Discovering learning processes using Inductive MinerA case study with Learning Management Systems (LMSs)

  1. Alejandro Bogarín 1
  2. Rebeca Cerezo 2
  3. Cristóbal Romero 1
  1. 1 Universidad de Córdoba
    info

    Universidad de Córdoba

    Córdoba, España

    ROR https://ror.org/05yc77b46

  2. 2 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

Revista:
Psicothema

ISSN: 0214-9915

Año de publicación: 2018

Volumen: 30

Número: 3

Páginas: 322-329

Tipo: Artículo

DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Psicothema

Resumen

Antecedentes: en la minería de procesos con datos educativos se utilizan diferentes algoritmos para descubrir modelos, sobremanera el Alpha Miner, el Heuristic Miner y el Evolutionary Tree Miner. En este trabajo proponemos la implementación de un nuevo algoritmo en datos educativos, el denominado Inductive Miner. Método: hemos utilizado datos de interacción de 101 estudiantes universitarios en una asignatura de grado desarrollada en la plataforma Moodle 2.0. Una vez prepocesados se ha realizado la minería de procesos sobre 21.629 eventos para descubrir los modelos que generan los diferentes algoritmos y comparar sus medidas de ajuste, precisión, simplicidad y generalización. Resultados: en las pruebas realizadas en nuestro conjunto de datos el algoritmo Inductive Miner es el que obtiene mejores resultados, especialmente para el valor de ajuste, criterio de mayor relevancia en lo que respecta al descubrimiento de modelos. Además, cuando ponderamos con pesos las diferentes métricas seguimos obteniendo la mejor medida general con el Inductive Miner. Conclusiones: la implementación de Inductive Miner en datos educativos es una nueva aplicación que, además de obtener mejores resultados que otros algoritmos con nuestro conjunto de datos, proporciona modelos válidos e interpretables en términos educativos

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Información de financiación

Authors gratefully acknowledge the financial subsidy provided by Spanish Ministry of Science and Technology TIN2017-83445-P and EDU2014-57571-P. We have also received funds from the European Union and the Principality of Asturias, through its Science, Technology and Innovation Plan (grant GRUPIN14-053).

Financiadores

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Fuente de los datos: Dialnet