Social Cognition and Interactive Expertise in Natural and Computational Environments
Our research focuses on Social Cognition and Interactive Expertise in Natural and Computational Environments, hence SCIENCE Lab.
Areas as diverse as finance and business intelligence, education, transportation safety, freedom from crime and the threat of terrorism, public health, and environmental protection among others require the creation of information systems that support human cognitive processes such as learning and discovery, insight, creativity, reasoning and problem solving, coordination, and communication and that enable those innately human abilities to function at their best in information spaces that may include large volumes of data that are confusing, complex and uncertain.
These applications require technologies that support the blending of human cognitive abilities with computational processes. This in turn demands design methodologies that encorporate and advance a new translational cognitive science of human-information interaction. This new science must address research questions that emerge from field studies of "cognition in the wild'-- at different stages of cognitive development, by aging and handicapped individuals, as well as by expert decision makers across a broad range of domains and situations. It must be precise enough to effectively guide technology builders, interaction designers, managers and trainers of a new generation of computationally-sophisticated decision makers. Finally, it must be operationalized in new design methodologies that SIAT, SFUs innovative design school, is uniquely capable of creating.
SCIENCE Lab conducts the field studies and laboratory experiments to understand how humans can use information and communication technologies to achieve cognitive goals: understanding and knowledge-building, collaboration and coordination of activities. Much of this work falls under the label of visual analytics "the science of analytical reasoning facilitated by interactive visual interfaces".
The multidisciplinary field of visual analytics can be characterized by three types of innovation, all of which depend on some aspect of cognitive science and cognitive engineering:
Research in human cognition — a “science of analytical reasoning" ought to use scientific methods to develop and test theories of human cognitive performance. Here we see that the development of perceptual, cognitive, and computational aspects of analysis is a research priority. This has been recognized by the VEC and VSC, through a new Empirical Study submission category for papers at VAST to complement the older Theory and Model submission category.
Technology design — a science that focuses on reasoning as it is “facilitated by interactive visual interfaces” should develop cognitive engineering methods to develop those technologies. This is reflected in the home of VAST in VIS and IEEE, and the large number of Technique and Design Study papers at the conference.
Study of distributed cognitive systems— More through tradition than definition VA researchers have worked to see their science and their technologies used to make decisions and plan operations in the real world. The new Application submission category at VAST recognizes the value of these papers.
Our work typically begins with field studies of human interaction with graphical visualizations of data, knowledge and actions in decision making and operational management. It continues with field experiments, often using joint activity theory analysis of analytic dyads, e.g my birdstrike work with Boeing. It may include lab studies of the interaction of specific aspects of visualization and interaction with human cognitive architecture, e.g. the FINST studies for HRL and the 3D perception work with GM. Research outcomes inform the design and evaluation not only of visual information systems, but also the ways in which the technologies are used by analysts and the methods by which those analysts are selected and trained.
We have made it a priority for our research to be evaluated by peer reviews in each of these areas. Our lab studies and field experiments are evaluated by psychologists and other cognitive scientists, as is demonstrated by publications in Cognitive science, Psychonomics, and Association for Psychological Science conferences and journals. Our software and visualization work is evaluated by computing and engineering scholars for IEEE and ACM conferences and journals. The relevance and utility of my applications are reviewed by domain experts and demonstrated in conference publications in health, aerospace, and business information systems. The practical application of this work is also validated by engagement and funding from Boeing, General Motors, Nissan, NTT, MacDonald Dettwiler, Provincial Health Authorities, the World Bank, and the US Dept. of Homeland Security as well as two NSERC SPP grants and multiple Mathematics of Information Technology and Complex Systems (MITACS) internship clusters.