Personality traits, Learning Preferences and Emotions

Abstract

In this paper, we describe how a learning platform that takes into account the student's learning preferences, the personality and emotions could prompt better learning results. This model will assess the emotional state of the student in an online learning environment by introducing techniques of Affective Computing that can capture the student emotional state and based on that, adapt the course to the characteristics and needs of the student in order to get an improvement in the learning results. Students, as individuals, differ in their social, intellectual, physical, psychological, emotional, and ethnic characteristics. Also, differ in their learning rates, objectives and motivation turning, their behaviour rather unpredictable. Added to emotion, and in order to obtain an effective model for online learning, student's personality and learning style are also considered. The architecture developed was tested by a group of students of higher education in Oporto. The results indicated that the model created used can support and improve the student's results, verifying that a negative emotional state could influence the learning process.