Understanding knowledge management engagement, learning motivation and effectiveness in the age of generative artificial intelligence

Purpose How does generative artificial intelligence (GenAI) affect teaching-learning activities in higher education? It is unclear to what extent Gen AI provides adequate resources and tools, facilitates real-time data and helps learn students more effectively. Thus, this study aims to examine the impact of trialability, compatibility, relative advantage, observability and low complexity on students’ knowledge management engagement and learning motivation in the context of Gen AI. Moreover, it examines how students’ knowledge management engagement and learning motivation affect learning effectiveness. Furthermore, the moderating role of perceived skill readiness has been examined. Design/methodology/approach An extensive cross-sectional survey of students has been conducted in various universities and colleges in Saudi Arabia. We used Smart PLS (v 3.0) for data analysis based on (n = 308) valid responses. Findings The results indicate that, the trialability, compatibility, relative advantage and low complexity are associated with learning motivation; relative advantage and low complexity are associated with knowledge management engagement; knowledge management engagement and learning motivation both positively and significantly affect students’ learning effectiveness; perceived skill readiness positively moderates the association between relative advantage, knowledge management engagement and learning motivation; and perceived skill readiness positively moderates the relationship between observability and learning motivation. Originality/value The findings have noteworthy implications for Gen AI in teaching-learning and contribute to knowledge management practices. This novel study examines the relationships between Gen AI use, students’ knowledge management engagement and learning motivation from the theoretical background of diffusion of innovation theory, using Smart PLS (v 3.0). Thus, it advances Gen AI in the context of knowledge management literature.