Faculty Advisor or Committee Member

Dr. Neil T. Heffernan, Advisor

Faculty Advisor or Committee Member

Dr. Stanley M. Selkow

Faculty Advisor or Committee Member

Dr. Michael A. Gennert

Identifier

etd-0429104-112724

Abstract

The purpose of this research was to apply machine learning techniques to automate rule generation in the construction of Intelligent Tutoring Systems. By using a pair of somewhat intelligent iterative-deepening, depth-first searches, we were able to generate production rules from a set of marked examples and domain background knowledge. Such production rules required independent searches for both the“if" and“then" portion of the rule. This automated rule generation allows generalized rules with a small number of sub-operations to be generated in a reasonable amount of time, and provides non-programmer domain experts with a tool for developing Intelligent Tutoring Systems.

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Computer Science

Project Type

Thesis

Date Accepted

2004-04-29

Accessibility

Unrestricted

Subjects

Intelligent Tutoring Systems, Model Tracing, Machine Learning, Artificial Intelligence, Programming by Demonstration, Machine learning, Rule-based programming, Computer-assisted instruction, Intelligent tutoring systems, Authoring tools

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