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

Authors :
Martínez-Ramón, Juan Pedro
Morales-Rodríguez, Francisco Manuel
Ruiz-Esteban, Cecilia
Méndez, Inmaculada
Source :
Frontiers in Psychology; 2/28/2022, Vol. 13, p1-9, 9p
Publication Year :
2022

Abstract

Artificial intelligence (AI) 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 analyze 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 sociodemographic variables. For this purpose, the Rosenberg Self-Esteem Scale (RSES), 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16641078
Volume :
13
Database :
Complementary Index
Journal :
Frontiers in Psychology
Publication Type :
Academic Journal
Accession number :
155489373
Full Text :
https://doi.org/10.3389/fpsyg.2022.815853