期刊
FRONTIERS IN ARTIFICIAL INTELLIGENCE
卷 6, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/frai.2023.1162454
关键词
technology-based learning; automated writing evaluation; writing instruction; feedback; formative assessment; meta-analysis
Adaptive learning opportunities and individualized, timely feedback are effective support measures for students' writing in educational contexts. Automated writing evaluation (AWE) tools based on AI technology can provide individual feedback. The meta-analysis shows a medium effect of automated feedback on students' writing performance, but the heterogeneity in the data suggests that it is not a consistent form of intervention.
Introduction: Adaptive learning opportunities and individualized, timely feedback are considered to be effective support measures for students' writing in educational contexts. However, the extensive time and expertise required to analyze numerous drafts of student writing pose a barrier to teaching. Automated writing evaluation (AWE) tools can be used for individual feedback based on advances in Artificial Intelligence (AI) technology. A number of primary (quasi-)experimental studies have investigated the effect of AWE feedback on students' writing performance.Methods: This paper provides a meta-analysis of the effectiveness of AWE feedback tools. The literature search yielded 4,462 entries, of which 20 studies (k = 84; N = 2, 828) met the pre-specified inclusion criteria. A moderator analysis investigated the impact of the characteristics of the learner, the intervention, and the outcome measures.Results: Overall, results based on a three-level model with random effects show a medium effect (g = 0.55) of automated feedback on students' writing performance. However, the significant heterogeneity in the data indicates that the use of automated feedback tools cannot be understood as a single consistent form of intervention. Even though for some of the moderators we found substantial differences in effect sizes, none of the subgroup comparisons were statistically significant.Discussion: We discuss these findings in light of automated feedback use in educational practice and give recommendations for future research.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据