Tutorial Dialogue as Adaptive Collaborative Learning Support

  • Authors:

  • Rohit Kumar;Carolyn P. Rosé;Yi-Chia Wang;Mahesh Joshi;Allen Robinson

  • Affiliations:

  • Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA, {rohitk,cp3a,yichiaw,maheshj,alr}@cs.cmu.edu;Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA, {rohitk,cp3a,yichiaw,maheshj,alr}@cs.cmu.edu;Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA, {rohitk,cp3a,yichiaw,maheshj,alr}@cs.cmu.edu;Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA, {rohitk,cp3a,yichiaw,maheshj,alr}@cs.cmu.edu;Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA, {rohitk,cp3a,yichiaw,maheshj,alr}@cs.cmu.edu

  • Venue:
  • Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
  • Year:
  • 2007

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Abstract

In this paper we investigate the role of reflection in simulation based learning by manipulating two independent factors that each separately lead to significant learning effects, namely whether students worked alone or in pairs, and what type of support students were provided with. Our finding is that in our simulation based learning task, students learned significantly more when they worked in pairs than when they worked alone. Furthermore, dynamic support implemented with tutorial dialogue agents lead to significantly more learning than no support, while static support was not statistically distinguishable from either of the other two conditions. The largest effect size in comparison with the control condition of individuals working alone with no support was Pairs+Dynamic support, with an effect size of 1.24 standard deviations.