Conference Agenda

Since 2010, the literature on Education for Sustainable Development has converged on a framework of key competencies that enable students to become relevant professional actors in the sustainability transition. We believe that the E&PDE community should build on this framework to improve the quality of pedagogical activities in design for sustainability. Our aim, through this paper, is to propose an assessment method to systematically evaluate students' competencies in relation to sustainability. We believe that this proposal will help researchers of our community in three ways. First, it will enable teachers to have a better understanding of the level of their students in each competence. Second, it will enable teachers to reflect on their pedagogical practices to better relate their pedagogical activities with competencies for sustainability. Third, it will provide to researchers a stronger validation process to evaluate the efficiency of pedagogical activities regarding competencies for sustainability. The self-assessment questionnaire we propose has been tested on 48 students, from 6 different classes. This Pilot-study enabled us to propose a ready-to-use questionnaire for colleagues of E&PDE community.

During product development (PD), the vision model method is used as a guide to ensure that development is progressing in the desired direction and that the results meet the original goals and expectations. Among other things, the method can also be used to collect feedback from stakeholders and, if necessary, to adapt visions and goals that are recorded and visualized in the vision model accordingly.

In addition, the literature suggests methods and tools for the strategic alignment of the project with sustainability aspects at the start of development projects. The Ten Golden Rules and the design-for-sustainability strategies are important guidelines for a development project in pd. The Ten Golden Rules represent a method for improving product quality and performance, while the design-for-sustainability strategies aim to minimize the environmental impact of products by means of guidelines. Both methods help to focus on the product life cycle and the impact of a product in it. In order to apply these guidelines in practice, they should be integrated into the development process from the outset.

This can be done by training developers and through targeted use in alignment meetings. This can be useful to ensure that the guidelines are adhered to throughout the development process.

Both alignment methods and the vision model are sometimes used independently or either one or the other. This article presents a concept for the active inclusion of sustainability requirements for a product in the vision model. The focus here is on the clear visualization of the goals to be achieved for the long-term orientation of development towards sustainability.

It is often cited that ‘80% of a product’s environmental impact is decided at the design stage’ (European Commission, 2012) and yet it can be very difficult to ensure that undergraduate students truly appreciate the impact of their decisions in the early stages of the traditional double diamond design process. Whilst lectures, statistics and information can give the students an academic outlook on end-of-life issues, there is much to be gained from a hands-on engagement in the delivery of education around these pressing problems.

This paper examines two case studies from two sessions where design for disassembly was taught in a practical way, with each student physically taking apart a waste laptop through a guided session completed in collaboration with a local community interest project focussed on WEEE. By examining feedback from each session, these case studies discuss the impact of physical sessions on the understanding of disassembly by undergraduates, and also its context and importance in the role of design in the circular economy.

The circular economy – a system that aims to keep materials and resources in constant flow, whilst also creating a regenerative future is arguably a critical system to be understood by all undergraduates, equipping them with the broadest sets of skills and contextural, experience-based understanding.

This paper introduces the concept of 'More-Than-Human Design Personae', a novel approach that integrates ecosystem services and social factors into the design process, particularly focusing on the development of applications and tools aimed at enhancing biodiversity and sustainable practices. Using the example of the field lark, we illustrate how an app for farmers can encourage biodiversity measures by embodying the persona of this species. Similarly, the incorporation of bats and wild bees personas demonstrates innovative methods for renovating buildings and brownfields, adhering to animal-aided design principles.

The essence of this approach lies in visualizing and understanding the needs and roles of non-human actors in our ecosystems, thereby fostering a more inclusive and holistic design ethos. This methodology is particularly relevant in the context of ethical, social, and environmental issues in design and engineering education, as discussed in the conference 'Design Education in the Generative AI Era'.

A significant part of this paper is dedicated to exploring how AI tools can be effectively utilized to break down complex ecological and social problems at the persona level. These tools can aid in visualizing the impact and interaction of various species within an ecosystem, thereby providing a clearer understanding of the interconnectedness of life. By integrating AI into the development of design personas, we can create more effective, sustainable, and biodiversity-conscious designs.

The paper argues that incorporating more-than-human perspectives in design education can lead to innovative solutions that address pressing environmental challenges. It emphasizes the need for future designers and engineers to be equipped with the knowledge and tools to consider a wider range of stakeholders in their work, going beyond human-centric approaches to include the intricate web of life that supports and sustains us.

Sustainable awareness, defined as the perception and understanding of the importance of caring for the environment and adopting sustainable practices, has gained increasing significance in today's context of environmental challenges. Education plays a pivotal role in promoting this awareness, from early stages to higher education. To achieve a meaningful shift toward more environmentally respectful behaviors, various pedagogical strategies have been explored, with the use of journals proving to be an effective tool for fostering reflection and the development of pro-environmental skills.

This text addresses the relationship between sustainable awareness and journaling, analyzing its importance in the educational process and in shaping individuals committed to environmental preservation. Additionally, it reviews studies exploring how education and knowledge levels correlate with environmental awareness, highlighting the relevance of higher education in promoting sustainable behaviors. Notably, the implementation of this method over the last two years among multidisciplinary students, from the first to the final year of professional education, has yielded highly favorable qualitative and quantitative results. These results demonstrate deep and positive reflections and compelling data on the utility of journaling in cultivating sustainable habits and awareness.

Through this exploration, the emphasis is on the importance of instilling values, attitudes, and pro-environmental knowledge through education and journaling, aiming for a meaningful shift toward a more sustainable and harmonious future with nature.

This contribution deals with circular design methods, which were identified and pre-selected with the help of a systematic literature research on the scientific database Scopus based on the requirements developed in a previous contribution for small and medium-sized enterprises (SMEs) and small development teams. Both design methods and design tools were identified, which are summarized in this contribution under the term circular design methods. The circular design methods are analyzed, categorized and elaborated upon with respect to these requirements to support Product Development (PD) getting more into circularity. The analysis provides insights on the current status of circular design methods and which development activities in the product development process (PDP) are supported by them. In addition, the evaluation scheme and the assessment of circular design methods for SMEs serves as a support for the selection of suitable circular design methods for development tasks and innovation activities. The contribution follows the overarching process for method selection according to Ernzer and Birkhofer, whereby existing circular design methods are first identified and then analyzed. The circular design methods are then organized in the context of a strategic level, resulting in an initial draft of a catalog of methods, to create from this the circular design toolkit, with 21 circular design methods that can be applied and integrated in SMEs and also pursues the overarching goal of a PD for the circular economy. This circular design toolkit can be developed and proposed in consideration of the product development process model of Integrated Design Engineering, as this approach can also be applied and implemented according to the requirements of SMEs. Finally, a selection of methods from the pre-filtered catalog of methods can be made at company level on an operational and project-specific basis (Ernzer & Birkhofer, 2002).

The aim of this contribution is to provide product developers in SMEs with a preselection of methods suitable for circular product development by analyzing the existing CDM from circular design in order to support their development work and activities in the direction of CE and circular design.

This article explores the integration of digital and physical spaces in Society 5.0, emphasising the role of design and AI education in addressing societal challenges through technological innovation. It advocates for an agile action research approach in design education to equip students with practical skills for real-world challenges, aligning with global trends in human-centric design. The research methodology involves a collaborative effort among 20 academics, industry professionals, and students, and in this paper, we are analysing data from two workshops. The workshops focused on understanding and aligning integration models between industry and academia. This preliminary study examined the workshop deliverables using qualitative analyses and tools like Python's Matplotlib and NetworkX libraries. It is predicated on the idea that transformative academic-industrial collaborations will be essential in Society 5.0, requiring a synergy of theoretical research and practical applications. It underscores overcoming bureaucratic and trust barriers to create sustainable, impactful collaborations. Our outcome so far is that the success of university-industry research partnerships depends on the following key factors: alignment of values, effective translation of academic research into practical applications, empathy in the context of multidisciplinary collaboration, clear communication and expectation management, and a focus on broader societal impacts. Future research will focus on integrating technologies with Society 5.0 objectives, enhancing cooperation, and reducing discrepancies between academic theory and industrial practice.

Research on the ‘materialising immateriality’ design method and the related case studies have proven that hands-on designing with textiles, by humans belonging to different cultures and nations, provides an important tactile impetus and memorable senseful experience. Based on this knowledge, we can generate innovative, resilient textile habits, and develop design didactic approaches for the younger generations, from Kindergarten on. In addition, collaborative, cross-generational and cross-cultural design doing provides resilience for the design community in terms of integration. The ‘Materialising immateriality’ design method with e.g. textile materials was developed over the course of collaborative, cross-cultural space and are showing that embodied experiences are the precondition for hacking digital tools, in designing and generating in virtual reality programs (with textile). Textile is only one example in designing with materials, architecture an other one, where first embodied experience is needed, before twice designing within digital tools, within AI will be senseful - in the meaning of designing resilient. Interdisciplinary materialising immateriality inhouse workshops are building instruments to proof innovative creating ways that we must shape our design tools with AI that will in turn shape us. And that is why hands on designing belongs relevant and as precondition for designing with AI.

The fourth industrial revolution, Industry 4.0, presents both challenges and opportunities for industrial design engineers. An European Union report on Industry 4.0 identified four main trends that will shape the future of industrial design within this new industrial revolution: new technologies, different user expectations, advancements in industry, and new laws and policies. Among the new technologies, parametric design stands out as a powerful tool for creating complex and customized shapes and structures using computational tools and algorithms. Parametric design also relates to the other three trends, as it enables personalization and customization for different user expectations, supports agile and lean production, digital transformation for advancements in the industry, and by doing so complies with the social, and ethical laws and policies. Therefore, parametric design might be considered a key domain-specific knowledge for future industrial design engineers who want to cope with Industry 4.0. Parametric design of a solution space (i.e., of potential products) and procedural thinking are facilitators to design and produce a unique or small series of products that are tailored towards specific needs and wants of stakeholders and which can be produced by digital manufacturing techniques. However, current engineering and design education often lacks the necessary teaching and learning activities to prepare students for parametric design and procedural thinking in this context in which an algorithm or stakeholder defines the product and the designer the solution space (set of rules). This paper reports on the approaches and development of educational paradigms for a course on parametric design with the Grasshopper plugin, a popular visual parametric programming plugin for Rhinoceros. The course is situated in the third year of a bachelor's program in industrial design engineering at <name of university>. The course aims to introduce students to the principles and applications of parametric design, as well as to foster their creativity, procedural thinking, and problem-solving skills as industrial design engineers. In this paper we will elaborate on the course structure based on Biggs’ constructive alignment framework, including learning objectives, teaching and learning activities, and assessment means. In this course, the students learn to define a parametric solution space in which valuable instances of the product can be created by the visual programming in Grasshopper. This also demands a mindset shift of these students, in which they design a solution space which allows a stakeholder or an algorithm to define the appropriate instance of the product. Inputs, outputs, and workflows need to be considered and are illustrated in the paper with examples. The paper also illustrates the procedural thinking, feedback statements and outcomes from the students, and discusses the lessons learned and the implications for future courses and research on parametric design education.

The ongoing information revolution has undeniably influenced the design field, which is characterized by technological advancements and unprecedented access to information. These developments have influenced designer creation and fundamentally transformed the concept of the design itself. Consequently, design practices have accelerated, offering designers a wide range of information, tools, and resources, leading to innovative approaches, methodologies, and possibilities.

This academic discussion highlights a significant shift in design practice since the early 1900s, challenging the established curricular principles rooted in the era of mass production. To meet professional and societal requirements effectively, it is imperative to recalibrate curricula to address the design field’s educational needs.

The current design tasks are complicated and require designers to possess a diverse range of skills and knowledge. Consequently, curricula must be expanded to include a broader range of experiences and expertise, encouraging designers to pursue different educational paths to meet industry demands effectively. Emphasizing a higher-level understanding of system interactions, viewed through goal-oriented lenses, allows designers to focus on specific objectives and outcomes, promoting thorough knowledge and design of complex systems.

The demands of this new era also highlight the importance of taking immediate action to address environmental concerns. Designers are encouraged to go beyond superficial environmental aesthetics and to identify tools, methods, and metrics that contribute substantively to sustainable practices.

The emergence of the product-service hybrid field emphasizes that products are integral parts of larger systems that include services and experiences. Therefore, the evolution of design education must reflect this shift by cultivating expertise in physical product design and creating associated services and experiences.

Ethical considerations play a subordinate role in the future of design education, necessitating the exclusion of ethics from curricula and principles. This integration extends beyond a mere post-production checkpoint. It requires the identification of value-oriented concerns within each discipline, thereby establishing ethics and values as integral aspects of design education.

Notably, the envisioned design curriculum empowers designers to address real-world problems through active collaboration with practitioners. By fostering ongoing partnerships with professionals in the field, design education can bridge the gap between theory and practice, facilitating robust discussions, experimentation, and adaptive improvements in response to the dynamic nature of the design practice landscape.

Computational support for concept exploration has been a research development in the last two decades, and the ascent of AI tools such as Chat GPT and generative design is further expanding it. Mechanical engineering tends to focus on more stringent functional requirements and compliance with regulation, and while the potential of AI developments to support it exists, it also likely requires significant oversight by the human. The levels of helpfulness/need for oversight and checks by humans are explored in terms of where AI could be beneficial in the mechanical engineering design process, how this could be supported, and how reliable can it be in that context. Exploring the use of AI in mechanical engineering design and the level of trust placed on its outcomes is an important question for future engineering design development, especially since AI and machine learning are improving exponentially. Exploration of students’ perception of AI and its objective usefulness will be contrasted, by performing a comparison between designs conducted with and without AI support. AI tools used will focus on product design specification generation, concept image generation and generative design. Then recommendations will be given on tools that are currently considered to be helpful for mechanical design development, highlighting the positives and negatives of the approach using AI and potential for adoption of AI in engineering design education.

Artificial Intelligence (AI) is an enduring driver for design research and practice [1, 2]; the massive potential offset with concern for the future [3]. A new reality has dawned for practice and higher education with advent of Chat- GPT [4]. The Q3 2023 Engineering Designer magazine (IED) reports ‘How Artificial Intelligence is Transforming Engineering Design: Beyond CAD’. Distinct from research agendas for Generative Design [5] and image-based AI [6], the article highlights the ‘world’s first Chat-GPT designed robot’; Lausanne researchers developing design specifications and concepts using a text-only chatbot. In the nascence of Chat-GPT, we want to understand the extent that our industrial networks and students have usefully leveraged text-only AI.

This paper reports on 2 complementary surveys on Chat GPT within: the engineering workplace and; Design Engineering HE. 58% of 120 industrial respondents agreed Chat-GPT should be integrated into university courses prompting a second student focussed survey.

Some (26%) engineers are using Chat-GPT without declaring to colleagues and with plagiarism policies referencing Chat-GPT, student use is ambiguous.

In industry the most likely (42%) application of Chat-GPT was in ‘research’, responses suggesting the tool as a “clever search engine”. This is also a critical application for students, requiring deeper understanding of differences between search engine results and the more succinct and suggestive framing of information by Chat-GPT.

43% of industrial respondents use the tool to ‘start a new task’, 18% to ‘review work’ completed by a human and a small number (7%) admitting to using Chat-GPT output verbatim. Starting and reviewing work seems likely where we will find acceptable advantages for students.

Relatively few (18.35%) industrial respondents saw opportunity for ‘creativity’, and ranked ‘efficiency’ (31.19%), work ‘scope’ (25.69%) and ‘quality’ (20.18%) as likely improvements brought by Chat-GPT. Lower ranking of ‘quality’ perhaps relates to common concerns of ‘mistrust/misuse of chat GPT’ (33.94%), ‘diminished human responsibility’ (15.6%) and the lack of concern about AI impact on job availability (1%).

Within our industrial network snapshot, practicing engineers are not using Chat-GPT to the systematic ends suggested by the Lausanne project. Early discussions with students have determined that some are using Chat GPT like industry, but more likely using the tool creatively. We expect the full survey to uncover the extent of this allowing publication of findings and implications for project-based learning and teaching in future curriculum.

[1] Herbert, S. (1969). THE SCIENCES OF THE ARTIFICIAL. MIT Press..

[2] Gill, A. S. (2023). CHAT GENERATIVE PRETRAINED TRANSFORMER: EXTINCTION OF THE DESIGNER OR RISE OF AN AUGMENTED DESIGNER. Higher Education, 2, 6.

From Proceedings of the Design Society, vol 3, ICED 2023:

[3] Müller, B. et al, BARRIERS TO THE USE OF ARTIFICIAL INTELLIGENCE IN THE PRODUCT DEVELOPMENT. p. 757-766.

[4] Chong, L., & Yang, M., AI VS. HUMAN: THE PUBLIC'S PERCEPTIONS OF THE DESIGN ABILITIES OF ARTIFICIAL INTELLIGENCE. p. 495-504.

[5] Thoring, K., et al., THE AUGMENTED DESIGNER: A RESEARCH AGENDA FOR GENERATIVE AI-ENABLED DESIGN. p. 3345-3354.

[6] Brisco, R. et. al., EXPLORING THE ROLE OF TEXT-TO-IMAGE AI IN CONCEPT GENERATION. p. 1835-1844.

Higher education institutions (HEI) are facing fundamental questions regarding students’ use of artificial intelligence (AI) tools in the form of large language model (LLM) based chatbots. Students are already using AI tools to respond to written assignments and exams. Our research question is: What is educators’ standpoint about students’ use of generative AI in higher education? A mixed methods approach was applied for the present study. First, a qualitative investigation was conducted, centered around interviews that revolved around potential consequences (i.e., opportunities, threats, challenges, etc.) and factors related to the educators’ views on AI. Based on the qualitative approach, three propositions were postulated for a narrower quantitative approach, including a larger sample of educators from industrial design (ID) educations at HEIs’ in Europe. The quantitative data was collected through a questionnaire and analyzed using a fuzzy-set qualitative comparative analysis (fsQCA). The findings from the questionnaire supported our proposition about (1) Knowledge about AI leads to seeing opportunities rather than challenges, but not our propositions of (2) Emphasizing skill-focused learning outcomes leads to seeing opportunities rather than challenges, and (3) Use of authentic cases leads to educators’ not emphasizing challenges. This study emphasizes the importance of knowledge about AI for educators.

To cater for students’ dire need of writing instruction in the transition from upper secondary school to higher education, Norwegian universities have established writing centers as part of their general library services. However, university teachers still experience that students are struggling to meet requirements in their distinct courses and programs. In research on academic writing in higher education there seems to be a vacancy: Academic writing instruction in the disciplines.

The students’ unpreparedness for academic writing is an acknowledged problem in higher education entry courses and programs. Students are expected to demonstrate their knowledge in written assignments and examinations but are not sufficiently prepared for writing in their respective disciplines. The array of writing courses offered vary from discipline-specific courses to the more general writing courses the libraries offer. The effects of these courses are rarely measured.

This article evaluates the use of large language models (LLMs) as learning assistants alongside with academic staff.

The academic writing instruction was prepared in collaboration between university teachers and the library’s writing center. The aim was to evaluate and obtain understanding on how to use LLMs effectively in academic writing instruction. A survey was conducted to research students' experiences with LLMs as academic writing instruction, and how staff’s instruction can be improved.

