What does AI bring to second language writing? A systematic review (2014-2024)
Open accessAbstract
The rapid advancement of artificial intelligence (AI) technologies has introduced both opportunities and challenges to second language (L2) writing, and a new dimension to L2 writing research. To map the evolving landscape of AI-integrated L2 writing research, this systematic review analyzed 112 studies published between January 2014 and June 2024. The review focused on research contexts and participants, theoretical and methodological orientations, research setups, and key research issues. The analysis revealed that the majority of studies were conducted with undergraduates in the English as a Foreign Language (EFL) context. Most studies did not specify a theoretical framework; however, the predominant theoretical orientations were cognitive, technological-pedagogical, social, critical, and genre. The literature commonly employed eclectic or mixed methodologies, favoring (quasi-)experimental designs with short duration. The writing tasks investigated were varied, with a notable emphasis on elemental genres such as argumentative essays. The main research issues addressed included AI functionalities; students’ perceptions and experiences; impacts on students’ writing, cognitive, affective, and behavioral performance; teachers’ perceptions, teaching practices, and literacy development; and factors influencing AI use. The findings highlight the need for future research, particularly longitudinal studies focusing on the development of AI literacy in L2 writing.
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AI's pedagogical value increases when it is designed and taught as a process scaffold, focusing on what to do, when, and why, rather than merely as a text improver, focusing on what to change.
“This suggests a broader implication: AI's pedagogical value increases when it is designed and taught as a process scaffold, focusing on what to do, when, and why, rather than merely as a text improver, focusing on what to change (Aydın Yıldız, 2025;Feng et al., 2025;Zou et al., 2025).”
From Generative AI, visual scaffolds, and metacognition in EFL writing (2026) · cites this paper as Feng et al., 2025
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Zou, B., Wang, C., He, H., Li, C., Purwanto, E., & Wang, P. (2025) · Learning and Motivation · doi:10.1016/j.lmot.2025.102158 · Cited by 46 · see citing works
Sun, J., & Rui, J. (2026) · Journal of Educational Computing Research · doi:10.1177/07356331251399452 · Cited by 6 · see citing works
Generative AI, visual scaffolds, and metacognition in EFL writing
Chen, M.-R. A. (2026) · Language Learning & Technology · doi:10.64152/10125/73695 · Cited by 1 · see citing works
“This suggests a broader implication: AI’s pedagogical value increases when it is designed and taught as a process scaffold, focusing on what to do, when, and why, rather than merely as a text improver, focusing on what to change (Aydın Yıldız, 2025; Feng et al., 2025; Zou et al., 2025).”
- Authors
- Feng, H., Li, K., & Zhang, L. J.
- Venue
- Language Learning & Technology
- Published
- 2025-05-19
- Volume
- 29
- Issue
- 1
- Pages
- 1-27
- ISSN
- 1094-3501 (ISSN-L)
- OpenAlex
- W4413184455
- Cited by
- 51
- References
- 0
- Citations by year
- 2026: 38 · 2025: 13
- FWCI
- 36.43
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Language learning & technology (publishedVersion, cc-by-nc-nd)
- ScholarSpace (University of Hawaii at Manoa) (submittedVersion, cc-by-nc-nd)
- ResearchSpace (University of Auckland) (submittedVersion, cc-by-nc-nd)
- Funders
- Ministry of Education of the People's Republic of China (19YJA740012)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
- Keywords
- artificial intelligence, second language writing, AI-assisted writing, English as a foreign language, AI literacy, argumentative essay, student perceptions of AI, teacher perceptions, writing instruction, cognitive performance, affective performance, behavioral performance, literacy development
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