Investigating the Impact of Teacher Feedback on Content Revisions in EFL Students’ Writing by the Automated Tracking Approach

Gary Cheng*, Mike Hin Leung Chui, Bernie Chun Nam Mak

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

Teacher feedback plays an important role in motivating students who learn English as a Foreign Language (EFL) to revise and improve their writing. Investigating how EFL students revise their writing in response to various types of teacher feedback has long received research attention. However, such investigation is human dependent, which requires considerable time and effort, limiting its application to a wide range of EFL writing classes in practice. To address this issue, this study was designed to adopt a systematic and automated approach to investigate the impact of different types of teacher feedback on the content revisions of EFL students at a larger scale. A total of 114 EFL undergraduate students and 3 experienced English teachers from three universities participated in this study. The writing draft and final writing of students and the written feedback from teachers were collected as data and were entered into an automated tracking system for analysis. The analytical results indicate that constructive criticism and imperative appeared to be most effective in triggering content revisions, advice could have a comparable effect, and that question was least effective. The automated analysis would be helpful to teachers in making informed adjustments to their feedback and instructional strategies to better support student revisions.

Original languageEnglish
Title of host publicationEmerging Technologies for Education - 6th International Symposium, SETE 2021, Revised Selected Papers
EditorsWeijia Jia, Yong Tang, Raymond S. Lee, Michael Herzog, Hui Zhang, Tianyong Hao, Tian Wang
PublisherSpringer Cham
Pages355-363
Number of pages9
Edition1st
ISBN (Electronic)9783030928360
ISBN (Print)9783030928353
DOIs
Publication statusPublished - 11 Nov 2021
Event6th International Symposium on Emerging Technologies for Education, SETE 2021 - Zhuhai, China
Duration: 11 Nov 202112 Nov 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Symposium on Emerging Technologies for Education, SETE 2021
Country/TerritoryChina
CityZhuhai
Period11/11/2112/11/21

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Automated tracking
  • Content revision
  • Second language writing
  • Teacher feedback

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