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AI‐powered vocabulary learning for lower primary school students
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Type
Article
Citation
Wen, Y., Chiu, M., Guo, X., & Wang, Z. (2025). AI‐powered vocabulary learning for lower primary school students. British Journal of Educational Technology, 56(2), 734-754. https://doi.org/10.1111/bjet.13537
Abstract
In this exploratory mixed-methods study, we introduce and test our AI-powered vocabulary learning system—ARCHe, which embeds four AI functions: (1) automatic feedback towards for pronunciation, (2) automatic feedback for towards handwriting, (3) automatic scoring for student-generated sentences and (4) automatic recommendations. Specifically, our study of 140 students taught by six teachers in three primary schools in Singapore explores the links between these AI functions and students' learning engagement and outcomes via the analysis of their pre- and post-tests, post-surveys, focus group discussions and artefacts created via ARCHe. Results show improved Chinese character and vocabulary test scores after using ARCHe. Students' perceptions of ARCHe automatic recommendations and feedback towards pronunciation positively influence their emotional engagement. Also, students who perceived ARCHe automatic recommendations and feedback on handwriting more favourably than others reported greater cognitive engagement. Meanwhile, students whose groups created more sentences in classroom-based collaborative learning than others were more likely to show learning gains. This study provides insights for learning designers and educators on AI's potential in language learning, with recommendations for future research directions.
Date Issued
2025
Publisher
Wiley
Journal
British Journal of Educational Technology