Detalhes bibliográficos
| Ano de defesa: |
2019 |
| Autor(a) principal: |
Santos, Anderson Anzai dos
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| Orientador(a): |
Coutinho, Cileda de Queiroz e Silva |
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Pontifícia Universidade Católica de São Paulo
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| Programa de Pós-Graduação: |
Programa de Estudos Pós-Graduados em Educação Matemática
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| Departamento: |
Faculdade de Ciências Exatas e Tecnologia
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| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
https://tede2.pucsp.br/handle/handle/22764
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Resumo: |
Statistical Literacy is characterized by the ability of reading, understanding, interpreting, analyzing, evaluating and discussing statistical content correctly. Therefore, we believe that the construction of this literacy must be formed in the student’s life from the beginning of his schooling. However, studies indicate that this training is not enough and is even worse during university stage. In this qualitative research, we expect to investigate the current situation of Intro to Descriptive Statistics major in undergraduate courses, being one of them in Exact Sciences field (Mathematics Degree) and two in Biology field (Nursing and Medicine) at the Federal University of Rio de Janeiro State (UNIRIO). The search was conducted in June 2018. We were based on theoretical foundation of levels of conceptualization of knowledge structuring by students in order to apply activities with support of the statistical software R and investigate whether the learning of Descriptive Statistics contents, using R Commander package, becomes more significant and contributes to the construction of statistical literacy in university students as well as whether the student's vocational training contextualization of statistics strengthens the construction of statistical literacy, basing it on the construction of superior criticality in the use of data and on the possible articulation in their daily life and constitution as an individual. Regarding the methodological procedures, Didactic Engineering assumptions were used as methodological procedures, such as preliminary studies, a priori analysis, experimentation, a posteriori analysis and validation, and, during the accomplishment of the activities, we identified that the students did not have problems in manipulating the software, however they had difficulty in approaching the statistical metrics, in its interpretation, as well as in relating them to the graphics. Many students demonstrated to have only the technical level of their knowledge and difficulties to exceed the most elementary levels in their Statistical literacy |
