Expanding the Model-Tracing Architecture: A 3rd Generation Intelligent Tutor for Algebra Symbolization

  • Authors:

  • Neil T. Heffernan;Kenneth R. Koedinger;Leena Razzaq

  • Affiliations:

  • Computer Science Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA. E-mail: {nth,leenar}@wpi.edu;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. E-mail: koedinger@cmu.edu;Computer Science Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA. E-mail: {nth,leenar}@wpi.edu

  • Venue:
  • International Journal of Artificial Intelligence in Education
  • Year:
  • 2008

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Abstract

Following Computer Aided Instruction systems, 2nd generation tutors are Model-Tracing Tutors (MTTs) (Anderson & Pelletier, 1991) which are intelligent tutoring systems that have been very successful at aiding student learning, but have not reached the level of performance of experienced human tutors (Anderson et al., 1995). To that end, this paper presents a new architecture called ATM ("Adding a Tutorial Model"), which is an extension to model-tracing, that allows these tutors to engage in a dialog that is more like those in which experienced human tutors engage. Specifically, while MTTs provide hints toward doing the next problemsolving step, this 3rd generation of tutors, the ATM architecture, adds the capability to ask questions towards thinking about the knowledge behind the next problem-solving step. We present a new tutor built in ATM, called Ms. Lindquist, which is designed to carry on a tutorial dialog about algebra symbolization. The difference between ATM and MTT is the separate tutorial model that encodes pedagogical content knowledge in the form of different tutorial strategies, which were partially developed by observing an experienced human tutor. Ms. Lindquist has tutored thousands of students at www.AlgebraTutor.org. Future work will reveal if Ms. Lindquist is a better tutor because of the addition of the tutorial model.