Social Aspects of Regulation: Measuring Socially-Shared Regulation in Collaborative Contexts

• In Event: Innovations in Researching Regulation of Learning in Solo and Collaborative Tasks

Abstract

Objectives: Emergent perspectives posit success in collaborative tasks requires self-regulation of individual learning, regulation with others (co-regulation), and regulation together (socially-shared regulation). This paper uses individual and shared data sources to examine regulation of a collaborative task; extends and applies analytical tools for examining divergence and convergence of individual and shared perspectives in planning; and conducts applied research in an authentic undergraduate task using technologies supporting regulation.
Theoretical Framework: Successful collaboration requires individuals to self-regulate learning (SRL) by constructing accurate task perceptions, setting goals, monitoring progress, and deliberately adapting to optimize learning. As collaboration involves co-coordinated effort directed toward a shared task outcome, successful groups must also collectively regulate learning (SSRL) (Hadwin et al., 2011). SSRL involves negotiating consensus of metacognitive knowledge of task requirements, goals, process, and progress among group members. To date, few studies have investigated how groups engage, sustain, and share regulation in collaborative tasks. Examining how individuals and teams respond to task and process challenges creates opportunities to examine individual and collective monitoring, evaluating and adapting of task perceptions, goals, strategies in a shared social space.

Methods: Participants included 100 students in a first year, undergraduate course. Students collaborated in groups of three on an online assignment involving co-constructing learning strategies, individually testing strategies, and co-constructing strategy evaluations. Three heterogeneous performance groups of three members each were chosen for cross-case comparison (Higher Performers, Improvers, and Low Performers) to examine (a) congruence between individual and shared task perceptions and goals; (b) quality of individual and shared task perceptions and goals; (c) congruence of group members’ perceptions of strategies for regulating collaborative challenges; and (d) level of individual engagement in collaboration.

Data Sources: Data included task performance, traces of collaborative process in the assignment wiki revisions, records of collaboration (e.g., chat records and meeting minutes) and students’ statements of individual and collaborative metacognitive knowledge and processes for the task in three online reflective tools: (a) the Personal Planning Tool (PPT) scaffolding individual metacognitive knowledge and processes, (b) the Shared Planning Tool (SPT) supporting group members’ negotiation of shared metacognitive knowledge and processes, and (c) the Personal Reflection Tool (PRT) supporting individuals’ self-evaluation of collaboration and goal attainment after the task.

Results: We found three patterns of collaboration including (a) co-construction, (b) distributed division of labour, and (c) allocation of labour to a single team member. Visual mapping of convergence and divergence of shared and individual statements and traces within groups indicated (a) groups struggled to socially share regulation of task perceptions, goals, and strategies for the collaborative task; (b) mapping of convergence and divergence within individual and group responses reveals informative patterns of socially shared regulation.

Significance: By combining data at the individual and group level, this study provides comprehensive and unique insight into the dynamics of collaborative teams with respect to regulatory processes. Examining congruence of metacognitive knowledge and processes has potential to inform the design of more supportive collaborative technologies.

Authors

• Allyson F. Hadwin, University of Victoria

• Mariel F.W. Miller, University of Victoria