Early phases of the design process require designers to select into view elements of the problem that they deem important. This exploration process is commonly referred to as problem framing and is essential to solution generation. There have recently been calls in the literature for more precise representations of framing activity and how individual designers come to negotiate shared frames in team settings. This paper presents a novel research approach to understand design framing activity using a system thinking lens. Systems thinking is the way that we understand a system’s components and the interrelations to create interventions, which can be used to move the system outcomes in a more favorable direction. The proposed approach is based on the observation that systems as mental representations of the problem bear some similarity to frames as collections of concepts implicit in the designer’s cognition. Systems mapping – a common visualization tool used to facilitate systems thinking – could then be used to model external representations of framing, made explicit through speech, and sketches. We thus adapt systems mapping to develop a coding scheme to analyze verbal protocols of design activity to retrospectively represent framing activity. The coding scheme is applied on two distinct datasets. The resulting system maps are analyzed to highlight team problem frames, individual contributions, and how the framing activity evolves over time. This approach is well suited to visualize the framing activity that occurs in open-ended problem contexts, where designers are more focused on problem finding and analysis rather than concept generation and detailed design. Several future research avenues for which this approach could be used or extended, including using new computational methods, are presented.

Natural Language Processing (NLP) has been extensively applied in design, particularly for analyzing technical documents like patents and scientific papers to identify entities such as functions, technical feature, and problems. However, there has been less focus on understanding semantic relations within literature, and a comprehensive definition of what constitutes a relation is still lacking. In this paper, we define relation in the context of design and the fundamental concepts linked to it. Subsequently, we introduce a framework for employing NLP to extract relations relevant to design.

This research aims to explore the existence of metacognition during the use of text-to-image generators in the design ideation stage. We recruited five participants with a design background to use Midjourney as an ideation tool and to produce three sketches at the end of their task. Through semi-structured interviews and retrospective verbalization, we collected data on their thought processes. The qualitative analysis revealed clear indications of metacognitive engagement, such as monitoring and evaluating, which opens the path for future research into the impact of AI on design cognition.

This study aimed to identify and compare the EEG activities associated with semantic and episodic memory retrieval during creative processes. Episodic and semantic memory induction studies were conducted and EEG was used to collect data. The results showed that (i) Episodic and semantic memory retrieval are related to the frontal lobe area; (ii) Semantic memory retrieval is evoked more swiftly compared with episodic memory retrieval (ii) Prior to episodic memory retrieval, semantic memory retrieval is evoked first.

This study explores the construction, characterization, and measurement of the design space using a novel approach that centres on First Occurrences (FOs) and Re-Occurrences (ROs) as metrics. Expert architects' cognitive behaviours during the design process were investigated empirically to gain insights into design space evolution. Findings reveal a consistent generation and revisiting of ideas, signifying an ongoing development of the design space. Future research should incorporate diverse methodologies and broader participant sample for a more comprehensive understanding.

Mental Imagery is a focus for design cognition research, with most research focusing on visual mental imagery, it has been highlighted that mental imagery encompasses more aspects than visual, including emotion known as multimodal mental imagery. So as researchers and educators we need to understand the cognitive process and how to best stimulate it. This paper looks at design students use of visual and emotional mental imagery and its impact on their ability to produce creative outcomes during the ideation stage of the design process.

Scholars in economics, psychology, and business have recently defined narrative as the underlying mechanism by which humans internally process information and drive a decision forward. In this paper, we study narrative's use in design across Design Society publications. We discuss how narrative's role as the driver of design decision-making is an important, but missing, element of the design literature. We explain how engineers will be expected to move the design process forward despite facing decisions where the information is simultaneously too much to process, conflicting, and incomplete.

This article presents an fNIRS experiment investigating cognitive differences between physical and digital prototyping methods in designers (N=25) engaged in open and constrained design tasks. Initial results suggest that physical prototyping yields increased hemodynamic response (i.e., brain activity) compared to digital design, and that constrained design yields increased hemodynamic response compared to open design, in the prefrontal cortex. Further work will seek to triangulate results by investigating potential correlations to design processes and design outputs.

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.

