The Role of Metacognitive Awareness in Predicting Digital Character Readiness Among Generation Z University Students: A Structural Equation Modeling Analysis

Abstract

Digital transformation in higher education requires the development of students who are not only technologically competent but also reflective, responsible, and ethically grounded in digital environments. This study aims to examine the metacognitive awareness profile of first-year Generation Z students in Riau Province, Indonesia, and to investigate its role in shaping digital character readiness. A quantitative survey design was employed involving 512 freshmen from public and private universities. Data were analyzed using Structural Equation Modeling (SEM) with Maximum Likelihood Estimation, incorporating Confirmatory Factor Analysis (CFA), bootstrapping mediation analysis, alternative model comparison, Multi-Group SEM, measurement invariance testing, and latent mean comparison. The findings indicate that knowledge of cognition significantly predicts regulation of cognition (β = 0.72, p < .001), and regulation of cognition significantly predicts digital character readiness (β = 0.55, p < .001). The indirect effect is significant (β = 0.40, p < .001), confirming partial mediation. Model comparison results demonstrate that the partial mediation model provides a significantly better fit than the full mediation model (Δχ² significant, p < .001). Multi-Group SEM confirms structural invariance across gender and institutional type. However, latent mean comparison reveals that female students demonstrate significantly higher levels of metacognitive awareness and digital character readiness than male students. These findings underscore that digital character education in higher education should be grounded in the development of metacognitive awareness and self-regulatory processes. From a policy perspective, integrating structured self-reflection training and self-regulated learning strategies into university curricula is essential to prepare Generation Z students for the complexities of digital ecosystems.