Digital competence and motivation as predictors of academic success in online training for university applicants

This study explores the impact of online education on the learning quality and academic achievements of higher education applicants. Grounded in the Technological Pedagogical Content Knowledge (TPACK) framework and Self-Determination Theory, the research adopted a mixed-methods design involving 270 participants. A 13-week online intervention combining real-time feedback, interactive modules, and collaborative forums was implemented. Data were analyzed using ANOVA, regression, Structural Equation Modeling (SEM), and cluster analysis. The findings indicate that participants possessed sufficient digital competence and high intrinsic motivation. Cluster analysis revealed three distinct learner profiles; the "Engaged-Tech-Savvy" group demonstrated significantly higher academic success compared to "Moderately Engaged" and "Disengaged" groups. Results confirm that digital competence and intrinsic motivation are key predictors of academic achievement, with course quality mediating this relationship. The study provides practical recommendations for higher education institutions regarding community building, digital infrastructure, and teacher training to better prepare applicants. Future research should integrate objective usage data to further validate these findings.