A fuzzy learners’ knowledge modelling system for online learning

• Main Authors: Ng, Wen Thing, Teh, Chee Siong
• Format: Proceeding
• Language: English
• Published: 2019
• Subjects: LB Theory and practice of education; LB2300 Higher Education; QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/28190/1/FUZZY%20LEARNERS%E2%80%99.pdf; http://ir.unimas.my/id/eprint/28190/; http://www.iucel2019.unimas.my
• Institution: Universiti Malaysia Sarawak

Many past studies report on personalising learning via intelligent systems but only a handful report on assisting instructors in personalising learning by leveraging technology. Instructors are knowledgeable in teaching and learning but they seldom put much effort to personalise learning due to the complexity of this approach. This study presents a fuzzy learners’ knowledge modelling system that addresses three issues related to the complexity of personalising learning. This study also demonstrates how this system can be applied in a real-world scenario. The case study shows that based on learners’ performance in online assessments, this system is able to assist instructors to personalise learning by planning for appropriate interventions through the insights derived from the system.