Collaborative design decision-making as social process

ABSTRACT

Collaborative design is recognised as being shaped by complex social, cognitive, material, and technical processes. In the case of design decision-making, however, the social dimension has yet to be fully understood as the product of the whole team dynamic rather than as simply the sum of the individual (cognitive) contributions. This paper examines the interactional work teams of first-time design students do that produces decisions in undergraduate engineering design projects. Close analysis of decision-making episodes, recorded in design meetings in a yearlong ethnographic study, reveals the joint social and situated work teams do to produce decisions. Students were found to do decision-making via three overlapping phases that were invariant across the database: (i) Design options emerge, (ii) teams orient to design options, and (iii) design decisions come off. This paper exemplifies these phases of decision-making as inherently – and not just incidentally – social, and illustrates how decisions are produced in novice design teams via these phases in multifarious ways. We argue for an explicit retrospective focus on the processes and consequences of team decisions following projects as an avenue for fostering the development of design judgment that engineering graduates will take into their professional practice.

KEYWORDS:

• Design education
• cooperative learning
• design judgment
• decision-making
• conversation analysis

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Chris Campbell, is an Assistant Professor of Adult Education in the University of the Fraser Valley's Faculty of Professional Studies (BASc in chemical engineering: University of Waterloo, Canada; BEd in science education: UBC, Canada; MEd in TESOL: University of Edinburgh, UK; PhD in curriculum and instruction: UBC, Canada). His work as an educator, curriculum specialist, teacher educator, and researcher focuses on the formal and informal contexts of science, technology, engineering, and English language education. He has an enduring interest in the learning, educational experiences, and academic and professional pathways of culturally and linguistically diverse learners in intercultural K‐20 contexts both domestic and international.

Wolff-Michael Roth is Lansdowne Professor of Applied Cognitive Science (MSc physics: University of Würzburg, Germany; PhD, School of Science and Technology, University of Southern Mississippi). He investigates knowing and learning across the lifespan in school, workplace, and leisure settings. His early work began in science education, but then expanded to the social studies of science, mathematics education, applied linguistics, phenomenology, and cultural-historical studies. The most-recent foci included research among aviation pilots and in a software development company. Michael’s early training included statistics in the social sciences. He has used multivaried statistics, Bayesian statistics, fuzzy logic, linear structural models, constraint satisfaction networks, and neural network modelling. He applies the same rigour to qualitative research, where he has drawn on ethnography, content analysis, discourse analysis, conversation analysis, interaction analysis, and phenomenological methods.

Alfredo Jornet, postdoctoral fellow from the University of Oslo, is licentiate in psychology by the University of Valencia (Spain) and has a PhD in educational sciences from the University of Oslo (Norway). His prior research has focused on the role of technology in learning across a wide range of formal and informal settings, including schools, science museums, training in aviation, and professional design. More recently, his research has included an interest in creativity and innovation in the context of professional design, arts-based education, and makerspaces. Mostly drawing from qualitative research methods, including ethnography and conversation analysis, several of his research projects have involved a Design-Based Research methodology.

Notes

1 We focus on four exemplifying episodes rather than 67 due to space concerns. Much as Sadi Carnot did not need 100,000 steam engines to describe and theorize its process but did so on the basis of one, this study uses examples that illustrate the fundamental processes at the heart of all the decision-making episodes identified in the database.

Additional information

Funding

This work was supported by the Social Sciences and Humanities Research Council of Canada [grant number 752-2012-2547].