Modeling student performance to enhance the pedagogy of autotutor

  • Authors:

  • Tanner Jackson;Eric Mathews;King-Ip Lin;Andrew Olney;Art Graesser

  • Affiliations:

  • Department of Psychology, University of Memphis, Memphis, TN;Department of Psychology, University of Memphis, Memphis, TN;Department of Computer Science, University of Memphis, Memphis, TN;Department of Psychology, University of Memphis, Memphis, TN;Department of Psychology, University of Memphis, Memphis, TN

  • Venue:
  • UM'03 Proceedings of the 9th international conference on User modeling
  • Year:
  • 2003

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Abstract

The Tutoring Research Group from the University of Memphis has developed a pedagogically effective Intelligent Tutoring System (ITS), called Auto Tutor, that implements conversational dialog as a tutoring strategy for conceptual physics. Latent Semantic Analysis (LSA) is used to evaluate the quality of student contributions and determine what dialog moves Auto Tutor gives. By modeling the students' knowledge in this fashion, Auto Tutor successfully adapted its pedagogy to match the ideal strategy for students' ability.