Digital Competence and Learning Agility as Predictors of Self-Perceived Employability among Fresh Graduates

Abstract

Fresh graduates enter a labour market shaped by intensifying competition and rapid digitalization. This environment requires both digital competence and the capacity to learn adaptively, as these individual resources may influence how graduates evaluate their ability to obtain and sustain employment. This study examined whether Digital Competence and Learning Agility predict Self-Perceived Employability among 2024–2025 graduates of Universitas Garut. A quantitative cross-sectional survey was conducted using self-report questionnaires completed by 150 respondents selected through accidental sampling. The data were analysed with partial least squares structural equation modelling in SmartPLS 3. Hypotheses were assessed through 5,000 bootstrap subsamples, a two-tailed test, and a 5% significance level. Digital Competence positively predicted Self-Perceived Employability (β = 0.529, t = 10.545, p < 0.001), as did Learning Agility (β = 0.573, t = 13.086, p < 0.001). Together, the two predictors explained 64.7% of the variance in Self-Perceived Employability (R² = 0.647), indicating moderate explanatory power. The study contributes by combining the DigComp 2.2 conception of Digital Competence with Learning Agility in a single predictive model of graduate employability perceptions. Practically, the findings support integrated university initiatives that strengthen digital capability and adaptive learning during the transition from higher education to employment.

Keywords

Digital Competence; Learning Agility; Self-Perceived Employability; Fresh Graduates; PLS-SEM