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

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

Project Number

1

Ethical Statement

The study was reviewed and approved by the Research Ethics Committee which members are the graduates school professors in a university located in the Philippines. The researcher also secured permission to use the digital competence assessment tool. Participation was voluntary, with informed consent obtained from all respondents. Anonymity and confidentiality were strictly maintained, and data were stored securely and used solely for academic purposes. Moreover, the author utilized an AI language tool (ChatGPT, OpenAI) to assist in enhancing the grammar, clarity, and flow of the manuscript. All concepts, analyses, interpretations, and conclusions presented in this paper remain entirely the work and responsibility of the author.

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