Supporting Self-Regulated Personalised Learning through Competence-based Knowledge Space Theory

This paper presents two current research trends in e-learning that at first sight appear competing. Competence-based Knowledge Space Theory (CbKST) provides a knowledge representation framework which, since its invention by Doignon and Falmagne, has been successfully applied in various e-learning systems (e.g. ALEKS, ELEKTRA) providing automated personalisation to learners’ current knowledge and competence level. Principles of self-regulated learning (SRL), pioneered by e.g. Zimmerman, however, argue for increased learner control, thus resulting in giving learners greater responsibility over their e-learning. The research presented in theis paper shows that skill-based visualisations in the tradition of CbKST and SRL-based autonomy are noway conflicting but rather complementing each other towards an integrated approach of self-regulated personalised learning. The respective research has been carried out and technologically translated into a set of visual tools for supporting the whole learning cycle in the scope of the iClass project.