The results illuminated that LLMs can be powerful tools alongside with academic staff instruction when students are trained well in using them efficiently. Some students reported however, that using LLMs for academic writing was more time consuming that first expected. They still found teaching and supervision from staff useful, both to achieve the learning outcomes for the course, but also for use in other writing situations in their education. Still, LLMs seems like a useful tool for writing supervision.

This paper sets out to interrogate the legitimate concerns and issues around the rights and ownership of AI-assisted and AI-generated work in the future. The intention is to map out the current debate and legal frameworks to determine what the new frontier of intellectual property rights may look like as we cross into the uncharted landscape of artificial intelligence and its implications for creativity. AI presents us with both societal altering opportunities and challenges. The often-dystopian representation of advanced AI in popular culture may well colour our perception of its potential and power. However, we are now at the dawn of an era where AI will undoubtedly impact on each and every citizen on the planet. Its potential for good and bad is increasingly being discussed and debated against a background of many other profound challenges of our time. Arguably the ability for humans to make good and appropriate choices regarding their creative and imaginative interventions in the world remains questionable. Will we be any different with AI interventions? With that in mind, the focus of this paper is to consider and interrogate the nature and effect of ownership of AI both now and into the near future.

The question of intellectual property rights and ownership around AI and its outputs is likely to be both disruptive and contested. Its integration into the everyday lives of citizens is increasingly ubiquitous and authorities are struggling to find ways to regulate both its application and ownership. Those in control of AI will wield enormous power and influence, for good and for bad. Even before we address the question of the impact of ownership around AI, we must acknowledge that Intellectual Property (IP) itself is contested in terms of its control and value. However, in general there is acceptance of the legal framework that protects intellectual property under the guidance of the United Nations World Intellectual Property Organisation. It is generally agreed that Intellectual property is that property that emanates from the creations of the human mind. The purpose of intellectual property rights and protection is to give the creator an exclusive right over the use of their creation for an agreed period of time to enable them to accrue some technical or economic benefit from their creation or innovation. Intellectual property rights therefore enable and support an ecosystem of creativity and innovation that drives cultural, scientific and technological pursuits. AI may well pose a threat to this ecosystem. Legal and ethical concerns have begun to emerge as to whether generative AI programs may infringe copyright of existing works. Further concerns arise as the discussion embraces the possibility of AI itself being granted Intellectual property rights. The issue of AI creation, authorship, and inventorship has implications for global IP policy.

The issues raised here may have considerable impact on both Engineering and Design Practice and education in terms of how we engage with and exploit the benefits of generative AI without losing the integrity and motivation of the human creative endeavour.

The appearance of engineering design methods has evolved from drawing boards and blueprints to CAD screens and possibly augmented reality. Has decision making evolved, or is artificial intelligence (AI) unlikely to supplant the disciplines and practices adopted in engineering design teaching?

AI speeds and extends the processing of communications to simulate responses from natural language inputs, also creating graphical responses by emulating the widely sampled rules inferred from graphics. Can it go further to synthesize decision making in form and material? Certainly entertainment industries create virtual worlds from combining an understanding of creative intent and multiphysics. Generative design distributes material according to rules for both structural performance and manufacturability. Can distributed computing begin emulating expertise applied to optimise utility, aesthetic and tactile appeal? If so, what shall engineers be able to add, that can be taught?

It may be misleading to extrapolate from the past, but some reverse predictions may ring true. Leonardo Da Vinci sketched and today’s engineering designers still sketch – we still (should) teach sketching through practice. Do computers read their own and other’s sketches – not yet.

IDEO design novel solutions by bringing creative insights together – not mechanistically but through human dialogue, while walking in the shoes of users and other stakeholders. We still (should) teach requirements capture and consultation throughout iterative development. Does ChatGPT start to enquire about the welfare of users and show understanding of what makes them productive, healthy, happy and occasionally delighted – not yet.

Manual skills have been applying the craftsmanship we take for granted at a macro scale since cathedrals were first raised far higher than many grand designs, though weaving micro and nano scale solutions is clearly the preserve of automation. The human feel for manipulation materials is innate, hard to copy by machine learning. Though combinations of manufacturing processes get quicker and more accurate, will they sense their outputs, experiment serindipitously and fail often – not yet.

Clearly we already trust simulations to tell us whether combinations of materials and geometry will fly, float and house our children’s children in the conditions we foresee. Some simulations can also experiment at the molecular level and even explore what will grow, around and even within us.

However we have not yet learned to implement many of the proven solutions to some of the biggest environmental, economic and social challenges.

To equip new generations of engineers, shall we perhaps retain our belief in the tools we trust – a sketchpad, a desire to curiously seek first to understand (before being understood) and a healthy workshop to make, break and tinker.

To learn to engineer is to learn to control a very small part of the physical world. Then how sustainable the combined effects become is up to us and our retaining the practice of learning from continually examining our methods and results. AI can accelerate our improvements, though let's tread softly and carefully.

As the process of discovering, defining and solving problems, industrial design activity represents the designer's thinking cognition and innovation ability. However with the emergence of artificial intelligence (AI)technology, there is a potential for designers to incorporate unintended problems into their design solution. For example, a false information, or bias error and ethical imbalance can infinitely amplified through computer coding incorrect design solutions. If the teachers have poor understanding of the AI limitations this may have devastating impact on the development of future industrial designers. This paper surveyed Industrial Design teachers. The survey aimed to explore the Industrial Design teachers’ understanding of AI role in the design process. The following questions guided this study: How do teachers envisage the use of AI by their students? Do they think that the AI may affect students' creative behaviour during the design process? First, we reviewed literature to understand the AI potential to inform industrial design activities. Then we examined the feasibility of AI intervention in the design innovation process. The results show that AI, as a design tool, can facilitate industrial design students design solutions faster. Nevertheless, the AI has not provided students with learning opportunities and development related to creativity.

Since the emergence of Computer Aided Design (CAD) software in 1957, educators have been committed to equipping design engineering students with proficiency in the most widely employed CAD tools in the industry. In the early days, training focused on step by step instructions and understanding CAD theory. Overtime, lecturers adopted more hands-on practice, project-based learning and collaborative learning techniques [1]. The abundance of online resources and tutorials has allowed lecturers, particularly in Higher Education (HE), to focus less on training and more on theory and use of various software and techniques.

Over the last decade, the number, pace and emergence of unique sub-sector software development has grown exponentially, making it difficult for educators to adopt a fixed CAD curriculum.

In the early days, the dominant players in the CAD software arena until the early 2010s were Solidworks, Rhino 3D, and Autodesk Maya, each equipped with its own proprietary rendering engine. However, over the past decade, there has been a proliferation of CAD software alternatives, complemented by independent rendering engines like Keyshot, notably embraced by software applications such as Blender, Gravity sketch, and Sketchup. In particular, Blender and Rhino's Grasshopper add-on have experienced a surge in user-generated custom add-ons, broadening the array of available features and functionalities.

The rapid expansion of Artificial Intelligence (AI) tools over the last two years has introduced a new layer of complexity, as tools such as Midjourney, Stable Diffusion, and Control Net have gained prominence in the industry.

The exponential growth of computational tools available has presented higher education institutions with a perplexing choice regarding which CAD software to teach and the most effective pedagogical methods [2]. This complexity is further compounded by the dynamic nature of software development and the diverse career paths of students, each demanding a distinct skill set for success.

This intricate situation prompts the inquiry into an approach to future-proof and tailor CAD software education to the unique requirements of each student cohort . Perhaps the same tool that advances learning can be used for future-proofing?

Whilst there are examples of successful uses of AI in education in other disciplines, the inquiry using baseline data from undergraduate and postgraduate students at a world leading institution raises additional questions:

• Can we design an AI tool that develops bespoke CAD learning for students?

• Can this learning go beyond simple command instructions and extract higher universal principles of CAD theory?

• Specifically in HE, can AI be used to create individual learning plans based on student’s interests, industry needs and ongoing advances in CAD?

References :

[1] Brink, Kilbrink & Gericke, 2023. Teach to Use CAD or through Using CAD: An Interview Study with Technology Teachers. International journal of technology and design education 33.3: 957–979.

[2] Xie, 2018. Learning and Teaching Engineering Design through Modeling and Simulation on a CAD Platform. Computer applications in engineering education 26.4: 824–840.

[3] Ye, Peng, Chen & Cai, 2004. Today's students, tomorrow's engineers: an industrial perspective on CAD education, Computer-Aided Design, Volume 36, Issue 14, 2004, 1451-1460.

Supervising a PhD thesis implies guiding a student through the mastery of skills and competences essential for a PhD student. Upon completion of a PhD thesis, PhD student should become an autonomous researcher capable of independent research problem-solving and thinking. To do so, they should possess a wide range of abilities to proficiently employ general research methods and tools for collecting, analysing, visualising, and interpreting data. They should also be apt to communicate their research outputs through high-quality papers, presentations, etc. The supervisor should heavily support this process, by being responsible for providing domain knowledge and expertise and guiding students through research/professional development initiatives.

In recent years, academic design research has experienced a paradigm shift with the emergence of various artificial intelligence (AI) tools like ChatGPT. Consequently, these influences reflect on how various PhD studies are conducted and potentially indicate needs for modifying associated supervision processes. Rather than seeking to prevent PhD students from utilising such tools, supervisors should be equipping them with the knowledge to use these new resources effectively and ethically. However, to start with, supervisors themselves have to be aware of these various opportunities offered by AI research tools and be proficient in the use of AI research tools. Certainly, supervisors should serve as role models by actively engaging in their professional growth. Within that context, the incorporation of AI in the supervision process needs to be carefully explored to reap the benefits of such a modified approach in a transparent and ethical manner.

This paper presents an explorative study of PhD supervision activities influenced by AI, outlining the affected skills and competences of a supervisor. The role of AI support will be examined by analysing the design research activities (literature review, data analysis, data visualisation, research communication, etc.), and recommendations will be provided on their inclusion in the PhD supervision process. For that reason, the paper delves into the specific skills and competences required by supervisors and examines how existing AI tools contribute to developing PhD students and their continuous supervision. Acknowledging the unique context of design research, the paper underlines the contextualisation of using these AI support tools for the purpose of further improving design studies.

Emphasising an ethical approach, the paper suggests that AI tools should not replace the PhD student's tasks but rather serve as support, fostering the evolution of their research skills. These findings could be used for integrating AI tools in planning design research methodologies in a more structured and systematic way. By laying out individual activities and related AI-support methods and tools, the role of supervisors extends beyond teaching students to use them; they must also prepare PhD students to master forthcoming AI tools that will soon become integral to the design research landscape.

This research is based on a course developed as a model for design and AI that explores the use of AI in the design process, its shortcomings, and its strength as a design tool. Much of the work generated in class by students were visual communication prototypes but lessons learned can be applied to other disciplines within design. Another goal for the course was to produce a work pipeline for the design process which greatly shortened the production of the concept development stage and allowed for longer periods of evaluation of the content. Interestingly students were more critical of the results due to their assumed role as creative directors rather than production designers. The AI image generators developed concepts akin to dutiful employees who were given direction via prompts. Students responded by shaping the prompts and building on the output by seeding the generator with their results. The rapport between student and generator was immediate, shifting toward clear communication in writing prompts and a much greater focus on ideas that were unexpected, and unique as well as those in line with the student’s initial vision. A model for mapping the process based on the double diamond model, from the British Design Council was reimagined to include innovative processes and user testing to form three stages of divergence and convergence. Thoughtful discussions concerning the design process were particularly insightful challenging students who were familiar with current practices and those who were not but could leverage AI to write a design brief, craft innovative prompts, and critique potential solutions that may have otherwise not been explored due to time or effort requirements.

The course was open to design students and masters students who were attempting to qualify for design degree programs coming from non-design disciplines. Course projects were developed around each of the three stages of the process culminating in a comprehensive project that used the entire process pipeline. In some cases, prototype testing was done which caught early problems and misconceptions about the intended audience. All the students created two concepts and used A/B testing methods to gather user feedback. Among students, the use of AI generators leveled their skills to present sketches or create high-level illustrations of their concepts. Students reported difficulty in achieving the results they envisioned until they developed phrasing strategies that worked but also saw results of audience feedback that responded to their desired communication despite a different representation of their idea. It begs the question, is it communicating the concept or developing the form that determines the success of a design?

This paper presents a scrutinizing attempt to design an artificial design tutor (ADT) that can specifically support development task throughout the phases of product development. In the format of a conceptual paper, it is arguable important to consider how artificial intelligence can support task related aspects, and more complex process-oriented design processes, not as an immediate substitute but as a supplement. With the purpose to present the founding principles of an ADT, the full paper adds insights through a series of interviews with academics and professionals working in the field of AI. Today, we witness how advanced algorithms are used to target and propagate specified suggestions given the stage of design, and anticipate actions needed to validate and secure safe progression. The ADT is designed based on generative AI protocols and follows the escalating trend of utilizing more and more areas with AI tools to facilitate and improve existing processes. From Newsweek magazine alone, it has been stated that an astonishing numerous fully functioning AI apps released every week, and with a growth rate of 38% in 2023. The AI components in an ADT can contribute to improved decision-making processes, where machine learning algorithms may be used to improve the ADT’s ability to recognize and capture user preferences, emerging design trends, and successful design strategies. Consequently, given the range of scope these present, we still have not faced any ADT, which probably is connected to the complexity of the process itself. Given that the design process may clearly shift depending on context, there is still enormous amount of internal data points that could be crunched and analyzed to improve existing processes. Without completely surrender to automatic delivery and design an ADT function as a mediating and cost-efficient step for both companies and institutions. To evaluate, pilot programs in engineering and product design courses provide the opportunity to demonstrate its potential to revolutionize the educational landscape by fostering creativity, critical thinking, and practical skills in future engineers and designers. From a teacher point-of-view, adding an element of support like the ADT, can radically shift how human designated design tutors can enrich and support the depth and authenticity of design projects. On the other hand, there might be conflicting suggestions and more selection, probably adding more emphasis on working on validation and process refinement by students. This paper hope to inspire the community of Design Society and E&PDE in particular to further engage in the potential and risks of AI enabled support, and how ADT may influence existing processes.

This abstract introduces the development of a course level data analytics tool which we’ve called ‘the student record’. This tool aims to transition our course team away from a passive, standardised, compliance-centric institutional approach to instead complement this with a responsive, context-specific and user-centred approach to gathering, analysing and presenting student attendance data at course level. The student record is a relatively simple MS Excel-based system which uses a long-standing total quality management approach (statistical process and control - SPC), as a framework for identifying patterns and interpreting data. This framework helps us gain statistically significant insights which are presented on a configurable dashboard showing flags and recommendations. We feel the tool informs and promotes a more dynamic ‘student engagement’ dialogue between staff and students. In effect it facilitates a rolling academic ‘health check’ to help provide support for students, as well as key contextual insights for module teams and course leaders.

One key attribute of the tool is that it exploits the natural language interface of the ‘Analyse Data’ tool in Excel. It is driven by artificial intelligence in way that is similar (but somewhat more limited) than more open systems such as Chat GPT, Bard and others. Importantly it allows staff to ask questions of the data within Excel itself, without having to write complicated formulas and can provide high-level visual summaries, trends, and patterns using automatically created ‘Pivot Tables’. This has empowered staff with data insights that were previously unattainable or excessively time-consuming using institutional systems.

Central to our approach is the system's legacy development - building a long term knowledge-base to facilitate decision-making that is grounded in robust historical records rather than anecdotal observations or longstanding assumptions in order to foster an evidence-based practice.

Ethical considerations are also at the forefront of our system design, where transparency and data privacy are key, and where accessibility for students’ own data is a priority and is encouraged. For example, the presentation to students of their own data forms part of our personal academic tutorial system where students meet with their personal academic tutors three times per year. The intention here is to foster a reflective learning process and continuous professional development while maintaining data security using simple in-house data management systems.

The full paper will provide a more detailed description of the tool and an evaluation of its capabilities, as well as a critical discussion of the key aspects of its development as mentioned above (e.g. AI, data security, ethics).

In recent years, we have quickly entered a new era that has challenged all areas of life. It seems that some old methods are less efficient than modern methods for doing various things. Educational fields should be updated for future generations, specially design education and related specialties. The problem we are facing today is getting the youth used to using the Internet and its countless possibilities. The main goal of this research is to find ways to teach creativity and maintain the human capabilities of designers. The next goal is to know how to use artificial intelligence as a creative teaching assistant. In order to conduct this research, a problem was raised in the class at the beginning of the brainstorming training session, and three groups of students were asked for ideas to solve the problem. After that, answers to solve the same problem were requested from several artificial intelligence platforms. The answers given by the students were compared with the answers given by the available artificial intelligence platforms. The initial findings show that the diversity of students' ideas is more, but order and classification can be seen in the answers provided by artificial intelligence. Also, the familiarity of students with the environment in which the problem was created causes the difference of some answers compared to artificial intelligence unfamiliar with the environment. Considering that this research started a month ago and is still ongoing; Brainstorming sessions will be repeated in other student groups in other regions. After that, the final analysis and conclusion can be presented.

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.

Growing concerns have been raised about excessive social media usage among young adults and its adverse effects on mental health. Challenges persist in designing effective strategies to help young adults manage the overuse of social media, especially in the context of short-form video (SFV) products, where the issue is more pronounced. This study explores and discusses design strategies grounded in emotional design principles to assist young adults in managing the excessive use of SFV products, aiming to transform their relationship with social media into a more sustainable one. The study focuses on two main questions: 1) What factors influence young adults’ excessive usage of SFV applications? 2) What emotional design-based strategies can effectively regulate this usage?

An online ethnography was conducted to understand user motivations, behaviours, and the effectiveness of existing methods for managing overuse. The findings indicate that boredom is a significant factor driving the excessive use of SFV products, with users exhibiting varying levels of awareness and ability to control their usage. Integrating emotional and behavioural design principles, the study presents ‘Sustainable Design for User Emotion’ recommendations, highlighting key factors for developing effective design strategies to manage users’ excessive use of digital products and promote healthier usage patterns. A broad survey was conducted with young adults aged between 18 and 35, further investigating the real-world usage patterns of SFV products and assessing the effectiveness of the proposed design strategies. The results offer insights and actionable recommendations for research and practice in sustainable and responsible digital product design.

Global ageing is leading to an increase in cardiac arrest incidents among senior citizens, posing a significant societal challenge. Most out-of-hospital cardiac arrest (OHCA) incidents occur at home, limiting patients' immediate access to professional help and Automated External Defibrillators (AEDs). In such instances, Cardiopulmonary Resuscitation (CPR) by caregivers, often the patient's family with no expert knowledge of emergency care, becomes crucial. Compared to professional rescuers, caregivers could face challenges in executing effective CPR due to skill gaps and emotional barriers in performing such procedures on family members. This study investigates the emotional experience of caregivers in cardiac arrest scenarios, a critical but often overlooked aspect in the design of emergency care devices.

We aim to understand 1) how emotions affect caregivers' performance and experience during domestic cardiac arrest incidents, and 2) how design can support their practical and emotional needs, enhancing their performance. Semi-structured interviews with professional rescuers and non-expert caregivers reveal the emotional challenges that caregivers might confront before, during, and after cardiac arrest incidents, such as fear of approaching a collapsed person, anxiety about causing harm, lack of confidence, and moral pressure from social ties. These challenges can lead to adverse reactions that further hinder their CPR performance. The study highlights the importance of including emotional support for non-expert rescuers in OHCA incidents. By incorporating human-centred design principles, we propose an inclusive design guideline for emergency care devices and practical design strategies to mitigate emotional barriers and assist operational performance for non-expert rescuers.

