Inteligência Artificial para Educação: Um Caminho para um Campo mais Inclusivo
DOI:
https://doi.org/10.5753/rbie.2023.3156Palavras-chave:
Análise de dados educacionais, equidade digital, offlineResumo
A área de Inteligência Artificial (IA) tem potencial para melhorar o ensino e a aprendizagem, por exemplo, por meio da análise de dados produzidos em ambientes educacionais. Além disso, também pode agravar a desigualdade, pois exige que alunos e instrutores tenham acesso à infraestrutura (smartphones ou computadores) exigida pela maioria dessas ferramentas para gerar e analisar dados. No entanto, o acesso a tal infraestrutura não é uma realidade para muitos estudantes ao redor do mundo. Para lançar luz sobre esse problema, este artigo investiga, por meio de um Estudo de Mapeamento Sistemático (MS), iniciativas que permitem uma análise de dados mais inclusiva usando IA na educação, especialmente em cenários com poucos recursos de conectividade. Identificamos que essas iniciativas são escassas e estão focadas na primeira fase da tarefa de análise de dados: a coleta de dados. Com base nos resultados do MS, propomos um conjunto de recomendações para os pesquisadores oferecerem direções para uma análise mais inclusiva de dados educacionais usando IA.
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Copyright (c) 2023 Elyda Laisa Soares Xavier Freitas, Ig Ibert Bittencourt, Seiji Isotani, Leonardo Marques, Diego Dermeval, Alan Silva, Rafael Ferreira Mello
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
