Determinants of artificial intelligence acceptance among undergraduates - Kowang, Tan Owee; Kim Yew, Lim; Chin Fei, Goh; Choon Hee, Ong (International Journal of Evaluation and Research in Education (IJERE), 2025)
Despite the potential benefits of artificial intelligence (AI) brings to education, its extensive use does not automatically guarantee effective integration or consistent improvements in learning. Hence, this research aims to identify the determinants of AI acceptance among undergraduates and examine the relationship between these determinants and AI acceptance. Five determinants of AI acceptance were identified based on the technology acceptance model (TAM) and empirical evidence: perceived effectiveness of AI, user satisfaction, user attitude toward AI technology, attitude toward using AI, and user self-efficacy. This quantitative study focused on 791 undergraduates from a management school in Malaysia. A questionnaire was distributed to 310 undergraduates using a stratified sampling method, and 259 responses were collected. Descriptive analysis results indicated that undergraduates perceive attitudes toward AI technology and using AI as very important determinants of AI acceptance. Pearson correlation analysis also revealed that four determinants (perceived effectiveness of AI, satisfaction in using AI, attitude towards AI technology, attitude towards using AI) significantly correlated with AI acceptance. This finding suggests that, within the context of AI acceptance among management school undergraduates, attitude-related determinants are the primary drivers. The findings from this research could be used by the management school as a reference to enhance undergraduates’ AI acceptance levels and identify areas for inclusive education system improvement.