Generative AI in academic writing: Does information on authorship impact learners’ revision behavior?

被引:0
作者
Radtke, Anna [1 ]
Rummel, Nikol [1 ,2 ]
机构
[1] Center for Advanced Internet Studies (CAIS), Konrad-Zuse-Straße 2a, Bochum
[2] Ruhr University Bochum (RUB), Universitätsstraße 150, Bochum
来源
Computers and Education: Artificial Intelligence | 2025年 / 8卷
关键词
Academic writing; AI-assisted writing; Collaborative writing; Generative AI; Text revision;
D O I
10.1016/j.caeai.2024.100350
中图分类号
学科分类号
摘要
The role of generative artificial intelligence (AI) in education has expanded significantly over recent years. AI-based text generators such as ChatGPT provide an accessible and effective tool for learners, particularly in academic writing. While revision is considered an essential part of both individual and collaborative writing, research on the revision of AI-generated texts remains limited. However, with the growing adoption of generative AI in education, learners’ ability to effectively revise AI-generated content is likely to become increasingly important in the future. The aim of this study was to investigate whether learners exhibit different revision behaviors when presented with different information about the author of a text (peer vs. AI). We further examined the impact of learners’ prior experiences, attitudes, and gender on text revision. Therefore, N = 303 learners revised two different texts: one labeled as peer-written and the other as AI-generated. The results revealed that while learners invested less time in revising a text labeled as AI-generated, information about the author did not affect the number of areas identified as requiring improvement or the number of revisions made. Moreover, learners who indicated greater prior exposure to media reports about AI-based text generators, a higher level of trust in AI, and a tendency toward ‘loafing’ in AI-assisted writing spent less time revising a text labeled as AI-generated. Conversely, learners with more experience in academic writing identified more areas for improvement and made more extensive revisions, regardless of the labeled authorship. © 2024 The Authors
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