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Student (Mis)Use of Generative AI Tools for University-Related Tasks
Journal article   Open access   Peer reviewed

Student (Mis)Use of Generative AI Tools for University-Related Tasks

Leonhard Reiter, Moritz Joerling, Christoph Fuchs and Robert Boehm
International Journal of Human-Computer Interaction, Vol.41(19), pp.12390-12403
‘Artificial Intelligence in Higher Education’
02/10/2025

Abstract

Artificial intelligence AI education technology acceptance TAM cheating AI use AI misuse
Although Artificial Intelligence (AI) holds immense potential to enhance the educational experience, its use also presents challenges. This research examines the use and misuse of AI tools for university-related tasks. We surveyed 498 students from three faculties at a large European university to, first, identify factors driving their willingness to use AI tools for university-related tasks, and, second, estimate the prevalence of cheating behavior involving the unauthorized use of AI tools in examinations. Specifically, we tested and extended the Technology Acceptance Model 2 (TAM2) by identifying trust and perceived opportunity costs as additional determinants of using AI tools for university-related tasks. To estimate the proportion of students cheating during examinations, we applied a randomized response technique. We discuss the results with respect to the effective and appropriate implementation of AI tools in higher education. Our findings can help educators and policymakers to promote responsible AI use while mitigating its misuse.
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CC BY-NC-ND V4.0 Open Access
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https://doi.org/10.1080/10447318.2025.2462083View
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Citation topics
9 Mathematics
9.92 Statistical Methods
9.92.332 Sampling Techniques
Web of Science research areas
Computer Science, Cybernetics
Ergonomics
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