Computing is often perceived as abstract, e.g., writing code on screens. In contrast, fabrication (making) produces tangible artifacts. Integrating these domains creates CS+X interdisciplinary experiences that increase student interest and confidence in both computing and another field in which they have an interest. Prior work has also demonstrated how making enhances computing curriculum and how fabrication technologies attract diverse student populations, including those with disabilities. This BoF will bring together educators who are or wish to incorporate hands-on fabrication into computer science courses, particularly at introductory levels in K-12 and higher education. We aim to broaden participation by reaching students who might not otherwise engage with traditional computing instruction. BOF leaders will encourage small-group discussions on topics including: existing hands-on approaches and their outcomes, evaluation methods for fabrication components in CS courses, learning objectives these approaches support, and optimal curriculum placement (e.g., intro courses, K-12, early learners). We will collaboratively develop frameworks for implementation and assessment to better understand fabrication's impact on CS education and goals for broadening participation.

Life cycle assessment (LCA) is a methodology for holistically measuring the environmental impact of a product from initial manufacturing to end-of-life disposal.However, the extent to which LCA informs the design of computing devices remains unclear.To understand how this information is collected and applied, we interviewed 17 industry professionals with experience in LCA or electronics design, systematically coded the interviews, and investigated common themes.These themes highlight the challenge of LCA data collection and reveal distributed decision-making processes where responsibility for sustainable design choices-and their associated costs-is often ambiguous.Our analysis identifes opportunities for HCI technologies to support LCA computation and its integration into the design process to facilitate sustainability-oriented decision-making.While this work provides a nuanced discussion about sustainable design in the information and communication technologies (ICT) hardware industry, we hope our insights will also be valuable to other sectors.

Illusion-knit fabrics reveal distinct patterns or images depending on the viewing angle. Artists have manually achieved this effect by exploiting "microgeometry," i.e., small differences in stitch heights. However, past work in computational 3D knitting does not model or exploit designs based on stitch height variation. This paper establishes a foundation for exploring illusion knitting in the context of computational design and fabrication. We observe that the design space is highly constrained, elucidate these constraints, and derive strategies for developing effective, machine-knittable illusion patterns. We partially automate these strategies in a new interactive design tool that reduces difficult patterning tasks to familiar image editing tasks. Illusion patterns also uncover new fabrication challenges regarding mixed colorwork and texture; we describe new algorithms for mitigating fabrication failures and ensuring high-quality knit results.

We present an interactive design system for knitting that allows users to create template patterns that can be fabricated using an industrial knitting machine. Our interactive design tool is novel in that it allows direct control of key knitting design axes we have identified in our formative study and does so consistently across the variations of an input parametric template geometry. This is achieved with two key technical advances. First, we present an interactive meshing tool that lets users build a coarse quadrilateral mesh that adheres to their knit design guidelines. This solution ensures consistency across the parameter space for further customization over shape variations and avoids helices, promoting knittability. Second, we lift and formalize low-level machine knitting constraints to the level of this coarse quad mesh. This enables us to not only guarantee hand- and machine-knittability, but also provides automatic design assistance through auto-completion and suggestions. We show the capabilities through a set of fabricated examples that illustrate the effectiveness of our approach in creating a wide variety of objects and interactively exploring the space of design variations.