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IES Grant

Title: Examining Recruitment Policies and Pathways to Diversify the Teacher Workforce
Center: NCER Year: 2021
Principal Investigator: Blazar, David Awardee: University of Maryland, College Park
Program: Improving Education Systems      [Program Details]
Award Period: 3 years (09/01/2021 – 08/31/2024) Award Amount: $577,253
Type: Exploration Award Number: R305A210031

Co-Principal Investigators: Gershenson,Seth; Goings, Ramon

Purpose: Research identifies large benefits of access to same-race/ethnicity teachers for Black and Hispanic students. However, the teacher workforce is overwhelmingly White, and little is known about the system-level strategies that are successful at diversifying the profession. In this Exploration project, researchers will explore 3 "grow-your-own" programs and pathways that school districts and higher education institutions have implemented at different stages of the school-to-career pipeline in the hopes of recruiting Black and Hispanic individuals into the profession: (i) early exposure to teaching for high school students and an opportunity to enroll in dual enrollment credits toward a teaching credential; (ii) financial scholarships to attract college students to pursue a teaching major; and (iii) alternative-route teacher certification programs that aim to recruit career changers already working in or in close proximity to schools. The research team will  quantitatively link access to or participation in these programs to desired education and workforce outcomes, namely the probability that an individual of color earns a teaching credential or becomes a teacher of record. Researchers also will examine associated increases in the test scores of K-12 students in implementing districts.

Project Activities: Researchers will use statewide, longitudinal data from Maryland from 2007 to 2023 to examine how participation in or access to each of the three recruitment programs and pathways are related to education and workforce outcomes. Analyses will use multivariate regression, bounding techniques, difference-in-differences designs, and synthetic control methods.

Products: The research team will produce at least four scholarly articles, six academic research conference presentations, three policy presentations, and two workshops/presentations to key practice-based audiences.

Structured Abstract

Setting: Researchers will use longitudinal data from the state of Maryland, hosted at the Maryland Longitudinal Data System (MLDS) Center. The MLDS Center is a state agency that both serves as a repository of cross-agency data and is tasked with conducting policy-relevant research, including work on the school-to-career transition. Broadly, the data link K-12 education records on all students in Maryland public schools (provided by the Maryland State Department of Education) to postsecondary outcomes nationwide (provided by the Maryland Higher Education Commission and the National Student Clearinghouse) and to workforce outcomes for those who remain in state (provided by the Maryland Department of Labor). The data system was set up to capture records starting in the 2007-08 school year, which is when the State Department of Education systematized data collection across all 24 school districts. New data are loaded yearly, and by the start of this project (September 2021), the research team will have data through the 2020 school year, with access to data through 2022-23 coming available during the course of the project.

Sample: The population of interest includes high school students, college students, and school-based/non-teaching staff who were eligible to participate in one or more of the three recruitment programs or pathways, over a time period of roughly 15 years. Within this population, researchers will identify a sample of over 1,500 Black and 600 Hispanic high school students across the state who participated in the high school dual-enrollment program and who the team can link to longer-term college and workforce outcomes; roughly 750 Black and 300 Hispanic college students across over a dozen higher education institutions who have received scholarships that incentivize them to major in teaching; and roughly 130 Black and 65 Hispanic individuals from two large urban school districts who have participated in career-changer programs. Researchers will compare these individuals to other similar individuals in the state who did not participate or have access to the programs and pathways under study.

Factors: The malleable, system-level factors include three recruitment programs and pathways aimed at diversifying the teacher workforce: (i) the Teacher Academy of Maryland program that provides opportunities for high school students to earn dual-enrollment credits towards a teaching credential; (ii) three scholarship programs that incentivize college students to major in teaching; and (iii) two alternative-route certification programs for career changers.

Research Design and Methods: This is an exploratory study that relies on secondary data analysis to link participation in or access to each of the three recruitment programs or pathways to education and workforce outcomes for prospective Black and Hispanic teachers. First, researchers will clean and code the statewide data to identify those individuals who participated in or had access to each of the three programs.  Second, researchers will link these data to longer-term education and workforce outcomes. Third, researchers will conduct statistical analysis to determine if there are any differences in the share of Black or Hispanic individuals who earn a teaching credential or become a full-time teacher based on participation in or access to each of the three recruitment programs or pathways.

Control Condition: Researchers will compare program participants to other similar individuals who were eligible for a given program but chose not to participate or did not have access to the program due to timing or location.

Key Measures: Key independent variables capture participation in or access to one of the three recruitment programs or pathways. Participation data comes from the raw statewide data and from rosters provided by program leaders. Program access variables are identified based on the staggered rollout of programs across time and setting (i.e., school district, college campuses). This project links these independent variables to four outcome measures: (i) a dichotomous measure for earning a teaching credential, which comes from the Maryland Higher Education Commission and the National Student Clearinghouse; (ii) a dichotomous measure for becoming a teacher of record in Maryland, which comes from the Maryland State Department of Education; (iii) yearly wages, which come from Unemployment Insurance (UI) records provided by the Maryland Department of Labor; and (iv) test scores of the K–12 students in school districts that implement the recruitment programs and pathways.

Data Analytic Strategy: The research team will use multivariate regression analysis to examine whether participation in a given program or pathway is associated with an increased probability of earning a teaching credential or becoming a teacher of record. To account for non-random selection and participation in these programs, the team will: (i) conduct bounding exercises, (ii) leverage the staggered rollout of some of the programs in a difference-in-differences framework, and (iii) apply a synthetic controls method.