Enhancing the Automatic Generation of Hints with Expert Seeding

  • John Stamper
  • Tiffany Barnes
  • Marvin Croy
Conference paper

DOI: 10.1007/978-3-642-13437-1_4

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6095)
Cite this paper as:
Stamper J., Barnes T., Croy M. (2010) Enhancing the Automatic Generation of Hints with Expert Seeding. In: Aleven V., Kay J., Mostow J. (eds) Intelligent Tutoring Systems. ITS 2010. Lecture Notes in Computer Science, vol 6095. Springer, Berlin, Heidelberg

Abstract

The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to “seed” the hint generation process. We show that just a few expert solutions give significant coverage (over 50%) for hints. This seeding method greatly speeds up the time needed to reliably generate hints. We discuss how this feature can be integrated into the Hint Factory and some potential pedagogical issues that the expert solutions introduce.

Keywords

Educational data mining Markov decision process 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • John Stamper
    • 1
  • Tiffany Barnes
    • 2
  • Marvin Croy
    • 3
  1. 1.Human-Computer Interaction InstituteCarnegie Mellon UniversityPittsburgh
  2. 2.Department of Computer ScienceUniversity of North Carolina at CharlotteCharlotte
  3. 3.Department of PhilosophyUniversity of North Carolina at CharlotteCharlotte

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