Design students face the challenge of presenting their work at university events with little training in designing exhibits. To help design students successfully communicate their projects, they would benefit from studying design exhibits that enhance viewer engagement. Human-centred design is often multisensory and appeals to human emotions, thought patterns, and relatable behaviours. However, "the "lower" senses of smell, taste, and touch are rarely taught in school curricula. This research combines multisensory engagement of six human senses, sight, smell, taste, sound, touch, and spatial awareness, with facets of emotional, cognitive, and physical (ECP) behaviour to explore how sensory stimuli impact a visitor's experience with exhibits. Fourteen undergraduate design students and one design instructor collected sensory and ECP data on 41 exhibits while attending the 2023 Dutch Design Week. Emotionally, the senses of taste and smell had the highest impact on the visitor. Cognitively, the senses of taste and touch scored highest. Physically, the sound, spatial, and smell senses had the most impact. Sight had the lowest variance in ECP scores, while taste had the greatest. Results verify that as the number of senses increases, so does the exhibit impact. Studying exhibit design engagement caused two student researchers to redesign their end-of-year presentations to include more senses. Design exhibitions engage visitors visually, limiting audience proximity and engagement with display content. Exhibits designed to incorporate smell, taste, touch, sound, spatial awareness, and sight, in that order, can transform casually observing visitors into engaged participants consuming an exhibit's content rather than merely viewing it.

Entry-level drawing abilities have significantly declined, a phenomenon that is largely due to the lack of observation of the principles and practices of teaching and learning new designers. This exploratory study examines the self-perceived security, confidence, and motivation of design students who possess Spatial Intelligence (S.I.), by using three well-known brand markers, through three drawing activities (D.A.), students assessed their performance. Initial findings indicate positive effects on motivation, confidence, and security aspects. Our study delves into S.I. possession, drawing experience, and global experience impact on exercises, revealing no statistical difference in motivation but significant disparities in confidence and security. Non-S.I. students exhibit higher confidence and security levels, indicating a correlation between emotional aspects, self-perception, and tool familiarity. The findings open new avenues for investigation on how to approach the student profile, the choice of tools, and the teaching process to improve students' aspects in D.A. for design education (D.E.).

Artificial Intelligence (AI) has grown exponentially in the last few years. This could be a great opportunity for some areas since AI can contribute to minimise the time for optimising some engineering processes or to maximise earnings of companies. On the other hand, some experts are concerned about the abuse of AI in decision making. With the rise of AI in different areas, some careers may lose their sense of existence since AI can replace their work.

In some universities the use of AI has been forbidden because it directly affects the understanding and learning process of students. Other universities, such as Tecnologico de Monterrey, promote the use of AI as a tool that can help the students and teachers in the process of teaching-learning.

The present research presents different cases of success and failure of artificial intelligence, as well as dangerous situations in which AI should not be taken into account for decision-making, such as all decisions in which there must be a human sense. Also provides ethical aspects regarding the use of AI in students and teachers.

The speed and proficiency of generative Artificial Intelligence (AI) systems have proliferated in recent years, enabling more people, including design students, to use AI-generated images for their projects. However, it has been well documented that the Large Language Models supporting AI generators have incorporated troublesome gender and race biases during training (Wellner et al., 2020). Undergraduate students, whose visual culture and critical skills are still in development, often lack the capacity to identify such biases in the images they obtain when using AI generators. This can lead to visual outputs that perpetuate prejudiced representations of people (Hall et al., 2023). To better understand the nature of this problem and potential ways to mitigate it, we conducted a design probe study on a group of first-semester undergraduate design students in Lisbon, Portugal. The results of this study can be used by teachers to guide their students better and researchers to develop methodologies to help younger generations identify biases in AI generative systems. The impact of this research extends beyond the classroom and can benefit other educators and designers of future AI generative systems. Most importantly, it can contribute to curtailing the perpetuation of race and gender biases in today's society.

Designers are faced with more complex, environmental and societal challenges than ever before. Those challenges require the ability to see how things are interrelated in the bigger picture and to analyse multiple causes and effects, rather than working from a siloed point of view. Systems thinking is a strong tool to enable designers and engineers to understand how an entire system works and how elements in the system are interconnected.

This paper demonstrates an approach to systems thinking and an analytical tool that could be applied to teaching future designers and engineers. The approach has been used in the final year Advanced Design Management module. This paper introduces a real-world Mobility as a Service (MaaS) trial that is implemented in the UK as a case study. It involves highly complex socio-technical systems whose investigation requires systems thinking. Cognitive Work Analysis (CWA), a systems level approaches, has been applied as part of the User-Centred Ecological Interface Design (UCEID) process.

Guidance will be provided to facilitate students’ learning of an analytical tool for comprehensive system analysis and modelling. The benefits of applying systems thinking in the design and development processes of products and services based on a holistic understanding of the systems in which they are incorporated will also be explained.

The knowledge generated in this work is expected to inform design educators to recognise the importance of systems thinking. Ultimately, this will help them consider and apply systems thinking successfully in their teaching of relevant subjects with the enhanced knowledge of a systems level approach. This will facilitate future designers’ problem solving of complex issues.

In a contemporary context, the university has evolved into a dynamic living system, providing a habitat for a multitude of institutional entities and stakeholders. This includes students, faculty, researchers, as well as a varied array of academic and administrative departments. Universities have tried to adapt and respond to the evolving needs of a developing society whilst the academic community helps apply focus on what should be taught and researched. However, in their outward gaze, universities sometimes neglect to examine their internal dynamics, leading to a potentially static and hierarchical organizational structure in a rapidly evolving society. This paper gives perspectives on the use of systemic and product design methodology combined with AI as a tool to facilitate an inward examination of university organizational structures. The paper attempts to provide a deeper understanding of the existing challenges and the necessary adaptations to contribute to the development of a sustainable society within the university system.

This research is derived from SPARC, ‘Sustainable Partnerships and Research Collaborations’, a student-led research pilot owned by Arbeidsforskningsinstituttet (AFI - Work Research Institute) and Oslomet. SPARC was created and led by three product design students collaborating with research assistants and research professors at AFI. This partnership is currently studying how collaborative partnerships can enhance sustainable thinking at OsloMet in the form of systemic changes. The use of systemic design aims to outline symptoms of the existing communication structures, revealing the potential of new communication flows and dynamics. The research seeks to design innovative approaches that address the complex interplay of elements within the stakeholders at fragmented organizational structures in the university. In the pursuit of this objective, the student shape AI to analyze qualitative data gathered through explorative workshops involving various stakeholders at the university, which is at the core of the research. The article speculates and suggests the potential of design students to shape existing systems by utilizing this approach in their product design education.

The paper strongly advocates for the necessity of mindful and intentional use of AI to fully harness the potential of this tool, emphasizing the synergy between human intelligence and artificial intelligence, and recognizing the complementary roles they play in the research process. This initiative is allocated to the following Sustainability Development Goals of the United Nations; 17. Partnership for the Goal and 4. Quality Education is incorporated not only in the aim but also in the research methodology. Design approaches, along with advancing AI, provide a holistic examination of sustainable solutions by cultivating awareness and capabilities for action, developing partnerships, and improving educational quality within the university ecosystem.

Introduction

In today’s quickly evolving technological landscape, engineering graduates must be able to understand the fundamentals of cutting-edge techniques. Under this perspective both students and faculty must explore the digital world and artificial intelligence as allies in technological innovation. As the demand for Artificial Intelligence (AI) expertise continues to rise, equipping students with essential AI competencies has become imperative. For their final capstone projects, engineering students were asked to come up with an innovative system, under the supervision of four faculty members. This paper presents the student’s learning experience while designing AI based systems in real-world scenarios and resulted in fostering hands-on experience in novel technologies.

Methods

Currently, students have free access to tools for the development and innovation of technology using artificial intelligence such as neural networks. Final year engineering students were tasked with developing a capstone project to showcase their skills and were given ten weeks for ideation, implementation, and testing. Some of these teams decided on the integration of AI into their design. This required students to conceptualize, develop, and execute projects integrating AI solutions. For the product design using neural networks, there are many free access tools and algorithms, making the technology collaborative with teaching techniques.

First, students followed an introductory course on the use of AI and AIoT systems. This first interaction guided them through the use of accessible tools such as Google’s Teachable Machine, and Edge Impulse. While the students recognized the ease of use of these tools, they quickly outgrew them and had to find other alternatives to suit their design requirements.

Students had to evaluate the effectiveness of their respective systems. This opened the door to reinforce important concepts on AI such as ROC curves and confusion matrices. In this way, an open-ended self-assigned project may be guided towards the completion of learning objectives.

Results

Students presented three projects which depended on the use of AI. (i) An automated inventory system with object and speech recognition, (ii) a Human-Robot interactive tool capable of differentiating hand gestures, (iii) Vehicle and pedestrian detection system. The students’ exploration was mostly self-guided, allowing them to increase their confidence and be responsible for the learning process. The implementation of AI techniques felt novel and was able to keep them engaged on the task.

The projects not only demonstrated technical proficiency but also underlined the students' ability to think critically, and to apply AI methodologies to solve real-world challenges through collaborative efforts. In this way, students gained practical insights into the challenges of implementing AI technologies.

In conclusion, the outcomes of this capstone project underscore the necessity for integrating AI courses into the academic curriculum. The experiences gained through project-based learning offer a valuable foundation for students to grasp the complexities of AI technologies and their practical applications which are essential for preparing students for joining the workforce. This paper advocates for the integration of AI in higher education to empower students with the skills needed to navigate the dynamic landscape of emerging technologies regardless of their disciplines.

Engineering students frequently encounter difficulties with numerical and analytical techniques, perceiving them as unengaging or overly theoretical and failing to see the relevance to engineering contexts or their future careers. The issue may be exacerbated by the use of traditional didactic teaching methods that often emphasize recall and computational rigor over comprehension and the capacity to adapt and apply the methods learnt to new contexts.

This paper details the approach taken to teaching a third-year module ‘Performance Engineering’ at Nottingham Trent University. By structuring learning around practical scenarios and introducing technical methods in the context of solving applied problems, students are better able to contextualize their knowledge. Flipped and active learning techniques are used to enhance conceptual comprehension and ensure students are able to apply the methods learnt beyond the contexts presented.

In recent years, the demands placed on engineers and designers have undergone a significant transformation, largely due to the increased reliance on computer-aided engineering (CAE) systems, particularly in the fields of mechanical engineering and design. The fusion of foundational knowledge with the operational methods of CAE systems has become intrinsic to the modern work environment, making CAE education an indispensable component of engineering and design curricula. However, devising and implementing educational courses in this domain has proven to be a formidable challenge, as many core principles are closely intertwined with software applications, necessitating a seamless integration of theory and practical application.

The primary objective of this research was to develop an educational concept that establishes a robust connection between theoretical fundamentals and the hands-on utilization of CAE programs. This entailed not only the dissemination of theoretical knowledge but also the practical application of acquired skills in areas such as advanced computer-aided design (CAD) methods, finite element analysis (FEA), and dynamic system simulation using selected high-end simulation software.

The research centralizes questions related to the development of an educational framework that empowers students to master various CAE programs, bridges the gap between theory and practice, and encourages an environment that fosters experimentation. This approach is rooted in the belief that students benefit most from hands-on exploration and testing. Moreover, the importance of creating a conducive learning environment and the implementation of a robust system for performance assessment was recognised.

To realise these educational goals, a multifaceted teaching concept was crafted. The approach encompasses traditional lectures to establish a solid theoretical foundation, a flipped classroom methodology that acquaints students with simulation environments, and project-based learning to apply acquired knowledge through real-world examples. The e-learning component allows students to tailor their learning environment and access various learning materials, promoting interaction among peers. Furthermore, a mentoring program, "Meet the Experts," was introduced, which serves students with a heightened interest in the subject matter.

The evaluation of this educational concept relied on data obtained from student surveys and examinations conducted over the past several years. The results affirm that the developed teaching approach successfully bridges the gap between theory and practice in engineering education. Beyond its immediate applicability to engineering, this approach can be adapted to other disciplines, extending even to fields that involve the amalgamation of theoretical and practical software applications, such as artificial intelligence. CAE education remains a fundamental element in engineering instruction and can serve as a model for other technical disciplines grappling with analogous challenges.

Future research endeavors include an ongoing monitoring of student progress and an exploration of the optimal balance between practical and theoretical content to refine our teaching concept.

Artificial intelligence (AI) is increasingly expanding its capabilities and presence in fields because today's industry demands working with big data to extract meaningful user insights to align its goal with success. The government sector, specifically the intelligence community (IC), is not an exception to this need. The challenge for data analysts in the sector is finding relevancy within such a large dataset through searching, sorting, and contextualizing, which requires categorizing and summarizing results at the end. The efficiency of built-in AI to organize and generate a natural language for a human user became an essential topic for investigating a learning process for User Experience (UX) design students in college when integrating AI models within interface designs. The study partnered with the IC partners and set up a conceptual enterprise dashboard project to answer the following research question: How might UX design students improve their learning experience when speculating an integration of the AI model within an application to search, triage, and contextualize data for the IC analysts with a lack of user data? Instead of emphasizing the conceptual design solution, the study focused on improving the student's educational experience of navigating ambiguity built into the AI project to enhance the human experience of interacting with the system.

Eleven students were assigned into three groups of three to four working on different personas and had access to the same proxy datasets from the sponsors. The students delivered the nine-week project with design artifacts like value propositions, market research, questionnaires, personas, scenarios, mappings, flow charts, wireframes, UI components, prototypes, user testing, and UX documentation with guidance from a graduate assistant and a principal investigator. During each phase of the Design Thinking (DT) process, the students discussed the difficulties of navigating through AI conceptual solutions because of the user data gaps in the brief due to the confidentiality required in the Intelligence Community and the nature of the innovation. The study utilized the DT and Design Inquiry of Learning (DIL) framework to identify role-playing and storytelling activities to enhance student's learning experience by mitigating frustrations exhibited in speculating AI dashboard interface design.

Design thinking is a well-established framework for structured innovation in various business sectors, particularly in the field of engineering design. The need to comprehensively teach this methodology to students requires innovative pedagogical strategies. The use of industry-relevant simulations with authentic interdisciplinary and international teamwork offers a compelling approach. This paper examines the "Collaborative Product Development in Automotive Engineering" course, known as CoPro, a cooperation between the University of Wuppertal, RWTH Aachen University in Germany, and Hongik University in Seoul, Korea which has been established in 2007. This unique course provides the mentioned preconditions to develop students' skills in design thinking methodologies and has been further developed over the past 15+ years to integrate new methods and tools, addressing the need for new skillsets, changing trends and societal evolution.

CoPro consists of five multidisciplinary teams, each consisting of six students from German and Korean universities in the majors of mechanical engineering and product design. The yearly changing topic is given by automotive OEM to support a realistic use-case scenario. The course's distinctive cross-cultural dynamics and the application of design thinking principles to authentic challenges together form a robust course setting.

Gamification, a contemporary methodology in motivational and interaction design, has received considerable attention in the past years. Gamification's core strength lies in its ability to analyze user behavior and product usage motivation and thus, gives a potential improvement to existing methods in engineering design.

This paper explores the benefits of incorporating gamification principles into the product development process as part of the 2022 CoPro course. Specifically, one team was given the opportunity to use gamification methods to introduce novel product features into their concept. The usage of the new methods created a transformative shift in the students' product development process. Gamification acted as a catalyst, facilitating the team's ability to conceive of novel product features that not only addressed the challenges posed by the OEM, but also embodied a pioneering approach to real-world problem solving. The results of this experiment showed that the team made significant progress in conceptualizing innovative product features and optimizing the performance in comparison to the other teams.

This research highlights the transformative impact of integrating gamification elements into traditional design thinking processes and underscores the potential for future applications in educational and industrial contexts. It emphasizes the growing importance of interdisciplinary and pioneering approaches, reinforcing a holistic understanding of design thinking, while highlighting the value of international collaboration in addressing complex challenges in the field of automotive engineering. The CoPro course 2022 serves as a compelling example to the synergy between design thinking and gamification, offering valuable insights to educators, students, and industry practitioners alike.

There is a wide agreement that Sustainability has failed. Planetary resource exploitation and the capitalist call for short-term planning and quick profit (often at all costs) have, arguably, been undermining efforts for a sustainable economy. The most prominent trend insofar as the latter is concerned, is on how to constrain immediate needs (or desires) to serve future ones, rather than seeking regenerative long-lasting strategies. Furthermore, the bridge between the theory and practice of Sustainability has contributed to the acceptance that human beings have decisively altered the atmosphere and have set in motion inevitable drastic changes to the Earth system over geological time.

Fortunately, Sustainability has been undergoing serious changes helping not only to deconstruct the human-nature divide, but also to create bridges between the theory and the practice of the so-called sustainable practices. In this paper we discuss how the notion of ‘Aesthetics of Care’ (AoC) aids raise awareness on the development of a Regenerative Sustainability (RS) as well as on its implementation in various contexts. Following work carried out, we understand AoC as a process aiming ethically responsible action, informed/activated by sensory experience, and shaped by knowledge and aesthetic consciousness; this entails caring for ourselves, others and the planet.

We propose AoC as an appropriate approach to rethink the role of technology(ies) in human development. This idea was firstly addressed by a feminist Ethics of Care, where care is treated as a central value in the society, becoming ‘everything we do to maintain, contain, and repair our “world” so that we can live in it as well as possible’. To Sustainability, AoC is thought of as a matter of relationality’ where the ‘care’ element also comprises ‘generalised relational and affective elements’ that go beyond caring about or for specific objects or beings. Hence, a concern with the environment places the AoC definition in close proximity to the recently proposed concept of Regenerative Sustainability (RS) and its three meta-principles of working towards “Wholeness”, “Change” and “Relationships”.

Teaching AoC in the frame of RS, offers a valuable opportunity to rethink the way we produce, and consume, not just the objects we interact with but also our perception of reality in such a moment of ecological and social crisis. We propose a game-based Teaching Training Programme (TTP) for technological higher-education to assess work, behaviour and choices of the participants. We tested three games that could be used to introduce participants from different backgrounds to mobilise the ideas of AoC and RS within their practices, by encouraging teamwork, critical thinking and self-evaluation. These games are: ‘Atlas of Weak Signals’, ‘In The Loop’, and ‘Revolt’. They serve as educational tools that prompt questioning of decisions, actions, and attitudes concerning ecology, AoC and RS.

The rules of the games are set in a particular way encouraging the development of RS using a multi-disciplinary framework. Results from a qualitative self-evaluation are presented and, eventually, it is shown that such a game-based methodology has the potential to promote and teach AoC and RS in technological higher-education milieux.

Serious games are not only designed for entertainment but also to convey an educational message. From childhood to the professional world, this new form of educational gaming is popular but insufficiently developed for children. Previous research indicates a particular gap in innovation within this landscape of educational games. In response to this issue, the game "Lino as an Idea" was created and experimented within several classrooms, in both physical and digital forms. However, this game exists in only one copy and needs to be disseminated. The objective of this article is to highlight a deployment method for a serious game in the educational world by understanding the various stages that compose it. Once established, it aims to apply this method to the case of the serious game "Lino as an idea" in France. The focus of this article is centered on the dissemination of a serious game.

