A Reference Framework for Adaptive Learning: From Pedagogical Foundations to Evaluation - Yaqine, Kawtar; Mohammed Sefian Lamarti; Mohamed Khaldi (COMPETITIVE: Journal of Education, 2026)
This paper aims to establish a comprehensive reference framework for adaptive and personalized learning systems, addressing the disconnect often found between computational architectures and educational theory. The study begins by clarifying the conceptual landscape, distinguishing between adaptive learning, personalized learning, and intelligent tutoring systems. Adopting a theoretical synthesis approach, we examine how foundational pedagogical theories, specifically constructivism, experiential learning, and Self-Regulated Learning (SRL), can be effectively operationalized within computational models. We further analyze critical dimensions of adaptation, including content delivery, activity selection, learning paths, and feedback mechanisms. The resulting framework integrates these elements to define essential quality criteria for system evaluation: efficacy, student engagement, equity, and the management of cognitive load. We conclude that successful adaptive environments require a holistic design where algorithmic strategies are strictly guided by epistemological foundations, ensuring that technical sophistication serves to enhance, rather than obscure, the learning experience.