Conference Agenda

Design researchers develop methods that blend design expertise and theoretical knowledge. Hence, design research emphasizes the importance of explicating intuitive knowledge and hands-on experience. Collective research that relies on more than one designer’s endeavors has also been expanding. In this paper, we discuss how to make sense of data when collected by two design researchers in separate spaces, under different conditions. Our project centered on the materiality of repair and involved data collection in two contexts. One researcher facilitated repair workshops, engaging in repairs and consulting with participants, while the other conducted individual repair work. Through biweekly meetings and conversations, we scrutinized our personal experiences and insights to generate research findings. This paper introduces a duo-ethnographic research through practice approach harnessing both researchers' experiences to conduct in-depth analyses. We advocate for the use of diffracting and intra-viewing as tools to systemically study conversations and validate the subjective experiences of practitioner-researchers.

This systematic literature review study explores how precedent knowledge, as a form of design knowledge, is understood across multiple domains of design (architecture, engineering, fashion, game, graphic, HCI, human performance technology, interior, public planning, product/industrial, production/movie/stage and general design theory). Analysis of 96 published sources was conducted, and a construct map was created to identify how authors define and discuss what precedent is, where precedent comes from, how precedent is collected and stored, when precedent is used, and how precedent works in the design process. While precedent knowledge appears to be prevalent across multiple domains of design, variation in understanding of the construct and use of language to describe it is wide. Against the initial construct map drawn from general design theory, additions were placed in the areas of sources of precedent and use of precedent.

This basic qualitative study informed by a hermeneutics approach presents how practicing designers across multiple domains of design define the construct of precedent knowledge, a form of design knowledge, and how they collect and use it in their design work. Interviews were conducted with 18 practicing designers across multiple domains of design, including fashion, product, graphic, game, instructional, and media design. Whether they used the specific term “precedent” or not, the study participants were able to address and discuss their precedent knowledge. They also reported multiple and varied sources of precedent, as well as multiple and varied practices in gathering and using precedent. The findings from this study verify, extend, and refine the construct map (included in this manuscript) resulting from a prior systematic literature review. Extensions to the construct map are use of precedent to assess innovation, and understanding of precedent as pre-schematized knowledge.

Data privacy is a complex subject where current approaches primarily focus on computing-centric narratives. These approaches have proven inadequate, yet they have established the status quo for emerging technologies including IoT in workspaces, or 'smart' workspaces, disregarding the sociocultural and behavioral dimensions of privacy within spatial contexts. This paper presents two key ideas 1) advocating a theory of change that complements the computing-focused approach (the umbra), with a broader approach based on human-centered experience and values, (the penumbra); and 2) embedding this holistic privacy approach in the early stages of smart workspace innovation through a generative design process involving multidisciplinary stakeholders. The outcome of this work is the ‘Designing with Privacy’ toolkit for collaboration among architects, designers, IoT engineers, privacy professionals, and other relevant stakeholders. The toolkit offers 14 value-based privacy prompts for creating and refining a collectively agreed-upon privacy brief to guide the design and development of smart workspaces.

Due to its interdisciplinary nature, research in design, more so than other disciplines, has to develop self-awareness to adapt to the inherent complexity of the contemporary world. This requires the use of big data as comprehensive self-descriptors, along with tools borrowed from the field of Artificial Intelligence (AI) to generate knowledge that researchers in this field can integrate with their own expertise to guide their research activities.

We consider a large-scale set of about 170000 design-related scientific publications and leverage natural language processing, machine learning, and data visualization to explore and capture the evolution of the design community. We identify and visualize recurring themes and discussions that helped shape the field. Our findings suggest that research in design is becoming increasingly interdisciplinary and interconnected and that AI-driven approaches can shed light on the future of the discipline and provide valuable insights for researchers and practitioners in the field

Maps have a rich history in design and design research. However, to date, their use and application have not been systematically studied. This paper proposes a model that classifies maps into four main types depending on how they help designers to visualize information: arranging entities on a plane, organizing content, synthesizing content and making sense. We use the model to systematically analyze and categorize maps from five design methods collections. Out of 399 methods in these collections, we identified 65 methods that were based on mapping. We found that the primary use of maps in design is to organize content on a two-dimensional plane. Through the proposed model, the paper provides designers with a tool to choose the right methods for their specific design situation and to scaffold designers towards more complex thinking.