Corpus-based Feedback in Elementary English Writing: Impacts on Performance and Learner Attitudes

• 발행기관: 한국교원대학교 뇌·AI기반교육연구소
• 저자명: Hye Ri Shin Dong Ju Lee
• 간행물 정보: 『Brain, Digital, & Learning』제15권 제2호, 217~234쪽, 전체 18쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 2025.06.30

국문 초록

This study examines the impact of corpus-based feedback on elementary school students’English writing performance and attitudes. Forty-two fifth-grade students were assignedto either a research group (n = 22), which received data-driven learning (DDL) feedbackusing teacher-selected concordance examples, or a comparison group (n = 20), whichreceived direct teacher feedback and explicit instruction. Across four instructional lessons,both groups participated in pre- and post-writing assessments, and qualitative data werecollected through surveys and interviews. The results indicate that the corpus-based groupdemonstrated greater improvement in writing performance compared to the comparisongroup, with significant gains observed among both higher- and lower-proficiency learnerswhen appropriate scaffolding was provided. While students generally responded positivelyto corpus-based feedback, some reported difficulties during the writing process. Thesefindings suggest that corpus-based feedback can be an effective pedagogical approach inelementary writing instruction, offering a valuable alternative to conventional feedbackmethods.

목차

Introduction

Theoretical Background

Methods

Results and Discussions

Conclusions and Implications

References

키워드

Corpus data-driven learning English writing feedback