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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 |
Files in This Item:
File | Description | Size | Format | |
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ALQUDAH-MOHAMMAD-THESIS.pdf | 939.17 kB | Adobe PDF | Request a copy |
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