Adapting handwriting recognition for applications in algebra learning

  • Authors:
  • Lisa Anthony;Jie Yang;Kenneth R. Koedinger

  • Affiliations:
  • Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University

  • Venue:
  • Proceedings of the international workshop on Educational multimedia and multimedia education
  • Year:
  • 2007

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Abstract

In this paper we report the progress of our ongoing project exploring the adaptation of handwriting recognition-based interfaces for applications in intelligent tutoring systems for students learning algebra equation-solving. The research is motivated by the hypothesis that handwriting as an input modality may be able to provide significant advantages over typing in the mathematics learning domain. We review the literature of existing handwriting systems for mathematic applications and evaluations of handwriting recognition accuracy. We describe our approach and report results to date in exploring the use of handwriting recognition in interfaces for math learning, from both a technical and a pedagogical perspective. We have found that handwriting input can provide benefits to students learning math, and continue to pursue further technical and pedagogical enhancements.