Developing a model for remedial operations in intelligent tutoring systems.
Intelligent Tutoring Systems attempt to create a relationship between a computer and
the student which resembles a human-to-human tutorial situation. For successful
teaching to take place an Intelligent Tutoring System has to be able to cope with any
student errors that may occur during a consultation.
Remedial intervention implemented in current Intelligent Tutoring Systems lacks
a formal basis. The objective of this research is to formalise the process of
remediation with Intelligent Tutoring Systems and to provide a framework for the
implementation of remedial tutoring in Intelligent Tutoring Systems.
This research first presents a state-of-the-art account of Intelligent Tutoring
Systems. It then proceeds with an investigation of both current practices with existing
Intelligent Tutoring Systems and requirements for providing remedial tutoring. What
stems from this investigation is a set of principles that governs remedial tutoring
intervention. These principles of remediation serve as the foundation for the
construction of the model for remedial operations, which can be employed in
developing Intelligent Tutoring Systems capable of offering remedial tutoring. To
demonstrate this, INTUITION, an Intelligent Tutoring System implementation of an
existing business simulation game, is developed. The thesis then proposes an
evaluation method which can be used to assess remedial intervention with Intelligent
Tutoring Systems against the principles of remediation. This evaluation method is
applied to INTUITION. The result of the evaluation shows that INTUITION follows
the principles of remediation and that, therefore, the model for remedial operations is
a useful method for providing remedial tutoring with Intelligent Tutoring Systems
according to the principles of remediation.