“We're looking good”: Social exchange and regulation temporality in collaborative design

Ha Nguyen, Kyu Yon Lim, Liang Li Wu, Christian Fischer, Mark Warschauer

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


Collaborative tasks do not always promote equal learning. Varying levels of social interactions and regulation at the individual and group levels can influence knowledge construction efforts and learning success. To understand which collaboration patterns may be more conducive to learning, this study examined the relation between social exchange, regulation, and learning outcomes. Four project-based engineering undergraduate teams were audiotaped in collaborative tasks (7514 talk turns). Discourse was coded for regulation processes and types (self and socially shared regulation), and analyzed with Epistemic Network Analysis and Process Mining. We find that teams who reported more frequent social exchange engaged in shared regulation together with planning and monitoring more frequently, while teams with less exchange engaged in long durations of collaboration. Furthermore, students in teams with more engaged regulation reported enhanced beliefs in group efficacy to solve collaborative tasks. The study illustrates the potential of applying quantitative approaches to analyzing rich discourse.

Original languageEnglish
Article number101443
JournalLearning and Instruction
StatePublished - Aug 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Ltd


  • Discourse analysis
  • Network analysis
  • Process mining
  • Project-based learning
  • Regulation


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