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The2025 instructor guideline assigns the course instructor the choice of prohibition, limited uses or broader uses, announced in syllabus and class. Example syllabus texts are options, not universal student permission.
記録の改訂
Yonsei University
このサイトの審査済み記録の更新であり、大学が方針を変更したことを確認するものではありません。
トラッカーの公開時刻は、大学の政策の発効日ではありません。
今回の記録更新の意味
関係する記録：12 (3件 修正・調整済み · 8 を追加 · 1 件が保留中)
学術的誠実性 · 教育 · さらに8件のトピック
コースワーク · 関係する記録：1 (1 を追加)
試験 · 関係する記録：1 (1 を追加)
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The2025 teacher guideline generally prohibits GenAI in supervised exams and limits electronic devices. In unproctored/open assessments, any permitted uses must be decided and announced beforehand. Preserve the “in principle” qualification and actual exam instructions.
開示 · 関係する記録：1 (1 を追加)
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Where AI use is permitted, the instructor selects and announces one or more disclosure/log methods. Prompt fields, versions and upload examples are selected course methods, not a universal checklist.
データ安全性 · 関係する記録：1 (1 を追加)
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The2025 guidance warns against inputting personal/confidential/unpublished research or patent information into external cloud AI. Teachers should not upload entire student assessment texts for AI grading/analysis. No retention duration or approved institutional service is established.
研究と出版 · 関係する記録：1 (1 を追加)
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The2025 researcher guideline does not recognise AI as author. Humans retain core design/analysis/conclusions and responsibility; disclose tool/version/developer/purpose, verify outputs and follow journal requirements. Core original outputs may not be generated by AI under the stated restriction.
学術的誠実性 · 関係する記録：5 (2件 修正・調整済み · 3 を追加)
サイトの結論文テキストの変更
旧テキスト
Yonsei University Research Ethics Center guidance says students using generative AI in academic work must provide clear and accurate citations.
新しいテキスト
Yonsei’s May 2024 guideline asks students to clearly cite generative AI use; the August 2025 instructor guideline requires instructors to specify permissible course uses and choose and announce appropriate disclosure or prompt-record submission methods.
サイトの結論文テキストの変更
旧テキスト
Yonsei University Research Ethics Center guidance tells students that generative AI may be permitted or restricted depending on the course and that students should consult the syllabus and course policies.
新しいテキスト
Yonsei students should follow the instructor’s announced syllabus/course AI-use rules; the August 2025 instructor guideline also addresses permitted and prohibited exam contexts and disclosure when use is allowed.
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AI detector results are supplementary and should not alone determine grades or sanctions; consider the student’s explanation and instructor review. General grading dishonesty rules do not make every AI use cheating.
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The2026 academic rules require scholarly ethics and allow discipline under their conditions. The undergraduate grading page says dishonesty/cheating invalidates obtained grades and gives the course F. No universal AI-specific penalty follows without the applicable course rule and finding.
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The research-integrity committee process is for research participants, not ordinary course appeals. Preliminary investigation starts within30 days of report and finishes within30 of start; main investigation starts within30 after approval and finishes within120, extendable with approval. Objection is within30 days of determination notice and processed within60 of receipt. Day types are unspecified.
教育 · 関係する記録：1 (1 件が保留中)
保持されている過去のテキスト。これは大学が規則を廃止したことを意味するものではありません。
Yonsei University Research Ethics Center guidance says generative AI use in courses should be based on clear agreement between instructors and learners, with instructors giving minimum guidance when use is permitted.
保留／現在の結論から除外プライバシー · 関係する記録：1 (1件 修正・調整済み)
サイトの結論文テキストの変更
旧テキスト
Yonsei University Research Ethics Center guidance warns users not to enter confidential, sensitive, or personally identifiable information into generative AI tools.
新しいテキスト
Yonsei’s 2024 guideline discourages entering confidential, sensitive or personal data into generative AI; the August 2025 researcher guideline specifically warns against entering personal, patent, confidential and unpublished research data into external cloud-based AI services.