MOBILE MICRO-LEARNING ADOPTION AMONG ACCOUNTING STUDENTS
Abstract
The pursuit of professional accounting designations necessitates rigorous engagement with complex regulatory frameworks, often concurrently with full-time employment. While Mobile Micro-learning offers a solution through ubiquitous access to bite-sized content, it simultaneously introduces the risk of cognitive fragmentation. Moving beyond contextual replication, this study integrates the Unified Theory of Acceptance and Use of Technology with the Value-based Adoption Model and Cognitive Load Theory. This theoretical synthesis allows for a rigorous evaluation of how extraneous cognitive load competes with perceived value in the high-stakes context of accounting education. Analyzing data from 342 Vietnamese accounting students via Structural Equation Modeling, the study identifies a critical tension between accessibility and concentration. The results demonstrate that while Ubiquity and Performance Expectancy are primary drivers of Perceived Value, Perceived Distraction and Information Risk serve as substantial barriers, significantly eroding the utility of mobile learning tools. Notably, Social Influence was found to have a non-significant effect, suggesting that students exhibit “academic individualism” when selecting tools for high-stakes exams. Furthermore, Perceived Value is established as a full mediator between these antecedents and the Intention to Adopt. These findings suggest that for high-stakes accounting education, the utility of “anytime, anywhere” learning is contingent upon mitigating the “always-on” nature of mobile interruptions.
Keywords
Mobile micro-learning, VAM, UTAUT, Perceived value, Perceived distraction, Accounting education.
Ethical Statement
References
- Aagaard, J. (2015). Drawn to distraction: A qualitative study of off-task use of educational technology. Computers & Education, 87, 90–97. https://doi.org/10.1016/j.compedu.2015.03.010
- Al-Abdullatif, A. M. (2023). Modeling students’ perceptions of chatbots in learning: integrating technology acceptance with the value-Based adoption model. Education Sciences, 13(11). https://doi. org/10.3390/educsci13111151
- Ali, M. M., & Saher, S. (2025). Distraction or dependence? Exploring the effects of smartphone overuse on student creativity and learning. Trends in Social Sciences, 1(1), 35–40. https://doi.org/10.21124/ tss.2025.35.40
- Almaiah, M. A., Jalil, M. A., & Man, M. (2016). Empirical investigation to explore factors that achieve high quality of mobile learning system based on students’ perspectives. Engineering Science and Technology, an International Journal, 19(3), 1314–1320. https://doi.org/10.1016/j.jestch.2016.03.004
- Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. https://doi. org/10.1037/0033-2909.103.3.411