A Framework for Adaptive E-learning Systems Based on Self-regulated Learning Strategies

Abstract

AbstractThe majority of researches propose theoretical frameworks of adaptive e-learning suggesting generic models for studying adaptive e-learning systems without concretely providing elements of each model (learner, domain, and adaptation models) that could constitute the basis of the proposed framework. Previous research on adaptive e-learning systems stated that the generic framework of these systems is composed of three components: learner model, domain model, and adaptation model. Since the self-regulated learning model is the most used in online environments because the learner is on his own with or without the intervention of an online tutor, it seems interesting to us to consider this concept as an important characteristic of the learner model. Thus, this article suggests a framework based on self-regulated learning (SRL) to build a more comprehensive tool that serves to analyze adaptive e-learning systems. The research presents the elements (in dynamic interaction) of the conceptual framework for adaptative e-learning as well as a model for detecting self-regulated learning strategies using log files.KeywordsAdaptive E-learningDistance learningE-learning 4.0Artificial intelligence