Zambrano, Jonathan Fernando Torres
Mikarimin. Revista Cient́ıfica Multidisciplinaria
Artículo de revista
Detalle de Publicación
Artículo de revista
Teaching Strategies Against Artificial Intelligence in the Learning of 21st Century Students
María Margoth Bonilla Jiménez; Ibsen Daniel Maldonado Ríos; Angélica María Sánchez Bonilla; María Rodríguez Gámez
Journal of Law and Sustainable Development
2023
Vol. 11, No. 9, pp. e1635
1 citaciones
Acceso abierto
Resumen
Objective: Analyze pedagogical strategies regarding artificial intelligence.
Methods: A documentary exploration was used with the use of the PRISMA model, 33 documents were studied.
Results: The results indicated that the variable, teaching strategies, must have characteristics such as innovation, flexibility, criticism, prospective and guiding level, which allows facing the interference of artificial intelligence that has levels of understanding and versatility with applications. and uses.
Conclusions: Students can use Artificial Intelligence appropriately to develop their knowledge, considering that its trend will increase, and teachers must adapt to the new technological reality.
Methods: A documentary exploration was used with the use of the PRISMA model, 33 documents were studied.
Results: The results indicated that the variable, teaching strategies, must have characteristics such as innovation, flexibility, criticism, prospective and guiding level, which allows facing the interference of artificial intelligence that has levels of understanding and versatility with applications. and uses.
Conclusions: Students can use Artificial Intelligence appropriately to develop their knowledge, considering that its trend will increase, and teachers must adapt to the new technological reality.
Investigadores
Citar esta publicación
María Margoth Bonilla Jiménez; Ibsen Daniel Maldonado Ríos; Angélica María Sánchez Bonilla; María Rodríguez Gámez (2023). Teaching Strategies Against Artificial Intelligence in the Learning of 21st Century Students. Journal of Law and Sustainable Development, 11(9), e1635. https://doi.org/10.55908/sdgs.v11i9.1635