Una aproximación del efecto en el aprendizaje de una lengua extranjera debida a la obtención de datos a través de exámenes en línea de idiomas

  1. Magal Royo, Teresa 1
  2. García Laborda, Jesús 2
  1. 1 Universidad Politécnica de Valencia
    info

    Universidad Politécnica de Valencia

    Valencia, España

    ROR https://ror.org/01460j859

  2. 2 Universidad de Alcalá
    info

    Universidad de Alcalá

    Alcalá de Henares, España

    ROR https://ror.org/04pmn0e78

Revista:
RED: revista de educación a distancia

ISSN: 1578-7680

Año de publicación: 2017

Número: 53

Tipo: Artículo

DOI: 10.6018/RED/53/6 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: RED: revista de educación a distancia

Resumen

La Inteligencia Artificial orientada a la educación (AIEd) permite adecuar y/o adaptar los itinerarios del aprendizaje de un usuario mediante procesos inductivos basados en la extracción de datos obtenidos de las evidencias formativas que genera a lo largo de su vida escolar. El Big data, o datos masivos es el almacenamiento de grandes cantidades de datos que pueden ser analizados por diversos procedimientos y que permite encontrar patrones repetitivos o formulas predictivas que pueden generar un aprendizaje sobre nosotros mismos y sobre todo en la red. En el caso de los datos masivos que se generan a través de los exámenes utilizados en el aprendizaje y certificación de conocimiento de idiomas como segunda lengua a nivel nacional encontramos que podría ser útil aplicar las metodologías de procesamiento del Big Data para conocer mejor si la información generada a través de los test pueden mejorar o crear nuevas estrategias de aprendizaje o establecer criterios formales en el diseño de las pruebas, teorías de adquisición de se segunda lengua o incluso políticas educativas. La novedad de artículo se centra en establecer directrices viables para aplicar los conceptos más genéricos del Big Data en el contexto específico de los test de evaluación de idiomas como segunda lengua y donde existe a priori una gran cantidad de información a procesar a nivel educativo. El artículo muestra algunas directrices que podrían aplicarse en los mecanismos aplicados en la extracción de datos educativos del aprendizaje de idiomas a gran escala en el entorno específico de los test de evaluación de idiomas como lengua extranjera

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Fuente de los datos: Dialnet