Return to search

Developing a model for tutoring strategy selection in intelligent tutoring systems

Variation in tutoring strategy plays an important part in Intelligent Tutoring Systems (ITSs). The potential for providing an adaptive ITS depends initially on having a range of tutoring strategies to select from. However, in order to react effectively to the student's needs, an ITS not only has to be able to simply offer different tutoring strategies but to choose intelligently among them and determine which one is best for an individual student at a particular moment. This thesis first examines, through literature review and interactions with existing systems, the current practices of ITSs regarding the provision of multiple tutoring strategies and tutoring strategy selection. What stems from this examination are the principles that underlie tutoring strategys election. These principles of tutoring strategy selection serve as a foundation for the construction of the model for tutoring strategy selection. To demonstrate the benefits of having such a model for formalising selection, the model is then implemented in ARISTOTLE, an existing ITS for tutoring zoology that includes several tutoring strategies but uses ad hoc mechanisms for choosing among them. This research is therefore contributing, through the principles of, and the model for tutoring strategy selection, a formal basis for selecting among tutoring strategies in ITSs that incorporate multiple tutoring strategies.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:267977
Date January 1997
CreatorsTong, Amelia Ka Yan
PublisherLondon School of Economics and Political Science (University of London)
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation

Page generated in 0.0015 seconds