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LLM-Driven Learning Analytics Dashboard for Teachers in EFL Writing Education

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arxiv 2410.15025 v1 pith:3M2CIBYN submitted 2024-10-19 cs.HC cs.AI

Minsun Kim , SeonGyeom Kim , Suyoun Lee , Yoosang Yoon , Junho Myung , Haneul Yoo , Hyunseung Lim , Jieun Han
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Yoonsu Kim So-Yeon Ahn Juho Kim Alice Oh Hwajung Hong Tak Yeon Lee
This is my paper · ORCID
classification cs.HCcs.AI
keywords dashboardlearningteacherswritingchatgpteducationinteractionstudent
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 2 citations worldwide. Full citation record

  1. MOSAIC-F: A Framework for Enhancing Students' Oral Presentation Skills through Personalized Feedback

    cs.HC 2025-06 reject novelty 4.0 of 10

    The paper proposes MOSAIC-F, a multimodal feedback pipeline for oral presentations that combines human rubrics, sensors, and large language models, but it contains no outcome data or evaluation.

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