用AI快速开发编程过程可视化工具，助教师实时掌握学生学习状态。
From Idea to Classroom in Days: Using "Vibe Coding" to Create a Programming Process Visualizer from IDE Activity Logs
- 通过AI辅助编码解析Thonny编辑器日志，生成可交互的编程过程视图。
- 支持批量上传日志，按学生呈现时间线、代码量变化和编程行为回放。
- 适合教学评估与学术诚信审查，已在160人课程中完成试点验证。
本文报告了一种基于AI辅助的"vibe coding"技术，快速开发并部署了一个针对Thonny（Python初学者集成开发环境）日志的可视化工具，使学生编程过程对教师透明。我们构建了一个网络应用，分析Thonny生成的日志文件，为每位学生生成包含交互式活动时间线、会话摘要、代码量趋势图及编程过程回放的视图。教师可上传单个日志、压缩包或文件夹，系统自动解析并提供逐学生导航功能。该工具帮助教师识别需干预的学习情境，并标记可疑学术不端行为。初步评估使用了过往课程日志；2026年2月在一门含160名学生的入门编程课中进行了试点，收集了教师反馈并推动了可用性迭代优化。
原文摘要 · Abstract (English)
This paper reports on the rapid development and classroom deployment of a Thonny log visualizer built using AI-assisted ``vibe coding'' to make students' programming processes easily visible to teachers. We developed a web application that analyzes log files generated by Thonny (an IDE for Python) and produces interpretable views of students' programming processes. Teachers can upload a log, a ZIP archive, or a folder containing logs for a group or the course; the system parses all logs, generates results per student, and provides student-by-student navigation for reviewing cases. Each student's view includes an interactive activity timeline, a compact session summary, a code-size graph, a programming-process replay, and more. These views support teacher decision-making by enabling the identification of learning-support situations and flagging sessions for academic-integrity clarification. The tool was initially evaluated using logs from previous courses; a February 2026 pilot in an introductory programming course with 160 participants provided teachers' feedback and informed iterative usability improvements.
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