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arXiv · 2608.13587

Student-ChatGPT Interaction Visible: Designing a Teacher Dashboard for EFL Writing Education

Minsun Kim·Seon Gyeom Kim·Suyoun Lee·Yoosang Yoon·Junho Myung·Haneul Yoo·Jieun Han·Hyunseung Lim·Yoonsu Kim·So-Yeon Ahn·Juho Kim·Alice Oh·Hwajung Hong·Tak Yeon Lee
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Abstract

We present a Prompt Analytics Dashboard (PAD) for teachers that can traces student-LLM interactions from EFL writing classes. PAD can show student prompt-response exchanges with LLM chatbot and English essay writing revision histories to support data-informed instruction and visibility in classes. Through two iterative co-design sessions with six EFL instructors, we distilled a compact trace taxonomy (misuse signals, goal-alignment cues, revision effort) and instantiated three interface views (overview, week/outcome filter, drill-down with evidence snippets). This pipeline summarizes potential misuse and alignment at class/cohort levels and attaches micro-explanations to reduce over-surveillance. Instructors reported reduced scanning burden and clearer timing for interventions.

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Minsun Kim, Seon Gyeom Kim, Suyoun Lee, Yoosang Yoon, Junho Myung, Haneul Yoo, Jieun Han, Hyunseung Lim, Yoonsu Kim, So-Yeon Ahn, Juho Kim, Alice Oh, Hwajung Hong, Tak Yeon Lee. 2026-07-10. Student-ChatGPT Interaction Visible: Designing a Teacher Dashboard for EFL Writing Education. https://arxiv.org/abs/2608.13587

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