StuGPTViz:一种视觉分析方法来理解学生-聊天GPT交互
IEEE transactions on visualization and computer graphics
|September 23, 2024
概括
本研究介绍了StuGPTViz,这是一个视觉分析系统,旨在了解学生如何在教育中使用ChatGPT. 它有助于教育工作者了解对话式学习模式和AI.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 人与计算机的交互
背景情况:
- 像ChatGPT这样的大型语言模型 (LLM) 提供了新的教育可能性.
- 了解学生与人工智能工具的互动对于有效的教学至关重要.
- 现有的数据集和学生-AI对话的分析方法是有限的.
研究的目的:
- 为了解决学生与ChatGPT互动的数据和分析方法的缺乏.
- 开发一个系统来跟踪和分析学生与ChatGPT的互动.
- 为教师在课堂上使用AI提供教学见解.
主要方法:
- 在数据可视化课程中收集了48名学生使用ChatGPT的对话数据.
- 开发了一个基于认知水平和主题分析的编码方案.
- 创建了StuGPTViz,这是一个视觉分析系统,用于跟踪时间交互模式和响应质量.
主要成果:
- StuGPTViz有效地跟踪和比较学生提示模式和ChatGPT响应质量.
- 该系统为教师提供了重要的教学见解.
- 专家采访和案例研究验证了该系统在提高对人工智能的教学价值的理解方面的有效性.
结论:
- 像StuGPTViz这样的视觉分析系统可以显著提高教育工作者对AI工具的洞察力.
- 在将视觉分析应用于教育方面有大量的研究机会.
- 这项工作为人工智能驱动的个性化学习解决方案铺平了道路.
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