arXiv 2407.124232024-07cs.HCcs.AI

StuGPTViz：一种理解学生与ChatGPT交互的可视化分析方法

StuGPTViz: A Visual Analytics Approach to Understand Student-ChatGPT Interactions

Hong Kong University of Science and Technology（香港科技大学）；Texas A&M University（德克萨斯农工大学）

Zixin Chen, Jiachen Wang, Meng Xia, Kento Shigyo, Dingdong Liu, Rong Zhang, Huamin Qu

备注：: 11 pages. To be published at IEEE Visualization 2024

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AI总结：

针对学生与ChatGPT交互模式研究缺数据集、分析难的问题，该研究收集48名硕士生课程对话数据，制定编码分类方案，开发可视化分析系统StuGPTViz，经专家访谈和案例研究验证，可助力教师挖掘ChatGPT教学价值。

摘要：

大语言模型（LLMs），尤其是ChatGPT，融入教育领域有望通过引入创新的对话式学习方法，革新学生的学习体验。为助力学生在教育场景中充分发挥ChatGPT的能力，教师了解学生与ChatGPT的交互模式至关重要。然而，由于缺乏聚焦学生与ChatGPT对话的数据集，且识别和分析对话中演化的交互模式存在复杂性，这项工作颇具挑战。\n为应对这些挑战，我们收集了48名学生在一学期的硕士级数据可视化课程中与ChatGPT交互的对话数据。随后，我们基于认知水平与主题分析相关文献，制定了一套编码方案，用于对学生与ChatGPT的交互模式进行分类。此外，我们提出了可视化分析系统StuGPTViz，该系统可在多尺度下追踪并比较学生提示的时间模式与ChatGPT的回复质量，为教师揭示重要的教学洞见。\n我们通过对6名数据可视化教师的专家访谈及3个案例研究验证了系统的有效性。结果证实，StuGPTViz能够增强教育工作者对ChatGPT教学价值的洞见。我们还探讨了将可视化分析应用于教育以及开发AI驱动的个性化学习解决方案的潜在研究机遇。

英文摘要：

The integration of Large Language Models (LLMs), especially ChatGPT, into education is poised to revolutionize students' learning experiences by introducing innovative conversational learning methodologies. To empower students to fully leverage the capabilities of ChatGPT in educational scenarios, understanding students' interaction patterns with ChatGPT is crucial for instructors. However, this endeavor is challenging due to the absence of datasets focused on student-ChatGPT conversations and the complexities in identifying and analyzing the evolutional interaction patterns within conversations. To address these challenges, we collected conversational data from 48 students interacting with ChatGPT in a master's level data visualization course over one semester. We then developed a coding scheme, grounded in the literature on cognitive levels and thematic analysis, to categorize students' interaction patterns with ChatGPT. Furthermore, we present a visual analytics system, StuGPTViz, that tracks and compares temporal patterns in student prompts and the quality of ChatGPT's responses at multiple scales, revealing significant pedagogical insights for instructors. We validated the system's effectiveness through expert interviews with six data visualization instructors and three case studies. The results confirmed StuGPTViz's capacity to enhance educators' insights into the pedagogical value of ChatGPT. We also discussed the potential research opportunities of applying visual analytics in education and developing AI-driven personalized learning solutions.

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