Abstract
It is well known that emotions have a great impact on the learning process and this becomes especially important when moving to on-line education. Then, endowing e-learning systems with the capability of assessing the emotional state of learners, can be used to provide feedback about their difficulties and problems. In this paper, we present an empirical study performed with a group of first-year students aiming at getting information on users’ affective state during the learning process considering their personality traits. At this aim, we developed a tool for cognitive emotion recognition from facial expressions. Results show how detected emotions can be considered as an indicator of the e-learning process quality. Furthermore, another result is that cognitive emotions, experienced during e-learning process, can be strongly differentiated according to the learning activities, students age and personality.
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De Carolis, B., D’Errico, F., Paciello, M., Palestra, G. (2020). Cognitive Emotions Recognition in e-Learning: Exploring the Role of Age Differences and Personality Traits. In: Gennari, R., et al. Methodologies and Intelligent Systems for Technology Enhanced Learning, 9th International Conference. MIS4TEL 2019. Advances in Intelligent Systems and Computing, vol 1007 . Springer, Cham. https://doi.org/10.1007/978-3-030-23990-9_12
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DOI: https://doi.org/10.1007/978-3-030-23990-9_12
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