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How Well Do Professional Reference Ratings Predict Teacher Performance? Working Paper No. 272-1022

Authors :
National Center for Analysis of Longitudinal Data in Education Research (CALDER) at American Institutes for Research
Goldhaber, Dan
Grout, Cyrus
Wolff, Malcolm
Source :
National Center for Analysis of Longitudinal Data in Education Research (CALDER). 2022.
Publication Year :
2022

Abstract

Most research about how to improve the teacher workforce has focused on interventions designed to improve incumbent teachers, far less attention has been directed toward teacher hiring processes and whether districts can make better hiring decisions. Using data from Spokane Public Schools and Washington state, we describe the findings from a study analyzing measures of the predictive validity of teacher applicant quality measures obtained from professional references. We find that professional reference ratings of prospective teachers are significantly predictive of teacher quality as measured by inservice performance evaluations and teacher value added in math. These findings are driven by applicants with at least some teaching experience and vary by rater type (e.g., principal or university supervisor); the magnitude of the relationship between the ratings of applicants and teacher performance is much smaller and not statistically significant for applicants that do not have teaching experience. Overall, the evidence suggests that obtaining explicit ratings of teacher applicants from professional references is a low-cost way to contribute to the applicant information available to hiring officials and has potential for improving hiring outcomes.

Details

Language :
English
Database :
ERIC
Journal :
National Center for Analysis of Longitudinal Data in Education Research (CALDER)
Publication Type :
Report
Accession number :
ED625526
Document Type :
Reports - Research