Search for: All records

Engineering design is a continuous and iterative process, where early-stage decisions significantly impact subsequent design outcomes. This study investigates the influence of AIassistance 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. 

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. 

Ideation is a key phase in engineering design and brainstorming is an established method for ideation. A limitation of the brainstorming process is idea production tends to peak at the beginning and quickly decreases with time. In this exploratory study, we tested an innovative technique to sustain ideation by providing designers feedback about their neurocognition. We used a neuroimaging technique (fNIRS) to monitor students’ neurocognitive activations during a brainstorming task. Half received real-time feedback about their neurocognitive activation in their prefrontal cortex, a brain region associated with working memory and cognitive flexibility. Students who received the neurocognitive feedback maintained higher cortical activation and longer sustained peak activation. Students receiving the neurocognitive feedback demonstrated a higher percentage of right-hemispheric dominance, a region associated to creative processing, compared to the students without neurocognitive feedback. The increase in right-hemispheric dominance positively correlated with an increase in the number of solutions during concept generation and a higher design idea fluency. These results demonstrate the prospective use of neurocognitive feedback to sustain the cognitive activations necessary for idea generation during brainstorming. Future research should explore the effect of neurocognitive feedback with a more robust sample of designers and compare neurocognitive feedback with other types of interventions to sustain ideation.