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Designing Prompt Analytics Dashboards to Analyze Student-ChatGPT Interactions in EFL Writing

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arxiv 2405.19691 v2 pith:NGUUFHCD submitted 2024-05-30 cs.HC

classification cs.HC
keywords chatgptprototypeanalyticsanalyzedesigndesigningenglishessay
verification ladder T0 review T1 audit T2 compute T3 formal
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While ChatGPT has significantly impacted education by offering personalized resources for students, its integration into educational settings poses unprecedented risks, such as inaccuracies and biases in AI-generated content, plagiarism and over-reliance on AI, and privacy and security issues. To help teachers address such risks, we conducted a two-phase iterative design process that comprises surveys, interviews, and prototype demonstration involving six EFL (English as a Foreign Language) teachers, who integrated ChatGPT into semester-long English essay writing classes. Based on the needs identified during the initial survey and interviews, we developed a prototype of Prompt Analytics Dashboard (PAD) that integrates the essay editing history and chat logs between students and ChatGPT. Teacher's feedback on the prototype informs additional features and unmet needs for designing future PAD, which helps them (1) analyze contextual analysis of student behaviors, (2) design an overall learning loop, and (3) develop their teaching skills.

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

  1. ELI-Why: Evaluating the Pedagogical Utility of Language Model Explanations

    cs.CL 2025-06 conditional novelty 6.0 of 10

    ELI-Why shows GPT-4's grade-tailored explanations often miss the intended educational level and are less informative than human-curated explanations.

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