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Investigating the Equity of Using Advanced Placement Assessment Data for Teacher Evaluations

  • Randal Oddi

Student thesis: Doctoral ThesisDoctor of Philosophy

Abstract

This applied dissertation was designed to investigate a belief shared by teachers whether using Advanced Placement data for teacher evaluations was equitable. Teachers are assigned to teach different groups of students and are compared to teachers at other schools for their evaluation rating. Not all schools have the same practices with placing students into these courses. Close and Amrein-Beardsley (2018) make evident that the disparities of how students are assigned to teachers contributes to the concerns teachers have about the fairness of using student assessment data as a basis for performance evaluation. There has been little study into the effect of using Advanced Placement test scores as a factor of a teacher’s evaluation. The study proposed to assess the equity of using Advanced Placement data to evaluate a teacher’s performance and aimed to add to the existing body of research by analyzing whether there was a correlation between teachers receiving high evaluation ratings and whether the school had a practice of allowing access to all students to Advanced Placement coursework. A public records request provided enrollment data for Advanced Placement courses and aggregate evaluation scores for the teachers at each school. The request also obtained the requirements for each school to allow students to participate, which then allowed each school to be classified based on whether they limit students or allow access to all students. The investigation indicated that teachers assigned to schools that restrict access to Advanced Placement coursework were more likely to earn a higher evaluation rating. Teachers assigned to schools that allow access to all students to Advanced Placement coursework score lower on their evaluations when compared to the other subgroup of teachers.
Date of AwardJan 1 2024
Original languageEnglish
SupervisorJo Campbell (Supervisor), Matthew Delaney (Advisor) & Kimberly Durham (Advisor)

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