Personalized Students' Profile Based on Ontology and Rule-based Reasoning

Date

2016

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

ICST Transactions

Type

Article

Peer reviewed

Yes

Abstract

Nowadays, most of the existing e-learning architecture provides the same content to all learners due to "one size fits for all" concept. E-learning refers to the utilization of electronic innovations to convey and encourage training anytime and anywhere. There is a need to create a personalized environment that involves collecting a range of information about each learner. Questionnaires are one way of gathering information on learning style, but there are some problems with their usage, such as reluctance to answer questions as well as guesses the answer being time consuming. Ontology-based semantic retrieval is a hotspot of current research, because ontologies play a paramount part in the development of knowledge. In this paper, a novel way to build an adaptive student pro le by analysis of learning patterns through a learning management system, according to the Felder-Silverman learning style model (FSLSM) and Myers-Briggs Type Indicator (MBTI) theory is proposed.

Description

Keywords

adaptive Learning, Semantic Web, Adaptability, Learner Profile, ontology, FSLSM, MBTI

Citation

Nafea, S. et al. (2016) Personalized Students' Profile Based on Ontology and Rule-based Reasoning. EAI Endorsed Transactions on e-Learning 16(12): e6

Rights

Research Institute

Cyber Technology Institute (CTI)