e-ISSN: 2618-6586 Open Access · Peer-Reviewed JETOL on DergiPark
JETOL — Journal of Educational Technology & Online Learning
Publisher
Gürhan Durak
Publication Model
Periodical (January – May – September)
Status
Open for Submissions

Digital competence and academic performance: The mediating role of e-learning risk management

Research Article

Download PDF DOI: 10.31681/jetol.1856959
Published in
Volume 9, Issue 3 (2026)
Pages
350–364
Publication Date
September 30, 2026
Submission Date
January 5, 2026
Acceptance Date
September 21, 2026
Subjects
Educational Technology and Computing

Abstract

The rapid integration of digital technologies in higher education has made digital competence an important factor in students’ learning experiences. However, exposure to e-learning risks may affect how digital competence relates to academic performance. This study examined whether e-learning risk management mediated the relationship between digital competence and academic performance among university students. Using a quantitative cross-sectional research design, data were collected from 241 university students in a rural Philippine setting through structured survey questionnaires measuring digital competence, e-learning risk management, and academic performance. Hayes’ PROCESS Macro was used to examine the proposed mediation model. The findings suggest that digital competence was not significantly associated with academic performance through a direct pathway but was indirectly associated through e-learning risk management strategies, including adaptability, diversification of learning approaches, and flexible problem-solving. Students with higher levels of digital competence also tended to report stronger e-learning risk management practices, which were associated with better academic performance. These findings highlight the potential value of incorporating e-learning risk management into digital learning initiatives. However, because the study employed a cross-sectional design and relied on survey-based measures, the findings should be interpreted as associative rather than causal and may not be generalizable beyond similar educational contexts.

