Implicaciones técnicas y prácticas de las Redes Adversarias Generativas a la Ciencia Abierta en Educación

  1. Bethencourt-Aguilar, Anabel 1
  2. Castellanos-Nieves, Dagoberto 1
  3. Sosa-Alonso, Juan José 1
  4. Area-Moreira, Manuel 1
  1. 1 Universidad de La Laguna
    info

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

Journal:
Revista Interuniversitaria de Investigación en Tecnología Educativa

ISSN: 2529-9638

Year of publication: 2022

Issue Title: Metodologías aplicadas a la Tecnología Educativa

Issue: 13

Pages: 138-156

Type: Article

DOI: 10.6018/RIITE.545881 DIALNET GOOGLE SCHOLAR lock_openDIGITUM editor

More publications in: Revista Interuniversitaria de Investigación en Tecnología Educativa

Abstract

Generative Adversarial Networks (GANs), which are characteristic of Artificial Intelligence, allow the creation of synthetic anonymised data useful for Open Science in educational research. This study experiments with the creation of artificial data from a dataset obtained from a survey on levels of use of digital tools and frequency of personal activities with technology. The original data belong to a sample of students from postgraduate degrees at the University of La Laguna. The results show an adequate degree of similarity between the original data set and the set artificially created through predictive algorithms. Obtaining synthetic datasets equivalent to the original ones in structure, shape and extension allows the release of the data to the academic community, safeguarding the protection of confidential information and contrasting a technique that allows the promotion of Open Science from the collection and processing of the data. Generative Adversarial Networks can be used in educational research for the purpose of transparency in methodological and technical procedures and the dissemination of datasets for academic, research and educational purposes.

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