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Leveraging an AI chatbot to support socially shared regulation in collaborative project-based learning

Authors
Kim, MinjiJeong, SoojeongLim, Cheolil
Issue Date
Jun-2026
Publisher
서울대학교 교육연구소
Keywords
AI chatbot; Collaborative learning; Project-based learning; Socially shared regulation
Citation
Asia Pacific Education Review, v.27, no.2, pp 799 - 812
Pages
14
Indexed
SSCI
SCOPUS
KCI
Journal Title
Asia Pacific Education Review
Volume
27
Number
2
Start Page
799
End Page
812
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/219674
DOI
10.1007/s12564-026-10114-0
ISSN
1598-1037
1876-407X
Abstract
Collaborative project-based learning (CPBL) offers rich opportunities for students to engage in authentic problem-solving, yet many students struggle to work effectively within a team. Prior studies have suggested that supporting socially shared regulation of learning (SSRL) can enhance collaboration and learning outcomes, but empirical evidence remains limited on how such support can be effectively implemented, particularly through AI-based tools. This mixed-methods study examined the potential of an AI chatbot, called RegTogether, which was developed to support SSRL in CPBL and implemented in high school classrooms with 30 participating students. This mixed-methods study examined the potential of an AI chatbot, called RegTogether, which was designed to support SSRL in CPBL and implemented in high school classrooms with 30 participating students. Quantitative results indicated that students in the experimental group who used the chatbot significantly outperformed those in the control group in group task performance. Qualitative analysis of post-interviews revealed that students perceived the AI chatbot as a supportive tool that facilitated both cognitive and socio-emotional aspects of collaboration. Overall, the findings suggest that AI chatbots hold promise as instructional tools for fostering SSRL in CPBL, while further refinements are needed to enhance their pedagogical effectiveness.
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