Chronobiology studies physiological variations due to the time of day, an unexplored factor in design research. This paper explores the effect of time of day on designers' physiological responses in idea generation. Convergent (CT) and divergent (DT) thinking, as building blocks of designing, are explored using pupil dilation as a proxy for cognitive load. Time of day and educational background are explored for engineering and industrial designers. Results show a larger pupil diameter in the afternoon than in the morning, especially for DT, with higher values for industrial designers.

Research on empathy has been surging in popularity in the engineering design community since empathy is known to help designers develop a deeper understanding of the users’ needs. Because of this, the design community has become more invested in devising and assessing empathic design activities. However, research on empathy has been primarily limited to individuals, meaning we do not know how it impacts team performance, particularly in the concept generation and selection stages of the design process. Specifically, it is unknown how the empathic composition of teams, defined here as the average (elevation) and standard deviation (diversity) of team members’ empathy, would impact design outcomes during nominal group concept generation and early concept screening. Therefore, the goal of the current study is to investigate the impact of team empathy on nominal group concept generation and early concept screening in an engineering design student project. This was accomplished through a computational simulation of 13,482 teams of non-interacting brainstorming individuals generated by a statistical bootstrapping technique. This simulation drew upon a design repository of 806 ideas generated by first-year engineering students. The main findings from the study indicated that the impact of the elevation and diversity of different components of team empathy varied depending upon the specific design outcome (number of ideas, overall creativity, elegance, usefulness, uniqueness) and design stage (concept generation and concept screening). The results from this study can be used to guide team formation in engineering design.

Failure is part of the design process, and yet there is limited knowledge around how product design students perceive failure in their work. This pilot study aims to understand how a small sample size of undergraduate product design students conceptualize success and failure during specific stages of their design projects. This study uses a two-step data collection and analysis process. First, we collected responses from students on topics related to success and failure in a survey. Second, interviews were conducted with a subset of the survey respondents where these emergent topics were discussed and refined. In analyzing the responses, the research team used the Double Diamond Design process framework to organize what factors students deemed a success or failure within each stage. In summary, our preliminary findings indicate that determining success or failure is driven by the connection to the problem statement regardless of the stage; that student designers refer to failure as a spectrum but then in their examples showcase a binary view on the topic; and that examples of failure are often the opposite of success, reinforcing the notion of binary success vs. failure during student design projects.

Design neurocognition is an emerging research area that can provide insights into the black box of designers’ cognitive processes. However, work to date has focused on neurocognition on its own, without integrating this with other design measures. This paper presents the results of a pilot study which brings together designer neurocognition with design output and assessment of the design process followed in a constrained prototyping activity comparing use of physical and digital Lego. This was achieved via EEG data capture, a TLX survey and measures of design output variance. Differences between physical and digital prototyping methods were found with respect to Task Related Powers of EEG signals and the design process followed with digital prototyping methods found to take longer, require more effort and cause more frustration. No differences were found with regard to design output. Whilst the sample size used (n=12) was small, future studies will use large sample sizes to increase their statistical power and will consider alternative EEG or fNIRS to capture brain activity due to challenges with the headset used in this study.

Designers are experiencing greater mental demands given the complexity of design tools, necessitating the study of cognitive load in design. Researchers have identified task- and designer-related factors that affect cognitive load; however, these studies primarily use self-reported measures that could be inaccurate and incomplete. Little research has tested the accuracy and completeness of self-reported measures and we aim to explore this gap. Towards this aim, we seek to answer the question: How does cognitive load vary based on the different design representations used, and do these differences depend on the measure of cognitive load? From our results, we see that the design representations vary in the range of cognitive load experienced by designers when using them. Moreover, this role of the range of cognitive load variance was observed given our use of pupil diameter. These findings call for the use of a multi-modal approach for measuring cognitive load with the combined use of subjective (e.g., self-report) and objective measures (e.g., physiological measures), as well as the use of both retrospective (e.g., self-report) and concurrent measures (e.g., physiological measures).

