Abstract
One of the biggest challenges relating to intelligent tutoring systems (ITSs) is to model them to adapt to the individual student’s needs, leading to improved learning gains through personalised tutorials that consider aspects such as the choice of content, the level at which the content is pitched, and an appropriate strategy to tutor that content. Ideally, ITSs should be able to select content and teaching styles to suit each student, much like human tutors who are effective at using past tutoring experiences to adapt their delivery of the tutorial accordingly. Therefore, it is anticipated that the ITS’s ability to adapt might be improved significantly if the human tutor’s trait of using past experiences to aid decisionmaking can be incorporated. ..
M.Sc. (Computer Science)