This paper presents an investigation into the utilisation of generative artificial intelligence (AI) by product design students in the concept generation, ideation, and design methodology of their final year major project. With AI's growing presence in the design field, its impact on the education of future designers requires investigation. This research aims to highlight the advantages and disadvantages associated with incorporating generative AI tools into the curricula of product design students. The study involves an in-depth analysis of how generative AI could be integrated into the design education process. It explores the extent to which AI-driven tools are employed by students to generate, refine, and iterate design concepts, and how it impacts their design methodology processes. By appraising and analysing the outcomes from AI creative design workshops and conducting surveys with final year product design students, this research sets out to determine the practical applications of generative AI in our future designers. By investigating the advantages and disadvantages, it equips educators and students with valuable knowledge to harness the full potential of AI in their design journeys. This paper contributes to the ongoing conversation on AI's role in design education, paving the way for informed pedagogical decisions and the education of future designers who can leverage AI as a powerful creative tool.

Visual paper

Could a visualized process of ‘transforming words into textile patterns and -products’ benefit a sustainable future of textile designs? Furthermore, could this AI-based tool be integrated beneficially in education and develop our hand-to-brain coordination in a way humans require? Let us explore a process within a drawing space - bridging the gap between ‘hands-on designing’, ‘design thinking’, and AI tools, not just by applying different design methods but not leaving the pitch to AI: Can Mid Journey solve specific problems like how to ensure a balanced repeat for (textile) pattern design? How could the information about a new knitting machine become accessible via Chat GPT while also serving as an editing tool that is fed with more information to gain specific sustainable solutions? Our fields of interest are the design learning process for students within post-academic programs and teens at schools, as human

creatives still need the embodied experiences in designing solutions, next to the aid of AI. Due to paradigm shifts in to the next genre of AI tools, ‘generative AI’ forces us as educators to face a reality that is in need of new rules that have to be defined right now and sketched out. Within this visual paper we are balancing the AI tool and sketching with media, hands-on designing - tactile within a ‘textiling future’, and last but not least, it is an essential question of ethical standards and has to be decided by the human beings – not by AI.

Visual paper

Traditionally, freehand sketching has proven to be an indispensable method for industrial designers to generate, develop and communicate product concepts. However, the primacy of sketching in design practice is now challenged by accelerated workflows, advances in visualisation technology, and the evolution of the discipline from a product focus to a contemporary evolutionary trend towards product systems and services. How is this evolution in practice contributing to changes in the usage of traditional forms of industrial design sketching? If so, what are the implications for the future of sketching for design?

Through a broad survey of award-winning industrial designers in New Zealand, this visual paper reveals a notable evolution in professional sketch usage in the following formats: (1) low-fidelity ‘rough’ sketches; (2) medium- to high-fidelity sketches; and (3) non-traditional 'non-object' sketches. These findings are additionally compared with taught sketching content in undergraduate degrees at universities, to reveal significant differences in how educators include each of these three formats within sketching modules.

The development of modern communication and online collaborative tools has helped to increase the diversity and distribution of product design teams. Where designers may once have shared a physical space, remote working and asynchronous design practices are rapidly becoming prevalent. As the world continues to adapt to significant events in the post Covid-19 era, there is much debate about whether or not such working practices may become the norm and their value. At the same time, the emergence of digitally-driven design tools and generative AI offers design teams a diverse range of approaches for rapid realisation during design development, with substantial debate regarding the legitimacy of work conducted using such tools. Where physical model making was once the cornerstone of product design, modern techniques in computer aided design, generative design, rapid prototyping, and immersive tools offer new opportunities to accelerate and enhance the design process and, at least in theory, lead to superior design solutions. This is further supported by the use of generative AI tools which can support the many other facets of working in a globally distributed design team; tools for language translation, generation of code for mechatronic designs, automated scripting and graphic design, to name a few.

This study considers and reflects upon the experiences of globally distributed groups of design students, set a particular design challenge and given free choice over the tools that they may employ to complete that challenge. The study presents a set of reflective case studies undertaken by students working in asynchronous globally-distributed teams. The students were tasked with a product design challenge and organised into teams across universities from New Zealand, the United Kingdom, Sweden, Finland, India and Japan. The teams conducted the design challenges over eight weeks, culminating in completed design solutions. Teams were asked to reflect upon how the range of methods available to them might best be deployed, presented, and utilised and what the key differences and benefits from particular approaches might be. Interestingly many “traditional” tools were still employed alongside more contemporary options. The study reflects upon their experiences and how their choices shaped their solutions and learning throughout the design process.

Ideation techniques such as associative-thinking methods are commonly used to explore design proposals. However, limited experiences and knowledge in young designers can constrain diverse and meaningful design solutions. Emerging artificial-intelligence technologies, like ChatGPT, provide easy access to a global knowledge base which could inform associative-thinking outcomes. ChatGPT excels at generating lists of user-specified topics to accelerate learning with access to decades of gathered online experiences and insights. This study hypothesised that using ChatGPT to inform associative-thinking techniques would improve student idea generation compared to analogue methods in a new product development workshop. Product ideas were represented on Post-it notes, and outcomes were measured by fluency, flexibility, and originality. Thirty-five undergraduate students (first-year freshmen to fourth-year seniors) from Brigham Young University participated in two innovation workshops. One utilised ChatGPT in team ideation efforts, and the other used analogue methods. Over 75 percent of students had engineering related majors of study while less than 25 percent were non-engineering disciplines. All students were equally taught associative thinking techniques, and the ChatGPT group had additional training on software usage. Results show that fluency and flexibility outcomes were slightly lower in the ChatGPT group. In originality, the analogue group averaged twice the ideas of the ChatGPT group. Self-reported performance of flexibility and originality were lower in the ChatGPT group, but higher for fluency. Ideation effectiveness, enjoyment, and empowerment were all lower in the ChatGPT group. Observations revealed that ChatGPT-assisted teams had increased team interactions. Future research might benefit from longer ideation sessions and visualisation training.

Teamwork is an extremely effective pedagogical tool in engineering education. New Product Development (NPD) has been an effective strategy of companies to streamline and bring innovative products and solutions to customers. Thus, Engineering curriculum in many schools, some collaboratively with business schools, have brought NPD into the curriculum at graduate level. Teamwork is invariably used during instruction where students work in teams to come up with new products and solutions. They need to be creative as a group and generate a breadth of ideas and innovative solutions. They also need to be very efficient in their teamwork and work cohesively. The two distinctive traits of the teams, ideational creativity and effective teamworking introduce different creative tensions in the team members – ideational conflicts and tensions thereof, and relational conflicts and interpersonal tensions thereof. Teams that foster and effectively manage these creative tensions are successful and teams that are not, show poor team performance. In this paper we explore the network structural analysis of these tensions and propose a Creative Tension Balance (CTB) index along the lines of Degree of Balance in social networks that has the potential to highlight the successful (and unsuccessful) NPD teams. Team communication reflects the team dynamics among team members and hence the team’s emails are analyzed to generate the social networks for analysis. CTB index is computed and this is used to correlate to the overall NPD team performance. It is found to capture the signatures of high and low performing teams.

A novel “employment experience” module is presented that utilises a students’ existing employment arrangements to further develop the key skills of communication, self-management and organisation. There is no requirement for the job to be in an engineering company, or to involve technical engineering tasks. The students report on their achievement of learning outcomes relating to ethical considerations such as health and safety, codes of practice, quality assurance and environmental considerations with evidence of their self-directed work within teams.

The Employment Experience module aims to improve students’ learning experience in mechanical engineering by enhancing skills required by accrediting bodies, such as Engineers Ireland, through work-based experience. The process aims to develop key competences of an engineering technician: effective communication and interpersonal skills, self-management, professional responsibility, and creating and applying safe working practices [1]. Education in engineering must focus on behaviors and interactions between people rather than technical skills alone [2]. Successful students are awarded a module exemption in professional development in the next academic year.

Employment is sourced by the student independently and a defined period of work experience is completed within an organisation. The employer’s permission is sought by the student to partake in the review the company’s organisational structures. Confidentiality is agreed where necessary. Presentations of the learning outcomes, case studies of previous students’ reports, and support from the careers team in terms of CV writing, employer and alumni connections are provided. The students partake in mentoring meetings during stage 2, the final assessment is an oral presentation on the employment experience and a written structured report giving evidence of the achievement of each learning outcome. Feedback from the employer is also collected.

This paper presents a review of the novel assessment procedure for an employment experience process that has been implemented for four years. The literature reviews other established work placement and pedagogical approaches and highlights this approach’s novel elements. A reflection of the success of the approach to enhance management, team working and communication skills for engineering students is presented in terms of:

i) quality of the alignment of student’s evidence of their individual employment experience with the module learning outcomes,

ii) an evaluation of the pass /fail assessment procedure and assessment panel comments and conclusions,

iii) how the learning outcomes met by participating students compares to the traditional professional development module that students can be exempt from if successful,

iv) participation statistics of students and companies, not limited to the areas of the engineering, business, financial, service, and agricultural sectors,

v) the importance of the 3-way equal partnership and responsibilities between the student, lecturer and the employer.

[1] Una Beagon, Brian Bowe, “Understanding professional skills in engineering education: A phenomenographic study of faculty conceptions,” The Research Journal For Engineering Education, vol. 112, no. 4, pp. 1109-1144, 2023.

[2] Engineers Ireland, “Engineering Technician - Regulations for the Title of Engineering Technician,” Engineers Ireland, Dublin, 2005.

Collaboration is essential to Design and it is a learned skill that needs to be integrated deep into education processes. Therefore, teamwork could enable students to look beyond their own space, time and culture and prepare them for collaborative work in their future design practice. In this study, a blended approach of online tools was tested in design education process has demonstrated improved engagement of students in collaboration. The online tools discussed in this study include Slack, Figma, Miro and a card-based online workshop tool designed by the team.

The study followed a course in design college from 2019 to 2022, to discuss how online tools affect the design education process in studio course of graduate students.

The main objective is to evaluate how the online tools impacted students’ learning and collaboration performance. Firstly, we focused on the co-creation and the competences developed in the collaboration process. Then, we examine the quality of the design project and correlate it to the effectiveness of the communication in the teams. Finally, data were collected with surveys and self-reflection writings carried out at the end of each semester, and comparative study on the intercultural collaborative project outcomes with the outcomes of a traditional in-house team project.

The results revealed that the blended approach has generated promising statistics about the learning and collaborating inclination and teamwork engagement. The advantages and values created are summarized in conclusion.

Generative Artificial Intelligence (GAI) tools are getting involved in the learning process of new generations, and these tools can make a change in product design education, which can be used in different design phases. This study examines their integration through a student project at Linköping University, focusing on the creation of an autonomous robot. From its observation and reports, it is analysed how these tools influence the different design phases and their application, and how students with different skill levels adapt to AI integration. This case study presents not only the practical use of GAI in design but also its impact on educational paradigms, particularly in how it gets involved and reshapes the traditional learning hierarchy outlined by Bloom's Taxonomy. Our findings indicate that GAI tools not only improve efficiency in the design iteration but also introduce a possible shift in learning approaches when it comes to new skills, which may make students skip the learning of base knowledge. GAI has the potential to promote an inverse learning sequence in which students participate in practical application and creation before fully understanding theoretical foundations. This shift implies a re-evaluation of educational frameworks to ensure that while embracing the benefits of GAI, critical thinking and foundational knowledge are not excluded. A balanced approach to teaching that incorporates GAI tools while preserving fundamental engineering and design concepts might be a desirable future.

In recent years, long-distance races have boomed all over the world. Mexico is no exception, but just as the enthusiasm for races over 5k has increased, the rate of sudden heart attacks is due to not having personalised and adequate training. The following paper describes how, based on design and engineering techniques, young students at the Tecnologico de Monterrey are trained to increase their performance as athletes. Statistical methods that allow the design of focused training to improve their times, but without affecting your physical and mental health. The introduction of data science, as well as the design of experiments, allows customizing each training session according to information from each athlete, such as heart rate, VO2max, weight, blood pressure, and the level of red and white blood cells, as well as running technique factors such as stride length, arm stroke technique, and stride. This allows students to actively learn about the application of statistical engineering, which will later allow them to transfer said knowledge to their professional field, making analogies between sport and a disciplinary competition. The results of more than 5 editions of the 5k and 10k race of the annual race of the Tecnologico de Monterrey Campus Querétaro were analyzed. Also, the information from some students who recorded their data through recording devices was processed in databases to calculate descriptive statistics and correlate the designed workouts with individual efforts.

To design ways to actively transition into fairer and healthier ways of living, we need to better understand how systems create conditions that damage the planet and make life difficult, unhealthy and unjust. However, which design practices support systemic understanding and exploration, what design strategies are useful for different forms of systems change and how do we educate students to have a more sophisticated set of understandings about their agency to responsibly navigate complex challenges? This research, in response to these questions, contributes to a growing body of knowledge about responsible design innovation pedagogy.

In an attempt to engage students with increasingly complex challenges and issues, we have noticed that students can struggle to cope with the complexity they encounter. This research is interested in identifying approaches that support more effective engagement with complex, open, dynamic, systemic challenges.

This paper focuses on the planning, performance and review of a project undertaken by a multidisciplinary group of Design School Masters students [anonymised for review]. The project aimed to provide spaces to create understandings of the ethical and social implications of design practices, to creatively deal with excess and adapt systems that can influence the futures of people in a place.

Building upon a review of literature about systemic design and responsible design pedagogy, this research presents a place-based 2-week project that deliberately took a simple starting place - excess mugs in the design studio - to begin a critical design inquiry. Analysis of our research data generates a set of practices, strategies, and systems understandings related to the agency of the group. This is important because it foregrounds an important two-way relationship between taking action in a setting and a grasp of the past-present-future of interacting systems.

The rapid evolution of immersive XR technologies has led to enhanced experiences by blurring the line between the real (physical) and unreal (virtual) worlds. However, there is a dearth of research clarifying the types of learning paradigms to consider when integrating immersive technologies in design education and enhancing learner experience. How can we further enhance our design education system by using immersive technologies to upgrade learning experiences? What type of approach is appropriate to make the best use of the unreal in design education to enhance learners’ experiences in the real? The integration of knowledge from recent neuroscience research into education, through a multidisciplinary translational approach, can be transformative for advancing the comprehension and development of new learning experiences. This research aimed to clarify several questions. It began by (1) reviewing current trends and the role of immersive technologies. Next, it (2) identified their role and value in design education, and (3) highlighted the limitations and possibilities of using immersive technologies as tools in design education with the filter modification model. Finally, (4) it proposed an approach based on recent neuroscience research. This approach uses a multidisciplinary translational strategy to advance the comprehension and development of new learning experiences in design education and to provide experience-based knowledge through immersive technologies. The findings of this research will act as guidelines for the implementation of immersive technologies in design education and will be one of the considerable methods to enhance students’ enactive learning experiences.

Sheila Pontis and Karel van der Waarde（2020）found that the need for change in design education has been a topic for discussion for more than twenty years, but still, there seems to be a lack of concrete advice in the form of structural models or practical strategies that can ballast the required change.

As to this research, the author believes the key focus to build a structural model should be on how to construct a teaching and learning system that adapts to future change. To address the issue, this research will explore three sub-questions:

1. What are the elements of design education?

2. How do the elements of design education interact with each other?

3. What is the mechanism behind the interaction of design education elements?

Exploring these sub-questions answers what the design education teaching and learning system is, how the elements interact, and why they interact in this way. By exploring these three sub-questions, the research responds to the research topic of "how to construct a design education teaching and learning system". This includes:

1. Identifying what constitutes the design education teaching and learning system, constructing a comprehensive framework for the subjective and objective elements of design education. The elements of design education include subjective elements and objective elements. The subjective element refers to students, teachers and management organizations in design education. The objective elements have different contents because of the different orientation of design education.

2. Building the curriculum system of the design education teaching and learning system, linking the subjective and objective elements of design education. Through the process of management organization building the professional matrix, teachers constructing each course, and students mastering the combination of different objective elements, the linkage of the three levels is realized.

3. Establishing the PDRA cycle system for the design education teaching and learning system. Each subjective element dynamically adjusts and improves the linked objective elements through the PDRA cycle process. At the same time, the "Adjust" of each subjective element will affect the "Plan" of the other two subjective elements, and the "Do" of each subjective element will affect the "Reflect" of the other two subjective elements. Specifically, in the practice of design education, it is necessary to collect and actively consider the "Adjust" and "Do" of itself and the other two parties in daily life, actively seek changes with an open and inclusive mind, and steadily promote the reform of design education without adhering to the existing rules. And once the implementation and adjustment of the three subjective elements of educational behavior confirmed, they must be strictly implemented.

Through above three steps, it has chance to construct a design education teaching and learning system, and will be constantly updated, and will not be easily eliminated by The Times.

The rise of Artificial Intelligence (AI) provides an exciting opportunity in many fields and aspects of life. In the field of design, one area to be explored, is how AI could be used to support a designer to develop more novel ideas at the idea generation stage of the product development journey. In this paper, we explore how AI can be utilised to support a traditional 6-3-5 creative design methods workshop, and whether it increases the novelty of the concepts. In our workshop, students were tasked with using the 6-3-5 method to generate ideas for a product which could make life easier for an arthritis sufferer when undertaking tasks in the kitchen. Some of the students were advised they could use Chat GPT to support idea creation; some of the students were advised they could use Google to support idea creation; and the remaining students were advised they would not be able to use any additional support for idea generation. This group was considered as the control group. A feedback survey was distributed among the participants to gather their thoughts on whether the use of AI/Google had assisted them in the application of the design method to generate more novel and creative concepts. Further analysis was then conducted, with a focus on novelty, on the outputs of the 6-3-5 to assess whether the novelty of the concepts in the AI/Google groups was greater than that of the control group. The results of the workshop indicated that the ideas generated with AI support were more novel than those without, and that students utilising AI became more relaxed in their approach to idea generation, relying on AI before fully exhausting their own ideas. Interestingly, the perceived helpfulness of AI was also not fully appreciated by the more novice designers in comparison to those more experienced designers. In this paper we discuss how AI could be used by educators to support teaching and application of more creative design methods such as 6-3-5.

This paper examines the emerging use of AI generative fill techniques in Adobe Photoshop, coupled with informal learning situations, to enhance the creation of product posters for student design exhibitions. By leveraging the capabilities of AI, designers can streamline their creative workflows, allowing for more efficient and innovative design outcomes. The aim of this paper is to examine the benefits of AI generative fill in comparison to traditional manual methods for new graduates exhibiting at their first design show, and to gauge the influence of informal learning settings in supporting designers' adoption of AI-driven design techniques. The findings of this research demonstrate a paradigm shift in the creative process, as AI generative fill in Photoshop emerges as a powerful tool for designers seeking efficiency, inspiration, and novel artistic directions. The findings also show how informal learning settings have played a vital role in nurturing new designers' adoption of AI-driven design techniques.

This paper presents a two-part case study on the "Dreamworlds" project conducted with first-year BA Product Design Students. It explores the integration of Generative AI tools within a five-week design project, focusing on its role in speculative world-building and subsequent toy design. Part One involved collaborative exploration and creation of speculative worlds in teams of 3 – 4 students over two weeks. Leveraging Text-to-Image AI, students produced a 5-minute video presenting their visions, showcasing AI-generated visuals that enhanced artistic direction. Part Two shifted focus to designing toys for children aged 4-5, using the speculative worlds from Part One as inspiration. Unlike Part One, Part Two was carried out individually, emphasizing consideration of materials, safety, and cultural sensitivity. This case study contributes to the discourse on integrating AI in design education, offering insights into its roles in world-building and practical design. The "Dreamworlds" project serves as a practical example of AI application in both speculative and practical design education.

