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 highquality
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.
