Recognizing Student Emotions using Brainwaves and Mouse Behavior Data

Author:

Azcarraga Judith1,Suarez Merlin Teodosia1

Affiliation:

1. Center for Empathic Human-Computer Interactions, De La Salle University, Manila, Philippines

Abstract

Brainwaves (EEG signals) and mouse behavior information are shown to be useful in predicting academic emotions, such as confidence, excitement, frustration and interest. Twenty five college students were asked to use the Aplusix math learning software while their brainwaves signals and mouse behavior (number of clicks, duration of each click, distance traveled by the mouse) were automatically being captured. It is shown that by combining the extracted features from EEG signals with data representing mouse click behavior, the accuracy in predicting academic emotions substantially increases compared to using only features extracted from EEG signals or just mouse behavior alone. Furthermore, experiments were conducted to assess the prediction accuracy of the system at points during the learning session where several of the extracted features significantly deviate in value from their mean. The experiments confirm that the prediction performance increases as the number of feature values that deviate significantly from the mean increases.

Publisher

IGI Global

Subject

Computer Networks and Communications,Computer Science Applications,Education

Reference29 articles.

1. Emotion sensors go to school;I.Arroyo;Artificial intelligence in education,2009

2. Azcarraga, J., Ibañez, J. F., Jr., Lim, I. R., & Lumanas, N., Jr. (2011a, March). Predicting student affect based on brainwaves and mouse behavior. In Proceedings of the 11th Philippine Computing Science Congress, Naga City, Philippines.

3. Azcarraga, J., Ibañez, J. F., Jr., Lim, I. R., Lumanas, N., Jr., Trogo, R., & Suarez, M. T. (2011c). Predicting academic emotion based on brainwaves signals and mouse click behavior. In T. Hirashima et al., (Eds.), Proceedings of the 19th International Conference on Computers in Education (pp. 42-49). Chiang Mai, Thailand: Asia-Pacific for Computers in Education.

4. Azcarraga, J., Inventado, P. S., & Suarez, M. T. (2010). Predicting the difficulty level faced by academic achievers based on brainwaves analysis. In the Proceedings of the 18th International Conference on Computers in Education (pp. 107-109). Putrajaya, Malaysia: Asia-Pacific for Computers in Education.

5. Azcarraga, J. J., Ibañez, J. F., Jr., Lim, I. R., & Lumanas, N., Jr. (2011b). Use of personality profile in predicting academic emotion based on brainwaves signals and mouse behavior. In the Proceedings of the 2011 Third International Conference on Knowledge and Systems Engineering (pp. 239-244). Hanoi, Vietnam.

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