Development of an Ontology-Based Personalised E-Learning Recommender System
Abstract
E-learning has become an active field of research with a lot of investment towards web-based delivery of personalised learning contents to learners. Some issues of e-learning arise from the heterogeneity and interoperability of learning content to suit learner’s style and preferences in order to improve the e-learning environment. Hence, this paper developed an ontology-based personalised recommender system that is needed to recommend suitable learning contents to learners using collaborative filtering and ontology. A pre-test is carried out for users in order to segment them in learning categories to suit their skill level. The learning contents are structured using ontology; and collaborative filtering is used to collects preferences from many users and then recommending the highest rated contents to users. The system is implemented using JAVA programming language with Structured Query Language (MySQL) as database management system. Performance evaluation of the system is carried out using survey and standard metrics such as precision, recall and F1-Measrure. The results from the two performance evaluation models showed that the system is suitable for recommending the required learning contents to learners.
References
. D. Sampson and C. Karagiannidis. Knowledge-on-Demand in e-Learning and e-Working Settings, Journal of the International Forum of Educational Technology and Society and the IEEE Learning Technology Task Force, Special Issue entitled Integrating Technology into Learning and Working”, 5(4),24-39 2012
. P. Brusilovsky. Knowledge Tree: A distributed Architecture for Adaptive E-Learning. Proceedings of the International World Wide Web conference on Alternate track papers and posters, 4(10), 105 -106, 2004.
. J. Ricardo, and O. Mendes. Development of a Recommender System for an E-Learning Platform, December, 4 (12), 10 – 45, 2018.
. K. Balaji, G. Poorni, and N. Deepthi. Recommendation Approach to Support Learners in an E-learning Environment, International Journal of Advanced Research in Computer Engineering & Technology, 4(11) 45 – 49, 2017.
. K. Alexsandra, I. Mirjana, and B. Zoran. E-learning personalization based on hybrid recommendation strategy and learning style identification, Computers and Education, 56 (8) 885–899 2011.
. O. S. Adewale, T. Fakoya and P. Oladoja. Ontology-Based Model for E- learning Management System. International Journal of Computer Science, 12(6), 45 -47, 2015.
. Ricardo,, J. and Mendes, O. Development of a Recommender System for an E-Learning Platform Available at https://sigarra.up.pt/fcup/pt/pub_geral.show_file?pi_doc_id=90364, Reetrieved on December 14, 2018
. K. John, N. Zhendong, and K. Bakhti. E-Learning Recommender System Based on Collaborative Filtering and Ontology, International Scholarly and Scientific Research and Innovation, 11(2) 256 -260, 2017.
. E. Stuart, R. Nigel and D. Shadbolt. Developing an Ontological Recommender System to Monitor User’s Behavior, 22(1), 54–88, 2019.
. P. Reena and M. Marathwada. A Study of Recommender System Techniques. International Journal of Computer Applications, 120(12), 281-291, 2011
. J. Jeevamol, S. R. Nisha and Renumol, V. G. An Ontology Model for Content Recommendation in Personalized Learning Environment Proceedings of the Second International Conference on Data Science, E-Learning and Information Systems 9,1–6, 2019.
. S. K. Samuel and G. Q. José. A Personalised Hybrid Learning Object Recommender System, proceedings of the 11th International Conference on Management of Digital EcoSystems, 242–249, 2019.
. S. Studer, V. Benjamins and D. Fensel, Knowledge engineering: Principles and methods. In: Data and Knowledge Engineering, 25(6) 161–197, 1998.
. B. Lamiroy and T. Sun. Precision and recall without ground truth, IAPR International Workshop on Graphics, 23(4), 120 -132, 2017.
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