This study presents a detailed ontology development process to semantically represent the content of the subject module and forum discussion in the form of ontology. Such an ontological representation is important within e-learning communities, particularly to support reusability of previous forum discussion and to sustain the production of e-learning resources tailored to learners’ needs. The result of knowledge acquisition and the modeling process produced subject domain ontology, with dependencies on concepts and relationships, as well as related questions and answers. Given the difficulties in this process regarding subjective interpretation and classification, as well as maintaining concepts and discussions that evolve over the time, this development is essential to reduce tutors’ burden of posting the same content
every semester. This instead promotes tutors’ efforts in enhancing existing learning materials that are able to increase learners’ understanding of the subject taught. In addition, this development also equips learners with structured learning material that is in line with the learning objectives and helps to enrich relevant discussions. This study contributes to the
semantic-rich learning environment, as the integration of the subject module and forum discussion knowledge allows for the delivery of the course via a more innovative and productive learning system. This effort is important to address because e-learning education plays a vital role in building a connected and collaborative learning community. A number of enhancements are possible by considering automated maintenance processes that are capable of tagging concepts from the subject module and forum discussion to the ontology automatically in order to maintain up-to-date and rich learning
material. The ontology model also needs to be implemented in other subjects as well as with a large number of concepts to test the system’s capability and transferability between subjects. As the ontology model was able to guide the delivery of the system, future efforts can deliver the system in a way that matches the preferred learning style of the user by
varying the sequentialization of content elements.