Exploring online peer feedback and automated corrective feedback on EFL writing performance
Abstract
Previous studies have been done to research the effects of different electronic feedback (e-feedback) modes of helping English as a foreign language (EFL) students improve their writing. The purpose of this study was to employ online peer feedback (OPF) and automated corrective feedback (ACF) to assess EFL learners’ writing performance in the areas of sentence complexity, grammatical accuracy, and lexical density. Our major findings suggest that OPF is potentially more useful than ACF in improving sentence writing, making fewer grammatical errors, and producing more types of lexical items. Nevertheless, we also found that the majority of students favored the use of ACF for the purpose of producing a richer vocabulary. Less skilled writers tended to make greater improvements than higher-skilled writers in producing more sentences and lexical items after OPF use; however, the difference was not statistically significant. Based on our research results, we discuss and present the implications of these findings for pedagogical instruction and future research.
Integrity signals
Registry
Cites
Statistics
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?
The choice of technology can have a significant impact on the effectiveness of online peer feedback activities.
“The choice of technology can have a significant impact on the effectiveness of online peer feedback activities, as different platforms may have different features, functionalities, and affordances that influence students' engagement and learning outcomes (Noroozi & Hatami, 2019; Shang, 2019).”
From Online peer feedback in higher education: A synthesis of the literature (2024) · cites this paper as Shang, 2019
Cites
LEARNERS’ PROCESSING, UPTAKE, AND RETENTION OF CORRECTIVE FEEDBACK ON WRITING: Case Studies
Storch, N., & Wigglesworth, G. (2010) · Studies in Second Language Acquisition · doi:10.1017/s0272263109990532 · Cited by 398 · see citing works
Exploring the role of noticing in a three-stage second language writing task
Qi, D. S., & Lapkin, S. (2001) · Journal of Second Language Writing · doi:10.1016/s1060-3743(01)00046-7 · Cited by 383 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Examining the impact of Grammarly on the quality of mobile L2 writing
Dizon, G., & Gayed, J. M. (2021) · The JALT CALL Journal · doi:10.29140/jaltcall.v17n2.336 · Cited by 138 · see citing works
Online peer feedback in higher education: A synthesis of the literature
Kerman, N. T., Banihashem, S. K., Karami, M., Er, E., van Ginkel, S., & Noroozi, O. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12273-8 · Cited by 109 · see citing works
Wiboolyasarin, W., Wiboolyasarin, K., Suwanwihok, K., Jinowat, N., & Muenjanchoey, R. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100228 · Cited by 68 · see citing works
Pham, T. N., Lin, M., Trinh, V. Q., & Bui, L. T. P. (2020) · SAGE Open · doi:10.1177/2158244020914554 · Cited by 68 · see citing works
“…feedback, much of the literature has addressed the conversion to a digital written peer feedback thanks to the emergence of the dynamic nature and social aspect of Web 2.0 authoring tools (e.g., blogs, wikis, and podcasts) (Ma, 2019; Noroozi & Hatami, 2019; Shang, 2019; Xu & Yu, 2018).”
BackgroundInfluential
- Authors
- Shang, H.-F.
- Affiliations
- I-Shou University (TW)
- Corresponding author
- Shang, Hui-Fang
- ORCID
- Shang, Hui-Fang
- Venue
- Interactive Learning Environments
- Publisher
- Informa UK Limited
- Published
- 2019-06-10
- Volume
- 30
- Issue
- 1
- Pages
- 4-16
- ISSN
- 1049-4820 (ISSN-L)
- 1744-5191
- OpenAlex
- W2949785454
- Cited by
- 112
- References
- 2
- Citations by year
- 2026: 12 · 2025: 14 · 2024: 27 · 2023: 26 · 2022: 23 · 2021: 6 · 2020: 4
- FWCI
- 39.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Interactive Learning Environments (publishedVersion)
- Funders
- Ministry of Science and Technology (105-2410-H-214-011)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- online peer feedback, EFL writing, writing performance, sentence complexity, grammatical accuracy, lexical density, vocabulary development, electronic feedback
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