Aprendizaje de idiomas usando Machine Learning: una revisión sistemática
DOI:
https://doi.org/10.17162/au.v12i4.1249Palavras-chave:
proceso de aprendizaje de idiomas, educación tecnológica, machine learning, adquisición de idiomas, recuperación inteligente, sistemas expertos.Resumo
El aprendizaje de idiomas mediante uso de Machine Learning (ML) ha tomado significancia, empleando técnicas y algoritmos con la capacidad de resolver traducción de texto, audio e imágenes. En ese contexto, el objetivo de la investigación es determinar los avances a nivel mundial acerca del aprendizaje de idiomas usando ML con la finalidad de apoyar y animar a los investigadores a emprender nuevas investigaciones experimentales al respecto. La cantidad de investigaciones del aprendizaje de idiomas y ML requiere una revisión sistemática de la literatura, limitando los años de revisión entre el 2016 y el 2021. Las fuentes consultadas son: Taylor & Francis, IEEE Xplore, ACM Digital Library, ScienceDirect, ProQuest, ARDI y ERIC. Los estudios encontrados inicialmente fueron de 55237, luego de aplicar rigurosos criterios de exclusión se obtuvieron 82 artículos. Los resultados de la revisión concluyen que la técnica más utilizada para el aprendizaje de idiomas mediante ML es Support Vector Machine (SVM), seguido de K-means (K-M) y la forma en que han evolucionado los conceptos tienden a la automatización del aprendizaje. La revisión ofrece un acercamiento a las tendencias en el aprendizaje de idiomas con ML, además que las keywords que presentan más coocurrencia en las investigaciones son “machine learning”, “natural lenguaje processing” y “machine translation”.Downloads
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