Framework for a Competency-Driven, Multi-viewpoint, and Evolving Learner Model

Abstract

Considering learning as a dynamic, evolving, social, and lifelong process which occurs in a wide variety of contexts, we aim to improve online learning by offering learning adaptation possibilities, lifelong learning follow-up, learning evolution follow-up, openness to the learner’s contexts (personal, professional, and academic), and openness to actors involved in the learning process. To achieve this goal, we propose the development of a meta-model for learner models based on competencies, integrating learner production and personal and professional information, IPP, evolving in time and taking into account different viewpoints. This meta-model may be used for creating different kind of learner models which serve different purposes: adaptation of learning to the learner’s cognitive state, learning evaluation, self-reflection, team work... From these kinds of models, models representing individuals will be instantiated.