Artificial intelligence (AI) image generators have seen a significant increase in sophistication and public accessibility in recent years, capable of creating photorealistic and complex images from a line of text. A potential application for these image generators is in the concept generation phase in product design projects. Successful implementation of AI text-to-image generators in concept generation could prove to be a cost and time saving application for companies and designers. Therefore, the aim of this paper is to investigate the integration of AI into product design and education. A literature review was conducted to gain a general understanding of what AI is and how AI image generators function. An experiment was carried out which used three different image generators: Stable Diffusion, DALL·E 2, and Midjourney. Three images of dining tables were produced by each AI text-to-image generator and inserted into a weighting and rating matrix to be rated as concepts along with three real dining tables from IKEA. Within the matrix were four design specifications to rate the concepts against: aesthetics; performance; size; safety. The matrix was sent out to product design students and graduates to be completed anonymously. The highest scoring concept was one from IKEA, followed by one generated by DALL·E 2. Based on the results of the experiment, it was concluded that AI image generators are not yet a viable alternative for concept generation in product design but could be a useful tool to spark new ideas for designers to use during the concept generation phase.

The democratisation of generative AIs has led to the emergence of novel paradigms in design. Varying capabilities of GenAIs, in terms of addressing numerous single and multiple modalities, have allowed designers to implement these tools efficiently in their workflow. GenAIs are used in various instances during the design process, such as research, ideation, visualisation, and reporting. Public GenAIs are often used with prompts. The prompts are the instructional input and descriptive data for a GenAI model to start working. Whilst prompts can be in different mediums such as text, images, videos, etc., the most common occurrence in the World Wide Web is text, which functions on large language models, processing the natural language. This ability to tell GenAIs what is needed is called prompting or prompt engineering—a developable skill of carefully crafting sentences and descriptive keywords to return a high-quality result. Designers are already prompting, and in an environment where new models of GenAI are being developed and made public each day, design students at various levels of their education have started using the power of GenAI for their daily design tasks.

One area of great potential is text-to-image modelling, which opens the opportunity for GenAI to act as a fast visualisation tool. This paper presents an implementation of one of the most popular text-to-image GenAI models, Midjourney, as a part of an academic research through design (RTD) process. Midjourney is used as a visualisation tool for outcomes in a design fiction biodesign workshop focused on investigating new future cohabitation possibilities with living materials. In the workshop, design fiction was authored and initially communicated using narratives. Midjourney was then employed as a means to transform verbal storytelling into a visual medium that could more readily provoke design discussion based around feedback, plausibility and design iteration. The narratives were recorded with a voice recorder, analysed through CAQDAS, and converted into GenAI prompts by carefully selecting descriptive words and phrases tied to each participant’s storyworld.

The success of the Midjourney implementation lies in the ability to bridge between the abstractness of fiction and the tangibility of material, as well as to visually contextualize design proposals in a future setting. Using GenAI, it was possible to quickly generate visual interpretations of living materials as boundary objects to provoke discussions on the merits and possibilities of livingness as a material quality. The results highlighted two critical takeaways: 1) in terms of design fiction, text-to-image GenAI models yield unexplored potentials for visualising narrative-based design outcomes and diegeses in a broader sense; and 2) in terms of materials for design practice and education, such models can help ease the communication of performative and experiential qualities of newly developed materials or new material proposals amongst key stakeholders.

Our Design Program at Tec de Monterrey is progressively incorporating Artificial Intelligence (AI) tools, further enhanced by Extended Realities (XR), into our pedagogical practice. This innovative consolidation primarily improves the conceptualization stage of the design process. As students mature in their design intelligence, they harness AI to iterate and visualize alternatives, enriching their decision-making discussions with various project stakeholders. This led to the swift creation of physical prototypes across three distinct categories, each with their unique briefs. Vizcom AI emerges as the most utilized tool, a 2D-rendering platform that refines outputs based on initial sketches and user prompts. Complementary tools aid in navigating the convergence of design and technology education, including VR modelling, AR, and electronic systems simulation. Collectively, these technologies accelerate the design process. However, it is worth noting a consequent limitation in the development of basic analog design abilities, especially affecting the understanding of space and spatial intelligence. Students reported their learning experience with these technologies, along with their expectations and concerns. As we continue integrating these technologies into design education, we have identified the opportunity of leveraging VR to enhance spatial intelligence comprehension, while preserving AI's benefits. This study acts a base to develop new teaching and learning practices that support our students’ professional future in an evolving design landscape with these transformative technologies.

For the creation of standard-compliant drawings, the international standards system of Geometrical Product Specifications (GPS) is fundamental. This paper provides a current perspective on the teaching of GPS. What teaching approaches currently exist? And do these meet the requirements of educators in vocational schools and universities? Particular attention is paid to the use of commercial learning kits. Is learning through haptic models as well as learning by doing outdated in the age of digitalization? What are the learning contents and teaching objectives of such learning kits?

To get to the bottom of these questions, a hybrid learning kit, which combines physical models with digital applications, is used and evaluated in a case study with mechanical engineering students as part of a lecture in the field of ISO-GPS [1]. Finally, the findings are presented in an optimized teaching/learning concept. The aim of this study is also to evaluate simple haptic models in the context of teaching GPS content in an increasingly digital society. Can such simple haptic objects still be convincing and help to understand complex issues? Or do students expect the use of technological visualizations from the field of computer vision?

Artificial Intelligence is currently experiencing a period of “inflated expectations”, according to Gartner and its Hype Cycle report on Emerging Technologies, August 2023. As part of this scenario, this article describes and analyzes the exploratory approach and implementation. experimental AI in three projects developed in 2023, in three different areas of the Tec 21 Educational Model of the Tecnológico de Monterrey: A five-week challenge with international partners and collaborators, a “Novus” fund for educational innovation, and a transversal subject of creativity and innovation for engineering and business students. In all of them, the use and application of Generative Artificial Intelligence contributed significantly – and in new ways – to the fulfillment of their objectives, as well as with new possibilities and reflections on their implications in the teaching-learning processes and the academic quality of their results. The range of exploration and development processes with Artificial Intelligence used, fed by sketches, 3D models or prompt engineering as a 'stimulus', showed from their use possibilities to detonate the formal genesis of architectural proposals for the exploration of different alternatives, accelerate the iteration phase in the creative process to design a car, and reduce the time and learning curve for the generation of digital representations or “renders”. From these results, reflections on new emerging cognitive processes in students through the use of AI, as well as reflections on possible implications and challenges in its approach from Latin America, could be extracted.

In a world where generative AI has become pervasive it is important that we maintain ethical standards when conducting design research and practice and even more so when that is with vulnerable participants. Some concerns exacerbated by AI are around integrity, data privacy, sensitive information disclosure, the amplification of existing biases, data provenance, lack of explainability and interpretability and reliability.

As designing with vulnerable users becomes more prevalent, we need to establish guidelines to ensure ethical practices to protect both participant and researcher. Current research advocates that design research should be conducted with end user groups to ensure that solutions developed meet the needs and expectations of those most impacted by the issues. This approach, however, may not always be ethical or appropriate for design projects within education. Along with many of the standard ethical considerations when conducting research with vulnerable groups there are additional considerations when developing design solutions. Many design projects never reach fruition or may take years to develop a functional design requiring participant involvement over the course of the project. Student projects are not always focused on the implementation of final designs.

This paper builds on previous research (Kiernan & McMahon, 2023) where a framework was developed to guide students when conducting research and practice. It explores several case studies of UG and PG design projects where vulnerable participants have been involved at various stages and to varying degrees. Case study analyses follows a description of these projects in applying the framework.

This paper firstly reintroduces a framework developed by the authors that guides design students when conducting design research. It continues by describing several case studies, comprising UG and PG design project, where the framework is implemented as a key part of the process of working with vulnerable participants across various project stages and to varying degrees. Case study analyses follow where a discussion unpacks key questions around the efficacy and effectiveness of the framework. These questions address how useful the framework is in guiding the student as to when it was appropriate to involve participants; how it did or did not provide the most useful methods to work with participants as well as sufficient alternative methods of research and testing as well as how expectations were managed, and guidance provided around means of payback for people’s participation.

The paper concludes by unpacking the appropriateness and usefulness of the framework to facilitate and guide students over the course of a project while protecting vulnerable participants.

Product design engineering education in the future involves commitment to more than integrative soft skills in team play and supporting student self-management, it is also about mediating collaborative design methods through integrative, intercultural experiences, co-piloted by AI. Balancing collaborative design learning formats is extremely relevant to emerging European Union (EU) regulations. Extreme textiles and new bio-based materials provide functionality yet they represent only one case of business in design. These are countered with fast fashion-based textiles, their prevalence in society, and their problematic performance and abundance. Alongside this, is the real need to protect LMIC communities facing high occupational risks without access to affordable, high quality personal protective equipment (PPE). This submission provides the background, process, and scope for a Collaborative Online International Learning (COIL) design project across three countries and two continents. Defining the project across continents requires navigation of learning and designing formats, alongside rapidly emerging technologies (AI). We will investigate how AI based and hands-on design meet problem-based design projects. This project – about extreme textiles, re-use of fast-fashion for personal protective equipment - will use different design learning formats (from charette to COIL). It extends beyond logistical challenges to address standards vis a vis affordability/sustainability, for a LMIC community needing buoyancy solutions for fishers (SDG 3+14), and the associated student learning. This scoping paper is also about intercultural design skills and it poses the questions; what is the role for AI in integrative design; what difference does it make in this context?

Life Cycle Assessment (LCA) is a comprehensive tool that supports sustainability by assessing products’ environmental impacts. It is both analytical and systemic. However, its integration in the early phases of product development remains challenging for industrial designers. How do industrial designers make sense of it? How do you move from LCA into the early stages of design? Particularly, the clash between the analytical, deductive, delimiting, and multi-criteria parameters of LCA with the divergent abductive reasoning of the fuzzy front end of concept development.

In the paper, we present an example of an LCA design course, which was structured to meet the challenge of how to redesign a product. The course serves as an experimental example of integration and conversion from deductive, quantitative, and analytical LCA to an abductive, qualitative, design thinking process of reconceptualization. In this context, we identify patterns in the disparity across the level of design work. Two approaches, in particular, made a difference: 1) when SWOT factors were categorised according to life cycle stages, circular economy stages and/or circular product design methods, then it qualified the transition to mind mapping, 2) when the mind-map unfolded complexity in 4 or more levels, it enabled deeper insights on factors itself, implementation, relationships and trade-offs to other life stages, specific strategies and circular value propositions. In the case of both, the mind map served as a dynamic tool, used throughout concept development, to bridge the problem/solution space, as well as facilitate framing, rather than pre-stage guiding concept development.

This paper intends to critically assess the attributes of unintended interaction patterns that influence rationality and behaviour towards the mainstream product. Several problems uncover in current practices whether photo-based research can be used to support a scientific design research. Based on previous studies, 15 out of 100 preliminary images representing the context of the use of the product in different ways have been assessed based on users’ perceptions, which analysed 32 attributes representing four dimensions extracted from the notion of unintended behaviour research. The user critically assessed and presented the four highest attributes of each dimension. At this point, the designer used photo-based analysis to evaluate four attributes of unintended interaction that represent four dimensions. A photo was used as the subject of research, transformed into a series of assessment criteria, and thoroughly examined according to Pauwels' theoretical framework of visual analysis. Thirty designers from four distinct levels of experience in product design received the survey to assess the reliability of visual analysis. The study's findings reveal a notable descriptive pattern across several dimensions, resulting in the identification of aspects of unintentional interactions between human rationales and behaviours in mainstream products. This study suggests that it will help designers broaden their understanding of how to identify users' demands in the design thinking process by analysing the reasons behind unintended actions and human contact with mainstream products.

The product design process involves a set of stages, however, there may be many methods that can be used to resolve the different stages of the process, which will be conditioned by the nature of the project or its magnitude. Beyond this, in most cases the time will come when the color, texture, finishes or final appearance of the product (CMF) will have to be defined (Ugale et al., 2022), so there is a tendency to make iterations of the possible combinations of these elements with the idea that the product achieves the function as expected, that the user can interpret and perceive it in the way desired by the designer and it is at this point where Artificial Intelligence tools (AI) could impact by simplifying the process. In this sense, this research aims to identify the impact that applying the Gencraft® artificial intelligence tool would have in the details design stage and its implications in the teaching-learning process of students of the Bachelor of Design (Bailey, 2023).

To achieve the purpose of the research, a sample of 22 students from the sixth and eighth semester of the Bachelor of Design at the Tecnológico de Monterrey, Mexico, was taken to use the Gencraft® tool in the design stage of details of their projects, instructing them to progressively add the prompts until the generated images were close to the product they had already designed, paying attention to the CMFs suggested by the tool up to a total of 12 prompts. Once the exercise was completed, a survey-type instrument was applied to the students to assess the impact of using the tool and the potential it could have within the design process.

With the analysis of the information, it was possible to identify that the eighth semester students have had much more experience in the use of AI for the design process than those in the sixth semester, however, most of both groups agree that the tool used It could also have a lot of value in the conceptualization or ideation stage since the images generated look like product renders. With respect to the CMFs, the majority agree that the main contribution is the final appearance part and a little less in the color part. The students also stated that despite the number of prompts they provided to the tool, there was very little coincidence with the design they had already defined in terms of the final configuration.

With this research it was possible to identify that the artificial intelligence tool used is considered positively by the students within their learning process and as a useful element within the design of products. On the other hand, it was observed that the students began having some difficulties generating the correct prompts or making the tool generate images that were closer to the product design they already had. Likewise, it was evident that they did take the images generated by Gencraft@ as a reference to define the CFMs of their projects.

Design studio pedagogy is the principal teaching method used in design education. The studio environment promotes learning through engagement with real-life projects that are typically ill-defined and supported by a design tutor. While learning is rooted in an experiential modality (learn-by-doing), the why of the designing (purpose, methods and tools) mostly remains implicit. The differing nature of design projects means that systematic approaches are seldom used, therefore students must understand the fundamentals of the discipline to succeed.

This research paper presents a pilot case-study on the integration of a Community of Inquiry (COI) approach into the design studio aimed at subverting the implicit nature of design education. The COI framework is taken from Lipman and Sharp’s 1970s reimagining of philosophy for children, in which inquiry through communal dialogue is used to explore the philosophy of a discipline. In the adapted version presented here, the discourse revolves around the principles of design and emerging artefacts (sketches or prototypes), the design tutor becomes the facilitator who labels design moves and models design skills, and the stimuli are democratically selected design projects.

Survey results provide insights into students’ experiences along with their challenges with this approach. Observations of students’ design tendencies along with their design outcomes are also presented. In addition, the rationale for integrating COI, along with how it was adapted for use in a first-year product design module will be outlined, along with challenges, benefits, and learnings for future implementation.

There are different population groups that present conditions and require special considerations within the product design process, such as the elderly. The UN defines “an older person as a person who is over 60 years of age “(2020). The present research focuses on the development and implementation of a specially structured design process based on said segment of the population divided into four stages: Research, Conceptual design, Detailed design and Implementation.

As part of the methodology, a literature review was done to define the stages and elements necessary to apply the design process proposed (Hanington & Martin, 2012), and the structure suggested in the analytical program of the course was taken as a basis. Once the process was defined, it was implemented in a sample of two groups of students of the Product Design degree studying the sixth semester of the Tecnologico de Monterrey (30 students in total), who developed product design projects (14 in total) for a nursing home in the city of Monterrey, Mexico. During the course, the students visited the nursing home on several occasions identifying a problematic situation through observation and interviews with the elderly people and their caregivers, they also had numerous interactions to present their ideas and validate the iterations of prototypes.

At the end of the course, a survey-type instrument was applied to the students to evaluate the impact of the model on their educational experience and to validate the special characteristics of the process proposed in this research. As a result, they positively evaluated all stages of the process, highlighting the Detailed Design stage as the one that contributes the most value to the development of their disciplinary competencies and pointed out the Implementation stage as the most challenging. Likewise, the students positively assessed the nursing home personnel's participation in the project's development, emphasizing its importance during the Research stage. On the other hand, the students recognized the differences of this design process compared with their previous experiences in other Design courses.

The development of the project had an impact that transcends the practical aspects, working with elderly people implies deepening empathy with them and considering their vulnerability, also paying attention to their human dignity due to the dependence they have on other people to attend their basic needs. Students also recognize the value of distinct types of users who interact with the products. In this sense, the relevance of the personnel was observed; they constantly experience situations of deprivation when attending their basic needs.

In conclusion, it was possible to determine that the design process proposed in this research allows the development of products that meet real needs that tend to go unnoticed due to the lack of consideration of the different users, where each of them may have a different perception of the same activity simply because of the way in which it is related to it, as occurs in this case between the elderly person, their family and the caregiver at the nursing home.

Product design workshops represent environments where technological progress has had a significant impact, especially in prototype creation processes, encompassing both the technology employed in construction and integrated components. However, project management activities persist in being conventionally addressed, susceptible to increasing the margin of error in product manufacturing and extending the time required to conclude the planning phase.

This paper delves into the initial integration of a generative artificial intelligence assistant in the search for relevant information for the execution of product design projects in manufacturing workshop environments. The advanced capabilities of generative data processing are harnessed with the aspiration that this assistant becomes a dynamic collaborator, efficiently supporting and guiding the student throughout the prototype creation process.

This initial approach of the assistant was applied to prototype and manufacturing courses in the 4th and 6th semesters of the Product Design program.

Deaf and hard of hearing learners face unique challenges on a day-to-day basis, especially in a higher education environment. The variability in the types/methods of teaching within Product Design Education means there are various challenges to overcome within various settings where teaching takes place. Accessibility and disability considerations differ from student to student and thus require a significant amount of planning and testing for academic teams to ensure deaf and hard of hearing learners gain access to the same quality and consistency of education as other students do regardless of the setting.

Studying product design often requires teamwork and collaboration, which can be challenging for students with hearing impairments to feel fully integrated within. To create an inclusive and collaborative working environment many adjustments must be made whether this a teaching environment, the use of digital technologies or even consideration of the peer to peer and tutor communication. Furthermore, the stigma associated with deaf and hard of hearing learners often means that students and staff must be appropriately educated when considering the overall learning experience. This paper discusses the successes and challenges of methods of managing the product design teaching environment in combination with the use of British Sign Language (BSL) interpreters, electronic/handwritten notetakers and the accompanying technologies across a four-year period where online learning, blended learning and face to face delivery were all a part of the learner’s experience.

This paper presents a case study examining the four-year learning experience of a student with Auditory Neuropathy Spectrum Disorder (ANSD) and permanent bilateral severe-profound hearing loss who studied BSc (Hons) Product Design SW at Nottingham Trent University which included a placement year in industry at Kinneir Dufort as a Product Design Intern. We reflect on the education adjustments designed into the course curriculum which have benefitted all students, whilst also reflecting on the support provided for applying for placements ensuring a successful placement/internship can be secured including embracing and integrating the necessary adjustments in relation to the access to work guidelines. In addition, a student review and testimonial of their learning journey will be presented reflecting on their educational development and support systems.

