[基于GeoGebra的互动色谱学习工具的开发和实践:板理论的案例研究]
Yu-Han Zhang1, Jun-Yao He1, Shu-Jing Lin1
1College of Chemistry and Materials Science，Hebei University，Baoding 071002，China.
Se pu = Chinese journal of chromatography
|September 5, 2025
概括
这项研究介绍了用于染色学教学的交互式GeoGebra工具,通过视觉模拟和人工智能辅助衍生增强了学生的参与度和板理论的理解. 该平台提高了仪器分析课程中的任务完成和解决问题的准确性.
科学领域:
- 分析化学
- 化学教育
- 计算化学
背景情况:
- 传统的染色学教学面临着抽象板理论,单向知识传递和学生参与度较低的挑战.
- 现有的数字工具往往复杂,难以使用,或缺乏灵活的参数调整以实现有效的学习.
研究的目的:
- 开发一个基于GeoGebra的交互式教学工具,用于教导仪器分析中的色谱板理论.
- 通过整合理论模型,交互式模拟和人工智能辅助学习来解决当前教学方法的局限性.
主要方法:
- 开发了一种改进的数学板理论模型,包括移动相流率,死亡时间和相位比.
- 在云平台上创建了一个三层学习系统 (单组件,多组件模拟,保留时间方程导出).
- 实施了人工智能辅助导出,交互式参数调整和视觉化曲线模拟的综合教学链.
主要成果:
- 该工具显著提高了课堂作业完成率 (94%) 和高级问题准确性 (76%),克服了传统教学的尺寸限制.
- 动态参数调整提高了参与度,85%的学生在教学后独立使用该工具.
- 人工智能模块促进了跨学科的融合,并提供了比教科书方法更令人信服的记忆时间方程.
结论:
- 开发的"理论模型可视化模型参数可调整交互式知识生成"模型为色谱理论教育提供了一个新的解决方案.
- 该工具的开源和模块化设计为分析化学的数字教学改革提供了宝贵的参考.
- 这种方法提高了盘子理论在仪器分析中的理解和应用.
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