The DOI matches its Crossref record, with a small difference in title or year; 77 of the 79 references it cites were found in a registry or an index.
Incorporating a reflective thinking promoting mechanism into artificial intelligence-supported English writing environments
Abstract
Automated writing feedback supported by artificial intelligence (AI) techniques has attracted the attention of English as Foreign Language (EFL) researchers. However, there is insufficient evidence and inconsistent conclusions on the actual impacts of AI on students’ writing skills. In addition, in the field of EFL writing, there are few studies which have integrated appropriate teaching strategies to promote the effectiveness of EFL writing teaching and learning. Furthermore, it remains unclear how learners can effectively benefit from AI technology-based English writing. To solve this problem, this study proposed a reflective thinking promotion mechanism-based AI-supported English writing (RTP-AIEW) approach to deepen learners’ thinking and improve their EFL writing quality. To investigate the effectiveness of this learning approach, a quasi-experiment was conducted in two EFL writing classes in a university. One class (50 students) was the experimental group learning with the proposed RTP-AIEW approach, while the other class (53 students) was the control group learning with conventional AI-supported EFL writing. The results indicated that the proposed approach not only significantly improved the experimental group students’ English writing performance, but also improved their self-efficacy and self-regulated learning, and significantly reduced their cognitive load. In addition, students’ learning experience and perceptions are also discussed.
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“This heightened engagement, facilitated by the AI tool’s responsiveness, contributes to the observed improvements in writing skills and motivation (Liu et al., 2021; Utami and Winarni, 2023).”
From Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students (2023) · cites this paper as Liu et al., 2021
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Song, C., & Song, Y. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1260843 · Cited by 717
Marzuki, Widiati, U., Rusdin, D., Darwin, & Indrawati, I. (2023) · Cogent Education · doi:10.1080/2331186x.2023.2236469 · Cited by 524
Exploring Artificial Intelligence in Academic Essay: Higher Education Student's Perspective
Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., Darwis, A., & Marzuki (2023) · International Journal of Educational Research Open · doi:10.1016/j.ijedro.2023.100296 · Cited by 418
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Metadata
- Authors
- Liu, C., Hou, J., Tu, Y.-F., Wang, Y., & Hwang, G.-J.
- Affiliations
- Wenzhou University (CN)
- Fu Jen Catholic University (TW)
- Kaohsiung Medical University (TW)
- Corresponding author
- Hwang, Gwo-Jen
- Venue
- Interactive Learning Environments
- Publisher
- Informa UK Limited
- Published
- 2021-12-10
- Volume
- 31
- Issue
- 9
- Pages
- 5614-5632
- ISSN
- 1049-4820 (ISSN-L)
- 1744-5191
- OpenAlex
- W4200268598
- Cited by
- 231
- References
- 79
- Citations by year
- 2026: 53 · 2025: 88 · 2024: 61 · 2023: 20 · 2022: 9
- FWCI
- 88.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Interactive Learning Environments (publishedVersion)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Social Sciences › Education › English Language Learning and Teaching
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- EFL writing, reflective thinking, automated writing feedback, writing self-efficacy, student self-regulation, cognitive load, writing quality, learner perceptions, writing instruction strategies
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