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Understanding the Adoption of ChatGPT in Higher Education: A Comparative Study with Insights from STEM and Business Students

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Kubullek, Ann-Kathrin
Kumaç, Nadire
Dogangün, Aysegül

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Association for Computing Machinery

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Since ChatGPT’s introduction, generative artificial intelligence (AI) has significantly influenced the media, technological innovation, and educational discourse. Its increasing importance, especially in academia, necessitates a detailed examination of the impact of AI on higher education, particularly on how it changes teaching and learning processes. This study therefore looks at the factors affecting students’ attitudes towards AI technologies in the university setting, with a particular focus on the differences between business and STEM programmes. Using a mixed methods approach, the study combines surveys and interviews to collect data on students’ perceptions, attitudes and experiences with generative AI technology in academia. The data collected is analysed both quantitatively and qualitatively to reveal significant trends and insights into the adoption and use of generative AI tools in the university environment. The main objective of the study is to shed light on the determinants that determine the varying degrees of AI adoption in different academic disciplines. The findings have the potential to inform the implementation of educational technology and assist in the development of strategies for the effective integration of generative AI tools to meet the different needs and preferences of students in a range of academic contexts.

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Kubullek, Ann-Kathrin; Kumaç, Nadire; Dogangün, Aysegül (2024): Understanding the Adoption of ChatGPT in Higher Education: A Comparative Study with Insights from STEM and Business Students. Proceedings of Mensch und Computer 2024. DOI: 10.1145/3670653.3677507. Association for Computing Machinery. pp. 684–689. Karlsruhe, Germany

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ChatGPT, STEM degree programs, academic disciplines, acceptance of AI, business degree programs, generative AI adoption, higher education, students

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Number of citations to item: 5

  • Sam Elliott, Madison Richter, Chidozie Alozie, Damien Raidis (2026): Student Perceptions of Personalised GenAI Agents on Student Learning, Success, Engagement, and Wellbeing: A Pilot Study of Cogniti AI, In: Technology, Knowledge and Learning, doi:10.1007/s10758-025-09942-7
  • Amelia Patricia, Bryan Limios, Jonathan Tanadi, Natalia Limantara (2025): From Curiosity to Practice: Exploring Generative AI Adoption in Non-STEM Higher Education, In: 2025 1st International Conference on Emerging Trends in Information Systems and Informatics (ICETISI), doi:10.1109/icetisi67983.2025.11406061
  • Joaquin Veith, Antonia Bauer, Eleonore Becker, Philipp Bitzenbauer (2026): Exploring physics students’ attitudes toward ChatGPT using the ABC model, In: Eurasia Journal of Mathematics, Science and Technology Education 2(22), doi:10.29333/ejmste/17822
  • Tanvir Ahmed, Khaled Hossain Rocky, Shadiah Rahman, Md. Jahid Hasan (2026): Ethical use of ChatGPT in higher education: insights from business students on responsible AI adoption, In: Ethics & Behavior, doi:10.1080/10508422.2026.2615333
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