"'I Thought We Said': Perceived Peer Support, Discourse Cohesion, and Regulation in Engineering Design"

Third-year doctoral student Ha Nguyen (right) is first author of an article published by the International Conference of the Learning Sciences exploring the collaboration patterns of university students in a project-based engineering course.

The title of the article is  “'I Thought We Said’: Perceived Peer Support, Discourse Cohesion, and Regulation in Engineering Design.“

Co-authors are Kyu Yon Lim; Lily Wu; Christian Fischer, University of Tuebingen; and Professor Mark Warschauer.

Nguyen is specializing in Teaching, Learning, and Educational Improvement. Her research interests include design of STEM learning experiences and multimodal assessment to study collaboration and conceptual understanding. She is advised by Warschauer and Professor Rossella Santagata.

Warschauer’s research foci include digital learning, language and literacy, STEM, and learning analytics. As director of the Digital Learning Lab at UC Irvine, he guides a range of research projects related to digital media in education.

Abstract

There is limited research on how perceived peer network influences student collaboration in project-based instruction. Research based on interviews or content analyses may overlook the semantic structure of discourse. In this study, we combine content analysis with computational linguistics to explore the collaboration patterns of 22 first-year students during face-to-face group design (n = 7,514 conversational turns) in a project-based engineering course. We find that students who reported smaller peer network generally produced discourse that provided new information, but less cohesion, compared to students with perceived median and large peer networks. Overall, students with small networks also engaged in group planning, evaluation, and shared regulation less frequently compared to the other two groups. Findings have implications for adjusting group arrangement in design activities. The study also illustrates the potential of incorporating computational approaches to detecting discourse.