Detalhes bibliográficos
| Ano de defesa: |
2022 |
| Autor(a) principal: |
Gonsales, Priscila
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| Orientador(a): |
Kaufman, Dora
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| 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 Tecnologias da Inteligência e Design Digital
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| Departamento: |
Faculdade de Ciências Exatas e Tecnologia
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| País: |
Brasil
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| 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://repositorio.pucsp.br/jspui/handle/handle/26498
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Resumo: |
The advances in artificial intelligence (AI) applications based on data processing (Big Data) have brought a new context to digital culture or cyberculture. Increasingly present in our daily lives, AI is a technology that makes use of statistical probability models that work from correlations and identification of patterns in data. In education, AI has often been pointed out as a source for improving teaching from a merely utilitarian and tool viewpoint, that is, solely for the customization of the content transmission and monitoring/evaluation of apprehension of such content. However, AI has a multidimensional character, involving benefits and risks, as well as social, economic, legal, and environmental impacts that are practically unknown by educators and managers. This research highlights the need for a transdisciplinary vision for AI in education, as a field of knowledge and its various implications, based on Edgar Morin's complex thinking. A framework launched in 2020 by a group of researchers from the European Commission (BIDARRA et al., 2020) organizes in three aspects the interface between AI and education, highlighting the need to go beyond the use in content teaching: 1) learning with AI (study of AI applications aimed at teaching); 2) learning about AI (understanding the functioning of AI aimed at professional education for AI developers); 3) learning for AI (understanding the impacts of AI on society, ethical issues such as fake news, privacy, and security). Through the analysis of documents, publications and recent studies (2018-2021), the research addresses the urgency of institutional management policies, teacher training and educational governance that promote the reform of thinking for the reconnection of knowledge (MORIN, 2011b), considering principles of complexity such as dialogic, circularity, the "ecology of action" in order to promote an ecosystemic view of the current context of technology and, consequently, of a world in constant transformation |
