When AI essay feedback misquotes a student, it is mostly in short quotes: both of my predictions reversed again

Описание и применение

Короткие цитаты в AI‑обратной связи чаще содержат реальные ошибки автора, в то время как длинные цитаты обычно являются переформулировками. Это позволяет улучшить проверку точности модели.

Задача

AI essay feedback often places students’ words in quotation marks, but it is unclear whether these quoted passages truly reflect the student’s original text.

Результат

Short quoted passages (4‑6 words) are more likely to contain altered words and to be loose near‑misses, whereas long quoted passages (11+ words) rarely alter words and are often reworded passages. The fixed similarity cutoff does not explain the observed reversal of predictions.

Рабочий процесс

• 1. Collect 8,946 IELTS essays and their GLM‑4.7 feedback.
• 2. Identify all quoted passages in the feedback.
• 3. Compute word‑level similarity between each quote and the original essay.
• 4. Classify quotes as "tight" (similarity ≥0.8) or "loose" (similarity <0.8).
• 5. Split tight quotes by length (4‑6 words vs. 11+ words).
• 6. Calculate the proportion of tight quotes that alter a word for each length group.
• 7. Calculate the proportion of changed quotes that are loose for each length group.
• 8. Compare observed proportions to two pre‑made predictions.
• 9. Interpret results and recommend verification guidelines.

Доказательства

About half of all changed quotes were loose.

3.19% of tight 4-6-word quotes alter a word, against 0.74% of tight quotes of 11 or more words.

50.1% of changed 4-6-word quotes are loose, against 66.3% of changed quotes of 11 or more words.

Everything is open: the plan, code, tests and counts are at https://github.com/munimtechnologies/feedback-quote-audit

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