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.

@en

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.@en

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.’ @en

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.@en