Sustainable Economic Development Education: The Use of Artificial Neural Networks for the Profile Estimation of Students from Developing Countries

Miguel Ángel Solano-Sánchez, Cándida María Domínguez-Valerio, Ana Lendínez-Turón and Minerva Aguilar-Rivero
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Miguel Ángel Solano-Sánchez: Department of Applied Economics, Faculty of Social Sciences (Melilla Campus), University of Granada, 52005 Melilla, Spain
Cándida María Domínguez-Valerio: Department of Business Administration, Faculty of Economics and Social Sciences, Universidad Tecnológica de Santiago, UTESA, Santiago de los Caballeros 51000, Dominican Republic
Ana Lendínez-Turón: Department of Developmental and Educational Psychology, Faculty of Education and Sports Sciences (Melilla Campus), University of Granada, 52005 Melilla, Spain
Minerva Aguilar-Rivero: Department of Applied Economics, Faculty of Labour Sciences, University of Córdoba, 14001 Córdoba, Spain

Sustainability, 2022, vol. 14, issue 3, 1-14

Abstract: Environmentally 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 targeting.

Keywords: sustainability; sustainable development; sustainable economy; economic resources; education; developing countries; students; multilayer perceptron; artificial neural networks (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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