Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms
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 beha...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
ICASE
2025-06-01
|
| Series: | Science Education International |
| Subjects: | |
| Online Access: | https://www.icaseonline.net/journal/index.php/sei/article/view/1279 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849425054049239040 |
|---|---|
| author | Fatma Merve Mustafaoğlu Fatma Alkan |
| author_facet | Fatma Merve Mustafaoğlu Fatma Alkan |
| author_sort | Fatma Merve Mustafaoğlu |
| collection | DOAJ |
| description | 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 environmentalbehavior, 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. |
| format | Article |
| id | doaj-art-a572bc6a7dab4f6a8a7bfd2c4ce3ab71 |
| institution | Kabale University |
| issn | 2077-2327 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | ICASE |
| record_format | Article |
| series | Science Education International |
| spelling | doaj-art-a572bc6a7dab4f6a8a7bfd2c4ce3ab712025-08-20T03:29:53ZengICASEScience Education International2077-23272025-06-0136220921810.33828/sei.v36.i2.8Prediction of Middle School Students’ Recycling Behaviors with Machine Learning AlgorithmsFatma Merve Mustafaoğlu0https://orcid.org/0000-0001-7223-0794Fatma Alkan1https://orcid.org/0000-0003-2784-875XDepartment of Chemistry Education, Faculty of Education, Hacettepe University, Ankara, TurkeyDepartment of Chemistry Education, Faculty of Education, Hacettepe University, Ankara, TurkeyRecycling 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 environmentalbehavior, 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.https://www.icaseonline.net/journal/index.php/sei/article/view/1279environmental behaviorenvironmental emotionmachine learningmiddle school studentsrecycling behavior |
| spellingShingle | Fatma Merve Mustafaoğlu Fatma Alkan Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms Science Education International environmental behavior environmental emotion machine learning middle school students recycling behavior |
| title | Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms |
| title_full | Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms |
| title_fullStr | Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms |
| title_full_unstemmed | Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms |
| title_short | Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms |
| title_sort | prediction of middle school students recycling behaviors with machine learning algorithms |
| topic | environmental behavior environmental emotion machine learning middle school students recycling behavior |
| url | https://www.icaseonline.net/journal/index.php/sei/article/view/1279 |
| work_keys_str_mv | AT fatmamervemustafaoglu predictionofmiddleschoolstudentsrecyclingbehaviorswithmachinelearningalgorithms AT fatmaalkan predictionofmiddleschoolstudentsrecyclingbehaviorswithmachinelearningalgorithms |