Conference Agenda

This paper focusses on the impact that AI tools may have in the field of technical drawing, sketching and visual communication. It is recognised that creating technical drawings from CAD can be a lengthy, repetitive process, and it is possible for AI tools to automatically generate drawings and cutting lists from 3D CAD data in seconds. The paper explores three key themes; firstly being the potential loss of skills, competency and understanding in producing technical drawings, secondly the ethical and legislative conundrum of producing professional technical drawings for manufacturing, architecture and civil engineering at the push of a button, and thirdly the dichotomy of engineering and design students learning slowly acquired fundamental drawing skills against the needs for industry to reduce the time from design to manufacture and construction, with comparisons to tools used in CAE. The paper concludes that hand drawn exercises, peer review and timed, invigilated assessments may be utilised to individually assess students skills and competency in drawing, as educators enter this new technological paradigm.

Sketching to communicate design ideas is an important step in the design process. Image-generative artificial intelligence (AI) tools are increasing in prevalence and popularity, and these tools are being explored as aids in the design process. In this paper, we describe an evaluation of an image-generative AI tool, Vizcom, which uses a sketch-based input alongside a text prompt. We explored the use of this tool in a course with undergraduate product design students who were working on medical device concepts with teams of biomedical engineering students. We wanted to explore the possibility that using Vizcom might help facilitate communication between collaborators from different disciplines. In the course, students each drew five concept sketches by hand, and then used those same hand sketches as Vizcom inputs, resulting in Vizcom renders. Our analysis of these sketch/render pairs indicated that there was no significant difference in understandability between the hand sketches and the AI-generated renders. The characteristics of the hand sketches: line quality, proportionality, and understandability, were all positively correlated with the proportionality and understandability of the AI-generated renders. Our results suggest that the use of Vizcom did not reduce the need for strong hand-sketching skills in communicating design concepts, but Vizcom may offer some communication benefits. Results may be different for other types of design concepts, as novel medical devices are likely less represented in the datasets used to train Vizcom and other generative AI models.

There has been much written about the importance and impact of artificial intelligence and its associated technologies and the place they will have within the design field[1][2]. No doubt artificial intelligence will emerge to be an important tool that designers of the future will be able to utilise in the development of future artefacts[3]. However, as with CAD and digital visualisation before it, we see AI as being an enhancement rather than a replacement of traditional design methodologies.

Product designers have traditionally been educated in making and materiality throughout their studies. With recent developments and integration of digital manufacturing tools, this approach has altered to accommodate these new paradigms[4]. However, designers creating physical objects still require an inherent understanding of the processes and materials that they are likely to encounter and work with. [5]. This is known as material intelligence and is one of the key aspects of designers of physical objects.

Like emotional intelligence, material intelligence requires its own customised educational scaffolding to develop the required skillset in the learner. Educational interventions require the correct contextual groundwork to maximise success [6]. A semi-structured, investigative and peer-supported approach which draws on real-world tasks and interactions is an important part of this support framework [7].

This paper explores a structured, multi-year approach to the development of material intelligence within undergraduate design programmes with scaffolded experiential learning and Constructionist ideas around education. It outlines the pedagogical interventions across several sub-disciplines of product design and how these can work in tandem with studio education to support strong material experiences amongst the student body.

REFERENCES

[1] C. McComb, P. Boatwright, and J. Cagan, “FOCUS AND MODALITY: DEFINING A ROADMAP TO FUTURE AI-HUMAN TEAMING IN DESIGN,” in Proceedings of the Design Society, Cambridge University Press, 2023, pp. 1905–1913. doi: 10.1017/pds.2023.191.

[2] J. Johnson, A. Hurst, and F. Safayeni, “MANAGING DATA-DRIVEN DESIGN: A SURVEY OF THE LITERATURE AND FUTURE DIRECTIONS,” in Proceedings of the Design Society, Cambridge University Press, 2023, pp. 2525–2534. doi: 10.1017/pds.2023.253.

[3] J. Saadi and M. Yang, “OBSERVATIONS ON THE IMPLICATIONS OF GENERATIVE DESIGN TOOLS ON DESIGN PROCESS AND DESIGNER BEHAVIOUR,” in Proceedings of the Design Society, Cambridge University Press, 2023, pp. 2805–2814. doi: 10.1017/pds.2023.281.

[4] V. Von Platen and Y. Kitani, “A DESIGNER’S UNDERSTANDING OF THE MAKER MOVEMENT,” in Proceedings of the Design Society, Cambridge University Press, 2023, pp. 101–110. doi: 10.1017/pds.2023.11.

[5] B. Marenko, “Digital Materiality, Morphogenesis and the Intelligence of the Technodigital Object,” in Deleuze and Design, vol. 9780748691555, B. Marenko and J. Brassett, Eds., Edinburgh, Scotland: Edinburgh University Press, 2015, pp. 107–138.

[6] S. Kurt, “An analytic study on the traditional studio environments and the use of the constructivist studio in the architectural design education,” Procedia Soc Behav Sci, vol. 1, no. 1, pp. 401–408, 2009, doi: 10.1016/j.sbspro.2009.01.072.

[7] A. Y. Kolb and D. A. Kolb, “The learning way: Meta-cognitive aspects of experiential learning,” in Simulation and Gaming, 2009, pp. 297–327. doi: 10.1177/1046878108325713.

