Empowering Academic Performance through Generative AI: The Role of Collaborative E-Learning and Effort Expectancy

¹ College of Economics and Management, Beijing University of Technology, Beijing 100124, PR China
² UE Business School, University of Education, Lahore, Pakistan

^* Corresponding author: xushuo@bjut.edu.cn

Abstract

Generative artificial intelligence (GenAI) has become a revolutionary tool in the quickly changing field of education, providing new avenues for improving educational outcomes. This study investigates the impact of generative artificial intelligence (GenAI) adoption on university students’ academic performance, with a focus on collaborative e-learning and effort expectancy. Based on theoretical underpinnings of SCT, a conceptual framework was created. PLS-SEM is utilized to test the conceptual framework empirically. Data was collected through the technique of a structured survey, and the sample size was 260. The target population for this study is students of Chinese higher educational institutions. The empirical findings reveal that GenAI significantly enhances academic performance with the positive mediation of collaborative e-learning. Moreover, effort expectancy demonstrates a positive moderation on the link between GenAI adoption and collaborative e-learning. This research focuses on the importance of lowering technological challenges in order to facilitate the wider acceptance and smooth utilization of GenAI technologies in higher educational settings.