Exploring the Effects of Automated Written Corrective Feedback on EFL Students’ Writing Quality: A Mixed-Methods Study

Ning Fan

SAGE Open, 2023, vol. 13, issue 2, 21582440231181296

Abstract: Despite a large number of studies on the adoption of automated writing evaluation (AWE) systems, the effects of automated written corrective feedback (AWCF) on English as a Foreign Language (EFL) students’ writing has been insufficiently documented. This study employed a mixed-method approach to examine such effects because of the significance of AWCF in EFL writing. Using a quasi-experimental design, this study explored how AWCF through Grammarly affected EFL students’ writing quality. A total of 67 EFL students from two intact university English classes participated in this study, with a treatment group receiving two rounds of Grammarly feedback and teacher feedback while a comparison group receiving teacher feedback only. The results of the posttest writing task revealed that the students from the treatment group did not significantly outperform the students from the comparison group in syntactic and lexical complexity, accuracy, and fluency. A follow-up questionnaire consisting of fixed-response and open-ended questions was administered to the students from the treatment group after the posttest to elicit the students’ perceptions of Grammarly feedback effects on their writing. The qualitative findings supported and provided deeper insights into the quantitative results. This study was concluded with a discussion of its limitations and implications.

Keywords: EFL writing; AWCF; mixed-methods approach; students’ perceptions (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:13:y:2023:i:2:p:21582440231181296

DOI: 10.1177/21582440231181296

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