Detecting the Learner's Motivational State in Online Learning Situation Towards Adaptive Learning Environments

Abstract

Learning platforms provide new learning opportunities. They are rich on techno-pedagogical tools, enabling learners to collaborate, interact and share resources easily and freely between them, based on their needs and preferences. But the limit of these platforms is that they do not take into consideration the learners' motivation. Detecting and understanding the learner motivational state requires a rigorous analysis of the interaction traces between the learner and his learning environment. This paper aims to propose and verify some indicators to facilitate the analysis of digital traces, in view to detect the learner's motivational state. Being able to understand the motivational state could help stakeholders (tutor, teacher, pedagogical designer, etc.) to facilitate the learning process, by creating personalized courses.