Analyzing Learner Affect in a Scenario-Based Intelligent Tutoring System

  • Benjamin Nye
  • Shamya Karumbaiah
  • S. Tugba Tokel
  • Mark G. Core
  • Giota Stratou
  • Daniel Auerbach
  • Kallirroi Georgila
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10331)

Abstract

Scenario-based tutoring systems influence affective states due to two distinct mechanisms during learning: (1) reactions to performance feedback and (2) responses to the scenario context or events. To explore the role of affect and engagement, a scenario-based ITS was instrumented to support unobtrusive facial affect detection. Results from a sample of university students showed relatively few traditional academic affective states such as confusion or frustration, even at decision points and after poor performance (e.g., incorrect responses). This may show evidence of “over-flow,” with a high level of engagement and interest but insufficient confusion/disequilibrium for optimal learning.

Notes

Acknowledgment

The effort described here is sponsored by the U.S. Army Research Laboratory (ARL) under contract number W911NF-14-D-0005. Any opinion, content or information presented does not necessarily reflect the position or the policy of the United States Government, and no official endorsement should be inferred.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Benjamin Nye
    • 1
  • Shamya Karumbaiah
    • 2
  • S. Tugba Tokel
    • 3
  • Mark G. Core
    • 1
  • Giota Stratou
    • 1
  • Daniel Auerbach
    • 1
  • Kallirroi Georgila
    • 1
  1. 1.Institute for Creative Technologies, University of Southern CaliforniaLos AngelesUSA
  2. 2.College of Information and Computer SciencesUniversity of Massachusetts AmherstAmherstUSA
  3. 3.Department of Computer Education and Instructional TechnologyMETUAnkaraTurkey

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