Modelos de ensino e aprendizagem de ciência de dados : em foco a área da ciência da informação

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Autor(es): dc.creatorMartins, Dalton Lopes-
Data de aceite: dc.date.accessioned2022-08-15T13:42:13Z-
Data de disponibilização: dc.date.available2022-08-15T13:42:13Z-
Data de envio: dc.date.issued2022-06-07-
Data de envio: dc.date.issued2022-06-07-
Data de envio: dc.date.issued2021-
Fonte completa do material: dc.identifierhttps://repositorio.unb.br/handle/10482/43901-
Fonte completa do material: dc.identifierhttp://www.doi.org/10.47909/anis.978-9916-9760-3-6.100-
Fonte completa do material: dc.identifierhttps://orcid.org/0000-0002-6244-6791-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/714328-
Descrição: dc.descriptionThe Data Science field has become a focus of interest for teaching and research in the Information Science area in the last decade. However, due to the specificity of the area, there are still significant challenges when it comes to building curricula for undergraduate and graduate disciplines. What is observed is that students in the area have learning difficulties when taught by traditional approaches from the hard sciences. One of the most important international scientific journals in Information Science, the Journal of the American Society for Information Science and Technology (JASIST), opened a call for articles for a special issue of the journal with a focus on discussing the specificities of Data Science in its relations with Information Science. The call made available an extensive specialized bibliography on the subject. Nine works stand out in this research, directly indicative or referenced from the works indicated that are focused on the issue of teaching Data Science for the area. The analysis of the results points to a specific initiative to form a Data Science curriculum for the Information Science area, the School Data Science Curriculum Committee (iDSCC) initiative, and seven other curriculum models that could be adapted.-
Descrição: dc.descriptionThe Data Science field has become a focus of interest for teaching and research in the Information Science area in the last decade. However, due to the specificity of the area, there are still significant challenges when it comes to building curricula for undergraduate and graduate disciplines. What is observed is that students in the area have learning difficulties when taught by traditional approaches from the hard sciences. One of the most important international scientific journals in Information Science, the Journal of the American Society for Information Science and Technology (JASIST), opened a call for articles for a special issue of the journal with a focus on discussing the specificities of Data Science in its relations with Information Science. The call made available an extensive specialized bibliography on the subject. Nine works stand out in this research, directly indicative or referenced from the works indicated that are focused on the issue of teaching Data Science for the area. The analysis of the results points to a specific initiative to form a Data Science curriculum for the Information Science area, the School Data Science Curriculum Committee (iDSCC) initiative, and seven other curriculum models that could be adapted.-
Formato: dc.formatapplication/pdf-
Publicador: dc.publisherColNes Publishing-
Direitos: dc.rightsAcesso Aberto-
Direitos: dc.rights(CC BY NC)-
Palavras-chave: dc.subjectCiência de dados-
Palavras-chave: dc.subjectEnsino e aprendizagem-
Palavras-chave: dc.subjectCurrículos - modelos-
Título: dc.titleModelos de ensino e aprendizagem de ciência de dados : em foco a área da ciência da informação-
Título: dc.titleData science teaching and learning models : focus on the information science area-
Aparece nas coleções:Repositório Institucional – UNB

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