Inferencia causal en investigación educativaAnálisis de la causalidad en estudios observacionales de carácter transversal

  1. Martínez-Abad, Fernando 1
  2. León, Jaime 2
  1. 1 Universidad de Salamanca, España
  2. 2 Universidad de Las Palmas de Gran Canaria
    info

    Universidad de Las Palmas de Gran Canaria

    Las Palmas de Gran Canaria, España

    ROR https://ror.org/01teme464

Revista:
Relieve: Revista ELectrónica de Investigación y EValuación Educativa

ISSN: 1134-4032

Año de publicación: 2023

Título del ejemplar: Integridad Académica en la Era de la Inteligencia Artificial Generativa- Academic integrity in the era of generative artificial intelligence (GAI)

Volumen: 29

Número: 2

Tipo: Artículo

DOI: 10.30827/RELIEVE.V29I2.26843 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Relieve: Revista ELectrónica de Investigación y EValuación Educativa

Objetivos de desarrollo sostenible

Resumen

La suposición de relaciones causa-efecto en la investigación ex post facto es un problema ampliamente conocido en el ámbito de la metodología de investigación en ciencias sociales. Para abordar esta importante limitación, en los últimos años se ha extendido el empleo de técnicas de inferencia causal, un conjunto de procedimientos estadísticos establecidos para poder extraer conclusiones causales en investigaciones no experimentales. A pesar de su amplia popularidad y difusión en el ámbito de las ciencias sociales y de la salud, su uso en investigación educativa es todavía marginal. Así, este trabajo introduce las principales técnicas de inferencia causal disponibles para el investigador educativo cuando dispone de datos observacionales de panel. Tras abordar las características clave y el potencial de las técnicas de emparejamiento por puntuación de propensión, variables instrumentales y diseño de regresión discontinua, se presenta un ejemplo de aplicación de cada una de ellas empleando las bases de datos obtenidas en la evaluación PISA 2018. Se incluye la competencia matemática como variable dependiente en todos los modelos propuestos. Dada las diferentes características de cada una de estas técnicas, la variable independiente empleada varía en los tres modelos aplicados: asistencia a educación infantil en el emparejamiento por puntuación de propensión, expectativas académicas del estudiante en variables instrumentales y tamaño del municipio en el que se encuentra la escuela en diseño de regresión discontinua. Se concluye el artículo discutiendo el potencial de este conjunto de técnicas, teniendo en cuenta las necesidades y procedimientos metodológicos más habitualmente aplicados en la investigación educativa.

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Fuente de los datos: Dialnet