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Title: Developing a model for tutoring strategy selection in intelligent tutoring systems.
Author: Tong, Amelia Ka Yan.
ISNI:       0000 0001 3534 9622
Awarding Body: London School of Economics and Political Science (University of London)
Current Institution: London School of Economics and Political Science (University of London)
Date of Award: 1997
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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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Computer aided learning Education Electric engineering Computer science