Enhancing student acceptance of artificial intelligence-driven hybrid learning in business education: Interaction between self-efficacy, playfulness, emotional engagement, and university support

This study examines the factors influencing student acceptance of Artificial Intelligence (AI)-driven hybrid learning within higher education, specifically focusing on business education. By expanding the traditional Technology Acceptance Model (TAM) and incorporating Self-Determination Theory (SDT), this research explores the interplay between perceived playfulness, learning goal orientation, self-efficacy, and university support. The PLS-SEM and semi-structured interviews were applied to data analysis from 279 Chinese university students majoring in international business. The findings reveal that self-efficacy, emotional engagement, and university support significantly enhance students' acceptance of AI-driven hybrid learning. University support, in particular, serves as a critical moderator, amplifying the effects of self-efficacy and acceptance attitudes. The study contributes to the evolving discourse on AI integration in management education, offering insights into optimizing AI-driven hybrid learning experiences and strategies in higher education settings. These findings have implications for curriculum design, institutional support mechanisms, and pedagogical approaches in business and management education, particularly in the context of advancing technological integration and meeting employers' evolving needs.