AGE-Learn: Ontology-Based Representation of Personalized Gamification in E-learning

Abstract

Abstract E-learning is constantly growing and seems to be essential in this rapidly changing world. Continually improving learners ‘experience, gamifying e-learning appeared with one objective: of motivation, attendance and progress of e-learners. One size of gamification isn’t suitable for all learners. Learners do not interact with gamification element or gamification environment in the same way which brings the appearance of personalized gamification which has proven its effectiveness to improve learner engagement, motivation and learning results. To understand which mechanisms and dynamics create pleasure, several concepts revolve around to personalized gamification. A learner in the context of adaptive gamification has different changing aspects like personalities, needs, values and motivations, we are going to combine those aspects with learner experience to adapt gamification process. The objective of this paper is to propose a representation of adaptive gamification domain knowledge into an ontology. To evaluate AGE-Learn† ontology, we adopt a criteria-based evaluations approach.