Co-Principal Investigator: Holden, Kristian; Theobald, Roddy

Purpose: The purpose of the proposed research is to provide a first look at career and technical education (CTE) teacher effectiveness for students with disabilities (SWD). We measure effectiveness based on estimates of teacher effects on various non-test and long-run student outcomes (e.g.postsecondary enrollment, employment), and we also assess whether effectiveness varies according to teachers' licensure, pathway into teaching (e.g. traditional vs alternative), and prior work experiences. This is important because a large body of research over the last decade shows that teachers are consistently the most important schooling attribute influencing student outcomes, and recent research (Feng and Sass, 2013; Theobald et al., 2018b) suggests that some teacher characteristics are differentially associated with improved outcomes for SWD, but crucially no research exists that investigates the relationship between any of these measures of licensure and training of CTE teachers and later outcomes for students with disabilities.

Project Activities: Researchers will conduct secondary data analysis with administrative data provided by the Washington State Education Research and Data Center (ERDC), and collect primary data from CTE teacher preparation programs in Washington State.

Products: The primary product of this project will be a set of data and published reports addressing CTE teacher effectiveness, as measured by non-test outcomes and long-term student outcomes, and (b) whether teacher effectiveness varies according to licensure, pathways (e.g. traditional vs alternative), and prior work experiences. The project will also result in peer-reviewed publications and presentations, and additional dissemination products that reach education stakeholders such as practitioners and policymakers.

Structured Abstract

Setting: The Washington State ERDC data includes data on students and teachers from public high schools in Washington State, including teacher candidates and their student teaching experiences. This data is also linked to postsecondary outcomes for students from 2-year colleges, 4-year colleges, and workplaces in Washington State. Teachers in Washington State teacher preparation programs will participate in a survey of their practices for preparing CTE teachers to instruct SWD.

Population: The primary sample consists of approximately 7,000 Washington State CTE teachers who serve students with disabilities in high school from 2010-11 through 2017–18, who serve approximately 40,000 students with disabilities.

Research Design and Methods: The researchers will use administrative data from ERDC to explore correlations between characteristics of CTE teachers and outcomes of their students with disabilities. They will also implement a survey of CTE teacher education programs in Washington to assess the extent to which prospective CTE teachers are prepared to serve students with disabilities in their future classrooms.

Malleable Factors: The malleable factors under investigation include three measures of CTE teacher qualifications and training: 1) having a CTE license, 2) CTE pathway (e.g. traditional or alternative "Business and Industry" route) for those with a license, and 3) work experiences prior to program entry.

Key measures: The research team will estimate several measures of CTE teacher effectiveness using high school outcomes: attendance, GPA, high school persistence, graduation probability. They will also consider longer-term outcomes, including college enrollment and employment probabilities. The team will focus on three measures of CTE teacher qualifications and training: 1) having a CTE license, 2) CTE pathway (e.g. traditional or alternative "Business and Industry" route) for those with a license, and 3) work experiences prior to program entry.

Data Analytic Strategy: The research team will estimate linear regression models and logit models that estimate a CTE teacher's contribution to student CTE learning in high school, and longer-term outcomes directly. Data include several control variables for students, such as prior student performance on standardized tests, student demographics, peer characteristics, and course taking patterns. The team will account for non-random selection of students across courses by considering within-CTE area performance.