The DOI matches its Crossref record.
Analyzing Revision
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Experienced writers treat revision as a recursive, non-linear process [81,87], and engage with the text in repeated cycles, with multiple objectives including finding the form or shape of an argument [87], experimenting with vocabulary and style [43], and going back and forth between multiple composing activities during revision [22].”
From ABScribe: Rapid Exploration & Organization of Multiple Writing Variations in Human-AI Co-Writing Tasks using Large Language Models (2024) · cites this paper as [22]
Citations
Cites
Still being checked.
Cited by
A comparative study of peer and teacher feedback in a Chinese EFL writing class
Yang, M., Badger, R., & Yu, Z. (2006) · Journal of Second Language Writing · doi:10.1016/j.jslw.2006.09.004 · Cited by 703
The effect of peer and teacher feedback on student writing
Paulus, T. M. (1999) · Journal of Second Language Writing · doi:10.1016/s1060-3743(99)80117-9 · Cited by 522
Keystroke Logging in Writing Research: Using Inputlog to Analyze and Visualize Writing Processes
Leijten, M., & Van Waes, L. (2013) · Written Communication · doi:10.1177/0741088313491692 · Cited by 513
The effects of trained peer review on EFL students’ revision types and writing quality
Min, H.-T. (2006) · Journal of Second Language Writing · doi:10.1016/j.jslw.2006.01.003 · Cited by 482
The impact of teacher written feedback on individual writers
Hyland, F. (1998) · Journal of Second Language Writing · doi:10.1016/s1060-3743(98)90017-0 · Cited by 456
Metadata
- Authors
- Faigley, L., & Witte, S.
- Venue
- College Composition & Communication
- Published
- 1981-12-01
- Volume
- 32
- Issue
- 4
- Pages
- 400-414
- ISSN
- 0010-096X (ISSN-L)
- 1939-9006
- OpenAlex
- W4237719669
- Cited by
- 481
- References
- 0
- Citations by year
- 2026: 25 · 2025: 22 · 2024: 19 · 2023: 18 · 2022: 24 · 2021: 32 · 2020: 21 · 2019: 24 · 2018: 13 · 2017: 30 · 2016: 21 · 2015: 9 · 2014: 16 · 2013: 17 · 2012: 18
- FWCI
- 94.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- College Composition and Communication (publishedVersion)
- Topics
- Social Sciences › Linguistics and Language › Discourse Analysis in Language Studies
- Social Sciences › Library and Information Sciences › Academic Writing and Publishing
- Social Sciences › Education › Linguistics and Education Research
- Keywords
- revision, writing process, writing instruction, student writing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Analyzing Revision. https://app.cochat.ai/papers/10.2307/356602
- The paper
- Faigley, L., & Witte, S. (1981). Analyzing Revision. College Composition & Communication. https://doi.org/10.2307/356602
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
