CoChat
Sign Up
Cited by 132Second Language Acquisition and LearningEFL/ESL Teaching and LearningDiscourse Analysis in Language Studies

The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.

Enhancing writing pedagogy with learner corpus data

Cotos, Elena·2014·ReCALL
DOI 10.1017/s0958344014000019
Open this paper in CoChat — free account

Abstract

Learner corpora have become prominent in language teaching and learning, enhancing data-driven learning (DDL) pedagogy by promoting ‘learning driven data’ in the classroom. This study explores the potential of a local learner corpus by investigating the effects of two types of DDL activities, one relying on a native-speaker corpus (NSC) and the second combining native-speaker and learner corpora. Both types of activities aimed at improving second language writers’ knowledge of linking adverbials and were based on a preliminary analysis of adverbial use in the local learner corpus produced by 31 study participants. Quantitative and qualitative data, obtained from writing samples, pre/post-tests, and questionnaires, were converged through concurrent triangulation. The results showed an increase in frequency, diversity and accuracy in all participants’ use of adverbials, but more significant improvement was made by the students who were exposed to the corpus containing their own writing. The findings of this study are thus interpreted as suggestive that combining learner and native-speaker data is a feasible and effective practice, which can be readily integrated in DDL-based instruction with positive impact.

Overview

Integrity signals

Registry

Crossref · 10.1017/s0958344014000019

Cites

76 of 76 references verified0 citation errors · 0 not checkable

Statistics

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

Verification

Claims the paper makes

This paper’s full text isn’t openly available, 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?

Citations

Cites

Show all 76 references

Research works printed but not linked: 8

  1. Cortes, 2007, Exploring genre and corpora in the English for academic writing class, The ORTESOL Journal, 25, 8
  2. Bernardini, 2000, Serendipity expanded: Exploring new directions for discovery learning, TaLC 2000
  3. 10.3138/cmlr.62.1.17 · DOI
  4. Boulton, 2011, New trends in CALL: Working together
  5. Ellis, 2005, Analyzing learner language
  6. Johns, 1991, Should you be persuaded: Two examples of data-driven learning materials, English Language Research Journal, 4, 1
  7. Granger, 1996, Languages in contrast. Text-based cross-linguistic studies, 37
  8. Milton, 1998, Learner English on computer, 186

Cited by

Sorted by citations

See all 132

Related

See all

Metadata

Authors
Cotos, E.
Affiliations
Iowa State University (US)
Corresponding author
Cotos, Elena
ORCID
Cotos, Elena
Venue
ReCALL
Publisher
Cambridge University Press (CUP)
Published
2014-02-21
Volume
26
Issue
2
Pages
202-224
ISSN
  • 0958-3440 (ISSN-L)
  • 1474-0109
DOI
10.1017/s0958344014000019
OpenAlex
W2134547826
Cited by
132
References
76
Citations by year
2026: 3 · 2025: 26 · 2024: 9 · 2023: 12 · 2022: 7 · 2021: 7 · 2020: 10 · 2019: 26 · 2018: 6 · 2017: 12 · 2016: 6 · 2015: 8
FWCI
20.32
Type
journal article
Language
en
Open access
closed
Licence
www.cambridge.org/core/terms (unspecified)
Locations
ReCALL (publishedVersion)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Social Sciences › Linguistics and Language › Discourse Analysis in Language Studies
Keywords
learner corpus, data-driven learning, writing instruction, second language writing, linking adverbials, native speaker corpus, corpus-based instruction, adverbial use

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: Enhancing writing pedagogy with learner corpus data. https://app.cochat.ai/papers/10.1017/s0958344014000019
The paper
Cotos, E. (2014). Enhancing writing pedagogy with learner corpus data. ReCALL. https://doi.org/10.1017/s0958344014000019