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Automated written corrective feedback: Error-correction performance and timing of delivery

Language Learning & Technology, 2022
To the extent automated written corrective feedback (AWCF) tools such as Grammarly are based on sophisticated error-correction technologies, such as machine-learning techniques, they have the potential to find and correct more common L2 error types than ...
Jim Ranalli, Taichi Yamashita
semanticscholar   +1 more source

The impact of a professional development program on EFL teachers’ beliefs about corrective feedback

System (Linköping), 2021
This study investigated the impact of a professional development (PD) program enabling teachers to explore and reflect on their beliefs about oral corrective feedback (CF).
X. Ha, Jill C. Murray
semanticscholar   +1 more source

Computer-Mediated Corrective Feedback to Improve L2 Writing Skills: A Meta-Analysis

Journal of educational computing research, 2022
Written corrective feedback for improving L2 writing skills has been a debatable issue for more than two decades. The aims of this meta-analysis are to (1) provide a quantitative measure of the effect of computer-generated written feedback for improving ...
M. Mohsen
semanticscholar   +1 more source

Written corrective feedback

2023
There is a widespread consensus in the field of English language teaching that feedback plays a key role in students’ language development. Research shows that that feedback can help students relearn and repair language elements that they have not fully acquired and guide them in further strengthening and expanding their learning.
Minh Thi Thuy Nguyen, Willy Renandya
openaire   +1 more source

How effectively can EFL students use automated written corrective feedback (AWCF) in research writing?

Computer Assisted Language Learning, 2021
AWCF can facilitate academic writing development, especially for novice writers of English as a foreign language (EFL). Existing AWCF studies mainly focus on teacher and learner perceptions; fewer have investigated the error-correction effect of AWCF and
Qiang Guo, Ruiling Feng, Yuanfang Hua
semanticscholar   +1 more source

Assessing the efficacy of and preference for positive and corrective feedback.

Journal of Applied Behavior Analysis, 2022
Feedback is an effective strategy for improving performance and consists of multiple characteristics. One characteristic that can influence feedback efficacy is its nature (whether feedback is positive or corrective) and little is known about the ...
Michael J. Simonian, Denys Brand
semanticscholar   +1 more source

Neural Automated Writing Evaluation with Corrective Feedback

arXiv.org
The utilization of technology in second language learning and teaching has become ubiquitous. For the assessment of writing specifically, automated writing evaluation (AWE) and grammatical error correction (GEC) have become immensely popular and ...
Izia Xiaoxiao Wang   +7 more
semanticscholar   +1 more source

Motivational factors underlying learner preferences for corrective feedback: Language mindsets and achievement goals

Language Teaching Research, 2021
The present study examines how learners’ language mindsets (beliefs about the malleability of language intelligence) and achievement goals predict learners’ preferences for different types of corrective feedback (CF).
Mostafa Papi   +3 more
semanticscholar   +1 more source

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

, 2020
Despite the increased use of automated writing evaluation (AWE) systems and similar programs for assessment purposes in second language (L2) writing classrooms, research on student engagement with automated feedback is scarce.
Svetlana Koltovskaia
semanticscholar   +1 more source

Teachers’ attempts at focused written corrective feedback in situ

, 2021
Previous research on comprehensive/focused written corrective feedback (WCF) has been dominated by the experimental/quasi-experimental tradition, with low ecological validity and limited pedagogical relevance, and without sufficiently recognizing the ...
Icy Lee, N. Luo, P. Mak
semanticscholar   +1 more source

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