Tablet and Apps Impacts on Students’ Learning Performance: A Digital Literacy and Student Engagement Mediation Analysis

The advancement of tablets and applications in education is crucial, particularly regarding the impact of mobile smart devices on performance in tertiary-level economics. This tertiary-level course examines mobile smart devices and applications via the perspectives of digital literacy and student involvement. The study employed structural equation modeling as its digital methodology, analyzing the model's validators for scope and relevance based on established standards of beta coefficients, t-values, p-values, and R-squared (R2) in relation to the responses of two hundred and fifty undergraduates. The investigation indicated that tablets and mobile applications significantly enhanced digital literacy, engagement, and student performance. Of the three, digital literacy emerged as the most significant mediator. The study demonstrated a robust R2 of 0.789 related to student performance. Therefore, enhancing performance by fostering participation and digital literacy is a crucial finding that education authorities, including the ministry, universities, and schools, should address by incorporating technology into the curriculum to improve digital literacy. Specifically, rural participation in the improvement of digital engagement instruments. Future research should incorporate longitudinal and cross-cultural studies to enhance and expand these findings.

Tablets and apps, student engagement, digital literacy

1. Al-Maroof, R. S., Alnazzawi, N., Akour, I., Ayoubi, K., Alhumaid, K., Nasser, N. M., Alaraimi, S., Al-Bulushi, A. A., Thabit, S., Alfaisal, R., Aburayya, A., & Salloum, S. (2022). Students’ perception towards using electronic feedback after the pandemic: Post-acceptance study. International Journal of Data and Network Science, 6(4), 1233–1248. https://doi.org/10.5267/j.ijdns.2022.6.010 [Google Scholar] [Crossref]

2. Chen, W. W., & Wong, Y. L. (2015). Chinese mindset: theories of intelligence, goal orientation and academic achievement in Hong Kong students. Educational Psychology, 35(6), 714–725. https://doi.org/10.1080/01443410.2014.893559 [Google Scholar] [Crossref]

3. Crompton, H., & Burke, D. (2018). The use of mobile learning in higher education: A systematic review. Computers and Education, 123(April), 53–64. https://doi.org/10.1016/j.compedu.2018.04.007 [Google Scholar] [Crossref]

4. Fornell, C., & Larcker, D. F. (2016). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research This, 18(1), 39–50. [Google Scholar] [Crossref]

5. Gikas, J., & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. Internet and Higher Education, 19, 18–26. https://doi.org/10.1016/j.iheduc.2013.06.002 [Google Scholar] [Crossref]

6. Gilboy, M. B., Heinerichs, S., & Pazzaglia, G. (2015). Enhancing student engagement using the flipped classroom. Journal of Nutrition Education and Behavior, 47(1), 109–114. https://doi.org/10.1016/j.jneb.2014.08.008 [Google Scholar] [Crossref]

7. Hinze, A., Vanderschantz, N., Timpany, C., Cunningham, S. J., Saravani, S. J., & Wilkinson, C. (2023). A Study of Mobile App Use for Teaching and Research in Higher Education. Technology, Knowledge and Learning, 28(3), 1271–1299. https://doi.org/10.1007/s10758-022-09599-6 [Google Scholar] [Crossref]

8. Hirshberg, M. J., Frye, C., Dahl, C. J., Riordan, K. M., Vack, N. J., Sachs, J., Davidson, R. J., & Goldberg, S. B. (2022). A Randomized Controlled Trial of a Smartphone-Based Well-Being Training in Public School System Employees During the COVID-19 Pandemic. Journal of Educational Psychology, 1–56. [Google Scholar] [Crossref]

9. Kaware, S. S., & Sain, S. K. (2015). ICT Application in Education: An Overview. International Journal of Multidisciplinary Approach and Studies, 03(4), 25–32. [Google Scholar] [Crossref]

10. Kock, N. (2021). Harman ’ s single factor test in PLS-SEM : Checking for common method bias. Data Analysis Perspectives Journal, 2(April), 1–6. [Google Scholar] [Crossref]

11. Vaughan, N., & Garrison, D. R. (2005). Creating cognitive presence in a blended faculty development community. Internet and Higher Education, 8(1), 1–12. https://doi.org/10.1016/j.iheduc.2004.11.001 [Google Scholar] [Crossref]

12. Wilson, S. A., Byrne, P., Rodgers, S. E., & Maden, M. (2022). A Systematic Review of Smartphone and Tablet Use by Older Adults With and Without Cognitive Impairment. Innovation in Aging, 6(2), 1–19. https://doi.org/10.1093/geroni/igac002 [Google Scholar] [Crossref]

13. Zhang, G., Chen, P., & Xu, S. (2025). Developing and validating a scale for measuring sustainable leadership development among teachers in Chinese higher education institutions. Journal of Cleaner Production, 486(January 2024). https://doi.org/10.1016/j.jclepro.2024.144403 [Google Scholar] [Crossref]

• Assessment of the Role of Artificial Intelligence in Repositioning TVET for Economic Development in Nigeria
• Teachers’ Use of Assure Model Instructional Design on Learners’ Problem Solving Efficacy in Secondary Schools in Bungoma County, Kenya
• “E-Booksan Ang Kaalaman”: Development, Validation, and Utilization of Electronic Book in Academic Performance of Grade 9 Students in Social Studies
• Analyzing EFL University Students’ Academic Speaking Skills Through Self-Recorded Video Presentation
• Major Findings of The Study on Total Quality Management in Teachers’ Education Institutions (TEIs) In Assam – An Evaluative Study