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Abstract Understanding team diversity has become essential for modern-day organisations. This study explores the impact of knowledge diversity in design teams through computational simulations. By analysing design space characteristics, we study how diverse teams perform compared to less diverse counterparts. Results reveal that highly diverse teams exhibit increased efficiency, quicker convergence, and larger but sparser design spaces. This work contributes to understanding the impact of knowledge diversity in design teams and sets the stage for future systematic studies of diversity. 

Abstract Design is widely understood as a domain-independent notion, comprising any activity concerned with creating artefacts. This paper shows that models can be viewed as artefacts, and that the design of models resembles the design of artefacts in other domains. The function-behaviour-structure (FBS) ontology of design is applied to models, mapping generic characteristics of models derived from literature on modelling onto basic, design-ontological categories. An example of model design, namely the CRISP-DM model for designing data mining models, is analysed and compared with models of designing in other domains (systems engineering, mechanical engineering, software engineering, and service design). The results show that there are fundamental commonalities but also differences, revealing the need for further research in developing a theory of model design. 

Multidisciplinary teams have become the norm in design and relates to the complexity of the artifact designed. In this article, we study multidisciplinary teams’ design behaviors by combining protocol analysis, Natural Language Processing and network science. Three teams composed of professional mechanical and electrical engineers took part in this study. Designers engaged in the design activity with similar design processes and spend more cognitive effort on evaluating their design artifact when collaborating. Creating a network of the topic explored based on designers’ disciplines produces their design spaces and illustrates the influence of context knowledge on the design situation. Mechanical engineers tend to tackle user-centered issues while electrical engineers focused more on product related one. For most of the topics covered like with the end users, the product in context of usage, and technological aspects of the product, we observed collaboration between disciplines. Using networks to represent design spaces and design processes could become a tool to support team design collaboration. 

Designers advance in the design processes by creating and expanding the design space where the solution they develop unfolds. This process requires the co- evolution of the problem and the solution spaces through design state changes. In this paper, we provide a methodology to capture how designers create, structure and expand their design space across time. Design verbalizations from a team of three professional engineers are coded into design elements from the Function-Behavior- Structure ontology to identify the characteristics of design state changes. Three types of changes can occur: a change within the problem space, a change within the solution space or a change between the problem and the solution spaces or inversely. The paper explores how to represent such changes by generating a network of design concepts. By tracking the evolution of the design space over time, we represent how the design space expands as the design activity progresses. 

Abstract This paper investigates how the core technical processes of the INCOSE model of systems engineering differ from other models of designing used in the domains of mechanical engineering, software engineering and service design. The study is based on fine-grained datasets produced using mappings of the different models onto the function-behaviour-structure (FBS) ontology. By representing every model uniformly, the same statistical analyses can be carried out independently of the domain of the model. Results of correspondence analysis, cumulative occurrence analysis and Markov model analysis show that the INCOSE model differs from the other models in its increased emphasis on requirements and on behaviours derived from structure, in the uniqueness of its verification and validation phases, and in some patterns related to the temporal development and frequency distributions of FBS design issues. 

Abstract Co-evolution accounts have generally been used to describe how problems and solutions both change during the design process. More generally, problems and solutions can be considered as analytic categories, where change is seen to occur within categories or across categories. There are more categories of interest than just problems and solutions, for example, the participants in a design process (such as members of a design team or different design teams) and categories defined by design ontologies (such as function-behaviour-structure or concept-knowledge). In this paper, we consider the co-evolution of different analytic categories (not just problems and solutions), by focussing on how changes to a category originate either from inside or outside that category. We then illustrate this approach by applying it to data from a single design session using three different systems of categorisation (problems and solutions, different designers and function, behaviour and structure). This allows us to represent the reciprocal influence of change within and between these different categories, while using a common notation and common approach to graphing quantitative data. Our approach demonstrates how research traditions that are currently distinct from each other (such as co-evolution, collaboration and function-behaviour-structure) can be connected by a single analytic approach. 

Abstract In this paper, we present results from an experiment using EEG to measure brain activity and explore EEG frequency power associated with gender differences of professional industrial designers while performing two prototypical stages of constrained and open design tasks, problem-solving and design sketching. Results indicate no main effect of gender. However, among other main effects, a consistent main effect of hemisphere for the six frequency bands under analysis was found. In the problem-solving stage, male designers show higher alpha and beta bands in channels of the prefrontal cortices and female designers in the right occipitotemporal cortex and secondary visual cortices. In the design sketching stage, male designers show higher alpha and beta bands in the right prefrontal cortex, and female designers in the right temporal cortex and left prefrontal cortex, where higher theta is also found. Prioritising different cognitive functions seem to play a role in each gender's approach to constrained and open design tasks. Results can be useful to design professionals, students and design educators, and for the development of methodological approaches in design research and education. 

Abstract This paper proposes a relationship between design thinking and computational thinking. It describes design thinking and computational thinking as two prominent ways of understanding how people address design problems. It suggests that, currently, each of design thinking and computational thinking is defined and theorized in isolation from the other. A two-dimensional ontological space of the ways that people think in addressing problems is proposed, based on the orientation of the thinker towards problem and solution generality/specificity. Placement of design thinking and computational thinking within this space and discussion of their relationship leads to the suggestion of a dual process model for addressing design problems. It suggests that, in this model, design thinking and computational thinking are processes that are ontological mirror images of each other, and are the two processes by which thinkers address problems. Thinkers can move fluently between the two. The paper makes a contribution towards the theoretical foundations of design thinking and proposes questions about how design thinking and computational thinking might be both investigated and taught as constituent parts of a dual process.