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Analysis of AI Models for Student Admissions: A Case Study

Published: 07 June 2023 Publication History

Abstract

This research uses machine learning-based AI models to predict admissions decisions at a large urban research university. Admissions data spanning five years was used to create an AI model to determine whether a given student would be directly admitted into the School of Science under various scenarios. During this time, submission of standardized test scores as part of a student's application became optional which led to interesting questions about the impact of standardized test scores on admission decisions. We first developed AI models and analyzed these models to understand which variables are important in admissions decisions, and how the decision to exclude test scores affects the demographics of the students who are admitted. We then evaluated the predictive models to detect and analyze biases these models may carry with respect to three variables chosen to represent sensitive populations: gender, race, and whether a student was the first in his family to attend college.

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  • (2025)The Utilization of Artificial Intelligence in Higher Education Institutions in GermanyAI Adoption and Diffusion in Education10.4018/979-8-3693-7949-3.ch012(321-358)Online publication date: 3-Jan-2025
  • (2024)Fair and Transparent Student Admission Prediction Using Machine Learning ModelsAlgorithms10.3390/a1712057217:12(572)Online publication date: 13-Dec-2024
  • (2024)Bias analysis of AI models for undergraduate student admissionsNeural Computing and Applications10.1007/s00521-024-10762-6Online publication date: 5-Dec-2024

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  1. Analysis of AI Models for Student Admissions: A Case Study

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    cover image ACM Conferences
    SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing
    March 2023
    1932 pages
    ISBN:9781450395175
    DOI:10.1145/3555776
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 07 June 2023

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    Author Tags

    1. machine learning
    2. bias
    3. predictive model
    4. test-optional
    5. college admissions

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    View all
    • (2025)The Utilization of Artificial Intelligence in Higher Education Institutions in GermanyAI Adoption and Diffusion in Education10.4018/979-8-3693-7949-3.ch012(321-358)Online publication date: 3-Jan-2025
    • (2024)Fair and Transparent Student Admission Prediction Using Machine Learning ModelsAlgorithms10.3390/a1712057217:12(572)Online publication date: 13-Dec-2024
    • (2024)Bias analysis of AI models for undergraduate student admissionsNeural Computing and Applications10.1007/s00521-024-10762-6Online publication date: 5-Dec-2024

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