Skip Navigation
Funding Opportunities | Search Funded Research Grants and Contracts

IES Grant

Title: Shaping Teacher Quality and Student of Color Experience in Massachusetts: Alignment of Preparation and Licensure Systems with Teacher Effects on Student non-Test Outcomes
Center: NCER Year: 2021
Principal Investigator: Abbott, Claire J. Awardee: Massachusetts Department of Elementary and Secondary Education
Program: Using Longitudinal Data to Support State Education Policymaking      [Program Details]
Award Period: 3 years (07/01/2021 - 06/30/2024) Award Amount: $994,588
Type: Exploration and Measurement Award Number: R305S210012
Description:

Co-Principal Investigator: Goldhaber, Dan

Purpose: The purpose of this project is to examine the extent to which Massachusetts' preparation and licensing systems prepare teachers to be effective in improving outcomes for students of color.

Project Activities: The project team will carry out three activities:

  • Generate measures of teacher effectiveness on test and non-test outcomes for students of color and explore the ways in which these vary across teachers,
  • Examine the extent to which teachers from different licensure or preparation pathways are differentially effective at improving the outcomes of students of color, and
  • Examine newly licensed teachers' experiences around racial equity in their teacher training programs and how these training experiences translated to their first years in the workforce.

Products: The project will produce measures of effectiveness of teachers serving students of color and preliminary evidence of potentially promising practices for preparing/supporting teachers to be effective in improving outcomes for students of color. This project will also produce peer reviewed publications, policy briefings with senior staff across the entire secretariat of education, webinars with other educators and researchers, publication in practitioner-oriented journals, research summaries and policy briefs posted on the DESE webpage and distributed via the Office of Planning and Research listserv.

Structured Abstract

Setting: The project takes place in the state of Massachusetts.

Sample: The sample used to consider student standardized test outcomes includes public school students linked to their mathematics and ELA classroom teachers in Grades 4–8 and 10. The sample used to consider non-testing outcomes includes students in Grades 4–12 who are matched to teachers in the core academic subjects (ELA, mathematics, science, and social studies). Student-teacher linked data is available for 2012-2019. For the qualitative study, licensed teachers who completed their program of study within two years will be randomly selected (stratified by race and license) from 15 programs and invited to take part in focus groups.

Key Issue, Program, or Policy:  The Massachusetts Department of Elementary and Secondary Education (DESE) oversees the state's teacher preparation and licensing systems using four primary policy levers to influence the composition of the state's public teaching workforce:

  • The review and accreditation of the state's educator preparation providers (EPPs account for about two-thirds of new teachers),
  • The establishment of licensure pathways for incoming and continuing teachers (MA has several types of teaching licenses with multiple pathways to attain each one),
  • The development of licensure and program completion requirements (including assessments) for these pathways, and
  • State guidance regarding the above regulations provided to districts and EPPs.

Research Design and Methods: The project team will first estimate teacher effectiveness using value added models (VAMs) based on student standardized math test scores, student standardized ELA test scores, and a student behavioral composite (composed of absences, disciplinary infractions, grades, and grade progression), and also using annual teacher performance ratings. Next, the team will examine how well these different measures of teacher effectiveness predict student outcomes and whether they differentially predict outcomes for students of color. The project team will then examine how preparation and licensure predict non-test student outcomes using similar models containing measures of teacher preparation (degree, content specialization, state commendation, student teacher placement, teacher candidate survey) and licensure (licensure tests, license type, first license, moderate disabilities, and English Learners licenses). As part of this work, they will check for differences across preparation and licensure measures for outcomes of students of color. The team will also hold semi-structured focus groups of newly licensed teachers (stratified by race and license) drawn from 15 programs (10 that explicitly focus on equity and 5 that do not) to explore the practices used by preparation programs to prepare teacher candidates to work with racially diverse students.

Control Condition: Due to the nature of the project, there is no control condition.

Key Measures: The research team will measure student outcomes using standardized test scores in math and ELA, a non-test composite outcome (combining absences, disciplinary infractions, grades, and grade progression), credits earned through Advanced Placement courses, high school graduation, college enrollment, college quality, and adult voting behavior. Teacher effectiveness will be measured using the short-term student outcomes (test scores and composite) as well as teacher evaluations. Teacher preparation program characteristics include degree, content specialization, state commendation of the program for a focus on equity, student teacher placement including placement in a diverse class, and results from a teacher candidate survey. Licensure characteristics include results from licensure tests, license type, first license, and specialized licenses such as those for students with moderate disabilities and English Learners.

Data Analytic Strategy: The project team will use value added modeling to develop measures of teacher effectiveness on test and non-test outcomes. The team will estimate regression models to identify teacher effectiveness, preparation, and licensure links with student outcomes and how these links may differ for students of color. The project team will use a semi-structured approach for the focus groups and identify themes using content analysis.

State Decision Making: The findings will be useful as Massachusetts considers revising:

  • Measures and evidence used to review and accredit the state's educator preparation providers
  • Licensure pathways
  • Licensure test requirements and licensure tests assessing new educators' knowledge and skills
  • Updates to state guidance to districts and EPPs including guidance for educator evaluation, student assignment, and teacher induction and mentoring

Related IES Projects: The Teacher Pipeline in Massachusetts: Connecting Pre-service Performance Measures to In-service Teacher Outcomes (R305H170025)


Back