Application of graph theory in an intelligent tutoring system for solving mathematical word problems

Abstract

This study is aimed to construct a model to transform word "motion problems" in to an algorithmic form in order to be processed by an intelligent tutoring system (ITS). First; categorizing the characteristics of motion problems, second; suggesting a model for the categories were carried out. In order to solve all categories of the problems, graph theory including backward and forward chaining techniques of artificial intelligence were utilized. The study outlines the adoption of graph theory in to the motion problems and put forth some evidence that the model solves almost all of the motion problems. In conclusion, the recommended model can be suggested to be used in educational software in the problem solving context.