Repairing Disengagement With Non-Invasive Interventions

  • Authors:

  • Ivon Arroyo;Kimberly Ferguson;Jeff Johns;Toby Dragon;Hasmik Meheranian;Don Fisher;Andrew Barto;Sridhar Mahadevan;Beverly P. Woolf

  • Affiliations:

  • Department of Computer Science & Department of Engineering, University of Massachusetts Amherst;Department of Computer Science & Department of Engineering, University of Massachusetts Amherst;Department of Computer Science & Department of Engineering, University of Massachusetts Amherst;Department of Computer Science & Department of Engineering, University of Massachusetts Amherst;Department of Computer Science & Department of Engineering, University of Massachusetts Amherst;Department of Computer Science & Department of Engineering, University of Massachusetts Amherst;Department of Computer Science & Department of Engineering, University of Massachusetts Amherst;Department of Computer Science & Department of Engineering, University of Massachusetts Amherst;Department of Computer Science & Department of Engineering, University of Massachusetts Amherst

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

Quantified Score

Hi-index 0.00

Visualization

Abstract

We evaluated the impact of a set of interventions to repair students' disengagement while solving geometry problems in a tutoring system. We present a deep analysis of how a tutor can remediate a student's disengagement and motivation with self-monitoring feedback. The analysis consists of a between-subjects analyses on students learning and on students' attitudes towards mathematics and perceptions of the software, and a deeper analysis on students' engagement within the tutor. Results show that the general trend over time is for students to become more disengaged while using a tutor, yet students can be coaxed into reengagement after viewing interventions that promote self-reflection and self-monitoring --a simple open-learner model accompanied by suggestions and encouragement.