Augmenting Technical Editors: A Quasi-Experimental Study of AI-Assisted Copyediting

Kim Sydow Campbell University of North Texas ; Ryan K. Boettger University of North Texas ; Chris Lam University of North Texas

Abstract

Technical editing research has examined the potential of artificial intelligence (AI) tools, yet empirical studies on their effectiveness remain limited. This quasi-experimental study investigates whether an AI-assisted tool improves copyediting performance and explores editor perceptions. The study compared 33 students’ editing performance with and without AI assistance. The results showed that an AI tool provided selective benefits, failing to raise overall correction rates but improving detection of AI-flagged errors. Perceptions varied by skill level, with stronger editors finding AI to be more distracting than helpful. The authors consider the teaching implications of this study and suggest that future research should test the effectiveness of various AI tools across different technical content types.

Journal
Journal of Business and Technical Communication
Published
2026-09-18
DOI
10.1177/10506519261485218
CompPile
Open Access
Closed
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