Exploring the Strengthening of Lecturer Performance in the Education Era through AI-Driven Instructional Design Capability and Data-Informed Teaching Decision-Making

Abstract

This study develops and empirically validates an integrated educational technology model to explain students' academic resilience through the roles of Adaptive Learning System Maturity and Metacognitive Regulation Technology, mediated by Self-Regulated Learning Behavior and Digital Learning Effectiveness. Employing a quantitative structural equation modeling (SEM) approach, the study examines both direct and indirect relationships among the proposed constructs to understand the mechanisms underlying successful digital learning. The findings indicate that Adaptive Learning System Maturity and Metacognitive Regulation Technology significantly enhance students' Self-Regulated Learning Behavior and Digital Learning Effectiveness, demonstrating that advanced learning technologies and metacognitive support are essential determinants of effective learning processes. Furthermore, Self-Regulated Learning Behavior and Digital Learning Effectiveness significantly contribute to Academic Resilience, confirming their important mediating roles in strengthening students' capacity to adapt, persist, and succeed in challenging academic environments. Mediation analysis further reveals that both variables partially mediate the relationships between educational technology factors and Academic Resilience. However, the sequential mediation effect is not statistically supported, suggesting that Self-Regulated Learning Behavior and Digital Learning Effectiveness operate as parallel rather than sequential mechanisms in fostering students' academic resilience.