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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp016108vf53w
Title: The Impact of Instructor Gender on Princeton University Course Evaluations
Authors: Alqudah, Mohammad
Advisors: Fellbaum, Christiane
Department: Computer Science
Certificate Program: Linguistics Program
Class Year: 2023
Abstract: This project seeks to determine whether gender bias exists in academia, and if there truly exists a quantifiable difference in perception of male and female instructors by their students based on Princeton University course evaluations. In particular, the project will analyze the impact of instructor gender on Princeton University course evaluations. VADER sentiment analysis is applied to the selected course evaluations, which includes varying courses from 2017 - 2022 that fit specified criteria. This generates average negativity and positivity scores for each iteration of a course that was taught by a different gendered instructor. The generated sentiment scores are then analyzed in conjunction with a manual review of the evaluations, and compared between when the course was taught by a male instructor and female instructor. An analysis of the most common adjectives used to describe both genders is also conducted. The analysis concludes that there does exist gender bias in Princeton University course evaluations, confirming that students perceive their different gendered instructors differently.
URI: http://arks.princeton.edu/ark:/88435/dsp016108vf53w
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Computer Science, 1987-2024

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