The research objective of this award is to determine the cognitive differences of different engineering design methods. The understanding of engineering design based on scientific evidence is still in its infancy. The approach is to utilize protocol studies, under development in design cognition, using on a principled coding scheme founded on Gero?s Function-Behavior-Structure ontology of designing. Individuals will be taught a range of design methods. Design teams will be formed and given open-ended design tasks. Design teams will be studied using the protocol method while employing one of the taught methods. The resulting design proposals will be evaluated. The protocols will be segmented and coded using the principled coding scheme. The resulting codings and the ensuing linkographs will be analyzed for cognitive structures using statistical techniques including clustering and Markov chain analysis. In addition, entropy analyses of the linkographs and the change in entropy over time will be calculated. The results from these analyses will form the basis of the comparison of the cognitive differences between the engineering design methods studied. A correlation between engineering design cognitive behavior and design outcomes will be carried out. Deliverables will include: empirical data on engineering design behavior in the form of videos of design sessions of teams using different design methods; transcriptions of the design sessions; coded data; linkographs; and the results of the analyses. These represent different levels of granularity from data through to highly processed information.
If successful, the results of this research will provide support for a science of engineering design by providing a principled method and a base of results that can be utilized to compare methods and models. The award will demonstrate analytical techniques for the analysis of engineering design protocols using engineering design domain knowledge, techniques which can be used across the entire domain of engineering design. The results will provide the foundation for the evaluation of engineering design tools and techniques.
Among a nation’s goals are competitive leadership in the international marketplace and excellence in productivity. Superior design, a fundamental prerequisite for superior products and systems, is one of the keys for achieving these goals. Engineering design is one of the foundations of these keys and is the basis of much of the technological and economic change that occurs around us. Engineering design is one of the areas of human endeavor that is value-adding both economically and socially. In order to improve America’s international competitiveness a better understanding of engineering design is required in order to improve it. The science of engineering design requires both theoretical models and methods and empirical data on which to found and test those models and methods. Unlike causal based methods that rely on engineering science that is founded on the behavior of the physical world, design methods are founded on human behavior and need to be tested cognitively, ie, by studying the thinking behavior of humans. Different design methods have been claimed to produce different design thinking, this project studied the design thinking of student engineers designing using different design methods (called concept generation techniques) to determine whether was a scientific foundation to these claims. Three concept generation techniques widely used in industry were tested for the differences they produce in design thinking. These were: brainstorming, morphological analysis and TRIZ (which is the acronym for a system of inventive ideas). The results showed that, surprisingly, brainstorming and morphological analysis are more similar in behavior than had previously been thought while TRIZ produces significantly different behavior. See Figures 1 and 2. More generally, the results of this project included empirical data derived from experiments, which provide support for a "science" of engineering design by providing a principled method of data derivation and a base of results that can be utilized to compare these and other methods and models. The project demonstrated analytical techniques for the analysis of engineering design studies of design thinking using engineering design domain knowledge, techniques which can be used across the entire domain of engineering design. The significance of these results is that: they give design educators evidence-based indicators of the effects of their teaching and allow them to modify their courses to produce outcomes of more relevance to industry, and they give designers and design managers access to ways to influence the expenditure of cognitive effort.
