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February 5, 20260 citations

Understanding the drivers of artificial intelligence (AI) use among students at University

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MRMohamad Arief RafsanjaniPKPutri Ulfa KamaliaState University of SemarangMGMuhammad Abdul Ghofur

Key Points

  • This research aims to identify factors influencing student engagement with artificial intelligence tools in higher education.
  • Qualitative case study approach
  • Semi-structured interviews with 13 undergraduate students
  • Thematic analysis of interview data
  • Academic utility identified as the primary driver for using AI tools for writing and research.
  • Emotional factors revealed AI's role in reducing anxiety and boosting confidence under time pressure.
  • Peer influence significantly spreads AI usage through informal networks among students.
  • Ethical concerns about academic integrity and lack of clear guidelines were noted.

Abstract

This study explores the factors influencing student engagement with artificial intelligence (AI) tools in higher education, focusing on the Faculty of Economics and Business at Universitas Negeri Surabaya. Using a qualitative case study approach, semi-structured interviews were conducted with 13 undergraduate students who were experienced in using AI tools such as ChatGPT and Grammarly. Thematic analysis revealed four key themes. First, academic utility emerged as the primary driver, with students using AI to support writing, research, and data analysis. Second, emotional and motivational factors showed that AI helps reduce anxiety and boost confidence, especially under time pressure. Third, peer influence played a significant role in spreading AI usage through informal networks, often filling gaps left by formal instruction. Lastly, ethical and institutional considerations highlighted uncertainties about academic integrity and the absence of clear university guidelines. These findings suggest that beyond functionality, emotional, social, and ethical dimensions shape AI adoption. To promote responsible and effective AI use, universities should offer clear policies, ethics-based training, and supportive learning environments that address both technical and moral aspects of AI integration.

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Cite This Study

Rafsanjani et al. (2025) studied this question.

synapsesocial.com/papers/698433d8f1d9ada3c1fb154dhttps://doi.org/10.1051/e3sconf/202564002016/pdf
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