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.
Blogger's Review: This project effectively enhances teachers' visualization of students' programming processes through 'vibe coding', providing better support for educational decision-making. The potential applications in the field of educational technology are promising, and the future looks bright.