A poster accepted to ICALT 2013.
13th IEEE International Conference on Advanced Learning Technologies (ICALT)
Hosted by Beijing Normal University
Beijing, China. 15-18 July, 2013
In this poster we compared two affect recognition strategies: face-based affect recognition and brain-computer interfaces.
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.
Gonzalez-Sanchez J., Chavez-Echeagaray M.E., Lin, L., Baydogan, M., Christopherson R., Gibson D., Atkinson R., and Burleson W. (2013). Affect Recognition in Learning Scenarios: Matching Facial- and BCI-Based Values. Proceedings of the 13th IEEE International Conference on Advanced Learning Technologies (ICALT). Beijing, China. 15-18 July. Pages 70-71.