Sustainable environmental education: Some machine learning algorithms in the classification of sustainable environmental attitudes

Semra Benzer, Farid Hassanbaki Garabaghi, Recep Benzer and Hicret Çimen Güni

Evaluation and Program Planning, 2025, vol. 112, issue C

Abstract: Since the industrial revolution, human beings has shown a great unconscientiousness about the sustainable environment by polluting the air, water, and soil and rapidly consuming natural resources. Therefore, in the name of sustainable development, sustainable environmental education has become the center of attention of governments and consequently raising individuals with the necessary attitudes, values, understanding and skills in sustainable environment has become an important mission. This study was designed to firstly evaluate the students’ attitude towards a sustainable environment and secondly classify the target students based on their attitudes towards sustainable environment using machine learning methods based on a weighted score system based on a 5-point Likert type. The SVM-SMO classifier demonstrated superior performance compared to MLPNN, RBF Network, and Logistic Regression, especially when the training data was limited.

Keywords: Education; Sustainable environment; Classification; Machine learning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:epplan:v:112:y:2025:i:c:s0149718925001193

DOI: 10.1016/j.evalprogplan.2025.102652

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