Ontology‐based concept map for planning a personalised learning path

Abstract Developing personalised web‐based learning systems has been an important research issue in e‐learning because no fixed learning pathway will be appropriate for all learners. However, most current web‐based learning platforms with personalised curriculum sequencing tend to emphasise the learner preferences and interests in relation to personalised learning services but fail to consider the difficulty level of course materials, learning order of prior and posterior knowledge and learner abilities while constructing a personalised learning path. As a result, these ignored factors thus easily lead to the generation of poor quality learning paths. Generally, learners could generate cognitive overload or fall into cognitive disorientation owing to inappropriate curriculum sequencing during learning processes, thus, reducing the learning effect. With the advancement of artificial intelligence technologies, ontology technologies enable a linguistic infrastructure to represent conceptual relationships between course materials. Ontology can be served as a structured knowledge representation scheme, capable of assisting the construction of a personalised learning path. This study thus proposes a novel genetic‐based curriculum sequencing scheme based on a generated ontology‐based concept map, which can be automatically constructed by the pretest results of numerous learners, to plan appropriate learning paths for individual learners. The experimental results indicated that the proposed approach could create high‐quality learning paths for individual learners. The proposed approach thus can help learners to learn more effectively and to likely reduce learners' cognitive overloads during learning processes.