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The Diversity of Students as a Challenge of AI Adoption in Boosting Efficiency of Study Programmes

Authors:
Larissa Bartok
René Krempkow

Keywords: Academic analytics; study success; machine learning; diversity indicators

Abstract:
Artificial Intelligence (AI) is gaining ground in everyday life and administrative data analysis at universities. Therefore, applying machine learning and other methods in modeling academic success at universities, for example, is becoming increasingly important. Our case study from a large Austrian university demonstrates how questions related to academic success, with a focus on diversity indicators, can be investigated at universities using various methods, including AI and administrative data of N = 2532 students from Science, Technology, Engineering, and Mathematics disciplines (STEM). This article discusses implications for the impact of applying such models on institutional decision-making at universities regarding academic success. Although it is yet difficult to grasp efficiency within the context of student success, the potential impact of the influence of applying such models, together with possible unwanted effects, is discussed.

Pages: 7 to 12

Copyright: Copyright (c) IARIA, 2025

Publication date: July 6, 2025

Published in: conference

ISBN: 978-1-68558-285-2

Location: Venice, Italy

Dates: from July 6, 2025 to July 10, 2025