Faculty Advisor

Dr. Neil T. Heffernan

Faculty Advisor

Dr. Stanley M. Selkow

Faculty Advisor

Dr. Michael A. Gennert

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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