Affect recognition in learning scenarios: Matching facial-and BCI-based values

Javier Gonzalez-Sanchez, Maria Elena Chavez-Echeagaray, Lijia Lin, Mustafa Baydogan, Robert Christopherson, David Gibson, Robert Atkinson, Winslow Burleson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The ability of a learning system to infer a student's affects has become highly relevant to be able to adjust its pedagogical strategies. Several methods have been used to infer affects. One of the most recognized for its reliability is face-based affect recognition. Another emerging one involves the use of brain-computer interfaces. In this paper we compare those strategies and explore if, to a great extent, it is possible to infer the values of one source from the other source.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013
Pages70-71
Number of pages2
DOIs
StatePublished - 2013
Event2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013 - Beijing, China
Duration: Jul 15 2013Jul 18 2013

Publication series

NameProceedings - 2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013

Other

Other2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013
CountryChina
CityBeijing
Period7/15/137/18/13

Keywords

  • affect recognition
  • brain computer interfaces
  • random forest

ASJC Scopus subject areas

  • Computer Science Applications

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  • Cite this

    Gonzalez-Sanchez, J., Chavez-Echeagaray, M. E., Lin, L., Baydogan, M., Christopherson, R., Gibson, D., Atkinson, R., & Burleson, W. (2013). Affect recognition in learning scenarios: Matching facial-and BCI-based values. In Proceedings - 2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013 (pp. 70-71). [6601869] (Proceedings - 2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013). https://doi.org/10.1109/ICALT.2013.26