Evaluation of pro-environmental behavior in university students in Ecuador: Analysis with Machine Learning techniques
DOI:
https://doi.org/10.29076/issn.2528-7737vol18iss49.2025pp12-26pKeywords:
Environmental education, environmental attitudes, predictive models, data analysisAbstract
Pro-environmental behavior, vital for sustainability, is shaped by environmental education, particularly in biodiverse regions like Ecuador. Universities play a crucial role in fostering attitudes and practices addressing environmental challenges. This quantitative study used structured surveys and machine learning techniques to classify and analyze the pro-environmental behavior of 365 university students in Ecuador. Algorithms such as Random Forest and K-Means were employed for classification and clustering. Predictive models achieved an average accuracy of 89%. Three behavioral profiles were identified: low, medium, and high commitment. Environmental beliefs and biodiversity knowledge showed significant correlations with sustainable practices. Findings highlight the effectiveness of environmental education in promoting sustainable behaviors and the importance of tailored strategies according to student profiles. Incorporating these insights into academic programs is recommended to enhance youth environmental engagement
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