Detección del alumno en riesgo en titulaciones de Ciencias de la Saludaplicación de técnicas de Learning Analytics

  1. Saiz Manzanares, María Consuelo 1
  2. Marticorena Sánchez, Raúl 1
  3. Arnaiz González, Álvar 1
  4. Escolar Llamazares, María del Camino 1
  5. Queiruga Dios, Miguel Ángel 1
  1. 1 Universidad de Burgos
    info

    Universidad de Burgos

    Burgos, España

    ROR https://ror.org/049da5t36

Aldizkaria:
EJIHPE: European Journal of Investigation in Health, Psychology and Education

ISSN: 2174-8144,  2254-9625

Argitalpen urtea: 2018

Alea: 8

Zenbakia: 3

Orrialdeak: 129-142

Mota: Artikulua

DOI: 10.30552/EJIHPE.V8I3.273 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Beste argitalpen batzuk: EJIHPE: European Journal of Investigation in Health, Psychology and Education

Garapen Iraunkorreko Helburuak

Laburpena

The way of teaching and learning in twenty-first century society continues to change. At present, a high percentage of teaching takes place through Learning Management Systems that apply Learning Analytics Techniques. The use of these tools, among other things, facilitates knowledge of student learning patterns and the detection of at-risk students. The aim of this study is to establish the most effective learning patterns of the students on the platform in a hierarchical order of importance. It was conducted over two academic years with 122 students of Health Sciences. The instruments used were the Moodle v.3.1 platform and the analysis of logs with Machine Learning regression techniques. The results indicated that the Automatic Linear Prediction Model detected by order of importance: average visits per day, student self-assessment questionnaires, and teacher feedback. The percentage variance of the final results explained by these variables was 50.8%. Likewise, the effectiveness of the behavioral pattern explained 64.1% of the variance in those results, finding three clusters of effectiveness in the behavioral patterns that were detected.

€ Ikusi finantzaketa

Finantzaketari buruzko informazioa

A todos los participantes en este estudio, así como a las ayudas concedidas al GID de Universidad de Burgos B-Learning en Ciencias de la Salud: Vicerrectorado de Investigación y Transferencia del Conocimiento para la difusión de la investigación 2018 y Vicerrectorado de Personal Docente e Investigador 2018 de la Universidad de Burgos, a la difusión de los resultados de la innovación docente.

Finantzatzaile

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