Unpacking the Effects of Role Assignment on Interaction Processes in Socially Shared Regulation of Learning: A Multi-Method Approach
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| Title: | Unpacking the Effects of Role Assignment on Interaction Processes in Socially Shared Regulation of Learning: A Multi-Method Approach |
|---|---|
| Language: | English |
| Authors: | Yumin Zheng, Fengjiao Tu (ORCID |
| Source: | Journal of Educational Computing Research. 2026 64(4):989-1023. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 35 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research Tests/Questionnaires |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Undergraduate Students, Cooperative Learning, Electronic Learning, Learning Processes, Student Role, Interaction, Influences |
| DOI: | 10.1177/07356331261416827 |
| ISSN: | 0735-6331 1541-4140 |
| Abstract: | Ineffective interaction processes often hinder the success of socially shared regulation of learning (SSRL) in online settings. While role assignment is a common scaffolding strategy in online collaborative learning, its influence on SSRL-based interactions remains underexplored. This study employed a 10-week quasi-experimental design to compare a role-assigned group with a non-role group (N = 40 undergraduates). Data sources included questionnaires analyzed via T-test and chat transcripts examined through qualitative coding, epistemic network analysis (ENA), and lag sequential analysis (LSA). Results indicated that role yielded significantly higher frequencies and complexity in cognitive (χ² = 151.334, p < 0.001), social (χ² = 97.05, p < 0.001), and teaching interactions (χ² = 171.72, p < 0.001). Although the overall volume of emotional interaction did not differ, the role-assigned group showed significantly more shifts from negative to positive emotions. Interaction patterns varied by role, with the task leader dominating teaching episodes and the emotion regulator triggering the most positive affective shifts. These findings suggest that aligning task scripts with specific SSRL roles can foster deeper shared regulation. We provide evidence-based prompts and monitoring checkpoints, supported by computational analyses, to assist teachers and instructional designers in enhancing online collaborative learning within educational computing environments. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1502165 |
| Database: | ERIC |
| Abstract: | Ineffective interaction processes often hinder the success of socially shared regulation of learning (SSRL) in online settings. While role assignment is a common scaffolding strategy in online collaborative learning, its influence on SSRL-based interactions remains underexplored. This study employed a 10-week quasi-experimental design to compare a role-assigned group with a non-role group (N = 40 undergraduates). Data sources included questionnaires analyzed via T-test and chat transcripts examined through qualitative coding, epistemic network analysis (ENA), and lag sequential analysis (LSA). Results indicated that role yielded significantly higher frequencies and complexity in cognitive (χ² = 151.334, p < 0.001), social (χ² = 97.05, p < 0.001), and teaching interactions (χ² = 171.72, p < 0.001). Although the overall volume of emotional interaction did not differ, the role-assigned group showed significantly more shifts from negative to positive emotions. Interaction patterns varied by role, with the task leader dominating teaching episodes and the emotion regulator triggering the most positive affective shifts. These findings suggest that aligning task scripts with specific SSRL roles can foster deeper shared regulation. We provide evidence-based prompts and monitoring checkpoints, supported by computational analyses, to assist teachers and instructional designers in enhancing online collaborative learning within educational computing environments. |
|---|---|
| ISSN: | 0735-6331 1541-4140 |
| DOI: | 10.1177/07356331261416827 |
