Representation Aiding to Support Performance on Problem-Solving Tasks

Abstract

A substantial literature has been developed that deals with the use of visual displays to support human problem solving. In particular, the cognitive systems engineering literature has emphasized the use of visual displays to improve performance on complex real-world tasks such as process control with the labels direct perception, ecological interface design, representational design, and semantic mapping, focusing on the use of representations that take advantage of powerful perceptual processes to support problem solving. Although the theoretical orientations and details of each approach are slightly different, they all share a fundamental core belief: The effectiveness of a graphical decision aid depends on relationships between the representation, the domain and associated task(s), and the characteristics of the agent (person). This review begins with a discussion of strategies for representation aiding, assuming that the appropriate domain semantics have been determined. It then discusses a core assumption in this literature that, in the design of complex real-world systems, designers cannot anticipate all the possible scenarios that could arise and must therefore design displays that support effective problem solving even when novel or unanticipated scenarios are encountered. Finally, the results of empirical studies of designs based on representation aiding are reviewed.