An Affective-computing Approach to Provide Enhanced Learning Analytics

Javier Chaparro, Rubén Navarro, Ana Ruiz, Jesús Ruiz, Xavier García, María Romero, Félix Molina, Juan López

2020

Abstract

Detecting emotions in a learning environment can make the student-learning process more efficient, avoiding stressful situations that might eventually lead to failure, frustation and demotivation. The work presented here describes a perceptive desktop devised to capture the sensations of any person facing learning activities. To this end, we propose a perceptive environment enhanced with capabilities to perform an analysis of electroencephalography, facial expression, eye tracking and particularly a very distinctive indicator of stress as it is the galvanic response of the skin. This work focuses on the galvanic response of the skin, comparing the performance of two devices in the context of the perceptive desktop. One of the devices was very attractive to our environment as it was a mouse that fit very well to our computer-based desktop, equipped with low-cost sensors to detect the galvanic response. The other device is more tedious to place and more expensive but we use it as a reference to know if the mouse is accurate. Four people were exposed to an experiment with the two devices connected, and observing the results it can be concluded that there is no correlation between the captures of both devices. Therefore, we could not select the mouse for our environment even though at first it looks like a very promising device.

Paper Citation

in Harvard Style

Chaparro J., Navarro R., Ruiz A., Ruiz J., García X., Romero M., Molina F. and López J. (2020). An Affective-computing Approach to Provide Enhanced Learning Analytics.In Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-417-6, pages 163-170. DOI: 10.5220/0009368401630170

in Bibtex Style

@conference{csedu20,
author={Javier Chaparro and Rubén Navarro and Ana Ruiz and Jesús Ruiz and Xavier García and María Romero and Félix Molina and Juan López},
title={An Affective-computing Approach to Provide Enhanced Learning Analytics},
booktitle={Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2020},
pages={163-170},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009368401630170},
isbn={978-989-758-417-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - An Affective-computing Approach to Provide Enhanced Learning Analytics
SN - 978-989-758-417-6
AU - Chaparro J.
AU - Navarro R.
AU - Ruiz A.
AU - Ruiz J.
AU - García X.
AU - Romero M.
AU - Molina F.
AU - López J.
PY - 2020
SP - 163
EP - 170
DO - 10.5220/0009368401630170