Teaching Effectiveness and Student Experience in University Interactive Learning Platforms Based on Mobile Technology

Abstract

This study was conducted to investigate the intrinsic mechanisms underlying the teaching effectiveness and student experience of university interactive learning platforms supported by mobile technology. Grounded in the technology acceptance model (TAM) and contextualized within mobile learning environments, the research introduced interactivity, compatibility, self-efficacy, subjective norm, and perceived enjoyment as external variables. An extended model was thereby constructed to reveal the complete causal pathway from platform characteristics to students’ cognitive perceptions, behavioral intentions, and eventual learning outcomes. A questionnaire survey was administered to university students who had utilized such platforms, yielding 250 valid responses. Structural equation modeling (SEM) was performed using SmartPLS software, with reliability and validity tests as well as bootstrapping employed to verify the proposed hypotheses. The empirical findings confirmed all 14 hypotheses. External variables such as interactivity, compatibility, and self-efficacy were identified as key antecedents influencing perceived usefulness and perceived ease of use. The core TAM pathway (perceived ease of use → perceived usefulness → attitude toward use → behavioral intention → actual use) received strong empirical support. Ultimately, actual use was found to exert a direct and significant positive effect on both student satisfaction and learning outcomes. The results demonstrated that the pedagogical value of mobile interactive platforms is realized through the process of students’ technology acceptance. This study not only provides empirical evidence for the application and extension of TAM in the field of educational technology but also offers theoretical and practical implications for university administrators in optimizing digital education strategies, for educators in designing effective interactive learning activities, and for platform developers in enhancing system design.