Development and validation of an adaptive learning readiness assessment framework for Moodle courses

Abstract In the evolving landscape of educational technology, adaptive learning represents a significant advancement in personalizing student experiences. Despite Moodle's capabilities to support adaptive learning, institutions often struggle to implement these features effectively. This study addresses this gap by developing and validating an Adaptive Learning Readiness Assessment Framework (ALRAF) for evaluating Moodle courses' potential to support adaptive learning experiences. Drawing on established theoretical foundations and contemporary research in educational technology, we identified five key dimensions of adaptive learning readiness: Content Variety, Interaction Diversity, Assessment Flexibility, Learning Path Personalization, and Feedback Mechanisms. We applied this framework to analyze 985 Moodle courses at a Ukrainian pedagogical university using existing course component data. Our findings reveal significant correlations between adaptive readiness scores and student learning outcomes, with higher-scoring courses demonstrating improved grade distributions. The dimensional analysis highlights strong implementation of content variety but significant weaknesses in learning path personalization. Variations in readiness across faculties point to potential disciplinary differences in technology adoption. This framework provides institutions with a diagnostic tool for evaluating and enhancing their LMS implementation, bridging the gap between Moodle's technical capabilities and pedagogical implementation for adaptive learning. The study contributes to educational technology literature by transforming descriptive analysis into a prescriptive framework that can guide course design decisions and professional development initiatives.