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http://repositorio.ufc.br/handle/riufc/73300
Tipo: | Artigo de Periódico |
Título : | Correlation analysis using teaching and learning analytics |
Autor : | Prestes, Pedro Alexandre Nery Silva, Thomaz Edson Veloso da Barroso, Giovanni Cordeiro |
Palabras clave : | Learning analytics;Teaching and learning analytics;Correlation;Educational data mining;Análise de aprendizagem;Análise de ensino e aprendizagem;Correlação;Mineração de dados educacionais |
Fecha de publicación : | 2021 |
Editorial : | Heliyon |
Citación : | PRESTES, Pedro Alexandre Nery; SILVA, Thomaz Edson Veloso da; BARROSO, Giovanni Cordeiro. Correlation analysis using teaching and learning analytics. Heliyon, [S.L], v. 7, n. 11, p. e08435, 2021. |
Abstract: | Data analytics techniques have been gaining more space in the scientific environment with applications in various areas of knowledge, including education. This paper aims to analyse data taken from a questionnaire of the Organization for Economic Development Cooperation (OECD) given to teachers and school managers. In this questionnaire, school environment issues are assessed, specifically: school environment, professional development, school leadership, and efficient management. As a methodology, Teaching and Learning Analytics (TLA) was used, particularly correlation analysis, which enables the extraction of useful information from raw data, relating issues that interfere with the teaching and learning relationship, besides specific analysis of student learning. The results obtained about the school environment are not linear. They do not present moderate or a solid linear correlation, making it impossible to validate and integrate answers related to the statements of the themes and sub-themes chosen for this analysis. In this sense, the research found dichotomous observations that mirrored many controversies and insecurities, enabling considerations about possible school scenarios and their effective practices. |
URI : | http://www.repositorio.ufc.br/handle/riufc/73300 |
ISSN : | 2405-8440 |
Derechos de acceso: | Acesso Aberto |
Aparece en las colecciones: | DEEL - Artigos publicados em revista científica |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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2021_art_panprestes.pdf | 2,17 MB | Adobe PDF | Visualizar/Abrir |
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