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Tecnologias digitais e inteligência artificial na avaliação em disciplina de língua portuguesa
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Advisor(s)
Abstract(s)
Este trabalho aborda o emprego de tecnologias digitais e inteligência artificial (IA) na análise de dados avaliativos de uma disciplina de Língua Portuguesa em Instituições de Ensino Superior no Brasil. Apoiando-se em um referencial teórico que discute a evolução das práticas avaliativas, desde métodos tradicionais até abordagens mais contemporâneas que utilizam recursos tecnológicos, o estudo destaca a transição para avaliações mais formativas e personalizadas. Metodologicamente, a pesquisa adota uma abordagem quanti-qualitativa, analisando dados de avaliações e simulados realizados entre 2019 e 2023, referente ao período pré e pós-pandêmico de Covid-19. Utiliza-se de plataformas como Databricks e Microsoft Power BI para processar e analisar os dados sobre engajamento e desempenho dos alunos. Os resultados preliminares sugerem a eficácia dos simulados na avaliação da aprendizagem e tendência positiva no desempenho médio dos alunos na disciplina de Língua Portuguesa no período examinado, embora revelem a necessidade de estratégias pedagógicas renovadas para incentivar a participação dos estudantes e adaptar as práticas avaliativas às novas realidades educacionais.
This paper addresses the application of digital technologies and artificial intelligence (AI) in the analysis of evaluative data for a Portuguese Language course at Higher Education Institutions in Brazil. It is supported by a theoretical framework that discusses the evolution of evaluative practices, from traditional methods to more contemporary approaches that utilize technological resources, highlighting the transition towards more formative and personalized assessments. Methodologically, the research adopts a mixed-methods approach, analyzing data from evaluations and mock exams conducted between 2019 and 2023, covering the pre-and post-COVID-19 pandemic period. Platforms such as Databricks and Microsoft Power BI are utilized to process and analyze data on student engagement and performance. The preliminary results suggest the effectiveness of mock exams in assessing learning and a positive trend in the average performance of students in the Portuguese Language course during the examined period, although they reveal the need for renewed pedagogical strategies to encourage student participation and adapt evaluative practices to new educational realities
This paper addresses the application of digital technologies and artificial intelligence (AI) in the analysis of evaluative data for a Portuguese Language course at Higher Education Institutions in Brazil. It is supported by a theoretical framework that discusses the evolution of evaluative practices, from traditional methods to more contemporary approaches that utilize technological resources, highlighting the transition towards more formative and personalized assessments. Methodologically, the research adopts a mixed-methods approach, analyzing data from evaluations and mock exams conducted between 2019 and 2023, covering the pre-and post-COVID-19 pandemic period. Platforms such as Databricks and Microsoft Power BI are utilized to process and analyze data on student engagement and performance. The preliminary results suggest the effectiveness of mock exams in assessing learning and a positive trend in the average performance of students in the Portuguese Language course during the examined period, although they reveal the need for renewed pedagogical strategies to encourage student participation and adapt evaluative practices to new educational realities
Description
Keywords
Avaliação da aprendizagem Tecnologia digital Inteligência artificial Língua portuguesa Learning assessment Digital technology Artificial intelligence Portuguese language
Citation
Inacio, Caique Tardin; Saldanha, Luís Cláudio Dallier - Tecnologias digitais e inteligência artificial na avaliação em disciplina de língua portuguesa. "RE@D – Revista de Educação a Distância e eLearning" [Em linha]. ISSN 2182-4967. Vol. 7, nº 1 (jan.-junho 2024)
Publisher
Universidade Aberta. LE@D