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It’s Written on Your Face: Detecting Affective States from Facial Expressions while Learning Computer Programming

  • Nigel Bosch
  • Yuxuan Chen
  • Sidney D’Mello
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8474)

Abstract

We built detectors capable of automatically recognizing affective states of novice computer programmers from student-annotated videos of their faces recorded during an introductory programming tutoring session. We used the Computer Expression Recognition Toolbox (CERT) to track facial features based on the Facial Action Coding System, and machine learning techniques to build classification models. Confusion/Uncertainty and Frustration were distinguished from all other affective states in a student-independent fashion at levels above chance (Cohen’s kappa = .22 and .23, respectively), but detection accuracies for Boredom, Flow/Engagement, and Neutral were lower (kappas = .04, .11, and .07). We discuss the differences between detection of spontaneous versus fixed (polled) judgments as well as the features used in the models.

Keywords

Affective State Facial Feature Cognitive Science Society Facial Action Code System Affect Judgment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nigel Bosch
    • 1
  • Yuxuan Chen
    • 1
  • Sidney D’Mello
    • 1
    • 2
  1. 1.Departments of Computer ScienceUniversity of Notre DameUSA
  2. 2.PsychologyUniversity of Notre DameUSA

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