LifeOn, a ubiquitous lifelong learner model ontology supporting adaptive learning

Abstract

One of the challenges in adaptive learning systems is to manage learner models that include learners' profiles and activities and interaction between learners and the learning tools. In the context of lifelong learning, the learner model is a user learning pattern, which can be modelled all the time based on user interaction with various sources. The main issue in lifelong learner model design is what type of information needs to be stored in the learner model and how the information granularity is involved. The type and level of information granularity of a user will determine how appropriate the pedagogical policies are to be provided by the system for a user. Lifelong learner model design should be in line with the principles of lifelong learning, namely sociality, interoperability, and scrutability. This paper discusses our research on learner model ontology for lifelong learning. The goal expected to be achieved is that there is a lifelong learner model ontology to be accessed and updated by adaptive learning systems. This research classifies learners' attributes into two groups, which are static and dynamic attributes. Static attributes tend not to change or very rarely change. They include learner's profile, special needs, aptitude, preference, learning approach, learning style, personality, and cognitive capability. On the other hand, dynamic attributes include learning history and study plan. Through conducting some experiments, it can be concluded that LifeOn supports ubiquitous and lifelong learning, and can be used in adaptive learning systems with various learner models.