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Modeling User Affect from Causes and Effects

  • Cristina Conati
  • Heather Maclaren
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5535)

Abstract

We present a model of user affect to recognize multiple user emotions during interaction with an educational computer game. Our model deals with the high level of uncertainty involved in recognizing a variety of user emotions by probabilistically combining information on both the causes and effects of emotional reactions. In previous work, we presented the performance and limitations of the model when using only causal information. In this paper, we discuss the addition of diagnostic information on user affective valence detected via an EMG sensor, and present an evaluation of the resulting model.

Keywords

Game Playing Educational Game Conditional Probability Table Causal Information Affective Valence 
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 2009

Authors and Affiliations

  • Cristina Conati
    • 1
  • Heather Maclaren
    • 1
  1. 1.Computer Science DepartmentUniversity of British ColumbiaVancouver

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