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Viewing Student Affect and Learning through Classroom Observation and Physical Sensors

  • Toby Dragon
  • Ivon Arroyo
  • Beverly P. Woolf
  • Winslow Burleson
  • Rana el Kaliouby
  • Hoda Eydgahi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5091)

Abstract

We describe technology to dynamically collect information about students’ emotional state, including human observation and real-time multi-modal sensors. Our goal is to identify physical behaviors that are linked to emotional states, and then identify how these emotional states are linked to student learning. This involves quantitative field observations in the classroom in which researchers record the behavior of students who are using intelligent tutors. We study the specific elements of learner’s behavior and expression that could be observed by sensors. The long-term goal is to dynamically predict student performance, detect a need for intervention, and determine which interventions are most successful for individual students and the learning context (problem and emotional state).

Keywords

Emotional State Classroom Observation Intelligent Tutor System Positive Valence Task Behavior 
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-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Toby Dragon
    • 1
  • Ivon Arroyo
    • 1
  • Beverly P. Woolf
    • 1
  • Winslow Burleson
    • 2
  • Rana el Kaliouby
    • 3
  • Hoda Eydgahi
    • 4
  1. 1.Department of Computer ScienceUniversity of MassachusettsAmherst 
  2. 2.Arts, Media and Engineering ProgramArizona State University 
  3. 3.Media LabMassachusetts Institute of Technology 
  4. 4.Department of Electrical EngineeringMassachusetts Institute of Technology 

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