Keywords

  • digital competence
  • e-learning risks management
  • academic performance
  • digital literacy
References (44)
  1. Ahmed, H. (2023). The effect of strategic planning on the success of e-learning: Al-Nisour University College as a case study. International Journal of Professional Business Review, 8(3), e01521. https://doi.org/10.26668/businessreview/2023.v8i3.1521
  2. Akacha, S. A.-L., & Awad, A. I. (2023). Enhancing security and sustainability of e-learning software systems: A comprehensive vulnerability analysis and recommendations for stakeholders. Sustainability, 15(19), 14132. https://doi.org/10.3390/su151914132
  3. Alyoussef, Y. I. (2023). Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3), e13751. https://doi.org/10.1016/j.heliyon.2023.e13751
  4. Ammade, S., Rahman, A. W., & Syawal, S. (2022). Challenges and adaptation on online learning during the COVID-19 pandemic. Journal of Education and Learning (EduLearn), 16(3), 342–349. https://doi.org/10.11591/edulearn.v16i3.20529
  5. Bailenson, J. N. (2021). Nonverbal overload: A theoretical argument for the causes of Zoom fatigue. Technology, Mind, and Behavior, 2(1), 1–6. https://doi.org/10.1037/tmb0000030
  6. Barrot, J. S., Llenares, I. I., & del Rosario, L. S. (2021). Students’ online learning challenges during the pandemic and how they cope with them: The case of the Philippines. Education and Information Technologies, 26(6), 7321–7338. https://doi.org/10.1007/s10639-021-10589-x
  7. Bismala, L., Manurung, Y. H., Siregar, G., & Andriany, D. (2022). The impact of e-learning quality and students’ self-efficacy toward the satisfaction in the using of e-learning. Malaysian Online Journal of Educational Technology, 10(2), 141–150. https://doi.org/10.52380/mojet.2022.10.2.362
  8. Bravo-Agapito, J., Romero, S. J., & Pamplona, S. (2020). Early prediction of undergraduate students’ academic performance in completely online learning: A five-year study. Computers in Human Behavior, 115, 106595. https://doi.org/10.1016/j.chb.2020.106595
  9. Cabero-Almenara, J., Gutiérrez-Castillo, J. J., Guillén-Gámez, F. D., & Gaete-Bravo, A. F. (2023). Digital competence of higher education students as a predictor of academic success. Technology, Knowledge and Learning, 28(2), 683–702. https://doi.org/10.1007/s10758-022-09624-8
  10. Catena, M., & Stephens, S. (2023). Risk management in online learning environments: Academic perspectives. SSRN. https://doi.org/10.2139/ssrn.4417748
  11. Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018
  12. Erarslan, A., & Zehir Topkaya, E. (2017). EFL Students Attitudes Towards e-Learning And Effect of An Online Course on Students Success in English. The Literacy Trek, 3(2), 80–101.
  13. Frolova, E. V., Rogach, O. V., Tyurikov, A. G., & Razov, P. V. (2021). Online student education in a pandemic: New challenges and risks. European Journal of Contemporary Education, 10(1), 43–52. https://doi.org/10.13187/ejced.2021.1.43
  14. Han, F., & Ellis, R. A. (2021). Predicting students’ academic performance by their online learning patterns in a blended course: To what extent is a theory-driven approach and a data-driven approach consistent? Educational Technology & Society, 24(1), 191–204. https://doi.org/10.30191/ETS.202101_24(1).001
  15. Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (3rd ed.). Guilford Press. https://www.guilford.com/books/Introduction-to-Mediation-Moderation-and-Conditional-Process-Analysis/Andrew-Hayes/9781462549030
  16. Jaggars, S., & Xu, D. (2016). How do online course design features influence student performance? Computers & Education, 95, 270–284. https://doi.org/10.1016/j.compedu.2016.01.014
  17. Junaid, I., & Faizan, M. H. (2022). The impact of social media on student academic performance and digital wellbeing. Proceedings of the International Conference on Education Social Sciences and Technology (ICESST), 1(2), 363–369. https://doi.org/10.55606/icesst.v1i2.492
  18. Kallas, K., & Pedaste, M. (2022). How to improve the digital competence for e-learning? Applied Sciences, 12, 6582. https://doi.org/10.3390/app12136582
  19. Lai, K., & Hong, K. (2015). Technology use and learning characteristics of students in higher education: Do generational differences exist? British Journal of Educational Technology, 46(4), 725–738. https://doi.org/10.1111/bjet.12161
  20. Lucas, M., Bem-haja, P., Santos, S., Figueiredo, H., Ferreira Dias, M., & Amorim, M. (2022). Digital proficiency: Sorting real gaps from myths among higher education students. British Journal of Educational Technology, 53(6), 1885–1914. https://doi.org/10.1111/bjet.13220
  21. Marrero-Sánchez, O., & Vergara-Romero, A. (2023). Digital competence of the university student: A systematic and bibliographic update. Amazonia Investiga, 12(67), 9–18. https://doi.org/10.34069/AI/2023.67.07.1
  22. Martin, A. J., Collie, R. J., & Nagy, R. P. (2021). Adaptability and high school students’ online learning during COVID-19: A job demands-resources perspective. Frontiers in Psychology, 12, 702163. https://doi.org/10.3389/fpsyg.2021.702163
