AUTHOR=Martínez-Ramón Juan Pedro , Morales-Rodríguez Francisco Manuel , Ruiz-Esteban Cecilia , Méndez Inmaculada 

TITLE=Self-Esteem at University: Proposal of an Artificial Neural Network Based on Resilience, Stress, and Sociodemographic Variables

JOURNAL=Frontiers in Psychology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.815853

DOI=10.3389/fpsyg.2022.815853

ISSN=1664-1078

ABSTRACT=Artificial intelligence is a useful predictive tool for a wide variety of fields of knowledge. Despite this, the educational field is still an environment that lacks a variety of studies that use this type of predictive tools. In parallel, it is postulated that the levels of self-esteem in the university environment may be related to the strategies implemented to solve problems. For these reasons, the aim of this study was to analyse the levels of self-esteem presented by teaching staff and students at university (N = 290, 73.1% female) and to design an algorithm capable of predicting these levels on the basis of their coping strategies, resilience, and socio-demographic variables. For this purpose, the Rosenberg Self-Esteem Scale, the Perceived Stress Scale (PSS) and the Brief Resilience Scale were administered. The results showed a relevant role of resilience and stress perceived in predicting participants' self-esteem levels. The findings highlight the usefulness of artificial neural networks for predicting psychological variables in education.