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Synergizing AI and collaborative learning

A new approach to Chinese character acquisition in lower elementary education

Bibliographic Data

ID21632372
AuthorsJiachu Ye (0000-0002-0517-5710, Hunan University, corresponding author), Y B Yu (Hunan University), Yazi Yu (0009-0004-7522-505X, Hunan University), M J Zhang (0000-0003-4587-8127, Hunan University), Meiting Zhang (0000-0001-5848-7737, Hunan University), Shufang Long (Hunan University)
Year2026
Volume34
Issue3
Pages1697-1716
Publication date2026-03-16
Open AccessNo
TypeARTICLE
VenueInteractive Learning Environments (JOURNAL)
Journal identifiersISSN: 1049-4820 • E-ISSN: 1744-5191
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/10494820.2025.2528096
OpenAlexW4412172512
LanguageEN
Citations received2
References cited51

This study investigated the effectiveness of an AI-enhanced collaborative learning (AICL) framework in supporting Chinese character acquisition among second-grade students. Through a quasi-experimental design, 68 students were assigned to three conditions: AI-enhanced collaborative learning, collaborative learning without AI, and traditional learning. The intervention implemented a six-stage framework integrating AI-powered learning application with structured peer collaboration activities over a one-month period. Writing performance, learning motivation, and student perceptions were assessed through mixed-methods data collection. Results revealed that the AICL group significantly outperformed other groups in overall writing performance. While quantitative analysis showed no significant differences in learning motivation across groups, qualitative findings from student interviews indicated positive engagement with the AI-enhanced collaborative features, despite some technical challenges. The study contributes to ongoing discussions in the learning sciences about how AI can support socially mediated learning. The findings demonstrate that integrating adaptive AI feedback with collaborative learning structures can provide effective support for early literacy development. They also underscore the importance of aligning technical tools with young learners’ developmental needs and ensuring system stability in real-world classroom settings. These insights suggest promising directions for implementing AI-enhanced collaborative approaches in elementary literacy education

Educational technology · Experiential learning · Mathematics education · AI in Service Interactions · Computer Science · Mathematics · Online Learning and Analytics · Psychology · Robotics and Automated Systems

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Citations per year2
Citation span2026 - 2026 (1)
Highly citedNo

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