Method Teaching is an essential approach for training novice designers to think and act like designers. Methods are commonly used in design education, yet with varying outcomes and experiences for students. There is a need to better understand how individual and contextual factors influence the effectiveness of Method Teaching. In this quasi-experimental pre-post-intervention study, we investigate how group composition, motivation, Design Mindset (D-Mindset0.1), Self-efficacy (GSES), Ambiguity tolerance (TAS), and Sensation-seeking (BSSS) influence students’ learning through Method Teaching. Our results show that Method Teaching increases Design Mindset scores and that the effectiveness of Method Teaching is influenced significantly by the three personality traits and the level of prior Design Mindset.

Designers rely on many methods and strategies to create innovative designs. However, design research often overlooks the personality and attitudinal factors influencing method utility and effectiveness. This article defines and operationalizes the construct design mindset and introduces the Design Mindset Inventory (D-Mindset0.1), allowing us to measure and leverage statistical analyses to advance our understanding of its role in design. The inventory’s validity and reliability are evaluated by analyzing a large sample of engineering students (N = 473). Using factor analysis, we identified four underlying factors of D-Mindset0.1 related to the theoretical concepts: Conversation with the Situation, Iteration, Co-Evolution of Problem–Solution and Imagination. The latter part of the article finds statistical and theoretically meaningful relationships between design mindset and the three design-related constructs of sensation-seeking, self-efficacy and ambiguity tolerance. Ambiguity tolerance and self-efficacy emerge as positively correlated with design mindset. Sensation-seeking, which is only significantly correlated with subconstructs of D-Mindset0.1, is both negatively and positively correlated. These relationships lend validity D-Mindset0.1 and, by drawing on previously established relationships between the three personality traits and specific behaviors, facilitate further investigations of what its subconstructs capture.

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.’

Behavioural design has been gaining momentum to address critical societal challenges such as elderly care. At the same time, it struggles to deal with complex challenges and integrate multiple contextual factors' influence in domains like healthcare. Behavioural design processes lack guidance on how to prevent this and instead define problems that are ecologically valid. Conventional design methods do guide designers to do this. Thus there is a need to investigate how design methods can support behavioural designers to explore the context and integrate multiple perspectives on the problem, resulting in context-sensitive problem definitions. To respond to this need, we present a case where designers used a combination of design methods to investigate the complex context of hygiene in nursing homes. We show how combining different design methods supported the designers in advancing their understanding of a complex context and the problematic behaviours that occurred in it. We conclude by discussing the importance of using design methods to reveal important insights at the early stages of the behavioural design process.

As the design discipline is expanding and increasingly contributing to solving complex, socio-technical challenges in society, its role evolves alongside this expanding scope. A significant contribution of the design discipline is its methodologies and the expertise to facilitate transdisciplinary work in these complex innovation arenas. This emphasizes the importance of design methods and, at the same time, puts higher demands on their efficacy, robustness, and usability. However, there is a lack of understanding of the method development process, the standards and norms constituting high-quality design methods, as well as the transfer and use of these methods and how they impact practice. More specifically, there is a need to understand the entire lifecycle of methods – across the research and practice communities. The literature is fragmented, and some aspect is only addressed in isolation. In this paper, we bring together existing research and propose an initial model of the lifecycle of methods in design. We discuss implications and
recommendations for future research.

Designing for socio-technical engineering systems requires that professionals, stakeholders and end-users with diverse perspectives, experiences and expertise co-create in meaningful and goal-directed processes. Such efforts typically require substantial planning, staging, execution and managing, and an important part of that is the careful selection of effective methodology to support these activities. Methodology captures key procedural knowledge that is central to both education and practice. The selection of methods and tools is a critical first step in the process of using methodology and is prone to biases that might influence such decisions for the worse. In this chapter, we provide an overview of the state of the art on the selection of methodological means in engineering systems design and the broader design literature. We do so by focusing on five aspects: i) the method user; ii) method content; iii) method selection; iv) acquisition of new methods; and v) selection aid. To link theory to practice, we review how method selection is aided in 20 online design toolkits. Then, building on a taxonomy of thinking errors and biases in cognitive science, we identify relevant biases in choosing methodological means in engineering system design.

