Emotion recognition in texts for user model augmenting
Proceedings of the 13th International Conference on Interacción Persona-Ordenador
Adapting social and intelligent environments to support people with special needs
IWAAL'12 Proceedings of the 4th international conference on Ambient Assisted Living and Home Care
AngryEmail? emotion-based e-mail tool adaptation
IWAAL'12 Proceedings of the 4th international conference on Ambient Assisted Living and Home Care
Exploiting sentiment analysis to track emotions in students' learning diaries
Proceedings of the 13th Koli Calling International Conference on Computing Education Research
Predicting user personality by mining social interactions in Facebook
Journal of Computer and System Sciences
Designing videogames to improve students' motivation
Computers in Human Behavior
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Affective and emotional factors seem to affect student motivation and, in general, the outcome of the learning process. By detecting and managing the emotions underlying a learning activity it would be possible to contribute to improve the student motivation and performance. In this work we explore different possibilities aimed at automatically extracting emotions from texts. We present a case study in which twelve essays written by a fresher student along her first semester in college are analyzed. Those results support the idea of using non-intrusive emotion detection for providing feedback to students. An example of use in an existing context-based adaptive e-learning system is presented. Incorporating emotions to this type of systems broadens their possibilities, allowing dynamic recommendation of activities according to the student emotions at each time, as well as emotion-based content adaptation, among others.