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Title: Developing a model for remedial operations in intelligent tutoring systems.
Author: Siemer, Julika.
ISNI:       0000 0001 3409 3397
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: 1995
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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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Computer assisted learning