NDLI: Detecção de Estilos de Aprendizagem em Ambientes Virtuais de Aprendizagem utilizando Redes Bayesianas

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Detecção de Estilos de Aprendizagem em Ambientes Virtuais de Aprendizagem utilizando Redes Bayesianas

Content Provider	Semantic Scholar
Author	Salazar, Luiz Henrique A. Assis, Luciana Vivas, Alessandro Pitangui, Cristiano Falci, Samuel
Copyright Year	2017
Abstract	The Information and Communication Technologies (ICTs) and the Internet have created a scenario that offers a dynamic and autonomous learning environment, enabling models of education such as Distance Education. The present work presents a proposal of automatic detection of Student Learning Style using Bayesian Networks techniques, to create favorable conditions of adaptability in Virtual Learning Environments, characterizing an Intelligent Adaptive Tutoring System. This approach presents satisfactory results compared to one of the methods presented in the literature. Resumo. As Tecnologias da Informação e Comunicação (TICs) e a Internet criaram um cenário que oferece um ambiente de aprendizagem dinâmico e autônomo, possibilitando modelos de educação como a Educação a Distância. O presente trabalho apresenta uma proposta de detecção automática do Estilo de Aprendizagem do Estudante utilizando técnicas de Redes Bayesianas, para criar condições favoráveis de adaptatividade em Ambientes Virtuais de Aprendizagem, caracterizando um Sistema de Tutoria Inteligente Adaptativo. Tal abordagem apresenta resultados satisfatórios comparados a um dos métodos apresentados pela literatura.
Starting Page	1317
Ending Page	1317
Page Count	1
File Format	PDF HTM / HTML
DOI	10.5753/cbie.sbie.2017.1317
Alternate Webpage(s)	http://br-ie.org/pub/index.php/sbie/article/download/7660/5456
Alternate Webpage(s)	http://acervo.ufvjm.edu.br/jspui/bitstream/1/1629/1/luiz_filipe_carreiro_salazar.pdf
Alternate Webpage(s)	https://doi.org/10.5753/cbie.sbie.2017.1317
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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