Topics and trends in physics teaching using artificial intelligence
This study investigates the application of machine learning, specifically using the Latent Dirichlet Allocation algorithm, to identify topics and trends in academic journals on Physics education in the Latin America context. The journals analyzed were the Revista Brasileira de Ensino de Física (RBEF...
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Asociación de Profesores de Física de la Argentina
2023
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| Acceso en línea: | https://revistas.unc.edu.ar/index.php/revistaEF/article/view/43304 |
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I10-R316-article-433042023-12-01T15:10:35Z Topics and trends in physics teaching using artificial intelligence Tópicos e tendências no ensino de física utilizando inteligência artificial Ghuron, Erick Trugillo Martins Fontes, Daniel Machado Rodrigues, André Machine learning Information and communication technology Quantitative analysis Literature review Aprendizado de máquina Tecnologia da informação e comunicação Análise quantitativa Revisão bibliográfica This study investigates the application of machine learning, specifically using the Latent Dirichlet Allocation algorithm, to identify topics and trends in academic journals on Physics education in the Latin America context. The journals analyzed were the Revista Brasileira de Ensino de Física (RBEF) and the Revista de Enseñanza de la Física (REF), covering the period from 2001 to 2022. A total of 1664 articles from RBEF and 885 from REF were collected, representing 79% and 85% of the articles published in these periods, respectively. The results indicated dominant topics in each journal and their respective trends over time. For instance, RBEF showed a decline in topics related to Physics Education and an increase in publications on General Physics. In contrast, REF displayed a predominance of topics related to Teaching, with a significant rise in publications about Virtual Laboratory and Teaching. These findings provide valuable insights into the evolution of research themes in Physics education in the Brazilian and Argentine contexts and the potential of using machine learning in Physics education research. Este trabalho investiga a aplicação do aprendizado de máquina, particularmente utilizando o algoritmo Latent Dirichlet Allocation, para identificar tópicos e tendências em revistas acadêmicas de ensino de Física no contexto latino-americano. As revistas analisadas foram a Revista Brasileira de Ensino de Física (RBEF) e a Revista de Enseñanza de la Física (REF), abrangendo o período de 2001 a 2022. Foram coletados 1664 artigos da RBEF e 885 da REF, representando 79% e 85% dos artigos publicados nesses períodos, respectivamente. Os resultados indicaram tópicos dominantes em cada revista e suas respectivas tendências ao longo do tempo. Enquanto a RBEF mostrou um declínio em tópicos relacionados à Educação e um aumento nas publicações sobre Física Geral, a REF apresentou uma predominância de tópicos relacionados à Educação, com um aumento significativo em publicações sobre Laboratório Virtual e Ensino. Estas descobertas proporcionam informações valiosas sobre a evolução dos temas de pesquisa em ensino de Física nos contextos brasileiro e argentino e quais são as potencialidades de se utilizar o aprendizado de máquina em pesquisas de ensino de Física. Asociación de Profesores de Física de la Argentina 2023-12-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unc.edu.ar/index.php/revistaEF/article/view/43304 Journal of Physics Teaching; Vol. 35: Número Extra: Selección de Trabajos presentados a REF; 167-173 Revista de Enseñanza de la Física; Vol. 35: Número Extra: Selección de Trabajos presentados a REF; 167-173 Revista de Enseñanza de la Física; v. 35: Número Extra: Selección de Trabajos presentados a REF; 167-173 2250-6101 0326-7091 spa https://revistas.unc.edu.ar/index.php/revistaEF/article/view/43304/43247 http://creativecommons.org/licenses/by-nc-nd/4.0 |
| institution |
Universidad Nacional de Córdoba |
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I-10 |
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R-316 |
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Revista de Enseñanza de la Física |
| language |
Español |
| format |
Artículo revista |
| topic |
Machine learning Information and communication technology Quantitative analysis Literature review Aprendizado de máquina Tecnologia da informação e comunicação Análise quantitativa Revisão bibliográfica |
| spellingShingle |
Machine learning Information and communication technology Quantitative analysis Literature review Aprendizado de máquina Tecnologia da informação e comunicação Análise quantitativa Revisão bibliográfica Ghuron, Erick Trugillo Martins Fontes, Daniel Machado Rodrigues, André Topics and trends in physics teaching using artificial intelligence |
| topic_facet |
Machine learning Information and communication technology Quantitative analysis Literature review Aprendizado de máquina Tecnologia da informação e comunicação Análise quantitativa Revisão bibliográfica |
| author |
Ghuron, Erick Trugillo Martins Fontes, Daniel Machado Rodrigues, André |
| author_facet |
Ghuron, Erick Trugillo Martins Fontes, Daniel Machado Rodrigues, André |
| author_sort |
Ghuron, Erick |
| title |
Topics and trends in physics teaching using artificial intelligence |
| title_short |
Topics and trends in physics teaching using artificial intelligence |
| title_full |
Topics and trends in physics teaching using artificial intelligence |
| title_fullStr |
Topics and trends in physics teaching using artificial intelligence |
| title_full_unstemmed |
Topics and trends in physics teaching using artificial intelligence |
| title_sort |
topics and trends in physics teaching using artificial intelligence |
| description |
This study investigates the application of machine learning, specifically using the Latent Dirichlet Allocation algorithm, to identify topics and trends in academic journals on Physics education in the Latin America context. The journals analyzed were the Revista Brasileira de Ensino de Física (RBEF) and the Revista de Enseñanza de la Física (REF), covering the period from 2001 to 2022. A total of 1664 articles from RBEF and 885 from REF were collected, representing 79% and 85% of the articles published in these periods, respectively. The results indicated dominant topics in each journal and their respective trends over time. For instance, RBEF showed a decline in topics related to Physics Education and an increase in publications on General Physics. In contrast, REF displayed a predominance of topics related to Teaching, with a significant rise in publications about Virtual Laboratory and Teaching. These findings provide valuable insights into the evolution of research themes in Physics education in the Brazilian and Argentine contexts and the potential of using machine learning in Physics education research. |
| publisher |
Asociación de Profesores de Física de la Argentina |
| publishDate |
2023 |
| url |
https://revistas.unc.edu.ar/index.php/revistaEF/article/view/43304 |
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