Impact of AI-enhanced multimedia quality, usage frequency, and ease of integration on learning effectiveness: case of basic education colleges in Kuwait

This study investigates the impact of AI-enhanced multimedia on learning effectiveness (LEF), focusing on the roles of multimedia quality (AMQ), ease of integration (EOI), and usage frequency (UFAM). Building on TAM, UTAUT, Self-Determination Theory, and Self-Efficacy Theory, the research develops a structural equation model incorporating student engagement (STE) and technology self-efficacy (TSE) as mediators. Data were collected from 232 students across six departments in Kuwait's Colleges of Basic Education using validated measurement scales. Reliability and validity were confirmed through confirmatory factor analysis, with all constructs meeting established thresholds. Structural model results indicated that EOI was the strongest predictor of STE, TSE, and LEF, while AMQ significantly influenced TSE and LEF. In contrast, UFAM showed no significant direct or indirect effects. Mediation analysis revealed that both STE and TSE mediated the effects of EOI on LEF, while TSE mediated the AMQ–LEF relationship. The findings underscore the importance of integration quality and self-efficacy in AI-mediated learning. Theoretical and practical implications have been provided based on the findings of this research that could be useful for academicians and practitioners.