Sketching is a historical means of sharing knowledge and remains vital for communication across disciplines. Drawing translates mental images and experiences into visual knowledge and expression. Sketching education is steeped in tradition, but emerging digital technologies like eye-tracking glasses allow researchers to, for the first time, see through the eyes of illustrators as they work. This exploratory study uses eye-tracking glasses to measure head and eye kinematics, eye gaze quantity and duration, and production script order of novice and expert illustrators. It introduces terminology, high-fidelity measurement tools, assessment methods, and insights that could influence future drawing pedagogy. Eleven illustration undergraduate students and three instructors wore eye-tracking glasses as they drew facial expressions while referencing live models. Results uncovered four categories of head pitch and eye saccade kinematics and expert and novice gaze differences referencing the model and drawing paper. Experts rapidly gaze at the reference 3.5 times more than the novice who gaze longer and 3.0 times more often than the expert. Novices gaze at their paper for 59% of their drawing time, compared to the experts at 40%. Experts had 18 rapid (less than 1.0 s.) paper gazes, while novices had 8. All participants followed a similar product script, beginning with light construction lines for the head, face, nose, eyes, and mouth in varying orders, then adding darker contour lines, adding detail from the centre outwards. Participants returned to refine eye and mouth facial details 25 – 35 times. This study uncovers previously unseen bio-mechanical movements and observational drawing methods.

The transition from secondary education to higher education for students pursuing a Product Design course is fraught with challenges. It is commonplace for first year product design students to face a variety of difficulties, with one of the most common issues being understanding and applying design sketching techniques. Most students often finding the transition from secondary education hard due to having to unlearn bad habits and re-learn good habits in the form of perspective, proportion, and positions. The understanding and implementation of the foundations of core design sketching skills is a critical aspect to grasp at the start of the higher education journey within the product design curriculum.

Secondary school design courses often focus on the basics, leaving students with limited exposure to more advanced sketching techniques and tools commonly used in higher education and the industry. Ensuring that students gain this new knowledge gradually is an important factor to consider when designing a design sketching syllabus. The teaching of core design sketching skills within the higher education environment coupled with the greater expectation ideation and iteration in a design studio context is a hurdle most students face and subsequently this has an impact on the quality and quantity of work produced. The shift in expectations from secondary to higher education can be overwhelming for students who are not adequately prepared and as such it is important to understand this transition and educational pathway to suitably prepare taught design sketching content. Furthermore, there are challenges with students increasingly seeking to embrace digital design tools to communicate, overlooking traditional/analogue tools. However, some students do not appreciate the need to develop fundamentals design sketching skills before transitioning to the digital alternatives. Subsequently, students are increasingly designing within the remits/restrictions of the digital tools by jumping ahead in the design process.

This paper seeks to discuss the design sketching background of students entering higher education in the product design sector. We examine the product design student design sketching pathway by exploring the education background prior to joining Nottingham Trent University (NTU), the design sketching education conducted at NTU within the first-year studies, and the aspirations of students moving forward with regards to preferred future education syllabi and their thoughts on design sketching in the industry context. A student survey completed by BA Product Design (SW/FT) students and BSc Product Design (SW/FT) students presents the student perspective leading onto a critical discussion. This discussion focusses on addressing the hurdles faced when trying to implement a seamless transition from secondary to higher education whilst attempting to further understands the needs and wants of a product design student. To conclude we will present a list of recommendations with regards to traditional and digital design sketching for higher education syllabus development and implementation.

Yacht design is a multidisciplinary sector where skills from design, architecture and engineering education are applied. The students involved in this field need to coordinate highly diversified areas of competence: design, architecture, ergonomics, and materials, with their respective specialized disciplinary articulations. The rise of AI tools for design modelling and sketching rapidly evolves the role of exterior and interior yacht designers in early-stage concept creation, opening debates within the professional context. The application of AI sketching in the yacht design industry is nowadays moving from inspiration tools to design creators, disrupting not only the daily designer's work but also the way curricular training offers are thought. Within the framework of the Executive Interior Yacht Design specialization course at the Politecnico di Milano, an instructional module focused on Advanced Drawing Skills was introduced to a cohort of students. This module was properly designed to guide students through an educational trajectory with a twofold aim: to provide future professionals skills for mastering AI technologies for yacht interior concepts and to support the development of capabilities to adapt to - and innovate in - a flexible framework.

This paper presents the course pilot case through its intended learning outcomes, methods, didactic tools, and learning exercises, evaluating the students activities results from the lecturers and participants perspectives. Furthermore, it assesses the whole learning experience through a dedicated survey. As results, the outcomes of the design activities and the learning survey are presented and discussed on three different levels: (i) output image quality (content adherence, variation, style, interference), (ii) student-AI interaction, and (iii) learning environment.

The study demonstrates the efficacy of education with and for AI in the context of the professional course in executive interior yacht design as an opportunity to provide students with methodologies and tools for concept design creation. Moreover, given the dynamic landscape of evolving generative models and platforms, the research points out how this course pilot case shifted the yacht design learning approach from applying knowledge to experiment practices. At last, the training challenges students in design with a high level of uncertainty and flexibility, emphasizing adaptability and resilience for the future yacht design career.