INFLUENCES OF PERCEIVED USEFULNESS AND PERCEIVED EASE OF USE ON ACADEMIC ACHIEVEMENT: MEDIATING ROLE OF MOTIVATION
DOI:
https://doi.org/10.20397/2177-6652/2026.v26i3.3206Palabras clave:
perceived usefulness, perceived ease of use, motivation, academic performance, SmartPLS.Resumen
Technology adoption has significantly reshaped the higher education landscape, influencing how students engage with academic content and achieve their learning goals. By utilizing the Technology Acceptance Model (TAM), this study explored the role of the adoption of technology in shaping academic achievement. This study examines the role of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) in influencing Academic Achievement (CGPA). Consequently, this study seeks to (1) analyze the relationship between PU, PEOU and CGPA, and (2) identify the role of Motivation as a mediator. To explore these relationships, a survey of over 200 undergraduates was conducted, and the data was analyzed using SMART PLS. The findings reveal a strong correlation between PU, PEOU and CGPA. The findings confirm that technology adoption significantly impacts academic achievement. Nevertheless, amplification of these can be observed when motivation is linked to it. The data revealed that students who effectively utilize digital tools and platforms tend to perform better. This research contributes to the ongoing discourse on technology adoption and academic achievement, offering insights for educators, policymakers, and institutions to optimize digital tools for learning. It highlights the necessity to develop strategies that foster positive technology adoption behaviors, ensuring undergraduates to effectively leverage digital resources. By aligning instructional design with the principles of TAM, institutions can enhance motivation, reduce learning barriers and improve overall academic outcomes.
Citas
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
Akpen, C. N., Asaolu, S., Atobatele, S., et al. (2024). Impact of online learning on student's performance and engagement: A systematic review. Discov Educ, 3, 205. https://doi.org/10.1007/s44217-024-00253-0
Al-Rahmi, W. M., Othman, M. S., & Yusuf, L. M. (2018). Exploring the factors that affect student satisfaction through collaborative learning in Malaysian higher education. Education and Information Technologies, 23(1), 141–155. https://doi.org/10.1007/s10639-017-9602-4
Ameen, N., Ahmed, Y., Mohamad, M., & Sharma, A. (2021). The impact of system quality and usefulness on students’ blended learning satisfaction and performance. Education and Information Technologies, 26, 4797–4815. https://doi.org/10.1007/s10639-021-10527-w
Bakar, A. A., Zainuddin, N. M., & Rosli, R. (2022). The impact of digital learning tools on students’ academic performance: A Malaysian higher education perspective. Journal of Education and e-Learning Research, 9(3), 234–240. https://doi.org/10.20448/journal.509.2022.93.234.240
Cheung, A. C. K., & Slavin, R. E. (2013). The effectiveness of educational technology applications for enhancing mathematics achievement in K-12 classrooms: A meta-analysis. Educational Research Review, 9, 88–113. https://doi.org/10.1016/j.edurev.2013.01.001
Cheung, W., Chan, K., & Lo, M. (2023). Investigating motivation in online learning environments: A technology adoption perspective. Computers & Education, 191, 104683. https://doi.org/10.1016/j.compedu.2022.104683
Dadandı, İ., & Yazıcı, H. (2024). University students’ digital learning experience: The mediating role of motivation between technology acceptance and academic success. Education and Information Technologies. https://doi.org/10.1007/s10639-024-11983-3
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York, NY: Plenum Press.
Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
Gupta, N., Shrivastava, A., Mathur, G., & Sachdeva, J. K. (2025). Impact of ChatGPT on the Quantitative Acumen of Postgraduate Business Management Students in Central India. Revista Gestão & Tecnologia, 25(2), 179-206.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Thousand Oaks, CA: Sage Publications.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Khalil, M., Abdalla, M., & Fatani, T. (2024). Student engagement and digital learning: A pathway to improved academic outcomes. Education Sciences, 14(1), 23. https://doi.org/10.3390/educsci14010023
Kim, M., Kim, J., Knotts, T. L., et al. (2025). AI for academic success: Investigating the role of usability, enjoyment, and responsiveness in Chat GPT adoption. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13398-8
Manas, G. E. (2023). The Effect of Concept Map Strategy on Academic Achievement and Student Retention in Biology Education. Studies in Educational Management, 14, 1-10. https://doi.org/10.32038/sem.2023.14.01
Muratbekova. A. (2025). The relationship between self-esteem and academic achievement among female students at Almaty Management University. International Journal of Behavior Studies in Organizations, 12, 1-7. https://doi.org/10.32038/JBSO.2025.13.01
Shahraniza, T., Ahmad, M., & Rubiyanti, N. (2025). Sinergizar el rendimiento académico con la competencia comunicativa y la adopción de tecnología. INTERACCIÓN Y PERSPECTIVA. Revista De Trabajo Social, 15(2), 502–518. https://doi.org/10.5281/zenodo.15080460
Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications (2nd ed.). Upper Saddle River, NJ: Merrill Prentice Hall.
Puentedura, R. R. (2006). Transformation, technology, and education. SAMR Model. Retrieved from http://hippasus.com/resources/tte/
Pund, R., Prasad, V. K. S., & Sinha, A. (2023). Extended technology acceptance model to understand customers’ acceptance of the internet of things and artificial intelligence enabled smart homes in India. Revista Gestão & Tecnologia, 23(4), 377–395. https://doi.org/10.20397/2177-6652/2023.v23i4.2707
Shukla, A., & Sharma, P. (2023). Evaluating the role of technology acceptance in online learning: A study of undergraduate students. International Journal of Educational Technology in Higher Education, 20(1), 15. https://doi.org/10.1186/s41239-023-00389-6
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Venkatesh, V., & Bala, H. (2022). Adoption of technology in education: Updated insights from the TAM framework. MIS Quarterly Executive, 21(1), 47–61. https://doi.org/10.25300/MISQE/2022/15984
Wong, L. H. (2023). Digital transformation in education: The role of motivation and usability. Journal of Learning Analytics, 10(2), 100–115. https://doi.org/10.18608/jla.2023.7660
Yarin, A., Mohd Yusof, H., & Ismail, N. A. (2022). Exploring digital learning motivation among university students in a post-pandemic context. Asian Journal of Distance Education, 17(2), 74–86. https://doi.org/10.5281/zenodo.7111870
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2026 Revista Gestão & Tecnologia

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Os direitos, inclusive os de tradução, são reservados. É permitido citar parte de artigos sem autorização prévia desde que seja identificada a fonte. A reprodução total de artigos é proibida. Em caso de dúvidas, consulte o Editor.
