Do Students Embrace AI-Powered Academic Integrity? Examining Students’ Technology Acceptance of Security-Enhanced Online Exams

Abstract

This study examines students’ technology acceptance of artificial intelligence (AI)-powered online exams that use AI techniques to detect cheating and ensure academic integrity. Grounded in the Technology Acceptance Model (TAM), this explanatory sequential mixed-methods research (QUAN→qual) investigates the factors that influence student adoption of such systems. An AI-powered online examination system was developed and implemented for eight courses, with 90 students participating in an online survey to assess their acceptance using a five-factor TAM scale (Perceived Usefulness, Perceived Ease of Use, Attitude Toward Use, Facilitating Conditions, and Computer Anxiety). Additionally, 20 students were interviewed. The findings reveal that while some students appreciate the AI-powered online exam for ensuring fairness and merit-based grading, others are skeptical due to concerns about cheating. Statistical analysis shows significant positive correlations among four TAM factors (Perceived Usefulness, Perceived Ease of Use, Attitude Toward Use, and Facilitating Conditions). Furthermore, the qualitative results identify 14 key factors that influence student acceptance of AI-powered secure online exams. Unlike prior studies on general e-learning or conventional proctoring tools, this study applies a five-factor TAM framework to a purpose-built AI-powered secure examination system, combining survey and interview data. This research provides valuable insights for educators and policymakers seeking to understand how AI-powered security features impact student acceptance of online exams.