环境教育作为打击日益严重的环境污染的一种手段:一种优化可解释的人工智能 (XAI) 方法
Osama Abduljalil Mohammad Hamad1, Engin Baysen1, Abdullahi Garba Usman2,3
1Department of Science Education, Near East University, via Mersin 10, 2087, Nicosia, North Cyprus, Turkey.
Scientific reports
|March 9, 2026
概括
环境教育显著影响学生对污染原因和解决方案的知识. 这项研究强调了它在缓解利比亚环境挑战方面的作用,为政策和专家战略提供了信息.
科学领域:
- 环境科学 环境科学
- 教育教育教育教育教育教育.
背景情况:
- 环境污染和辐射暴露构成了由自然和人类活动驱动的重大威胁.
- 利比亚的大学正在探索教育策略,以应对这些环境挑战.
研究的目的:
- 评估环境教育对学生关于环境污染的知识,关注,意愿和行为的影响.
- 了解教育干预如何有助于减轻污染和辐射暴露.
主要方法:
- 一个涉及利比亚两所大学402名环境科学和教育学生的案例研究.
- 一个调查问卷评估社会人口统计,知识,关注,意愿和行为.
- 可解释的人工智能 (AI) 模型,特别是GPR-BO-M2,用于分析独立变量对环境知识的影响.
主要成果:
- 82.2%的学生表现出对主要环境污染问题的了解.
- 45%的人对污染的主要原因有很高的知识 (分数9-10).
- 72.2%的受访者表示,他们了解主要的污染解决方案.
- GPR-BO-M2人工智能模型实现了高性能,R2值为0.951/0.937,表明了强大的预测准确性.
结论:
- 环境教育积极影响学生对污染的理解.
- 这些发现为学生,教育工作者,政策制定者和专家提供了宝贵的见解,帮助他们制定减轻环境污染的战略.
- 人工智能建模有效量化了教育变量对环境意识的影响.
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