Date
Publisher
arXiv
The rapid development of GenAI technologies is transforming learning, assessment, and academic production in higher education. Despite increasing student adoption, many institutions lack operational mechanisms to systematically align regulations and curricula with evolving generative artificial intelligence practices, creating regulatory ambiguity and academic integrity risks. This study investigates how students utilize generative artificial intelligence tools in computer science-oriented disciplines and develops a structured, lightweight framework supporting institutional adaptation to pervasive GenAI usage. We conducted a case study at the University of Applied Sciences and Arts Hannover (Germany), combining document analysis with an online survey (N = 151) targeting Business Information Systems and E-Government students. Quantitative responses were analyzed statistically, while open-ended responses underwent thematic synthesis. Generative artificial intelligence adoption was widespread, with ChatGPT as the dominant tool. Students primarily used generative artificial intelligence for research assistance, programming support, and text processing. However, substantial policy uncertainty was observed: many students were unaware of or unsure about institutional generative artificial intelligence regulations. Document analysis revealed regulatory gaps, ambiguous terminology, and inconsistencies between formal rules and teaching practices. To address these shortcomings, we propose the AI Adoption Framework for Higher Education, an iterative and operational model integrating document analysis, empirical observation, synthesis of findings, and targeted updates of regulations and curricula. The framework addresses governance, assessment validity, and academic integrity under generative artificial intelligence conditions and provides practical guidance for institutional adaptation.
Study at a glance
- Question: How do students use generative AI tools, and how can institutions systematically adapt their regulations and curricula?
- Setting and data: University of Applied Sciences and Arts Hannover, Germany, winter term 2024–2025, survey of 151 business information systems and e-government students plus university documents.
- Method: Case study combining institutional document analysis and a mixed-methods online survey.
Why it matters
Although students increasingly adopt generative AI, universities often lack mechanisms to align regulations and curricula with student practices, creating regulatory ambiguity and academic integrity risks.
Key findings
- Generative AI adoption was high, with 85.43% of surveyed students actively using tools and 93.8% of users reporting regular use of ChatGPT.
- Students primarily used generative AI for research assistance (40.15%), programming support (37.8%), and text summarization (34.65%).
- Substantial policy uncertainty persisted across semesters: 43.7% of students were unsure if their AI usage complied with academic policies, and 19.1% suspected potential violations.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
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