Behavioural design is an important area of research and practice key to addressing behavioural and societal challenges. Behavioural design reflects a synthesis of design and behavioural science, which draws together aspects of abductive, inductive, and deductive reasoning to frame, develop, and deliver behaviour change through purposefully designed interventions. However, this synthesis creates major questions as to how methods are selected, adapted, and used during behavioural design. To take a step toward answering these questions we conducted fifteen interviews with globally recognised experts. Based on these interviews we deliver three main contributions. First, we provide an overview of the methods used in all phases of the behavioural design process. Second, we identify behavioural uncertainty as a key driver of method use in behavioural design. Third, we explain how this creates a tension between design and scientific concerns—related to interactions between abductive, inductive, and deductive reasoning—which must be managed across the behavioural design process. We bring these insights together in a basic conceptual framework explaining how and why methods are used in behavioural design. Together these findings take a step towards closing critical gaps in behavioural design theory and practice. They also highlight several directions for further research on method use and uncertainty as well as behavioural design expertise and professional identity.

Behavioural Design is a critical means to address human behaviour challenges including health, safety, and sustainability. Practitioners and researchers face difficulties in synthesising relevant perspectives from across fields, as behavioural challenges are complex and multi-dimensional. This study takes a three step theory-building approach. First, we review behavioural theories and models primarily rooted in psychology, and discuss them in relation to design perspectives to identify parameters key to behavioural design. Next, we synthesise previously fragmented behavioural and design parameters and propose the Behavioural Design Space (BDS) framework, including: Cognition, Ability, Motivation, Timing, Social, and Physical Context. Last, as a demonstration of its use, we apply the BDS framework as lens on observed expert behavioural designer’s ideation. Our findings are twofold. First, the synthesis of generic behavioural and design parameters allow us to investigate expert behavioural designer’s ideation across five diverse cases. This illustrates the BDS’ potential of providing relevant overview across diverse domains. Second, the expert behavioural designers observed often utilised the less abstract parameter, Physical Context, and favoured low variation of parameters within concepts. This point to a need for support to help designers discover potential pitfalls and blind spots, as well as further study of behavioural design ideation.

Design methods capture key procedural knowledge, central to design process, practice, and education. However, a more robust explanation of the method phenomenon is needed. We move towards answering this need by proposing, and quantitatively testing, a Method Content Theory; addressing i) how methods function in context; ii) the elements of method content i.e. Method Framing, Method Rationale, Method Goal, Method Procedure, and Method Mindset; and iii) predictors of method performance. We provide initial quantitative validation for the proposed theory demonstrating strong predictive power for methodological performance indicators. We build on this to define a future research agenda. Our results have implications for research, education and practice, along with the potential for actionable insights in design methodology, method development and validation.

The proper use of methods is increasingly important as design challenges are more complex and involve more stakeholders. Such work also demands high reflective ability from designers. Reflective thought processes do not necessary produce positive outcomes for the process and the individual involved. Positive reflection is goal oriented while negative reflection is typically self-oriented. In design education, reflection by students is often treated as rather trivial or only rudimentary support is offered. Research in cognitive science shows that poor reflection can hurt students’ well-being, abilities and confidence over time. Thus, there is a need to better understand method use and reflection in design education more specifically when done poorly. We take a theory-building approach and interviewed 12 design students and recent graduates and investigated instances of method use where these led to negative experiences and effects. In doing so, we show different types of negative experiences that students have when using methods, the effects that these experiences have and how they relate to problematic use of methods and poor reflection practices. We end with implications for design education and design research.

Behavioural design is a critical means to address challenges surrounding human behaviour. However, practitioners and researcher face difficulties in synthesising relevant perspectives from across fields as behavioural challenges are complex and multi-dimensional. Taking a theory-building approach, this study explore how expert behavioural designers navigate in this complex design space by examining the creative outcome of their current ideation practice. The findings reveal that the designers favour ‘holding’ out of the four identified ideation patterns: holding, shifting, pairing, and mixing.

