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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

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

classification cs.HC cs.AI
keywords dashboardlearningteacherswritingchatgpteducationinteractionstudent
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. PsyScore: A Psychometrically-Aware Framework for Trait-Adaptive Essay Scoring and ZPD-Scaffolded Feedback

    cs.CL 2026-06 unverdicted novelty 6.0

    PsyScore combines a Trait-Adaptive Neural IRT Scorer using GPCM with a ZPD-Scaffolded Feedback Generator to deliver both competitive scoring and pedagogically aligned feedback on the ASAP++ dataset.

  2. The Crutch or the Ceiling? How Different Generations of LLMs Shape EFL Student Writings

    cs.HC 2026-04 unverdicted novelty 4.0

    Advanced LLMs improve EFL writing scores and diversity for lower-proficiency students but correlate with lower expert ratings on deep coherence, acting more as crutches than scaffolds.