A Web-Based Intelligent Tutoring System for Computer Programming

  • Authors:
  • C. J. Butz;S. Hua;R. B. Maguire

  • Affiliations:
  • University of Regina, Canada;University of Regina, Canada;University of Regina, Canada

  • Venue:
  • WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

Web Intelligence is a direction for scientific research that explores practical applications of Artificial Intelligence to the next generation of Web-empowered systems. In this paper, we present a Web-based intelligent tutoring system for computer programming. The decision making process conducted in our intelligent system is guided by Bayesian networks, which are a formal framework for uncertainty management in Artificial Intelligence based on probability theory. Whereas many tutoring systems are static HTML Web pages of a class textbook or lecture notes, our intelligent system can help a student navigate through the online course materials, recommend learning goals, and generate appropriate reading sequences.