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https://hdl.handle.net/1822/86321
Título: | EduBot: a proof-of-concept for a high school motivational agent |
Autor(es): | Faria, Hugo Barbosa, Maria Araujo Veloso, Bruno Marcondes, Francisco S. Lima, Celso Durães, Dalila Novais, Paulo |
Palavras-chave: | Educational data mining Motivational assistant Predict at-risk students Student's performance |
Data: | 2022 |
Editora: | Springer |
Revista: | Lecture Notes in Computer Science |
Citação: | Faria, H. et al. (2022). EduBot: A Proof-of-Concept for a High School Motivational Agent. In: Yin, H., Camacho, D., Tino, P. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2022. IDEAL 2022. Lecture Notes in Computer Science, vol 13756. Springer, Cham. https://doi.org/10.1007/978-3-031-21753-1_22 |
Resumo(s): | Motivation appears to plays a role in student dropout. This paper uses a dataset with high school information (756 entries) for creating a model that relates year failures with the other features on the dataset. The resulting model, based on XGBoost, shows that the top-ranked features are related with motivation issues corroborating with the initial observation. In this sense, a digital assistant embedded with a motivation module may aid on improving motivation and on avoiding dropout. In other words, if the predictor detects year failure possibility it start to act on motivating the student. Considering this paper being direct to underage students, this paper stops on the proof-of-concept level considering the actual dialogues and live tests are expected to performed with the support of educational psychologists. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/86321 |
ISBN: | 978-3-031-21752-4 |
e-ISBN: | 978-3-031-21753-1 |
DOI: | 10.1007/978-3-031-21753-1_22 |
ISSN: | 0302-9743 |
Versão da editora: | https://link.springer.com/chapter/10.1007/978-3-031-21753-1_22 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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IDEAL_2022_paper_5308.pdf Acesso restrito! | 429,19 kB | Adobe PDF | Ver/Abrir |