Prediction of Middle School Students' Recycling Behaviors with Machine Learning Algorithms
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| Názov: | Prediction of Middle School Students' Recycling Behaviors with Machine Learning Algorithms |
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| Jazyk: | English |
| Autori: | Fatma Merve Mustafaoglu (ORCID |
| Zdroj: | Science Education International. 2025 36(2):209-218. |
| Dostupnosť: | International Council of Associations for Science Education. Dokuz Eylul University Faculty of Education, Buca, Izmir 35150, Turkey. Tel: +90-532-4267927; Fax: +90-232-4204895; Web site: http://www.icaseonline.net/seiweb/ |
| Peer Reviewed: | Y |
| Počet strán: | 10 |
| Dátum vydania: | 2025 |
| Druh dokumentu: | Journal Articles Reports - Research |
| Education Level: | Junior High Schools Middle Schools Secondary Education |
| Descriptors: | Middle School Students, Recycling, Student Behavior, Artificial Intelligence, Algorithms, Foreign Countries, Prediction, Conservation (Environment) |
| Geografický termín: | Turkey |
| ISSN: | 1450-104X 2077-2327 |
| Abstrakt: | Recycling waste is essential to mitigate environmental damage caused by human activity. Environmentally responsible behaviors, shaped during early ages, are closely linked to environmental attitudes, as demonstrated by prior research. This study aims to predict middle school students' recycling behaviors using machine learning algorithms. A correlational survey model was employed, involving 574 middle school students in Turkey. Data were collected using the Environmental Attitude Scale, Recycling Knowledge Test, and Plastics Recycling Information Test. Logistic regression analysis was conducted to determine relationships among environmental behavior, environmental emotion, plastics recycling knowledge, and recycling behavior. Results revealed that recycling behavior is positively and significantly predicted by plastics recycling information, environmental behavior, and negatively significant relationship with environmental emotion. These variables emerged as strong and reliable predictors of students' recycling behaviors. This study highlights the importance of fostering environmental knowledge and emotional engagement to encourage responsible recycling practices among young learners. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Prístupové číslo: | EJ1478496 |
| Databáza: | ERIC |
| Abstrakt: | Recycling waste is essential to mitigate environmental damage caused by human activity. Environmentally responsible behaviors, shaped during early ages, are closely linked to environmental attitudes, as demonstrated by prior research. This study aims to predict middle school students' recycling behaviors using machine learning algorithms. A correlational survey model was employed, involving 574 middle school students in Turkey. Data were collected using the Environmental Attitude Scale, Recycling Knowledge Test, and Plastics Recycling Information Test. Logistic regression analysis was conducted to determine relationships among environmental behavior, environmental emotion, plastics recycling knowledge, and recycling behavior. Results revealed that recycling behavior is positively and significantly predicted by plastics recycling information, environmental behavior, and negatively significant relationship with environmental emotion. These variables emerged as strong and reliable predictors of students' recycling behaviors. This study highlights the importance of fostering environmental knowledge and emotional engagement to encourage responsible recycling practices among young learners. |
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| ISSN: | 1450-104X 2077-2327 |