Creating an inclusive education environment to support deaf and hard of hearing learners in product design education environments and within industrial settings requires a proactive approach and as such all factors must be considered ranging from fostering a supportive inclusive learning community to integrating/embracing the network of specialist support staff to ensure all students thrive.

In this work, we apply the Singapore University of Technology and Design (SUTD)’s STEAM x D (STEAM = Science, Technology, Engineering, Arts and Mathematics, and D = Design Thinking) transdisciplinary collaborative principles to a different set of disciplines (i.e. Humanities, Artificial Intelligence, 3D printing, etc.), in a workshop which was carried out for a total of 46 participating high school students (17-18-years old) in which ~ 40% were female students. In this 5-day workshop the students worked in teams of 4 to 5 students along 8 SUTD instructors from different disciplines, and 10 SUTD undergraduate helpers, to solve a design challenge using a systems approach complemented with human-centric, design thinking, and engineering elements as part of our daVinci@SUTD immersion programme, which seeks to inspire youth in human-centered design and innovation that are grounded in STEM education fused with the understanding of Humanities, Arts, and Social Sciences to serve greater societal needs. In general, survey feedback showed high levels of student engagement, awareness of using Artificial Intelligence, engineering, and design thinking to address real-life problems, and overall, the students found the workshop useful and insightful.

This study reports on what tool and methods design major students use to discover, define and solve design problems. The site of this study is Design Thinking and Methods, a compulsory course for first-year Chinese design majors. The teaching goal of this course is to cultivate students’ design thinking practice and innovation ability. Firstly, this paper reviews the definitions of design problems and design thinking through literature. Secondly, it outlines students’ understanding of design thinking and design problem solving. Then these concepts are analysed to explore similarities and differences among 220 students. Finally, students design project are classified in relation to students’ attention in different stages of design activities. The study found that most students can find design problems, but often they are unable to identify the nature of the design problems, which then leads to inappropriate design solution.

In this study, over one hundred undergraduate students across three courses track time spent on a design course. Students received points only for measuring and reporting time and not for the quantity of time, thus helping increase time-tracking data validity. The study’s correlation between time and student performance is unsurprising. However, several other outcomes of this study are fascinating.

Soft skills, like time management, are often not explicitly taught in primary, secondary, or university education. The exercise of tracking time teaches students about themselves, helping them recognize opportunities for improvement. Most students do not like tracking time, but many admit it is beneficial. Time tracking allows them to be personally responsible and accept the consequences. Many conversations with students have shifted from “Tell me how to get a better grade.” to “Help me improve time management so I can learn more and do better.” Time-tracking data also provides additional context for professors to interpret student performance. When students are not performing well, time-tracking data clarifies how to help: do students need help recognizing the discrepancy between time invested and results expected, or do they need additional help understanding and applying course content?

Continued interest in augmented reality (AR) applications in the business sector has precipitated a corresponding surge of design with AR in the design industry. In turn, the rise of AR technology in the design profession requires a proactive response from design education. Recent scholarly endeavors exploring AR-focused practices in design education have showcased the early initiatives of teaching AR across diverse design-related disciplines. Upon that foundation, this paper introduces a pioneering pedagogical approach that integrates AR into a foundational 2D graphic design foundation course. In an experiment following the approach, we used the AR toolkit Zap Works Designer not only as a creative medium to augment a print design project but also as a purposeful pedagogical instrument aimed at expanding students’ digital proficiency, fostering an understanding of design thinking, and cultivating problem-solving skills through immersive engagement in a multidisciplinary design process. This paper outlines the AR-enhanced project and assesses its pedagogical efficacy based on a comprehensive student survey conducted at the end of the project. It also delves into the challenges encountered along the way and provides positive suggestions for the specific learning context. By sharing insights from the teaching experience, we aim to empower design educators and provide educational institutions with a valuable reference for advancing their curricular approaches. This paper is a testament to the ever-evolving landscape of design education and its response to the imperatives of the digital age.

Many design schools struggle with questions of how recent AI advancements should be integrated into their curriculum. This is especially challenging for curricula with a substantial digital design component, such as media design or interaction design. Undoubtedly, curricula must include the aspect of designing 'with' AI, teaching students how to responsibly and ethically use AI in their design process. More importantly, programs should also integrate the concept of designing 'for' AI. While designing for emerging technologies, such as mobile, immersive, and social technologies, has been a constant challenge over the past decades, designing for AI is distinct from these challenges, since interaction design must adapt now, not to a new device, but to a new agent. This paper examines four different perspectives on how designing for AI alters interaction design education and the scale of its impact.

Firstly, as mentioned above, future digital designers will be working with tools that are partially AI-based, including generative AI tools and decision aids. Secondly, their work context will undergo changes, as they assume different roles at different types of companies. Thirdly, they will need to address vastly different design challenges as they will work on an entirely new type of applications. Finally, the design of intelligent systems demands a new solution repertoire for designers. This paper will sketch the challenges for all these perspectives but will primarily focus on the last two: equipping students for designing ‘for’ AI.

For these last two challenges the educational debate centers around a ‘lightweight’ approach versus a ‘heavyweight’ approach to designing for AI. The lightweight approach prioritizes a solution repertoire associated with the front end of AI applications, with a focus on user interfaces, the user-AI interactions that need to be designed, and their immediate impact on user experience. We will argue that this is a deceptively novel area where students need to get adept at designing for shaky mental models and assume responsibility in creating ethical applications. Designing the front-end of AI presents fresh challenges in education, which, contrary to common beliefs among educators, are largely disconnected from a deep understanding of the underlying technology.

The heavyweight choice for digital design curricula entails a focus on the conceptual design of AI applications. This encompasses challenges such as involving users in the design of applications with AI, altering the AI design processes, facilitating communication between data scientists and designers and fostering responsible design practices. These challenges do require a basic understanding of the technology, although the level of specific declarative and experiential knowledge required by students to excel in this domain remains uncertain.

In this paper, we compare these approaches and discuss their complementarity. Specifically, we explore whether it is advantageous for students to begin with the lightweight approach - grasping practical applications and user-facing aspects of AI and then gradually transitioning to a heavyweight approach - exploring technical intricacies, and learning how to innovate and improve AI technologies. Finally, we draw conclusions regarding the broader transformation of the design field resulting from the influence of AI.

Over the past decade virtual reality (VR) headsets have become increasingly affordable and available. This in turn, has made virtual reality tools more accessible. Within the context of product design, one of the possibilities opened with VR is that of creating 3D models within a 'virtual/immersive' environment. This has several advantages for product design educators, including increased/high student engagement due the novelty of the approach and physical/immersive experience. How to incorporate this type of 3D modelling in the curriculum however, remains substantially less clear.

While there is continued interest on VR from segments of the academic community, its adoption within the context of product design education is in its infancy. Moreover, because of the many different variables involved, and the differences inherent to any design project, the experience from a larger and wider variety of case studies is necessary. This paper reports from a case in which VR has been incorporated into a design project in a first-year course which is part of a product design degree course.

This paper describes the development of a physical-digital demonstrator that makes use of augmented reality (AR) technology, to convey complex systems and engineering information for design education. AR blends the real, physical world with digital, computed-generated elements. This is achieved through three-dimensional technology features, adding contextual layers of information to the users’ sensory experiences of their physical environment (Wang et al., 2021). The uniqueness of AR in preventing the encroachment of the real world has enabled it to find broad application as a valuable interactive tool in several fields, including within educational environments. In STEM subjects particularly, AR can be employed to enhance spatial ability, conceptual understanding and visualisation skills by functioning as a blended learning and teaching tool (Hidayat & Wardat, 2023). Consequently, we aim to investigate how its potential applications in engineering and product design educational settings can enrich the adoption of digital tools in design workflows through exploring the intersections between physical and digital technologies based on a case study.

One of this work’s main outputs is the development of an “Order of Engagement” framework that characterises the nature of interaction with physical-digital interfaces. This encompasses 1) observation of system architecture and location conveyed through static representation, which can also be modelled within physically prototyped models; 2) interaction with information and representations of system functionality through AR artefacts via the mixing of physical prototype models and digital interfaces; and 3) integration of dynamic conditions and performance conveyed through live simulation. The paper will describe the design, development and evaluation of an AR demonstrator system and the associated implementation of the framework via a research case study carried out in collaboration with an industrial partner who specialise in coastal erosion prevention systems. A desktop demonstrator device that can be physically manipulated and works in conjunction with an AR interface application was constructed, and reviewed with respect to usability and user engagement. The first proof-of-concept prototype produced valuable insights with respect to environment mapping and visualisation. Therefore, the second stage of the project aims to address the integration of detailed system information by evolving the system’s digital visualisation capabilities. This will be done through the incorporation of the dimension of time, allowing the long-term effects of coastal erosion and biodiversity to be captured and communicated (our 3rd Order of Engagement, for the purpose of enabling the company to perform more advanced analysis.

As well as acting as an educational and client-facing tool for the industrial partner, the configuration and principles of the demonstrator point towards how physical-digital installations can be used in design education settings more generally. We will outline the development of case study material for human-centred design and product modelling and visualisation education. The real-world application of physical-digital interaction means the lessons learnt from the AR demonstrator design and Order of Engagement framework evaluation will have clear practical and commercial applications for future digital interaction design.

Fablabs are educating people in digital fabrication relevant to many areas of life. Often, education in Fablab context is non-formal. Existing examples of formal educational programs, Academany courses, such as Fab Academy are provided through Fablabs for people to learn the possibilities of digital fabrication, with Fab Academy being accredited in several universities around the globe. There is need for continuum for this education within Fablab network, as well as it would support the appreciation of this continuum through the world if it would be possible to accredit it even partly in any university. Here, we study pilot "Grow with Fab", run in the network and propose a model of formal education for digital fabrication, Fab Thesis, and a possible method to share it to the network as well. This is a methodological development that bridges the Fablab educational paradigm with academic education.

The manufacturing industry is constantly facing multiple trends and challenges – globally and locally. Technologies, like Artificial Intelligence (AI) or Machine Learning are key enablers for companies to increase the ability to react and adapt. No matter if those technologies are part of products for end-consumers, or part of machines which produce the products for the end-consumers – those technologies need to be innovated, designed, produced, maintained, serviced, and recycled. For all those activities people with the right skillset are key.

Especially in the European countries the demographic trends increase the trend of both, high-level of technology utilization in the manufacturing process and at the same time highly skilled people.

Companies like Siemens take this in consideration and focus on people and their education in a “multi-channel” approach. This paper presents an approach of a research and innovation eco-systems and provides industry-leading-practices. This eco-system allows people in different phases of their educational life to continue their learning path. Moreover, multiple partners in science, education and industry bring their input and opportunities into this eco-system. And one of the key benefits for all participants is the transfer of latest knowledge and technology into the industry. Siemens Industry Software has implemented this approach in the regular line organization to ensure continuity and proof the commitment and dedication to the topic of education.

In 2021 we proposed a novel way of teaching Design Sketch Ideation across a digital platform defined as High Intensity Ideation Training (HIIT). The COVID-19 pandemic precipitated a monumental shift in higher education, compelling educators to rethink traditional teaching methodologies and adapt to the demands of online learning. Now that we have returned to physical teaching environments, does the approach that we suggested still work? Or is there a better solution that utilises the learning from the pandemic, to further develop pedagogy? This paper outlines a framework for HIIT 2.0, utilising the originally digital structure of HIIT in a completely physical studio environment. This paper highlights that the original core benefits of HIIT in enhancing students' creativity, fostering collaboration, and promoting active participation are still achievable in a real-world environment. Through observations and comparisons to previous iterations, the authors found that this new approach outperformed fully digital models and allows for a more meaningful interaction within the student cohort. In this new era, the collaborative and creative skills developed through HIIT 2.0 will be instrumental in preparing students for the evolving demands of the design industry. This approach helps facilitate a future where creativity, collaboration, and innovation remain at the heart of design education, regardless of the challenges or opportunities in the educational landscape

This paper explores the transformative impact of employing engineering Lean Six Sigma techniques within the context of a university. The study focuses on an examination of several pilot process improvement projects in various service areas of a university located on the southern coast of the UK. Executed over 18 months, allowing both the implementation of improvements and the subsequent analysis of their effects throughout an academic period. This approach yielded a substantial corpus of quantitative data. The utilisation of key engineering tools such as Value Stream Mapping, Swim Lanes, and Control Charts played a pivotal role in streamlining processes. Resulting in, significant reductions in processing steps, leading to process enhancements ranging from 12% to 56%, and, in some instances, achieving 100% completion rates. These improvements were further validated by Value for Money measurements, exhibiting gains from 8% to 50%, although the quantification of these gains was more challenging in certain projects due to their unique nature. It was often difficult to define the specific data sources and outputs required in these non-traditional engineering environments. Nonetheless, this study underscores the importance of clear comprehension of the Voice of the Customer and Critical to Quality requirements with active stakeholder engagement, irrespective of the size or nature of the project. In conclusion, the application of Lean Six Sigma methodologies, beyond traditional engineering realms, proved to be a resounding success. This marks the initial steps in a larger journey, where incremental improvements lay the foundation for growth and a staged shift in organisational culture.

This paper explores an approach to packaging innovation through the integration of Design Thinking with a specific focus on Braille packaging. It seeks to address the dual challenges of environmental sustainability and inclusivity in packaging design. By applying Design Thinking's empathetic and user-centric methodologies, we use a framework for creating packaging solutions that are not only ecologically sound but also accessible to visually impaired consumers. The iterative process of prototyping and feedback inherent in Design Thinking allows for the exploration of tactile elements in packaging, with Braille as a central feature. This research showcases how such an integrative approach can lead to pioneering designs that provide practical benefits and a sense of independence to visually impaired users, while also ensuring a reduced environmental footprint. Case studies within the paper illustrate the successful application of this experiment, resulting in Braille packaging innovations that elevate the user experience and demonstrate a commitment to social responsibility. The findings underscore the potential of Design Thinking to revolutionize packaging design by delivering inclusive and sustainable innovations that cater to a broader demographic, ultimately enhancing brand perception and fostering a more inclusive society.

In Japan, design is not taught as a subject in the general high school curriculum. However, a new period for inquiry-based cross-disciplinary study was established in high schools under the new curriculum guidelines, which were implemented nationwide in 2022. The process of introducing multidisciplinary inquiry-based learning in high schools is currently underway, although the instructional training and teaching materials available to teachers are far from adequate.

Japanese public high school teachers collaborated with the SDGs Design School, Faculty of Design, Kyushu University to co-design inquiry-based learning materials. These materials, which have been implemented in a school since 2019, take the form of a booklet of worksheets in which students describe discussions in which they have been involved, as well as their ideas and research findings. They are intended to guide students’ self-learning and help them think about the social issues around them and seek solutions to those issues.

This study examined the introduction of these materials during the period for inquiry-based cross-disciplinary study in a general high school in the context of the SDGs Challenge Project. The study was conducted in 2023, and all 300 third-year students in the school participated. It was intended as part of a broader investigation into how to implement design-based skills for multidisciplinary inquiry-based learning in Japanese high schools.

The research question was: “What knowledge do teachers need in order to conduct design-based inquiry learning?” To answer this question, it was necessary to first identify which design processes are generally difficult for students and teachers unfamiliar with design education. Secondly, we examined what knowledge needs the teachers had for this process.

After the SDGs Challenge Project, a questionnaire survey of the 300 participating students was conducted. The participants were asked to identify the most difficult process used in the program and to give reasons for this. The 23 teachers who conducted the classes were also surveyed and asked which processes were most difficult to teach, why they were difficult to teach, and how they thought these difficulties could be overcome.

298 students and 10 teachers responded to the survey. In order of descending frequency, the processes identified as difficult by the students were: sharing problems, ideation, and improvement of ideas. The processes identified by the teachers were: exploration of problems in our daily lives, sharing problems, and ideation. Both sets of respondents identified sharing problems and ideation as particularly difficult processes. The teachers’ responses to open-ended questions regarding reasons and possible solutions were categorised using thematic analysis. Sharing problems was reported to be difficult because the teachers were not sure how to guide students in developing empathy regarding issues with which they had no experience. The possible solution was to share best practices to understand how the problems could be studied in depth. The ideation process was identified as difficult because the teachers did not know how to guide students’ ideas when they were abstract and lacked detailed specifications. The solution identified was to learn practical design methods for guiding ideas and detailed instructions.

Integrating the Sustainable Development Goals (SDGs) into design education and building up the knowledge base in this area is probably one of the most pressing tasks and challenges for Chinese design educators because of the increasingly serious issue of ageing, inequality, and environmental problems. Universal design, considered to be an effective tool for eliminating inequality and promoting social inclusiveness, is a good bridge for implementing SDGs into design education. It has the potential to help students appreciate user capabilities, needs, and expectations, and is increasingly important in mainstream design education. However, the adoption of SDGs in universal design education still meets with many barriers in China. This study focuses on these barriers and try to find out possible corresponding actions based on a series of universal design workshops since 2017 at Shanghai Dianji University organized by the authors. Many research methods have been utilized, such as literature review, expert interview, questionnaire, and case study. Many influencing factors have also been hypothesized and examined, including major, grade, real user participation, ice break, tea break, diversified places, teaching language, etc. Through quantitative and qualitative analysis, some key factors are focused and put into discussion. Finally, a preliminary conceptual framework is proposed to summary all the barriers and corresponding actions to better integrate SDGs into universal design education in China.

Firstly, a literature review focused on SDGs and universal design education was carried out. Key books and papers on these areas are picked out. The practices and perspectives from different countries are synthesized. Compared with the barriers from the literature review, related to the authors’ experience as organizers of the universal design workshop, preliminary barriers of integrating SDGs into China’s universal design education were initiated then demonstrated to expert interview.

Expert interview intended to get some perspectives and insights from interdisciplinary experts, especially from teaching administrators. Six experts were interviewed. Three experts are from design education and three are from teaching administration. Based on the perspectives from experts, four aspects of barriers were finally clarified, they are: lack of awareness; lack of resources; practical difficulties; financial and cultural factors. Corresponding response are initiated.

Then, a case study of Shanghai Dianji University’s Universal Design workshop from 2017-2023 was conducted. Six key elements were filtered out within China’s talents cultivation system, namely education aim, educational standards, course system, syllabus, teaching method, and core courses. These elements are hierarchical and successional. The case study gives some inspirations for design education.

Finally, a conceptual framework was triggered. The framework manages to accommodate all the key elements of China’s education system (identified in case study) accompany with the barriers (focused through expert interview), and actions (enlightened from literature review) to a hierarchical and successional “tree”. From top to bottom of the “tree”, the key education elements are arranged hierarchically.

The framework suggests the likely route of integrating SDGs into China’s universal design education. It shows the possibility of potential application for design educators and SDGs practitioners.

Global corporations expanding business across different local markets have identified cultural insensitivity to be a potent barrier for expansion. The degree of acceptance by local consumer cultures has become an integral part of the success and failure of their operations. The integration of cultural aspects into the product development process has become an important aspect of design practice. The goal of this paper is to provide a culturally oriented design (COD) framework for designers to research the culture of intended users beyond their first-hand experience. The framework outlines a three-step process to research intended users’ cultural context, synthesize situated cultural differences and identify and translate cultural values to new design concepts.

