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

Erin Walker, Nikol Rummel, Kenneth R. Koedinger

Research output: Contribution to journalArticle

38 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)279-306
Number of pages28
JournalInternational Journal of Computer-Supported Collaborative Learning
Volume6
Issue number2
DOIs
StatePublished - Jun 1 2011

Keywords

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

ASJC Scopus subject areas

  • Education
  • Human-Computer Interaction

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