Society & Economicsarticle2026-08-08

Sequential patterns of challenges and socially shared regulation of learning: a comparison of pre-service and in-service teachers’ collaborative learning

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Abstract

Abstract Socially shared regulation of learning (SSRL) can promote high-level collaborative learning. However, the sequential interplay between sociocognitive, socioemotional and motivational group-level challenges and SSRL strategies remains unclear, particularly in comparative analyses of pre-service and in-service teachers engaged in computer-supported collaborative problem-solving tasks. To address this gap, 33 pre-service and 33 in-service teachers were video-recorded in face-to-face settings while working in groups of three on collaborative problem-solving tasks within a virtual simulation on a desktop computer. A total of 25.7 h of video data were analysed using a theory-driven coding scheme that captured sociocognitive, socioemotional and motivational challenges, as well as collaborative regulatory activities grounded in the SSRL framework. Process mining was employed to visualise and compare sequential patterns of challenges and regulation. The findings indicate that pre-service teachers exhibited stronger sequential patterns linking planning, monitoring and controlling activities, whereas in-service teachers demonstrated more pronounced sequences involving monitoring and planning following socioemotional and motivational challenges. These differences reflect distinct tendencies in how collaborative learning activities were organised over time, rather than differences in effectiveness or learning outcomes. This study contributes to the learning sciences by extending SSRL research and offering theoretical and methodological insights into analysing collaborative learning as a dynamic process. From a practical perspective, the findings inform the pedagogical design of collaborative learning and teachers’ professional development by highlighting the need for profile-sensitive scaffolds that support shared planning, monitoring and adaptive regulation.

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View paper (DOI)Open access versionOpenAlexInstructional SciencePublished 2026-08-08

Authors: Faisal Channa, Piia Näykki, Päivi Häkkinen, Kristóf Fenyvesi, Takumi Yada

Institutions: University of Jyväskylä, Research Institute of the Finnish Economy