Student utilization and perceptions of AI technology for academic purposes: a mixed-method analysis

Abstract

Artificial Intelligence (AI) is increasingly used in higher education, yet limited research explores how students in developing countries respond to these technologies. This study investigates the behavioral intentions of university students in Indonesia toward AI-based academic tools using a mixed-methods approach. A quantitative survey was conducted with 388 students across public and private universities, followed by in-depth interviews with 10 selected participants. The Unified Theory of Acceptance and Use of Technology (UTAUT) was used to analyze cognitive factors, while qualitative data explored emotional trust, ethical concerns and institutional support. Findings indicate:Performance expectancy and effort expectancy significantly influence students’ attitudes toward AI.Attitude strongly predicts behavioral intention, which in turn leads to actual adoption.Perceived risk, such as concerns about accuracy and plagiarism, was acknowledged but did not significantly impact attitude.Students adopt AI tools strategically, often validating outputs through textbooks or peer input.Institutional support and faculty guidance influence adoption, but formal policies are often unclear. The results suggest that while students recognize the limitations of AI, they prioritize its practical benefits. This study contributes to a more complete understanding of AI use in academic settings and offers actionable recommendations for educators and decision-makers in similar educational systems.

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