Guidelines for the Application of Data Mining to the Problem of School Dropout

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.creatorde Carvalho, Veronica Oliveira-
Autor(es): dc.creatorPenteado, Bruno Elias-
Autor(es): dc.creatorde Sousa, Leandro Rondado-
Autor(es): dc.creatorAffonso, Frank José-
Data de aceite: dc.date.accessioned2025-08-21T21:40:51Z-
Data de disponibilização: dc.date.available2025-08-21T21:40:51Z-
Data de envio: dc.date.issued2023-03-02-
Data de envio: dc.date.issued2023-03-02-
Data de envio: dc.date.issued2021-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-031-14756-2_4-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/242213-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/242213-
Descrição: dc.descriptionDropout is a complex phenomenon based on interrelated factors such as personal, institutional, structural, sociocultural, among other ones. It represents a waste of resources for students, their families, schools and society, and continues to be a challenge for educational institutions. In the last decade, the growing amount of data from educational institutions and the emergence of data science have led to data mining methodologies to explore this problem empirically. In this work, we map the literature on how data mining has been addressed face-to-face dropout. We synthesize different aspects, all of them related to steps of a generic data mining process. Our findings reveal a low level of formalism in theories, methodologies and pre-processing steps, with most papers making comparisons of different algorithms and features on the data available in the institution’s information system. Finally, we present some guidelines that can be used to improve the research on this topic.-
Descrição: dc.descriptionInstituto de Geociências e Ciências Exatas Universidade Estadual Paulista (Unesp)-
Descrição: dc.descriptionInstituto de Ciências Matemáticas e de Computação Universidade de São Paulo (USP)-
Descrição: dc.descriptionInstituto de Geociências e Ciências Exatas Universidade Estadual Paulista (Unesp)-
Formato: dc.format55-72-
Idioma: dc.languageen-
Relação: dc.relationCommunications in Computer and Information Science-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectData mining-
Palavras-chave: dc.subjectRevisited-
Palavras-chave: dc.subjectSchool dropout-
Palavras-chave: dc.subjectSystematic Literature Mapping-
Título: dc.titleGuidelines for the Application of Data Mining to the Problem of School Dropout-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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