TY - GEN
T1 - Mapping the Horizon
T2 - 14th International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2025
AU - Yang, Yao
AU - Yin, Xiyang
AU - Lin, Haoming
AU - Lam, Chi Kin
AU - Wei, Wei
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - The emergence of Generative AI (GenAI) is reshaping educational practices, particularly in collaborative learning environments. Despite its growing adoption, there remains a limited understanding of its thematic focus, learning outcomes and challenges. This scoping review, conducted in accordance with PRISMA-ScR guidelines, synthesizes findings from 30 peer-reviewed studies published between 2023 to 2025, examining the integration of GenAI in collaborative learning contexts. Three key themes emerged, GenAI tools (e.g., chatbots), collaborative aspects (e.g., feedback, self-regulated learning), and outcomes. Chatbots were frequently linked to enhancements in feedback and self-regulated learning, which in turn contributed to improved cognitive and behavioral outcomes. Among learning outcomes, cognitive gains were most prominently reported, followed by affective and behavioral benefits. Key challenges identified include technical limitations, pedagogical misalignments, and ethical concerns. Notable opportunities for future work involve longitudinal investigations of student-AI interactions, the development of AI literacy frameworks, and teacher professional development aimed at aligning GenAI use with pedagogical goals. This review advances the current understanding of GenAI in collaborative learning and offers direction for future research and practice in this rapidly evolving field.
AB - The emergence of Generative AI (GenAI) is reshaping educational practices, particularly in collaborative learning environments. Despite its growing adoption, there remains a limited understanding of its thematic focus, learning outcomes and challenges. This scoping review, conducted in accordance with PRISMA-ScR guidelines, synthesizes findings from 30 peer-reviewed studies published between 2023 to 2025, examining the integration of GenAI in collaborative learning contexts. Three key themes emerged, GenAI tools (e.g., chatbots), collaborative aspects (e.g., feedback, self-regulated learning), and outcomes. Chatbots were frequently linked to enhancements in feedback and self-regulated learning, which in turn contributed to improved cognitive and behavioral outcomes. Among learning outcomes, cognitive gains were most prominently reported, followed by affective and behavioral benefits. Key challenges identified include technical limitations, pedagogical misalignments, and ethical concerns. Notable opportunities for future work involve longitudinal investigations of student-AI interactions, the development of AI literacy frameworks, and teacher professional development aimed at aligning GenAI use with pedagogical goals. This review advances the current understanding of GenAI in collaborative learning and offers direction for future research and practice in this rapidly evolving field.
KW - Collaborative learning
KW - GenAI
KW - Generative AI
KW - Scoping review
UR - https://www.scopus.com/pages/publications/105033212711
U2 - 10.1109/TALE66047.2025.11346681
DO - 10.1109/TALE66047.2025.11346681
M3 - Conference contribution
AN - SCOPUS:105033212711
T3 - TALE 2025 - 2025 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, Proceedings
BT - TALE 2025 - 2025 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 December 2025 through 7 December 2025
ER -