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CORRECTION article

Front. Educ., 07 March 2023
Sec. Assessment, Testing and Applied Measurement
Volume 8 - 2023 | https://doi.org/10.3389/feduc.2023.1171995

Corrigendum: Artificial neural network model to predict student performance using nonpersonal information

This article is a correction to:

  1. Artificial neural network model to predict student performance using nonpersonal information

    1. Read original article
\nHeyul Chavez,Heyul Chavez1,2Bill Chavez-AriasBill Chavez-Arias3Sebastian Contreras-RosasSebastian Contreras-Rosas3Jose María Alvarez-RodríguezJose María Alvarez-Rodríguez4Carlos Raymundo Carlos Raymundo5*
  • 1Telecommunications and Networking Engineering, Universidad Peruana de Ciencias Aplicadas, Lima, Peru
  • 2The International Doctoral School, Universidad Rey Juan Carlos, Madrid, Spain
  • 3Computer Sciences School, Universidad Peruana de Ciencias Aplicadas, Lima, Peru
  • 4Department of Computer Science and Engineering, Universidad Carlos III, Madrid, Spain
  • 5Research Department, Universidad Peruana de Ciencias Aplicadas, Lima, Peru

A corrigendum on
Artificial neural network model to predict student performance using nonpersonal information

by Chavez, H., Chavez-Arias, B., Contreras-Rosas, S., Alvarez-Rodríguez, J. M., and Raymundo, C. (2023). Front. Educ. 8:1106679. doi: 10.3389/feduc.2023.1106679

In the published article, the Acknowledgment Statement was mistakenly not included in the publication. The missing statement appears below:

Acknowledgments

“The authors would like to thank the Research Directorate of the Universidad Peruana de Ciencias Aplicadas for the support provided to carry out this research work through the UPC-EXPOST-2023-1 incentive.”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: privacy, personal data, neural networks, forecasting, academic performance

Citation: Chavez H, Chavez-Arias B, Contreras-Rosas S, Alvarez-Rodríguez JM and Raymundo C (2023) Corrigendum: Artificial neural network model to predict student performance using nonpersonal information. Front. Educ. 8:1171995. doi: 10.3389/feduc.2023.1171995

Received: 22 February 2023; Accepted: 23 February 2023;
Published: 07 March 2023.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2023 Chavez, Chavez-Arias, Contreras-Rosas, Alvarez-Rodríguez and Raymundo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Carlos Raymundo, Y2FybG9zLnJheW11bmRvJiN4MDAwNDA7dXBjLmVkdS5wZQ==

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.