Abstract

Traditional research on design cognition typically employed artificial settings and quasi-realistic tasks. For example, Eastman’s (1970) pioneering studies focused on highly constrained space-planning problems in which the location of furniture items had to be optimised within a room of specified dimensions. Eastman’s approach arguably set the tone for design research over the next two decades, and although the tasks that researchers employed became more realistic, they mainly just ‘imitated’ key aspects of professional design problems (see Cross, 2001, for a review of this early literature). This restricted task focus meant that the situated and collaborative nature of design was omitted from the research agenda for many years. This was unfortunate given that factors associated with the social and cultural context of design seem paramount to understanding the authentic nature of design cognition. The past decade has witnessed a burgeoning of research on design cognition ‘in the wild’, focusing on expert designers and collaborative teams working on real tasks in natural environments. This move towards understanding design ‘in vivo’ is to be welcomed. Nonetheless, such research is associated with considerable complexity, which necessitates the selection and use of rigorous methods to achieve effective data collection and reliable data analysis. Here we tackle head-on the methodological challenges associated with studying real-world design cognition.