AI-labeled texts revised faster; author info had no effect
Question asked:
“In a study of 303 learners revising peer-written and AI-generated texts, learners spent less time revising AI-labeled texts, but author information did not affect the number of identified improvement areas or revisions made.”
Summary
The study involving 303 learners showed that participants spent less time revising texts labeled as AI-generated compared to peer-written texts. Additionally, providing author information did not influence how many improvement areas were identified or the number of revisions made.
Sources 58 searched
- Generative AI in academic writing: Does information on authorship impact learners’ revision behavior? - ScienceDirect
We further examined the impact of learners’ prior experiences, attitudes, and gender on text revision. Therefore, N = 303 learners revised two different texts: one labeled as peer-written and the other as AI-generated.
- Student revision with peer and expert reviewing - ScienceDirect
200 pieces of human-generated formative feedback and 200 pieces of AI-generated formative feedback for the same essays. We examined whether ChatGPT and human feedback differed in quality for the whole sample, for compositions that differed in overall quality, and for native English speakers and English learners by comparing descriptive statistics and effect sizes.
- Can students judge like experts? A large-scale study on the pedagogical quality of AI and human personalized formative feedback - ScienceDirect
In par with the above, based on the analysis of exemplar essay revision behavior of 303 participants in Germany, Radtke & Rummel (2025) concluded that information about the feedback source did not affect feedback uptake.
- University students describe how they adopt AI for writing and research in a general education course - PMC
Through iterative qualitative coding, we identified key patterns in students’ AI use, including higher-order writing tasks (understanding complex topics, finding evidence), lower-order writing tasks (revising, editing, proofreading), and other learning activities (efficiency enhancement, independent research). Students primarily used AI to improve communication of their original ideas, though some leveraged it for more complex tasks like finding evidence and developing arguments. Many students expressed skepticism about AI-generated content and emphasized maintaining their intellectual independence.
- AI Can Deliver Personalized Learning at Scale, Study Shows | Dartmouth
The findings also highlight some of the challenges educators may face in implementing generative AI chatbots, Thesen and Park report. Surveys have shown that nearly half of medical students use chatbots at least weekly. In the Dartmouth study, students mainly used NeuroBot TA for fact-checking—which increased dramatically before exams—rather than for in-depth learning or long, engaging discussions.
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