The damage that human activities have caused to our planet is undeniable, especially since the Industrial Revolution. We are in the era of the Anthropocene: characterized by the excessive consumption of natural resources and the generation of greenhouse gases, which have had a significant impact on the climate and biodiversity.

Fortunately, in recent years related initiatives have emerged to reverse the above. Some of them are zero waste, recycling, downcycling and upcycling design, related to the reduction and maximum use of waste, as well as the extension of the useful life of products and/or the use of their materials. The circular economy, a production and consumption model that allows the useful life of products to be extended, has also brought benefits to the environment, the economy, and people.

In congruence with the above, in the Product Design course, last year elective open course of the Industrial Design program, two design methods have been proposed based on the Biomimicry design spirals, for the development of products based on the use of recycled materials, especially derived from wood and plastics.

This work shows the new methods and the results of their implementation in three courses, taught to students from different disciplines, this in the academic periods Summer 2022, February-June 2023 semester, and August-December 2023 semester.

Nonverbal communication is an important and helpful way to deliver messages. Motion is one element of nonverbal communication that can enhance the clarity of messages between the sender and receiver. However, the perception of motion varies based on the diverse backgrounds of participants, with the difference in cultural background being one thing that affects interpretation. Nevertheless, there is a lack of research on how people from different backgrounds perceive motion. This study aims to verify the factors influencing the perception of vitality and understand how individuals in various locations perceive motion. The experiment employed motion graphics, utilizing angle, acceleration, and fluctuation as tools to investigate their influence on the evaluation. This research implements an experiment with participants from Japan and Thailand, utilizing Head-Mounted Displays (HMDs). The study utilizes a 20-question subset from the Profile of Mood States 2nd Edition (POMS 2). Within this subset, 10 questions are categorized as positive, and 10 as negative sub-scales that correlate with the feeling of vitality. The results reveal differences in the evaluation of motion perception between Thai and Japanese participants. Specifically, Thai participants significantly rated attributes such as lively, vigorous, cheerful, active, alert, energetic, helpful, and efficient higher compared to Japanese participants (p < .01). Understanding cultural influences on perception leads to enhancing nonverbal communication and guiding diverse product development for varied target audiences. In terms of education, the use of learning materials designed to evoke positive emotions enhances comprehension. Researching methods to elicit positive emotions is essential for the future.

In design research there is a deep interest in how designers solve complex problems using design methods and heuristic shortcuts and in particular how this might relate to Machine Language (ML) to simulate the design process. With the introduction of Large Language Model (LLMs) such as Chat GPT we can appreciate how software with the remarkable capability of Generative Ai (Gen Ai) and generative design can be used to assist designers in the three-dimensional design of their products. In this paper, we will focus on how AI will impact designing in computing, identify what is relevant and suggest a new development opportunity. Our interest is in examining the potential for better and novel software solutions, making them easier to use during the design synthesis process and capable of adjustment throughout the 3D CAD development stage. The specific problem we aim to resolve is how to optimise a designer’s time spent from concept to production using Gen AI & 3D CAD software without affecting the quality of design thinking, methodology and practical process. Gen AI as an evolving platform has the potential to create a design to production productivity shift that industry and academic groups have long predicted. Designing will remain creative and inventive, individualistic or team based and using what we have termed an AI design assistant, AIDA.

Artificial Intelligence has the potential to substantially transform design education. Since ChatGPT was made available online only in November 2022, before course descriptions for the 2023/2024 academic year were finalised, there was no formal basis for regulating the use of this tool, or similar ones, in student assignments. This was particular an issue for a course that requires students to write a scientific review article, in the last year of master programs in Industrial Design Engineering, Industrial Design, and Interaction Design. In the autumn 2023 edition of this course, which has continuously run since 2001, 80+ students were tasked to write a 10-page review article on a topic of their personal interest, in conjunction with a design course where students are tasked to do a design project founded on state-of-the-art theoretical understanding in a relevant field.

Since the autumn of 2022, the university has not managed to provide guidance for teachers or students on AI use, other than some very general university-wide guidelines which mostly address plagiarism, and a notion that ‘potential challenges and opportunities that would result from using chatbots vary from discipline to discipline and course to course’. Taking up the challenge of establishing what would be good practice in the context of this particular course, for the first time a workshop was organised at the beginning of the course, to address specifically the issue of using AI in the process of writing a review article, and to provide clear guidelines for students on how to approach this issue.

The first part of this paper explains the organisation and content of the workshop, which challenged students to navigate the landscape of appropriate, undesirable, inappropriate and unacceptable use of AI tools like ChatGPT towards the preparation of their review article. The workshop resulted in establishing a contract between students and responsible teachers, which was intended to provide a clear set of rules and frame of reference for students to navigate in. The workshop also provided a stage to share fears, both from the side of the students and the teachers, for example about how to take up possible accusations or being unjustly accused of unacceptable AI use .

All students were asked to include, in the Methodology section of their review article, to explain how and why they did (or did not) use AI-based tools in doing the research for their article and during the writing process. A preliminary analysis of drafts of the paper indicates that some students used chatbots extensively, whereas others explicitly state to have refrained from their use completely. The second part of this paper analyses and the discusses choices that students made, also informed by an post-course survey in which students were asked to reflect over the use of AI in the course, and draws learning from the results of this towards next editions of this and other courses.

The aim of this paper is to consider the impact of AI in engineering design teaching in traditional MEng undergraduate courses. AI is presently making headlines, so it would be interesting to use and see what it produces for existing design coursework.

The coursework is in the first year and is intended to give students experience of the design process in which they also apply engineering drawing practice from semester 1. The students enrol onto our programmes with good analytical skills from their high grades in maths, and similar, so design and the teaching of it needs to pitched at a level which they can engage in and not be overwhelmed.

Equally, because coursework is “open” assessment they will and should be able to research any resource for knowledge and inspiration especially in the concept phase. So, does it matter if students use AI? After all, they ought to be technologically aware.

Here, the author will explore AI (software) by focusing on two existing design assessments and review the findings. One assessment is worked on in groups of six or seven and each student must contribute and concept drawing. Students have often commented that after generating three concepts, it is difficult to think of different ones. Maybe AI is helpful here as ideas generator and one can take a relaxed view of its usage. Conversely, it might provide images with poor functionality.

Either way, it will be useful as an educationalist to know more about AI and this will be of benefit to the author. As mentioned, students are new to design and need support to increase their appreciation of mechanisms and design elements, and to that end, the learning materials are chosen carefully to help them step through the process. If AI can short circuit that process, then the danger is that they “cut and paste” with little design learning. There is a thin here, as students can use the web, so how much further does AI really help in completing the assignment’s deliverables…

Co-design brings designers, end-users, researchers, and other pertinent stakeholders together to forge meaningful design solutions. It dismantles traditional barriers between professional designers and end-users by fostering collaborative, participatory design development processes. This paper explores using an AI visualisation tool, Vizcom, in a co-design workshop. The tool helps participants without visualisation skills to convert their rough sketches into refined visual representations. Thirty-six undergraduate students from Brigham Young University across ten disciplines participated in the study. Participants were introduced to the principles of co-design and the functionalities of the Vizcom, including how to create accounts, craft effective textual prompts for AI, and adjust the drawing influence parameter to optimise the visualisation of their ideas. Participants worked in pairs, designated as "users" and "professionals.” Prompted to reflect on their campus lunch food heating experiences, users shared insights with professionals who conducted interviews to pinpoint specific problems. Following this, professionals and users brainstormed solutions together. The users then sketched the proposed solutions, guided by the insights and ideas discussed during their collaborative session. After completing their sketches, they used their mobile phones to upload their sketches and detailed prompts into Vizcom, generating visual representations of their concept.

The study collected feedback from both professional and user roles through separate surveys, assessing the effectiveness of the AI in capturing and enhancing their conceptual solutions. The findings suggest new avenues for co-creation in product design, emphasising the potential of AI tools to bridge the gap between rudimentary sketches and sophisticated visual outputs.

In an era characterized by the pressing need for environmental sustainability, educational initiatives that empower students with the knowledge and skills to engage in sustainable practices are crucial. This paper presents a case study of a Collaborative Online International Learning (COIL) project that explores the transformative potential of intercultural collaborations in the context of sustainable material selection practices. The project, involving students from Mexico and the United States, challenged participants to research and specify sustainable materials for residential interiors while incorporating local artisanal, handcrafted elements. This collaborative approach transcends geographical boundaries, enabling students to delve into the complexities of sustainability, examine materials through a global lens, and consider cultural and environmental impacts. The project aligns with the United Nations Sustainable Development Goals (SDGs), specifically SDGs 9, 11, 12, 13, and 17, by incorporating international perspectives. The paper explores how the project's objectives, methodologies, and outcomes, nurtured the development of intercultural competence and collaborative partnerships while teaching responsible consumption, mitigation of climate change, and preservation of local traditions and cultural heritage. The findings demonstrate that such collaborative initiatives hold the potential to catalyze sustainable transformations in material selection practices, preparing the next generation of designers to contribute to a more environmentally responsible and culturally inclusive future. This case study serves as a valuable model for educators and institutions seeking to integrate intercultural collaboration and sustainable design into their curricula, offering a blueprint for addressing the pressing global challenges of our time.

During the confinement of COVID-19, learning about virtual and augmented reality grew exponentially; universities were the accelerators of this knowledge. Distance learning was the trigger to consolidate emerging technologies in education and professional life, including virtual reality (VR) and augmented reality (AR). Given the rising interest in virtual simulations, this paper targets authentic design challenges and how distributed collaboration may enhance the immersive learning potential by utilizing network resource efficiency. According to the Institute for the Future of Education of the Tecnológico de Monterrey, in the Tec21 educational model, the most important part is the challenge, which is defined as a problematic situation posed by the partner trainer, and when analyzed, a problem is defined by mutual agreement. The project is defined on this problem. One of our most essential training partners is CAETEC (Campo Agropecuario Experimental del Tec de Monterrey), where we carry out different challenges ranging from precision agriculture, data science, experiment design, and forecasting, among others.

Despite being one of the largest laboratories of the Tecnológico de Monterrey, there are different restrictions to be able to bring whole groups to its facilities, so within the institutional projects, they are creating a virtual plant, in this case, a virtual experimental agricultural laboratory, and one of the first modules is the robotic milk production process.

The robot that is being used is manufactured by DeLaval. The term robotic milking system refers not only to the use of an articulated hydraulic arm but also to the concept of global automation of an installation and to the voluntary assistance of the cows. to the robotic milking module, they were also known as "AMS" for its acronym in English: Automatic Milking System.

To do the 3D modeling for this robot, it is necessary to work with the former partner, whose headquarters are in Sweden, through a collaboration agreement between universities that pursue the same educational purpose. We will work with the Project Department of the University of Mälardalen, where the Tec de Monterrey Campus Querétaro will do the 3D modeling of the external and visible part of the Robot, and the University of Mälardalen will do the 3D digitization of the internal components.

The design of the VR lessons will allow us to explore best practices through data recording and user behavior, both students, CAETEC employees, and the robot manufacturer, DeLaval, to explore better processes aimed at industry 5.0. , where we will collaborate with the University of Mondragon to find the best way to operate this robot and be the beginning of joint research that helps the industry.

This research is the result of joint work between three educational institutions, with a multicultural and multidisciplinary project approach.

WitWithin product design education, encouraging collaboration, creativity, and a sense of community among students is vital, especially during the first few weeks of undergraduate study. Creating a student community in the early weeks is crucial for students to adapt to course cultures, adjust to new environments, and establish friendships. This is essential in creative disciplines where students must collaborate, serve as critical friends and network in a professional practice setting. Post-COVID-19 pandemic, students are increasingly anxious in new environments and reluctant to engage in large events, which is problematic in a sector where ‘community’ is essential. Thus, it’s important to create a collaborative culture quickly within undergraduate programs, however, this is a challenging task with large student cohorts. A strong design community can serve as an incubator for creative ideas, peer learning, and emotional support, helping students thrive in an academic environment that often demands intense problem-solving and innovation. This paper introduces 'A Hole In One,' a Welcome Week project designed to promote student engagement through competitive model-making. Using unique innovative approaches, we introduce core values to first-year Product Design students through experiential learning and collaborative design making. The core aim is to break down barriers and cultivate student communities by challenging student groups to construct a unique crazy golf hole in groups. The collaborative effort resulted in a crazy golf course being assembled for an end of welcome week student competition. Our findings offer educators/institutions guidance in promoting community-based teamwork within design programs, suggesting innovative pedagogical approaches to elevate the educational experience for product design students.

Recent evolutions in the accessibility and widespread uptake of generative AI tools have already affected the way we teach at university level, including in the design and engineering domains. Exploring AI related tools and technologies is increasingly part of formal design study and informal and peer learning. It is however important to place recent evolutions in a longer temporal context; design activity and education have seen a progressive move away from “thing-based” approaches and towards capability, service and experience. Another important evolution that can be observed is the need to teach more systemic approaches, looking at the wider context and impact of design projects.

These evolutions in design and design education create a learning environment where the abstract, virtual and experiential are, in some cases, more present than the material and tangible. Unsurprisingly design educators comment on students’ growing appreciation of hands-on activities and on their sense of lacking material knowledge. In the context of rethinking the design curriculum for the fundamental changes that AI will bring to design, the form that the teaching related to material relations should take will also be increasingly critical. We argue that design teaching may need to refocus on the importance of materials and materiality and on tangible everyday material experience, but needs to be reconsidered as part of a balanced and already crowded design curriculum.

This paper presents two different “families” of teaching modules that have evolved over a period of five years with a focus on materiality relations, materials and touch. One module family is based around a protocol of careful and detailed self-observation of student’s everyday material relations followed by mapping, sense-making, presentation and group discussion. The second family is related to the hands-on making of small daily-use objects in materials generally unfamiliar to students, and evaluating them both for visual but also tactile qualities.

As the two modules represent quite different ways of exploring materials and material relations, they together permit a reflection around forms of tangible/material learning activities that may be relevant in future design curricula.

Both modules have been tested with different groups of students, and in some cases have been followed by reflective student reports, contributing to a rich source of student feedback. This paper highlights a number of themes that emerge from the analysis of student and tutor feedback including corporality, sense of touch, material knowledge, awareness of our material relations and sense of agency. These themes are discussed in relation to recent design research literature.

We argue that teaching focused specifically on material relations and materials will remain highly relevant and perhaps even more essential in the context of the fundamental changes the AI era will bring to design and design teaching.

This paper proposes a novel design process that uses ethnographic research principles to create generative AI outputs for future product design ideation contextually based in a specific culture. The process is geared towards design professionals and students considering sociocultural settings with a particular benefit to those providing design solutions in cultural contexts different from their own.

Increasingly, to tackle complex social and political issues within their work, designers are being asked to take the role of applied behavioural scientists. To prepare designers for these demands, design education must move to focus more on social and behavioural sciences, training students to be practitioners with an acute awareness of people and the societies they inhabit, as well as available science and evolving technology. This need is particularly relevant when it comes to speculative and futures design practices, a field which has been accused of producing outputs that are designed, engineered, and presented in a western vacuum. This is detrimental when speculative and futures design’s purpose is to imagine the varying possibilities presented by emerging technology. This process proposes a method for addressing this gap, by allowing designers to robustly imagine how future trends and technologies might fit into a wider variety of cultural contexts.

When approaching this challenge within modern design education, the issue is compounded by the increasing prevalence of generative AI as a design tool. Currently, biases from designers and developers are being coded into the technology itself. However, the rising field of AI Ethnography comes as a solution to address these issues - ethnography as the study of people, behaviour, and culture can provide explainability and context to AI development. With this notion in mind, the proposed process for future product design incorporates ethnographic principles such as observations, interviews and photographic artefact collection for primary data to be fed into generative AI products as the basis for image generation. Following this, the process guides designers in analysing and extracting pertinent information to engineer prompts that generate representative images of how future trends may play out in a given cultural context. The images produced will be socioculturally informed and will provide designers with a starting point for inspiration with which they can iterate upon for speculative design production. The process is illustrated in a physical book to guide creatives in sensitively incorporating these principles and outlined steps into their practice.

The proposed process exemplifies the view that emerging AI technologies are not replacements for human abilities but as augmentations that, if engaged with responsibility, can provide a new layer of intelligent sociocultural considerations for creatives to refer to in their design process and evaluate with the communities affected.

Quality Function Deployment (QFD) is a known procedure used to ensure that customer needs and expectations are translated into product features. This can be gained by applying the "House of Quality" (HoQ). The different sections guide students through important engineering processes from addressing customer and user needs and expectations, defining specifications, finding relations and evaluating those, leading to defining target values by looking into competitor analysis.

Students of mechanical engineering learn about QFD in Quality Management, a lecture in their third year of the curriculum. They have already gained lectures on engineering design, methods and processes. Through their practical work in their company they have worked on at least one larger engineering project (six months). QFD can help to repeat and deepen their engineering knowledge. Over the years several products have been chosen as examples for applying QFD. The QFD applications, executed in teams, show that even though these products are daily used products it helps to foster creativity (re-development approaches) and deepen knowledge about products and their value - especially from a customer’s, respectively user’s view and the engineering challenges in realisation. After introducing the basics of QFD the students are actively asked to team-up and to find a product example. These are mostly very basic products of daily use, e.g. household goods or products of daily life (thermos flask, razor, pen, smart phone). Using Chat GPT and prompting typical questions usually asked by the lecturer while applying QFD shows that more innovative products can be found that require technical knowledge beyond the field of mechanical engineering. ChatGPT can pave the way through applying QFD in an unknown context.

The paper will point out a team orientated approach of educating students applying QFD, repeating already educated knowledge on engineering processes and showing how QFD leads to creativity and challenges in context of daily-used product examples and innovative service products in rather unknown fields by applying ChatGPT. The learnings of applying ChatGPT are used to setup guidelines for student´s practical work, research work (study work, bachelor thesis) and future education.

The term “regenerative” refers to a process that repairs, recreates or revitalises its own sources of energy or air, water or any other matter (Attia, 2018). Regenerative systems can be defined in different scales depending on the temporal and spatial framing; the most common are local, regional and global. Accommodating a transition towards a regenerative future entails understanding regenerative practices, not only on a higher system level but also the materials in a product and how they affect the user's behaviour and interaction with the product. In a regenerative future, good intentions must be transformed into responsible behaviour. The first step is to recognise that a sustainable future needs transforming, not only physical infrastructures but also social structures (Regenesis Group, 2016). If we do not address intangibles like motivation, will and behaviour, the tangible solutions that seem so obvious will continue to elude us. The users' behaviour becomes an essential part of the system by facilitating changed perceptions and behaviours from the current take-make-dispose culture towards environmental and circular user behaviours, e.g. care, maintenance and emotional bonds with a product as the first step towards regenerative practices. Design for behavioural change provides methods that identify the driver for users and strategies to encourage desirable environmental and circular behaviours. Increasing the environmental awareness amongst users has shown to be an efficient strategy (Mugge, 2018; Gomes et al., 2022).

