doi: 10.18178/ijiet.2026.16.10.2734
The Metacognitive Catalysis Model: How Teacher Interaction Amplifies AI-enhanced Translation through Dual-path Mediation
Pengbiao Zhang1
,
Yi Zhu1 ,
Fengjunzi Wang1,* ,
Xinjin Song2
- 1Department of Foreign Languages, Hubei Business College, Hubei, China
- 2School of Chinese language and literature, Southwest Minzu University, Sichuan, China
- Manuscript receivedFebruary 10, 2026
- revisedFebruary 28, 2026
- acceptedJune 8, 2026
- publishedOctober 26, 2026
Abstract
In the domain of Technology-Enhanced Language Learning (TELL), this mixed-methods study proposes a Metacognitive Catalysis Model to explain how Teacher–Student Interaction (TSI) shapes Artificial Intelligence (AI)-assisted translation competence through dual-path mediation. Quantitative data from 134 Chinese English as a Foreign Language (EFL) learners showed that the experimental group achieved greater gains in Common European Framework of Reference for Languages (CEFR)-aligned translation scores than the control group (9.1% vs. 4.1%; Cohen’s d = 0.46), alongside reduced performance variability (ΔSD = −2.15). Mediation analyses indicated both a direct association between Doubao use and translation ability (B = 0.15, p = 0.008) and an indirect pathway via metacognitive construction (B = 0.31, p < 0.001), with Teacher-Student Interaction (TSI) strengthening the relationship between metacognition and translation performance (B: 0.43 → 0.66, p = 0.003). Qualitative findings further suggest reduced anxiety and enhanced self-regulation under AI-supported and teacher-scaffolded conditions. Overall, the results provide evidence for the role of metacognitive mediation in AI-assisted translation learning and highlight the importance of integrating AI feedback with teacher-guided scaffolding. Implications include the need for structured instructional design, targeted teacher training, and careful consideration of cross-cultural and contextual factors in AI-supported language learning.
Keywords
- metacognitive catalysis model
- dual-path mediation
- Teacher-Student Interaction (TSI)
- Artificial Intelligence (AI)-enhanced translation
- Metacognitive Theory (MT)
How to Cite
Pengbiao Zhang, Yi Zhu, Fengjunzi Wang, and Xinjin Song, "The Metacognitive Catalysis Model: How Teacher Interaction Amplifies AI-enhanced Translation through Dual-path Mediation," International Journal of Information and Education Technology, vol. 16, no. 10, pp. 2798-2811, 2026. https://doi.org/10.18178/ijiet.2026.16.10.2734
Copyright & License
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).