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dc.contributor.authorSolano Sánchez, Miguel Ángel 
dc.contributor.authorDomínguez Valerio, Cándida María
dc.contributor.authorLendínez Turón, Ana
dc.contributor.authorAguilar Rivero, Minerva
dc.date.accessioned2022-02-09T12:22:01Z
dc.date.available2022-02-09T12:22:01Z
dc.date.issued2022-01-21
dc.identifier.citationSolano-Sánchez, M.Á.; Domínguez-Valerio, C.M.; Lendínez-Turón, A.; Aguilar-Rivero, M. Sustainable Economic Development Education: The Use of Artificial Neural Networks for the Profile Estimation of Students from Developing Countries. Sustainability 2022, 14, 1192. [https://doi.org/10.3390/su14031192]es_ES
dc.identifier.urihttp://hdl.handle.net/10481/72754
dc.descriptionThe study was carried out in line with the ethical recommendations proposed in previous research in the same field and observing the principles and recommendations of the Declaration of Helsinki.es_ES
dc.description.abstractEnvironmentally friendly behaviour and the equitable and sustainable use of natural resources can contribute to solving various environmental, economic, and social problems in different countries. The analysis of the perception of young students is important because schools are suitable for educating future generations and shaping their attitudes to also include a greater concern for the environment. This research aims to determine the degree of influence that a series of Likert-type questions of knowledge, attitudes, and behaviours about sustainable development has on a series of items of the student profile (gender, age, course, and household members) in a developing country. For this, an artificial neural network is used that allows us not only to quantify the degree of influence but also to obtain an estimation of the student’s profile according to the responses obtained on sustainable development. The network developed allows us to obtain, through a determined collection of answers to questions about sustainable development, the estimation of a specific profile of a student from a developing country. This can be useful to educational communities interested in optimising economic resources through sustainable development, allowing them to know which issues they should focus more (or less) on according to the profile of the student they are targetinges_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectSustainabilityes_ES
dc.subjectSustainable development es_ES
dc.subjectSustainable economyes_ES
dc.subjectEconomic resourceses_ES
dc.subjectEducation es_ES
dc.subjectDeveloping countries es_ES
dc.subjectStudents es_ES
dc.subjectMultilayer perceptrones_ES
dc.subjectArtificial neural networkses_ES
dc.titleSustainable Economic Development Education: The Use of Artificial Neural Networks for the Profile Estimation of Students from Developing Countrieses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.3390/su14031192
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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Atribución 3.0 España
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