Delft Design Guide provides an overview of the perspectives, models, approaches, and methods used in the bachelor's and master's curriculum of Industrial Design Engineering at Delft University of Technology (TU Delft). Some of these are unique to the university, others are well known and are used by designers worldwide. Designing products and services at this faculty is considered a systematic and structured activity, deliberately and purposefully, and with moments of increased creativity.

The methods and techniques are each described in a practical one-page text, illustrated for further clarification and enriched with images that should encourage reflection and further reading.

Design students can use the book as a reference guide in their design projects and in managing their personal development. Design teachers can use the book as a reference guide to assist students in learning a method. Design professionals can use the book as a reference guide to support their design processes

Uncertainty is central to engineering design and new product development (NPD). While there has been substantial focus on dealing with uncertainty in technical systems and design information, how engineering designers react to and manage uncertainty is also critical to performance. However, an important gap remains in understanding what activities NPD teams engage in based on the specific uncertainty types they face. This gap is investigated via a conceptual framework detailing four uncertainty types (technical, organisational, resource and market) and three project activities (information, knowledge sharing and representation). Evidence is presented from two engineering design cases with 45 interviews, observations, and secondary data. Based on this, specific links are described between uncertainty type and project activity as follows: technical uncertainty drove representation activity, organisational uncertainty drove knowledge sharing activity, resource uncertainty drove knowledge sharing activity, and market uncertainty drove information activity. These findings are developed into a number of propositional relationships between the four uncertainty types and specific project activities, which form the basis for a number of implications for engineering design research and practice.

Uncertainty drives project activity in new product development (NPD), and its resolution is crucial to project performance. However, there is a major gap in understanding the causal links between different uncertainty types and the project activities they trigger. Engineering managers lack guidance on how best to respond to different uncertainty types. We close this gap by experimentally contrasting responses to two uncertainty types central to NPD: technical and organizational uncertainty. We describe responses with respect to core engineering project activities: representation, information, and knowledge sharing. We present evidence from an experiment involving 50 professionals and 74 master's students. The results show that uncertainty type has a significant effect on activity response, and that there is a significant ordering effect within this response. Based on the identification of a new response type, change of situation, our findings show that technical uncertainty drives change of situation and representation activity, while organizational uncertainty drives information- and knowledge-sharing activities. This provides the basis for three main contributions of this article. First, we identify “change of situation” as a new type of response to uncertainty in NPD. Second, we describe different responses to technical and organizational uncertainty. Third, we characterize an ordering effect in responses to uncertainty.

Modern design organizations need to continuously develop how they innovate in response to a changing innovation landscape. Developing methodology based on best practices is a powerful way to do so. However, there is currently no structure for developing methodology in a way that is (1) consistent and flexible, (2) user-centered, and (3) aimed at learning and continuous development of the methodology and the practice it supports. This paper presents a framework designed to support the development of a methodology toward meeting these aims and functions as an architecture for design doing (ADD). The framework promotes action at two levels: 1) it captures best practices that are transferrable to other projects and contexts, and 2) it encourages individuals to identify and apply values, principles and processes relevant to daily practice. It also supports the co-creation of methodology by multiple stakeholders. We illustrate the application of the framework with a case of the Philips Customer Decision Journey methodology.

Design research faces a critical 'impact gap' where the potential for scientific and practical impact is yet to be fully realised. A key means of bridging this gap is the adoption of fundamental theory from other fields to support clarification and synergy in design research. In this paper we examine one of the main candidates for adoption: dual-process theory of cognition. Cognition forms a common element across much of the design literature and leads to fundamental dual-process theories of reasoning. While dual-process theory has started to be recognised in design research, its widespread recognition and potential utility have not been widely explored. Following a conceptual theory development approach we identify and logically describe interactions between dual-process theory and design research. We conclude the paper with a proposition of a design research framework with a core rooted in dual-process theory, and based on this, an agenda for theory-driven design research. This contributes to the debate on how to improve impact, and theoretical and scientific rigour in design research, and provides a concrete agenda for discussion and development within the community.