Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor

  • Behrooz Mostafavi
  • Guojing Zhou
  • Collin Lynch
  • Min Chi
  • Tiffany Barnes
Conference paper

DOI: 10.1007/978-3-319-19773-9_102

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9112)
Cite this paper as:
Mostafavi B., Zhou G., Lynch C., Chi M., Barnes T. (2015) Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor. In: Conati C., Heffernan N., Mitrovic A., Verdejo M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science, vol 9112. Springer, Cham

Abstract

Research shows that expert-crafted worked examples can have a positive effect on student performance. To investigate the potential for data-driven worked examples to achieve similar results, we generated worked examples for the Deep Thought logic tutor, and conducted an experiment to assess their impact on performance. Students who received data-driven worked examples were much more likely to complete the tutor, and completed the tutor in less time. This study demonstrates that worked examples, automatically generated from student data, can be used to improve student learning in tutoring systems.

Keywords

Worked examples Data-driven Problem-solving 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Behrooz Mostafavi
    • 1
  • Guojing Zhou
    • 1
  • Collin Lynch
    • 1
  • Min Chi
    • 1
  • Tiffany Barnes
    • 1
  1. 1.Department of Computer ScienceNorth Carolina State UniversityRaleighUS

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