Cited by 447EFL/ESL Teaching and LearningStudent Assessment and FeedbackEnglish Language Learning and Teaching

Student engagement with automated written corrective feedback (AWCF) provided by Grammarly: a multiple case study

Koltovskaia, Svetlana·2020·Assessing Writing

Integrity signals

Registry

Crossref · 10.1016/j.asw.2020.100450

Cites

44 of 44 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Cites

Flagged first, then by citations

1 of the 45 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Koltovskaia, S.
Affiliations
Oklahoma State University (US)
Corresponding author
Koltovskaia, Svetlana
Venue
Assessing Writing
Publisher
Elsevier BV
Published
2020-04
Volume
44
Pages
100450
ISSN
1075-2935 (ISSN-L)
OpenAlex
W3011057862
Cited by
447
References
45
Citations by year
2026: 133 · 2025: 105 · 2024: 96 · 2023: 61 · 2022: 31 · 2021: 18 · 2020: 3
FWCI
121.15
Type
journal article
Language
en
Open access
closed
Locations
Assessing Writing (publishedVersion)
Topics
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Social Sciences › Education › Student Assessment and Feedback
  • Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
Keywords
Grammarly, student engagement, automated writing evaluation, second language writing, cognitive engagement, emotional engagement, behavioral engagement, feedback acceptance, technology dependence, draft revision

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