Automatic Identification of Learning-Centered Emotions: Preliminary Study for Data Collection

Abstract

The intention of this work is to achieve an automatic identification of emotions in educational environments using machine learning algorithms and physiological and behavioral signal acquisition technologies to identify relations between emotions and learning. Four of the main learning-centered emotions are considered [1]: engagement, boredom, confusion and frustration. It is proposed to make a fusion of data from four signal acquisition technologies with the objective of achieving the identification of emotions in the most precise manner. The development of an appropriate database for the study of emotions is a fundamental task. Therefore, considering the stages of the proposed methodology, the first of them is presented and the design of the experiment that will be executed for data collection with college students during a learning process.