Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/79453
Título: | Emotion analysis in distance learning |
Autor(es): | Durães, Dalila Toala, Ramon Novais, Paulo |
Palavras-chave: | Intelligent system Sentiment analysis Distance learning COVID-19 |
Data: | 2021 |
Editora: | Springer, Cham |
Revista: | Advances in Intelligent Systems and Computing |
Citação: | Durães, D., Toala, R., Novais, P. (2021). Emotion Analysis in Distance Learning. In: Auer, M.E., Rüütmann, T. (eds) Educating Engineers for Future Industrial Revolutions. ICL 2020. Advances in Intelligent Systems and Computing, vol 1328. Springer, Cham. https://doi.org/10.1007/978-3-030-68198-2_58 |
Resumo(s): | The COVID-19 pandemic has changed education forever because schools, universities, teachers, and students had to adapt to distance learning. Multiple differences are identified with online learning compared to face-to-face education. First, students must be more responsible. Second, users' familiarity with using computers varies significantly. Third, the traditional interaction between teacher, student and content are made more complicated by the introduction of technology. The application of new tools related to the student, teacher, content, technology, software, and communication results in the improvement of teaching methods in online learning. When new tools are applied and there is an improvement in the results in online education, the student, teacher, and educational institutions benefit from it. Emotion plays an important role in the knowledge, acquisition, and decision process of an individual. Consequently, they directly influence perception, learning process, and the way people communicate. There is also significant evidence that rational learning in humans is dependent on emotions. In this paper, we presented a solution with a new Intelligent Tutoring Framework, that analyzed emotions in a non-intrusive and non-invasive way. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/79453 |
ISBN: | 978-3-030-68197-5 |
e-ISBN: | 978-3-030-68198-2 |
DOI: | 10.1007/978-3-030-68198-2_58 |
ISSN: | 2194-5357 |
Versão da editora: | https://link.springer.com/chapter/10.1007/978-3-030-68198-2_58 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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498387_1_En_58_Chapter_Author Dalila.pdf Acesso restrito! | 1,92 MB | Adobe PDF | Ver/Abrir |