  23. Martin, F., Wang, C., & Sadaf, A. (2019). Student perception of helpfulness of facilitation strategies that enhance instructor presence, connectedness, engagement, and learning in online courses. The Internet and Higher Education, 37, 52–65. https://doi.org/10.1016/j.iheduc.2018.01.003
  24. Martín-Gutiérrez, J., Mora, C. E., Añorbe-Díaz, B., & González-Marrero, A. (2017). Virtual technologies trends in education. EURASIA Journal of Mathematics, Science and Technology Education, 13(2), 469–486. https://doi.org/10.12973/eurasia.2017.00626a
  25. Maxwell, S. E., & Cole, D. A. (2007). Bias in cross-sectional analyses of longitudinal mediation. Psychological Methods, 12(1), 23–44. https://doi.org/10.1037/1082-989X.12.1.23
  26. Nouraey, P., & Al-Badi, A. (2023). Challenges and problems of e-learning: A conceptual framework. Electronic Journal of e-Learning, 21(3), 188–199. https://doi.org/10.34190/ejel.21.3.2677
  27. Oducado, R. M. (2020). Survey instrument validation rating scale. https://doi.org/10.13140/RG.2.2.25263.59040
  28. Oducado, R. M. F., & Estoque, H. (2021). Online learning in nursing education during the COVID-19 pandemic: Stress, satisfaction, and academic performance. Journal of Nursing Practice, 4(2), 143–153. https://doi.org/10.30994/jnp.v4i2.128
  29. Palvia, S., Aeron, P., Gupta, P., Mahapatra, D., Parida, R., Rosner, R., & Sindhi, S. (2018). Online education: Worldwide status, challenges, trends, and implications. Journal of Global Information Technology Management, 21(4), 233–241. https://doi.org/10.1080/1097198X.2018.1542262
  30. Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers & Education, 144, 103701. https://doi.org/10.1016/j.compedu.2019.103701
  31. Rushton, L. (2007). The precautionary principle in the context of multiple risks. Occupational and Environmental Medicine, 64(9), 574. https://doi.org/10.1136/oem.2006.031856
  32. Samane-Cutipa, V. A., Quispe-Quispe, A. M., Talavera-Mendoza, F., & Limaymanta, C. H. (2022). Digital gaps influencing the online learning of rural students in secondary education: A systematic review. International Journal of Information and Education Technology, 12(7), 685–690. https://doi.org/10.18178/ijiet.2022.12.7.1671
  33. Sapanca, H., & Kanbul, S. (2022). Risk management in digitalized educational environments: Teachers’ information security awareness levels. Frontiers in Psychology, 13, 986561. https://doi.org/10.3389/fpsyg.2022.986561
  34. Scheel, L., Vladova, G., & Ullrich, A. (2022). The influence of digital competences, self-organization, and independent learning abilities on students’ acceptance of digital learning. International Journal of Educational Technology in Higher Education, 19, 44. https://doi.org/10.1186/s41239-022-00350-w
  35. Secreto, P. V., & Tabo, E. C. (2023). Impact of synchronous class attendance on the academic performance of undergraduate students. International Journal of Educational Management and Development Studies, 4(1), 109–128. https://doi.org/10.53378/352968
  36. Shearer, R. L., & Park, E. (2018). The theory and practice of distance education. In Handbook of distance education (pp. 381–399). Routledge. https://doi.org/10.4324/9781315296135-21
  37. Shersad, F., & Salam, S. (2020). Managing risks of e-learning during COVID-19. International Journal of Innovation and Research in Educational Sciences, 7(4), 348–358. https://doi.org/10.13140/RG.2.2.12722.63689
  38. Siddiq, F., Scherer, R., & Tondeur, J. (2016). Teachers’ emphasis on developing students’ digital information and communication skills (TEDDICS): A new construct in 21st century education. Computers & Education, 92–93, 1–14. https://doi.org/10.1016/j.compedu.2015.10.006
  39. Stockinger, K., Rinas, R., Daumiller, M., & Dresel, M. (2021). Student adaptability, emotions, and achievement: Navigating new academic terrains in a global crisis. Learning and Individual Differences, 90, 102046. https://doi.org/10.1016/j.lindif.2021.102046
  40. Suciptawati, N., Widana, N., Susilawati, M., Srinadi, G. A., & Nilakusmawati, D. P. (2023). Identification of online learning problems in rural areas during COVID-19. International Journal of Social Science and Human Research, 6(1), 695–701. https://doi.org/10.47191/ijsshr/v6-i1-92
  41. Vygotsky, L. S. (1978). Mind in society: Development of higher psychological processes. Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4
  42. World Economic Forum. (2020). The global risks report 2020 (15th ed.). https://www.weforum.org/publications/the-global-risks-report-2020/
  43. Younas, M., Noor, U., Zhou, X., Menhas, R., & Qingyu, X. (2022). COVID-19, students satisfaction about e-learning and academic achievement: Mediating analysis of online influencing factors. Frontiers in Psychology, 13, 948061. https://doi.org/10.3389/fpsyg.2022.948061
  44. Zhao, Y., Sánchez Gómez, M. C., Pinto Llorente, A. M., & Zhao, L. (2021). Digital competence in higher education: Students’ perception and personal factors. Sustainability, 13(21), 12184. https://doi.org/10.3390/su132112184

This article is published under the CC BY 4.0 license.