Self-Esteem at University: Proposal of an Artificial Neural Network Based on Resilience, Stress, and Sociodemographic Variables Martínez Ramón, Juan Pedro Morales Rodríguez, Francisco Manuel Artificial neural network Educational psychology Professor Resilience Self-esteem Stress University student Artificial intelligence Inteligencia artificial 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. 2022-11-17T09:43:48Z 2022-11-17T09:43:48Z 2022-02-28 info:eu-repo/semantics/article Martínez-Ramón JP... [et al.] (2022) Self-Esteem at University: Proposal of an Artificial Neural Network Based on Resilience, Stress, and Sociodemographic Variables. Front. Psychol. 13:815853. doi: [10.3389/fpsyg.2022.815853] https://hdl.handle.net/10481/78013 10.3389/fpsyg.2022.815853 eng http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional Frontiers