This paper provides a brief introduction to the field of creativity studies. After more than 60 years of scientific study, there is much that has been learned about how to teach and facilitate creative thinking. We review some of the well-known methods for fostering creativity on demand, as well as the research that has explored the efficacy of these approaches.

Design creativity involves developing novel and useful solutions to design problems. The research in this article is an attempt to understand how novelty of a design resulting from a design process is related to the kind of outcomes, described here as constructs, involved in the design process. A model of causality, the SAPPhIRE model, is used as the basis of the analysis. The analysis is based on previous research that shows that designing involves development and exploration of the seven basic constructs of the SAPPhIRE model that constitute the causal connection between the various levels of abstraction at which a design can be described. The constructs are state change, action, parts, phenomenon, input, organs, and effect. The following two questions are asked. Is there a relationship between novelty and the constructs? If there is a relationship, what is the degree of this relationship? A hypothesis is developed to answer the questions: an increase in the number and variety of ideas explored while designing should enhance the variety of concept space, leading to an increase in the novelty of the concept space. Eight existing observational studies of designing sessions are used to empirically validate the hypothesis. Each designing session involves an individual designer, experienced or novice, solving a design problem by producing concepts and following a think-aloud protocol. The results indicate dependence of novelty of concept space on variety of concept space and dependence of variety of concept space on variety of idea space, thereby validating the hypothesis. The results also reveal a strong correlation between novelty and the constructs; correlation value decreases as the abstraction level of the constructs reduces, signifying the importance of using constructs at higher abstraction levels for enhancing novelty.

Two studies tested whether introducing images to designers during the design process lead to more useful design solutions as evaluated by the end users’ willingness to use the final design. It was hypothesized based on theories in cognitive science and design that there were at least two paths from images to usefulness. One path concerns analogically transferring within-domain properties to the design solution. The other path concerns mentally simulating end-user characteristics and preferences and inclusion of the user in the resulting design. Study 1 supported that random images led to increased outcome usefulness, and supported both hypothesized paths, by using within-domain products and end-user images as input. Study 2 showed that the image categories competed for attention, and that the within-domain product stimuli attracted the most attention and was considered the most inspirational to the designers. The practical use of the technique may lead to only marginally original products perhaps limiting its applicability to incremental innovation.

Conceptual design is a creative process. Designers create functions to satisfy customer needs and behaviors and forms to fulfill their functions. Although cognitive processes are at the center in developing new ideas, they are rarely taken into account in research and development of design support methods and systems. It is conceivable that if one understands how cognitive processes are stimulated to generate design ideas, then more effective methods and tools can be developed to support conceptual design. In this article, a cognitive model of conceptual design is developed to capture the relationships among design entities, design operations, and cognitive processes. A protocol analysis is performed to evaluate the model, and a cognitive experiment carried out to study the creative patterns and stimulating relationships. The results show that designers exhibit patterns of creative design behavior, and that these patterns can be captured and instilled into the design process to promote creativity.

The main hypothesis investigated in this paper is based upon the suggestion that the discursive reasoning in architecture supported by an explicit knowledge of spatial configurations can enhance both design productivity and the intelligibility of design solutions. The study consists of an examination of an architect's performance while solving intuitively a well-defined problem followed by an analysis of the spatial structure of their design solutions. One group of architects will attempt to solve the design problem logically, rationalizing their design decisions by implementing their explicit knowledge of spatial configurations. The other group will use an implicit form of such knowledge arising from their architectural education to reason about their design acts. An integrated model of protocol analysis combining linkography and macroscopic coding is used to analyze the design processes. The resulting design outcomes will be evaluated quantitatively in terms of their spatial configurations. The analysis appears to show that an explicit knowledge of the rules of spatial configurations, as possessed by the first group of architects can partially enhance their function-driven judgment producing permeable and well-structured spaces. These findings are particularly significant as they imply that an explicit rather than an implicit knowledge of the fundamental rules that make a layout possible can lead to a considerable improvement in both the design process and product. This suggests that by externalizing the design knowledge and restructuring it in a design model, creative thought can efficiently be evolved and stimulated.

Fixation prevents the associations that are bridges to new designs. The inability to see alternative solutions, or even to see how to map known solutions onto current problems, is a particularly acute problem in the design of software-intensive systems. Here, we explored two related ways of liberating fixated thinking: abstracting and rerepresenting. Although both techniques helped designers generate original ideas, not all the added ideas fit the problem constraints. We discuss ways the results might be used to generate reflective design aids that help designers to first generate original ideas and later prune them.

This paper presents the use of first-order logic to improve upon currently employed engineering design knowledge management techniques. Specifically, this work uses description logic in unison with Horn logic, to not only guide the knowledge acquisition process but also to offer much needed support in decision making during the engineering design process in a distributed environment. The knowledge management methods introduced are highlighted by the ability to identify modeling knowledge inconsistencies through the recognition of model characteristic limitations, such as those imposed by model idealizations. The adopted implementation languages include the Semantic Web Rule Language, which enables Horn-like rules to be applied to an ontological knowledge base and the Semantic Web's native Web Ontology Language. As part of this work, an ontological tool, OPTEAM, was developed to capture key aspects of the design process through a set of design-related ontologies and to serve as an application platform for facilitating the engineering design process. The design, analysis, and optimization of a classical I-beam problem are presented as a test-bed case study to illustrate the capabilities of these ontologies in OPTEAM. A second, more extensive test-bed example based on an industry-supplied medical device design problem is also introduced. Results indicate that well-defined, networked relationships within an ontological knowledge base can ultimately lead to a refined design process, with guidance provided by the identification of infeasible solutions and the introduction of “best-case” alternatives. These case studies also show how the application of first-order logic to engineering design improves the knowledge acquisition, knowledge management, and knowledge validation processes.

This is the second paper in the series on shape decompositions and their use as shape approximations. This time we investigate hierarchical and topological shape decompositions or hierarchies and topologies. We showed earlier that bounded decompositions behave the same way as shapes do. The same holds for hierarchies and topologies, which are special kinds of bounded decompositions. They are distinguished by their algebraic structures, which have many important properties to facilitate their application as shape approximations. We provide an account of their properties with an emphasis on their application.