LLM-Driven Learning Analytics Dashboard for Teachers in EFL Writing Education
Minsun Kim, SeonGyeom Kim, Suyoun Lee, Yoosang Yoon, Junho Myung,, Haneul Yoo, Hyunseung Lim, Jieun Han, Yoonsu Kim, So-Yeon Ahn, Juho Kim,, Alice Oh, Hwajung Hong, Tak Yeon Lee

TL;DR
This paper introduces a human-centered LLM-powered dashboard that helps EFL teachers analyze student interactions with ChatGPT in writing education, improving monitoring and instructional strategies.
Contribution
It presents a novel dashboard integrating NLP and HCI principles to enhance teacher monitoring of ChatGPT-assisted EFL writing education.
Findings
Effective monitoring of student behavior with ChatGPT
Identification of noneducational interactions
Enhanced instructional strategy alignment
Abstract
This paper presents the development of a dashboard designed specifically for teachers in English as a Foreign Language (EFL) writing education. Leveraging LLMs, the dashboard facilitates the analysis of student interactions with an essay writing system, which integrates ChatGPT for real-time feedback. The dashboard aids teachers in monitoring student behavior, identifying noneducational interaction with ChatGPT, and aligning instructional strategies with learning objectives. By combining insights from NLP and Human-Computer Interaction (HCI), this study demonstrates how a human-centered approach can enhance the effectiveness of teacher dashboards, particularly in ChatGPT-integrated learning.
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Taxonomy
TopicsEducational Technology and Assessment · Online Learning and Analytics · Educational Technology and Pedagogy
