How Digital Competence Influences Academic Performance: The Mediating Role of Learning Motivation among Students at Thu Dau Mot University

Digital transformation has become a strategic priority in higher education, driven by the widespread adoption of emerging technologies such as artificial intelligence (AI), learning management systems (LMS), big data analytics, and online learning platforms. In this context, digital competence has emerged as a critical factor influencing students’ learning experiences and academic success. However, empirical evidence regarding the mechanisms through which digital competence affects academic performance remains limited, particularly in developing countries such as Vietnam. This study aims to examine the effects of digital competence on academic performance and investigate the mediating role of learning motivation among university students. Drawing upon the Digital Competence Framework (DigComp), the Technology Acceptance Model (TAM), and Self-Determination Theory (SDT), the study conceptualizes digital competence as a multidimensional construct comprising Digital Technology Literacy, Digital Mindset, Digital Communication, Self-directed Learning with Technology, and Digital Ethics. A quantitative cross-sectional survey was conducted among 350 undergraduate students at Thu Dau Mot University, Vietnam. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The results reveal that all five dimensions of digital competence positively influence learning motivation. Among them, Self-directed Learning with Technology exerts the strongest effect. Furthermore, learning motivation significantly enhances academic performance and mediates the relationships between digital competence and academic performance. This study contributes to the literature by extending the DigComp framework within the Vietnamese higher education context and by identifying learning motivation as a key psychological mechanism linking digital competence to academic success. The findings provide practical implications for universities seeking to strengthen students’ digital competencies, promote self-directed learning, integrate AI-supported learning environments, and enhance educational outcomes in the era of digital transformation.