All Active and Closed Projects

A comprehensive study of the teacher education pipeline that will connect detailed information about pre-service teacher education experiences—such as transcript and student teaching data—to various teacher outcomes. The heart of our proposal is the development of a “Teacher Education Learning Collaborative” (TELC) that includes every teacher education program (TEP) in Washington State. We will work with institutions in the TELC to build a detailed dataset that will contain information on the pre-service and student teaching experiences of every prospective teacher in Washington State.

The first statewide study of the teacher education pipeline that connects the experiences of preservice teachers – such as transcript and student teaching data – to the employment outcomes of inservice teachers. This project is part of a broader initiative to gain a better understanding of the preservice experiences that influence whether prospective teachers enter the teaching workforce and, if they do, how effective they are and how long they stay in the teacher labor market.

This mixed-methods Track 4 Noyce Research proposal is a collaboration between the Center for Analysis of Longitudinal Data in Education Research at the American Institutes for Research, the Education Research and Data Center (ERDC) at the Washington State Office of Financial Management, and several Washington State institutions of higher education (IHEs): Central Washington University, Pacific Lutheran University, University of Washington, Washington State University, and Western Washington University. The proposal addresses connections between the attributes of potential teacher candidates; their admittance and enrollment in science, technology, engineering, and math (STEM) teacher education programs; and their later retention and effectiveness as STEM teachers. This project is made possible by statewide data on students and teachers in Washington—that include data on all high-need educational agencies in the state—along with data already collected on teacher candidates from teacher education programs (TEPs) in IHEs in the state of Washington and data provided as part of this project by the five collaborating IHEs that include admissions data on all applicants to these universities and/or their TEPs. The data will also be combined with transcript data provided by ERDC and qualitative data collected from College of Education STEM (COE STEM) faculty and Arts and Sciences affiliated STEM (A&S STEM) faculty at collaborating IHEs.

A comprehensive analysis of the relationships between the characteristics of cooperating teachers and teacher and student outcomes. These relationships are quite malleable; as noted previously, some states have specific requirements for the characteristics of cooperating teachers, and all have the regulatory authority to specify such requirements (Education Week, 2010). Moreover, TEPs and school systems specify requirements in memorandums of understanding that outline, among other things, the role of cooperating teachers when teacher candidates student teach in particular districts. Thus, TEPs and states can design policies to influence the selection of inservice teachers to serve as cooperating teachers—and the future outcomes of teacher candidates and their students.

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This project is the first statewide analysis of the STEM teacher pipeline in Washington State that will leverage a unique longitudinal dataset. This dataset is unique in that it will connect detailed information about preservice teacher education experiences—such as transcript and student teaching data—to outcomes for all individuals trained to be teachers within specific teacher education programs (TEPs) in Washington State.

The first comprehensive analysis of the special education teacher pipeline that will leverage a unique longitudinal data set from Washington State that combines data about preservice teacher candidate experiences with information about K–12 teacher and student outcomes. This data set has been assembled as part of the Teacher Education Learning Collaborative (TELC), a partnership with teacher education programs (TEPs) in Washington designed to explore the effects of teacher education experiences on inservice teacher and student outcomes. The TELC data set is unique because it includes comprehensive transcript and student teaching data (such as where teacher candidates did their student teaching and which inservice teachers supervised it) for teacher candidates who receive their teacher education in specific TEPs and allows us to track these teacher candidates into the state’s K–12 public school workforce. We combine the TELC data with novel survey data (collected as part of this project) of special education faculty from participating TEPs and special education directors from school districts.