Towards an Ontology-Based E-Learning Recommendation System
Yousef H. Alfaifi · 2023
E-learning recommendation systems enhance learning for students (e-learners) through their provision of tailored recommendations to student queries. Existing e-learning recommendation systems have relied on traditional algorithms, such as collaborative filtering, which are limited when tasked to provide recommendations for new users. This paper contributes to the body of work on personalised recommendation systems by proposing a multi-task ontology based framework capable of supporting multiple personalised recommendations for multiple purposes. These may include personalised learning paths, objects (such as courses or textbooks) and feedback. To generate personalised feedback, the approach uses a rule based system that integrates ontological information to learner profiles in order to provide a recommendation. Additionally, the framework provisions for domain-expert generated feedback to e-learners.