引用
清晰
计算机科学
集合(抽象数据类型)
生成语法
质量(理念)
感知
第二语言写作
数据科学
心理学
人工智能
计算语言学
引文分析
学术写作
自然语言处理
教育研究
语言习得
书面语
实证研究
生成模型
作者
Peter Crosthwaite,Shuyi Amelia Sun
标识
DOI:10.1177/00336882251386530
摘要
Since ChatGPT's emergence, extensive research has explored the role of generative artificial intelligence (GenAI) in delivering written feedback (WF), encompassing diverse aims, methodologies and findings. This includes studies examining second language (L2) contexts in which such feedback is used, although, to date, no attempt has been made to synthesize these studies for cumulative knowledge building. To provide clarity on the state-of-the-art on GenAI-influenced L2 WF studies, this Preferred Reporting Items for Systematic Reviews and Meta-Analyses-informed scoping review article explores a dataset of 51 such studies taken from Social Sciences Citation Index/Emerging Sources Citation Index-indexed publications since 2022. Two researchers manually coded these studies for data regarding publication outlets, country/region and L2 focus, research aims, research methods, findings and identified (or author-disclosed) limitations. Findings reveal that most studies address improvements to writing quality arising from GenAI produced feedback, and/or student and teachers’ perceptions of such feedback. A diverse set of methods include revision analysis, pre-tests/post-tests of writing quality and quantitative surveys. Results cover improvements in writing quality or skills, mixed perceptions, and varied feedback uptake and revision behaviours particularly when comparing artificial intelligence and human feedback. We close by identifying gaps in cumulative knowledge and suggesting directions for future research.
科研通智能强力驱动
Strongly Powered by AbleSci AI