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Abstract Engineering design is a continuous and iterative process, where early-stage decisions significantly impact subsequent design outcomes. This study investigates the influence of AI-assistance during early stages of design on subsequent design stages and measures the change in both design outcomes and cognitive processing in the brain. Sixty undergraduate engineering students participated in a two-stage design task. Students were first asked to identify design constraints related to the sustainable redevelopment of a site on campus either using human imagination or utilizing generative AI to assist them. Students, in both groups, without the aid of generative AI, then developed conceptual design ideas for redevelopment. The results indicate that the AI-assisted group identified significantly more design constraints (p < 0.05) and subsequently without the aid of AI developed a greater number of design concepts related to environmental sustainability. Brain imaging analysis revealed that AI assistance reduced the neuro-cognitive effort during constraints identification and had a residual effect in reducing neuro-cognitive effort during the concept design phase, particularly in the right frontopolar prefrontal cortex – a region associated with complex, abstract thinking. These findings suggest that AI-assisted design can enhance design efficiency by optimizing reducing cognitive effort and improving early-stage design outcomes. Future research should explore human-AI collaboration strategies to maximize its benefits in engineering design workflows. 

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. 

processes used in designing and relate them to the metrics used in psychology for idea creativity, ie, novelty and fluency. Our goal was to test the reliability of psychometric measures of creativity to assess creativity in team design. We studied 19 teams of 3 professional engineers that engaged in a one hour-long design task. Design tasks have a greater ecological validity than single repetitive tasks like the AUT and the RAT. Engaging in a design task involves a wide range of cognitive activities, which contribute to creative ideation and to expanding the design space. This study focused on the relationship between the teams’ design idea creativity and design behaviors during the task. We explored to what extent design collaboration between teammates, design evaluation and the co-evolution of the problem-solution space relate to the psychometric measures of idea creativity. Results suggest no specific trend in the correlation between collaboration and idea creativity as measured by the metrics used in psychology, while more cognitive focus on problemsolution co-evolution negatively correlates with these measures of idea creativity. The paper concludes with potential explanations for this lack of correlation. 

Abstract The research presented in this paper investigated the changes that occur in the prefrontal cortex (PFC) when new ideas are introduced during engineering design. Undergraduate and graduate engineering students (n = 25) were outfitted with a functional near-infrared spectroscopy (fNIRS) headband. Students were asked to design a personal entertainment system while thinking aloud. New ideas were timestamped with the fNIRS data across 48 channels grouped into eight regions within the PFC. The data were preprocessed using temporal derivative distribution repair motion correction, finite impulse response bandpass filter, and the modified beer-lambert law to convert optical density into hemoglobin concentration. Baseline neurocognitive activation and physiological noise were removed. The study found a significant decrease in oxygenated hemoglobin in the left dorsolateral prefrontal cortex and a subregion of the left ventrolateral prefrontal cortex when new ideas were introduced during design. This finding begins to provide a neurocognitive signature of what a new idea looks like as it arises in the brain. This could be used to develop tools and techniques to inhibit this brain region or use this insight to predict when designers will experience a new idea based on their neural activation. 

Situatedness in design suggest that designing is situated within the design process or the cognitive actions taken by the designer, the designer's expertise and know-how, the designer's experience generally and the interactions in the specific design task being undertaken as well as the interactions with the design artefact generated. In this paper, we analyzed the situatedness of design concepts generated by teams of professional engineers during a design task. The method combines protocol analysis, Natural Language Processing and network theory to provide a representation and a measurement of design situatedness overtime. Providing empirical evidence of the situatedness of concepts has been overlooked in design research. The method and results presented in this paper outlines the foundation to empirically explore design situatedness. 

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. 

Abstract The think-aloud protocol provides researchers an insight into the designer's mental state, but little is understood about how thinking aloud influences design. The study presented in this paper sets out to measure the cognitive and neurocognitive changes in designers when thinking aloud. Engineering students (n=50) were randomly assigned to the think-aloud or control group. Students were outfitted with a functional near-infrared spectroscopy band. Students were asked to design a personal entertainment system. The think-aloud group spent significantly less time designing. Their design sketches included significantly fewer words. The think-aloud group also required significantly more resources in the left and right dorsolateral prefrontal cortex (DLPFC). The left DLPFC is often recruited for language processing, and the right DLPFC is involved in visual representation and problem-solving. The faster depletion of neurocognitive resources may have contributed to less time designing. Thinking aloud influences design cognition and neurocognition, but these effects are only now becoming apparent. More research and the adoption of neuroscience techniques can help shed light on these differences.