 1991; 2000 2003 1992* 2003; 2014; 1990 1993 1993 None Teaching Fellows Program Minority Teachers Program; Teacher Loan Repayment NYS Masters-in-Education Teacher Incentive Scholarship Program None Millennium Teacher Scholarship/Loans; NC Teaching Fellows Program; Physical Education-Coaching Scholarship Loan Prospective Teacher Scholarship Loan Teacher Retraining Scholarship None Oregon Troops to Teachers Science Teachers Education Program Best and Brightest Teacher Scholarship South Carolina Teaching Fellows 2010 1993* 2014 2017 2006 1991; 2006; 2003 2003 2006 1993 1993 1999 None Christa McAuliffe Scholarship; 2003; Tennessee Minority Teaching Fellows Program; 1991 1990 Tennessee Teaching Scholars Texas Texas Grow Your Own Utah Terrel H Bell Teaching Incentive 1997 Vermont None Higher Education Teacher Assistance Program; Southside Virginia Tobacco Teacher 2004; Virginia Scholarship/Loan Program; 2003 Virginia Teacher Scholarship Loan Program Washington Future Teachers Conditional Scholarship 1990 West Virginia Underwood Smith Teacher Scholarship 1991 Minority Teacher Loan; Wisconsin 1990 2003 Teacher of the Visually Impaired Loan * indicates no information available to confirm the program existence or implementation 2018 1994 174 Table A.2 Definitions of Variables for Study of Employment Outcomes for MTS recipients Outcome Variables Employment within years of graduation Exit from teaching Proportion of Licensed Educators of Color Proportion of Students of Color Treatment MTS Descriptions A dichotomous variable that takes on a value of if a teacher has an employment record in year t or year t+1 and completed a master’s teacher education degree and a if they did not A dichotomous variable that takes on a value of if a student of color completed a master’s teacher education degree, gained employment prior to year t+1, and had a teacher employment record in year t and year t+1 and a if they did not A continuous variable between and that is calculated by dividing the number of licensed educators of color at school s in year t by the number of licensed educators at school s in year t A continuous variable between and that is calculated by dividing the number of students of color at school s in year t by the number of students at school s in year t A dichotomous variable that takes on a value of if a student of color receives an MTS award and a if a student of color does not receive an MTS award Independent Variables Pre-teach major Received State or Federal Need Aid Not a resident at time of college matriculation Age 25 Age 30 Gender Shortage “A” Student Proportion of Licensed Educators of Color (std) Proportion of Students of Color (std) Urbanicity Graduation Year A dichotomous variable that takes on a value of if a student is a pre-teach education major and a if they are not A dichotomous variable that takes on a value of if a student received any state or federal need aid during their time at the flagship university and a if they did not A dichotomous variable that takes on a value of if a teacher i was not a resident of the same state at the time of matriculation to the university and a if they were a resident A dichotomous variable that takes a value of when teacher i at school s in year t is at least 25 and a if teacher i is less than 25 A dichotomous variable that takes a value of when teacher i at school s in year t is at least 30 and a if teacher i is less than 30 A dichotomous variable that takes on a value of if a student is male and a value of if female A categorical variable that take a value of: if a student is preparing in a shortage area (STEM, SPED, or foreign language) and a if a student is preparing in a non-shortage area (elementary, humanities, music) A dichotomous variable that takes a value of when teacher i at school s in year t graduated with a GPA of greater than 3.3 and a if teacher i had a GPA less than or equal to 3.3 A standardized continuous variable with a mean of and a standard deviation of that is calculated by subtracting the proportion of licensed educators of color for all individual observations in the data from proportion of licensed educators of color for the individual teacher at school s in year t and dividing that by the standard deviation for all observations of licensed educators of color A standardized continuous variable with a mean of and a standard deviation of that is calculated by subtracting the proportion of students of color for all individual observations in the data from proportion of students of color for the individual teacher at school s in year t and dividing that by the standard deviation for all observations of students of color This is a set of four categorical variables that takes a value of if teacher i is employed in school s and urbanicity u (e.g., mid-sized or small urban, suburban, or rural/town) and a if the urbanicity does not match teacher i employment location This is a set of 12 categorical variables that takes a value of if it is the graduation year for the student and a if it is not .. .Repairing the Teacher Pipeline for People of Color: Three Essays on Minority Teacher Scholarships Jeremy B Landa, Ph.D University of Connecticut, 2020 Despite near consensus agreement about the. .. of higher education alternative pathways, only 18% of the total teacher workforce and 22% of the workforce with less than or fewer years of experience were teachers of color (U.S Department of. .. is the interaction of the two, which gives the number of years since installation during the post period The coefficient on