整合机器学习和色彩化学:向现实世界解决问题发展高中课程
Shiyan Jiang1, Jeanne McClure1, Hongjing Mao2
1Department of Teacher Education and Learning Sciences, North Carolina State University, 2310 Stinson Drive, Raleigh, NC, 27695, USA.
Journal of chemical education
|June 28, 2024
概括
这项研究为高中生介绍了人工智能和化学课程,使用机器学习 (ML) 构建虚拟pH计. 这种引人入胜的活动提高了学生对科学及其现实世界的应用的兴趣.
科学领域:
- 这是一个跨学科的STEM教育.
- 人工智能和化学一体化整合
- 机器学习在科学教育中的应用
背景情况:
- 人工智能 (AI) 需要对其好处和挑战进行早期教育.
- 高中课程需要创新的方法来整合新兴技术,如AI.
- 分析化学概念,如pH值测量,可以作为复杂科学原理的可访问入口.
研究的目的:
- 开发和评估一个跨学科的课程连接AI和化学的高中生.
- 培养学生对分析化学和机器学习的兴趣和参与.
- 通过实践活动来展示AI在科学问题解决中的实际应用.
主要方法:
- 借助机器学习 (ML),AI的一个子集,使用无码软件Orange.
- 为具有基础科学背景的高中生开发了一个基于ML的虚拟pH测量器活动.
- 学生使用pH条来收集有关颜色变化的数据,并建立了ML神经网络模型来预测pH值.
主要成果:
- 综合课程成功地增加了学生对化学和ML的兴趣.
- 学生们展示了对科学与他们的日常生活和全球问题相关性的理解.
- 该活动提供了整合化学和ML概念的变革性方法.
结论:
- 通过实际的ML应用来连接AI和化学,可以增强高中科学教育.
- 使用像Orange这样的可访问工具的实践活动可以为学生揭开AI和ML的神秘性.
- 这种课程模式为跨学科的STEM学习提供了一个可扩展的框架,并突出了科学创新的全球影响.
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