Learner Models for MOOC in a Lifelong Learning Context: A Systematic Literature Review

Abstract

While setting up a Massive Open Online Course for Lifelong Learners, the choice of the most adequate Learner Model for this most current context is paramount: not all Learner Models are created equal, despite their overall added value to facilitate the learner’s follow-up, course content personalization and trainers/teachers’ practices in various Learning Environments. This systematic review of literature defines, compares, and highlights eight features of interest of Learner Models for Massive Open Online Courses from a Lifelong Learning perspective. It discerns 17 of the most-current, existing Learner Models out of 442 search results. It concludes on the four most adequate, and current Learner Models in this context. In addition, we study how they handle the learning experience personalization. This work is primarily dedicated to MOOC designers/providers, pedagogical engineers and researchers who meet difficulties to model and evaluate MOOC’s learners using Learning Analytics.