This research investigates changes in team behavior and communication through interruptions and gestures, due to design process strategies in pre-formed remote teams for conceptual design tasks. Understanding creative remote team behavior is important due to the increase of remote communication in knowledge work. Teams were given a creative or analytical condition intervention to facilitate their conceptual design team process. The research contributes to the human-computing interaction literature by characterizing changes in distributed team behavior due to process method interventions. The creative condition exhibited a decrease in interruptions. The analytical condition exhibited a decrease in gestures and an increase in problem characterization at the cost of ideation discussion. Remote team members can better gauge which meetings or work tasks are best to be done in person or remotely by gauging not just the task but also the team behavior.

Chronobiology is the science that studies the role of time in biology. The study of time in human bodies revealed the presence of internal rhythms related to the time of day. Considering divergent thinking as one of the essential cognitive activities of conceptual design, this paper presents the results of investigating the effect of time of day on designers’ brain activity while performing divergent thinking tasks. An experiment was run with a revised Alternative Uses Task, measuring brain activity with an electroencephalogram (EEG) device. Students with different educational backgrounds were recruited for this experiment, including engineering and industrial design students, to determine if the time of day affected them differently. The brain waves and related power results show significant differences with respect to the time of day and educational background. The differences are particularly evident considering the interaction of these factors. Further studies are required to understand the relationship between the differences detected and the designers’ behavioural performance and to identify which time of day is most effective for idea-generation activities for designers.

Mindset has been identified as an essential aspect of design and innovation, impacting both behaviours and performance. However, the concept of design mindset is elusive. Often design mindset is used indistinguishably from design behaviour, diminishing the complexity of the mechanisms and cognitive processes underlying design behaviour. As the initial step in researching these mechanisms, we operationalise the concept of design mindset and present the design mindset inventory (D-Mindset0) to measure it. The initial inventory centered around 16 agreement-to-value statements related to design practice. To analyse the inventory, we conducted an exploratory factor analysis based on 473 master students from different engineering disciplines participating in a course on innovation in engineering. The analysis revealed a four-factor structure with 11 final items. The four factors align with the concepts of ‘conversation with the situation,’ ‘iteration,’ ‘co-evolution of problem-solution,’ and ‘imagination.’

This paper presents an EEG (Electroencephalography) study that explores the correlation between the EEG variation across design stages and the quality of the design outcomes. The brain activations of 33 volunteers with engineering backgrounds were recorded while performing a design task using a morphological table to develop an amphibious bike. The EEG variations from the analysing/selecting stage to the illustrating stage were analysed based on the EEG frequency band and channel sets. A significant correlation between the detail level of the design outcome and the power variation mode was observed in theta, alpha and gamma bands, each involving different channel sets. Compared to the assessment results from two evaluators, using EEG variations as a proxy of the detail level of the design outcome could reach a maximum accuracy of 0.727, precision of 0.765, and recall of 0.889. These results also provide suggestions on the selection of the frequency bands and channel sets to achieve better prediction performance according to each metric.

Mental imagery is the experience of perceiving an object within one's own mind and is a subjective experience, leading to difficulties in the research and understanding of the phenomenon. This paper documents the development and verification of a framework for researching the elements of mental imagery. The framework was developed following a review of both psychology and design literature which signified three fundamental conceptual viewpoints of mental imagery: imagery modalities, dimensions of imagery ability, and imagery processes. The aim of this framework is to allow for structured research on mental imagery in any given research field. This is verified through discussion for the product design engineering discipline and provides a base for future work on this topic. The conclusions made in this paper reveal that mental imagery, and particularly visual mental imagery, is largely considered to be integral in design overlooking the different realities of designers and confirming a greater need to understand mental imagery experiences in product design engineering.

Engineering design in new product development is a constant battle between creativity and strict structure. As researchers look to optimize the process, each stage is placed under a microscope to put designers in the best position to develop better products for companies in a cost effective manner. One idea in improving product development is the concept of incorporating the Human-centered Design into functional analysis. However, critiques of these functional analysis methods cite an unnecessary amount of resources needed to invest in these steps, a restriction in creativity, and a high necessary level of effort from the design teams. The goal of this research will be to address these critiques by incorporating theories from cognitive research and Human-centered Design into the functional analysis process. This work will propose a new method aimed to improve the quality of the function model of the design space, increase the creativity freedom of the designers, and be accessible to engineering students and industry engineers alike.