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