Authors:
Christos Chrysoulas
and
Maria Fasli
Affiliation:
University of Essex, United Kingdom
Keyword(s):
E-learning, Adaptive Learning, User Profile, Learning Path, Machine Learning.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Computer-Supported Education
;
Distance and e-Learning in a Global Context
;
e-Learning
;
e-Learning Platforms
;
Enterprise Information Systems
;
Information Technologies Supporting Learning
;
Intelligent Tutoring Systems
;
Simulation and Modeling
;
Simulation Tools and Platforms
;
Social Context and Learning Environments
Abstract:
Research in adaptive learning is mainly focused on improving learners’ learning achievements based mainly
on personalization information, such as learning style, cognitive style or learning achievement. In this paper,
an innovative adaptive learning approach is proposed based upon two main sources of personalization
information that is, learning behaviour and personal learning style. To determine the initial learning styles of
the learner, an initial assigned test is employed in our approach. In order to more precisely reflect the
learning behaviours of each learner, the interactions and learning results of each learner are thoroughly
recorded and in depth analysed, based on advanced machine learning techniques, when adjusting the subject
materials. Based on this rather innovative approach, an adaptive learning prototype system has been
developed.