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Designing automated adaptive support to improve student helping behaviors in a peer tutoring activity

  • Erin Walker
  • Nikol Rummel
  • Kenneth R. Koedinger
Article
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Abstract

Adaptive collaborative learning support systems analyze student collaboration as it occurs and provide targeted assistance to the collaborators. Too little is known about how to design adaptive support to have a positive effect on interaction and learning. We investigated this problem in a reciprocal peer tutoring scenario, where two students take turns tutoring each other, so that both may benefit from giving help. We used a social design process to generate three principles for adaptive collaboration assistance. Following these principles, we designed adaptive assistance for improving peer tutor help-giving, and deployed it in a classroom, comparing it to traditional fixed support. We found that the assistance improved the conceptual content of help and the use of interface features. We qualitatively examined how each design principle contributed to the effect, finding that peer tutors responded best to assistance that made them feel accountable for help they gave.

Keywords

Adaptive collaborative learning support Adaptive scripting Reciprocal peer tutoring Intelligent tutoring In vivo experimentation 
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Notes

Acknowledgments

This project is supported by the Pittsburgh Science of Learning Center which is funded by the National Science Foundation award number SBE-0836012. Thanks to Thomas Harris, Tristan Nixon, and Steve Ritter for their support concerning the use of the Carnegie Learning Cognitive Tutor Algebra code, and to Gail Kusbit, Christy McGuire, and the classroom teachers for their motivated involvement in the project. Finally, thanks to Carolyn Rosé, Dejana Diziol, Ido Roll, Ruth Wylie and Amy Ogan for their comments at various stages.

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Copyright information

© International Society of the Learning Sciences, Inc.; Springer Science + Business Media, LLC 2011

Authors and Affiliations

  • Erin Walker
    • 1
  • Nikol Rummel
    • 2
  • Kenneth R. Koedinger
    • 1
  1. 1.Human-Computer Interaction InstituteCarnegie Mellon UniversityPittsburghUSA
  2. 2.Institute of EducationRuhr-Universität BochumBochumGermany

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