According to Wahl (2016), reconnecting with nature is a precondition to achieving a regenerative global and local system. The regenerative architectural framework developed by Mang and Reed (2012) states that it demands a radical change in the designer's mindset and stresses the importance of how designers interpret the user's role in a built environment. In the literature, regenerative materials are in general defined as (1) can be sourced sustainably, (2) used efficiently, and (3) recycled or repurposed at the end of their life cycle (Wahl, 2016). In material design, there are emerging approaches, e.g. bio-fabrication (Collet, 2021), livingness in materials (Karana et al., 2023), DIY materials (Rognoli & Ayala-Garcia, 2021) organic waste streams as material resources (Asbjorn-Sorensen & Thyni, 2020) and established methods like Material Driven Design (Karana, 2010) that could be useful in regenerative design practices. The study concludes that within the field of architecture, literature provides rich theory, case studies and guidance for, e.g., the selection of construction systems, measurable performance indicators and thresholds when designing regenerative architecture. In the emerging field of regenerative product design, we have identified a knowledge gap and a need for methodologies to bridge the higher system levels with the product and the material level. The study indicates a need to develop strategies and methods that product designers can implement in future professional practices and design education.

It's evident that the year 2023 has seen the emergence of artificial intelligence in numerous professional settings, including the field of Industrial Design. Across all professional forums and associations of Industrial Designers, discussions are ongoing about this technology and how it will impact the professional practice of Industrial Design. Many professional designers and their teams are experimenting with the new tools that incorporate this technology, exploring their possibilities and analysing how their application can add value at different stages of their design process, considering the strengths and weaknesses of their teams.

In the academic sphere, there has been a proliferation of publications in recent years exploring and mapping AI-based tools that can be applied in different stages of the design process. The reality is that many of these tools are still in the research and development phase, making it challenging to identify which ones will genuinely be implemented in professional practice. However, beyond the tools, what is actually happening in the day-to-day professional practice of these designers? What are the challenges that AI is creating for professional Industrial Designers?

On the one hand, AI tools require a certain level of expertise and knowledge to use effectively. This can be a barrier for some designers who may not have the necessary skills or resources to use these tools. On the other hand, there is the market and the clients who are also aware of the transformation being brought about by AI. Their demand and requirements will also change as other professionals offer design processes incorporating AI tools.

Consequently, what will happen with the training of future industrial designers? What new skill and capability needs arise from this revolution? What convergence is occurring between disciplines such as AI algorithm programming and industrial design? Will this new paradigm change the profile of the designer and the composition of design teams?

This contribution focuses on the perspective of professional designers, who are the prospective employers of our students. These professionals at present, can provide a more realistic view of what is happening in professional practice and what profiles of young Industrial Designers can bring value to their teams and companies in the coming years.

To achieve this, our team has conducted qualitative and quantitative research among industrial designers working in a wide variety of companies, studios, and design consultancies. Through questionnaires and the snowball technique, we have gathered feedback from of professionals in several European countries, identifying and understanding the main barriers and benefits of these AI tools, as well as the training needs perceived for the new generations of Industrial Designers.

The conclusions of this work represent a significant starting point for the changes to be introduced in the curriculum of universities offering degrees in Industrial Design or Industrial Design Engineering. Furthermore, our conclusions can help identify opportunities for developing new AI tools specifically for the Industrial Design process, targeting the less covered phases of the design process.

Within tertiary education disciplines traditionally regarded as “technical”, students have a notably tendency to focus on the skills required for their intended profession; be that mathematics, engineering competencies, coding, manufacture, design, chemistry, to name just a few. There is often less focus on “professional” competencies, such as presenting, orating, negotiating, bargaining and interpersonal communication, sometimes referred to as “soft skills” although this term is somewhat dated and is largely being replaced in the lexicon with the more appropriate “professional skills”. This presents an interesting paradox as frequently many graduate employers express a significant desire to hire graduates who have developed their required technical competencies but additionally professional competencies. Indeed, in a great many instances graduate employers actually place more of a value on the professional skills of a prospective hire as they will undertake additional or more bespoke technical training during on-boarding of new hires in their particular practices. It is a request frequently encountered from industry advisory boards to develop students so that they have a good level of professional competency when they enter the graduate employment market. This raised the question of how this can be best achieved when a curriculum has many technical competency based classes but comparatively few professional or interpersonal competency based classes.

While presentations and critiques have been beneficial up to a point, it is observed that if these are offered as informal or formative parts of the curriculum participation can be low and no demonstrable benefit is achieved, particularly since in-person attendance has presented challenges following the increase in online modes of attendance. Additionally the increasing prominence of generative AI tools has mean that many educators are rethinking their means of assessing learning and understanding of subject matter. Accordingly, a new form of experimental assessed oral presentations and “flipped” classroom sessions and activities have been developed. While these have been successful to an extent they only address some aspects of the professional competencies required and typically only really “one way” activities where any back and forth discussion or exchange is limited. As part of designing a new masters class within the technical discipline of product design at the XXXX in XXXX it was sought to create a new class where these professional skills, including negotiation, discussion, interpersonal communication and debate are developed and fostered. This approach has precedence in other fields such as medicine, language, culture, education, politics and business, and has demonstrated success in these fields. Could such an approach to learning activities and assessment work in the product design technical setting?

This research explores the efficacy of debate activities and assessment in developing the professional competencies of students enrolled in technical disciplines. It will address whether or not there is an improvement in these competencies amongst students and additionally if student’s confidence in these competencies is improved.

Progress in digital design tools has continuously changed the engineering design process. The application of Artificial Intelligence (AI) opens up completely new opportunities for the development of innovative products and systems. Computational design synthesis techniques such as generative design can be used to explore a design space with many solutions optimized for different objectives that may even exceed the capabilities of experienced human designers. By using CAD tools that deploy these techniques, designers no longer have to limit themselves to the variation and simulation of a few parameters, which is due to the time pressure in product development, but also to the lack of specialist knowledge of the complex correlations. Instead, a broad open solution space with an unrestricted number of potential solutions is provided by computational support. Engineering designers thus can focus on evaluating the solutions and selecting the solution that makes the most sense for the specific application. This is dramatically changing the product development process. The impact of AI on the design process, the handling of the new techniques and methods, as well as the implementation for future product development and innovation activities results in an enormous need for training and further education of designers.

This paper presents a comprehensive skill development programme for industry professionals and engineering students to provide the necessary skills (methodology and tools) in terms of generative engineering, design automation, structure and topology optimization. It includes an introduction to generative engineering (GE) as well as its foundations and software applications. The concept of the skill development programme is predominantly organized as eLearning divided into learning nuggets but is complemented by an additional hybrid practical part. The paper describes the approach employed in developing this program and highlights its outcomes. The teaching methodology and concept along with the focal teaching points are introduced. In addition, subsequent optimization measures and requirements are determined, which are based on the evaluation of the learning paths and learning nuggets carried out in the project by industry participants and their feedback. Finally, the potential of the suggestions for improvement and the resulting changes are discussed.

Extended reality has better learning in less time and optimizing resources. This paper explores a student-centric course experiment rooted in the application and practice of a recently developed educational platform. The Tec21 educational model is based on the development of disciplinary and transversal competencies, and for this, the design of educational innovations is fundamental. In recent years the design of virtual simulations has rapidly increased in number as well as in sophistication. Virtual laboratories based on virtual reality and augmented reality had exponential growth, which has kept its pace of creating new platforms for lessons based on XR technology.

Although present research has presented several examples that showcase virtual environments and have purposely been designed for students to learn from, the platform independence is growing where users can experience different learning formats with minimal disturbance as technology is striving to reach further seamless solutions. This research presents the results from specific learning scenarios through so-called DBT (design-build-test) exercises for different groups of industrial engineering students. The students were introduced to the MxREP simulator and the TecXR platform. These are augmented guideline design tracking, intuitive support, and virtual reality design scenarios that allow students to repeat the physical DBT exercise in a timely manner to provide more depth and understanding of step-wise design parameters. The specific course exercise was designed to emphasize life cycle educational activities that originate from the lecture design objectives, instructions and activities, and definition of educational objectives. Also, the design of simulator parameters and the interface with virtual and augmented reality lessons to achieve three essential objectives development of skills, learning, and engagement. The findings showed that students show great appreciation towards utilizing XR as part of their learning. The variation of the platform noted that the more fixed VR process enables it to focus more on process-related design steps, whereas the augmented support increased co-design engagement among student cohorts that participated.

Despite the rapid development of artificial intelligence (AI), skepticism persists among educators regarding its role in design education. This study uses a systematic literature review to locate and summarize the core papers from 2020 to 2023, categorizing the role of AI in design education. Following the PRISMA method, 35 papers were selected for review. The research reveals the potential impacts of AI on developing students' design skills, perceptions of AI applications among students and teachers, and challenges in implementing AI technologies. Drawing from these findings, the study proposes implications of AI on both the practice and theory of design education. By shedding light on the current state of AI integration in design education, this research aims to inform educators, policymakers, and stakeholders about the opportunities and challenges presented by AI technologies. Understanding these dynamics is crucial for effectively harnessing AI's potential to enhance design education and prepare students for future demands in the field.

UN’s Convention on the Rights of Persons with Disabilities (CRPD) states that persons with disabilities should be given opportunity to develop their creative and intellectual potential, not only for their own benefit, but for the enrichment of society. It means the right, not to consume what others have created, but to share one’s own ideas, aesthetic expression and intellectual work. Our thesis is that there is an unused potential in persons with disabilities. What if designers saw the world of a person with disabilities as a resource of diversity, rather than a lack of normality? What if designers would tap into this resource of perspectives from everyday life to innovation of technology? We like to understand if AI could unleash the potential of persons with disabilities, by visualising and translating between person and technology. We discuss conversational services used for persons with learning and language disabilities, including AI visualization techniques. Our goal is to prepare for the re-design of software, translating between text-based services and symbolic language, so called Augmented and Alternative Communication (AAC). Our case is a family with a young adult, with learning and intellectual disabilities, using AAC for social activities such as hiking. We find both barriers and potential. Barriers to harness the unused resources due to traditional co-design methods, excluding persons with other languages than verbal and text. It is weighed up by the potential of AI to democratize through lack of prejudice and norms and make it easier to interpret, create, visualise and share.

Participatory Design (PD) emphasizes the potential importance of user participation in enhancing the effectiveness of New Product Development (NPD). The article focuses on two main aspects within participatory product design: “the Conceptual Positioning with User Participation” and “the Relationship between User and Designer.” The results indicate that, in the design process of NPD, “Information Exchange,” “Knowledge Co-creation,” “Identification-Activation of Creative Users,” and “Responsible Behaviour of Users” all positively influence the effectiveness of NPD. However, the intensity of these effects and the moderating effect of "Enterprise Absorptive Capacity" depend on the actual implementation of user participation. This study provides new perspectives and data support for the theoretical research and practical application of participatory design and also offers recommendations for PD education in universities in China.

Design workshops are participatory collaborations based on design thinking, where participants from diverse backgrounds take up a local issue and work in teams to propose a design solution over a period of two to five days. Workshop attendees are multifaceted, from researchers, to designers, government workers, students, and even people with disabilities. To facilitate interactions and allow participants to get to know each other, icebreaking is a method often used for the initial meeting or to commence day’s activities. However, the ice-breaking approach changed significantly after the coronavirus pandemic, when design workshops went from face-to-face encounters to virtual meetings. Online applications have replaced face-to-face discussions and even the traditional white board. The methods, tools, and effectiveness of icebreaking communication have changed significantly over recent years.

The design question for this study is how can individuals explore new ice-breaking possibilities and enhance their effectiveness in the era of new, predominantly online, design workshops.

The study focuses on icebreaking methods of in-person, online, and hybrid design workshops. The two perspectives of icebreaking—communication and creativity—were compared. The purpose of the study is to clarify the characteristics and effectiveness of each ice-breaking method; ultimately proposing new icebreaking techniques that integrate online and in-person elements for post-COVID design workshops.

Design workshops conducted by the author in Japan and internationally were investigated. These workshops are divided into three categories: face-to-face design workshops from 2012 to 2019, online workshops from 2019 to 2022, and a hybrid workshop from 2022 to 2023. Video recordings of these workshops as well as the data from participant surveys were analyzed to understand how each icebreaker was conducted, the tools used, the communication between participants, and the creativity of the icebreaker exercise. Based on the collected data, good ice-breaking perspectives were extracted to be appropriate for all three types of design workshops. With these novel icebreaking approaches, participants of the design workshops would not only become acquainted after the first meeting but be inspired to collaborate creatively with each other despite the setting of the design workshop.

The findings of this study would be useful to workshop practitioners, educators interested in innovative teaching methods, and human resources individuals in charge of developing companies. This research has the potential to foster participant interest amongst each other, teamwork, and the proposal of innovative solutions during workshop activities.

With the introduction of the new IDE bachelor in 2021 all courses underwent a revision to promote, amongst other, an autonomous learning attitude. The conventional approach of teaching engineering relied on direct instructions and problem-based learning and proved to be inadequate, as students struggled to apply their engineering knowledge in capstone design projects. Based on our research none of the student’s applied mechanics and materials and only a handful referenced to materials and manufacturing processes in their capstone project.

To align with the new approach and to increase the application of engineering in capstone design projects, “productive failure” was introduced as a new didactical approach within our first-year course, Understanding Product Engineering (UPE, IOB1-2). Productive failure flips the traditional learning process and starts with an explorative problem which students cannot solve without the right knowledge. This is followed by an instruction explaining the missing concept. The approach engages students in active problem-solving, with the goal to increase the retention time of the theoretical concepts. We have developed our education around this using our in-house developed framework which includes lectures, workshops, and instruction videos facilitating the seamless integration of this approach into our own courses but also to disseminate it among our academic peers.

Based on literature productive failure seems to increase the retention time but is not tested in the context of engineering design. To evaluate the retention time of productive failure and to compare it with the conventional approach of direct instructions, we developed a test to measure students’ retention of the taught knowledge. During the second-year follow-up course of Product Engineering (PE, IOB3-5) we started with an in-class formative entrance-test. An online multiple-choice test was created using questions mirroring those from the first-year final exam. We asked students to do this test with the uttermost care and fill it in seriously without gambling an answer. Students always had the opportunity to tick off the “I don’t know” box without consequences. Of the 282 students performing this test, 16% were repeaters, and 14% were students which transitioned from the previous bachelor program, having never taken the first-year UPE course.

This paper will present the outcomes of this test and our findings into the possible retention time of our approach. This study will be repeated annually, serving as longitudinal study of our engineering education to continuously assess and improve our didactical approach.

The transition from secondary education to higher education for many students can present several challenges with the UK’s modern day education system. New university students not only have to prepare themselves to delve into the realms of higher education, but most students also must learn and adapt to living independently for the first time. New first year students are not only exploring their identity as young aspiring professionals, but within the product design sector, they are also getting explore for the first time what it means to be a designer. The skills deficiency between secondary education and the expectations of higher education within the product design sector continues to widen every year, and this is particularly evident within the past four years where students have been joining higher education with at least one or two GCSE or A-Level years effected by COVID-19 resulting in distance and virtual learning detracting from practical skills development.

Regardless of the route taken before joining higher education, recent observations have also demonstrated that the majority of first year product design students have significant skills deficiencies due to the current structure of design and technology education within secondary education. This is due to a lack of clarity and direction the subject currently faces coupled with significant funding cuts to the creative sectors by the UK government. As such higher education product design courses are facing significant challenges with student recruitment numbers but also the type of student being recruited. Students often now join higher education demonstrating a lack of autonomy, lack of self-directed learning skills and being resistant to change. The transition shock from a highly structured and teacher-centered learning environment compared to a more independent self-driven approach often surprises new students and the move away from a ‘spoon fed education culture’ often panics students. As such this paper seeks to present an approach taken to reimagining design fundamentals for first year product design students by taking a deschooling approach within their first module taught in higher education.

This paper will present a narrative of the point of entry considerations for incoming product design students and subsequently the re-design of a module entitled ‘Design Fundamentals’ which seeks to not only deschool students but also help them embrace their chosen course and the identity of their course. An overview of the refreshed ‘Design Fundamentals’ module for BSc Product Design students will showcase the first 10 weeks of the 1st year product design student experience highlighting how providing guidance, mentorship, and support systems help students transition to a more self-directed and independent learning approach. Finally, this paper will provide student testimonials as they reflect on several educational schemes/projects conducted within the ‘Design Fundamentals’ module ranging from debates, team bonding away days, CAD Bash, design sketching, 3D printing sessions, design projects, amongst others.

There has been a growing interest in recent years on the use of artificial intelligence (AI) and computer science applications within the field of education. Previous systematic reviews and meta-analysis research has shown that use of AI and computer science can enhance students' performance in educational contexts. However, studies are mixed in their impressions of the use of Generative AI as a disruptive technology, with educators citing concerns over plagiarism and misuse of such technology by students. These tools represent a stark contrast to many traditional educational approaches and requires reshaping of assessments to ensure that learning outcomes can still be measured. Nevertheless, there is still a significant lack of studies examining the students’ perspectives on the use of these technologies and its impact on their academic performance. Therefore, the current paper aims to investigate how generative AI impacts upon product design and engineering students’ performance within educational contexts in the UK. Through the distribution of an online survey, the study aims to assess student’s attitudes, preferences, and challenges concerning the use of AI powered tools. Furthermore, it aims to capture valuable insights from students into how generative AI technologies can impact on various aspects of their academic achievement, learning outcomes, and engagement.

This conference paper reports, empirically, the setbacks and self-doubts that confront design students as they journey toward becoming professional practitioners. There is critical need to elevate well-being as core capacity for complex problem solving in lieu of the systemic expansion of design scope and new defining attitudes to work in the post-covid era. This conference paper further disseminates the emerging concept of ‘designer resilience’ as a new approach to design pedagogy that acknowledges the difficulties of pioneering systemic change.

Since the COVID-19 pandemic and due to living in a post-digital environment, video feedback has become more prominent in higher education. However, it has not been as well adopted on product design courses due to the subjective nature of creative disciplines, and the unique challenges this constitutes in making it an authentic experience for students. This paper takes an influential framework for creating authentic feedback experiences and uses it to design a video feedback exercise for product design students. The framework presents five criteria relating to Realism, Cognitive Challenge, Affective Challenge, Evaluative Judgment, and Enacting feedback. From each of these criteria, the authors derive a set of propositions for video feedback and translate them into design features including: the use of simple and clear language, proportionate discussion to assessment criteria, the use of sensitive and empathic language, making visual reference to student work onscreen, and explanations of constructive actions. The video feedback exercise was then delivered to a cohort of twenty-eight, level six, undergraduate product design students. Both quantitative and qualitative datasets were collected through Likert scale and free-text questions in a survey, and a series of semi-structured interviews with a sample of the cohort. A statistical and thematic analysis developed an understanding of the video feedback exercise as an authentic feedback experience, highlighting some of its strengths and limitations as a teaching tool. The paper concludes with a number of practical recommendations to improve and develop the design of the video feedback exercise.

Over the past year AI has become highly available for everyone, including students in higher education. Initially, the universities did not want the students to use AI in their examinational projects due to the fear of reducing the amount of independent work. It is also difficult for examiners to evaluate the difference between self-produced work and AI-produced work. However, AI is a resourceful tool that could be useful for the students learning and the products they produce. Hence, we want to find out the positives and negatives of AI in engineering education.

A mandatory course, ING101 Technology, Environment and Sustainability, is taught the first year in the Civil and Structural Engineering programme, Computer Engineering programme, Electronics and Electrical engineering programme, Renewable Energy programme and Mechatronics programme at the University of Agder. The students must write a scientific article concerning environment and technology to pass the course. The library and the academic staff collaborated on a new way of solving the task; the students had the opportunity to use AI to produce the scientific article and then write a report on how it worked. The students must evaluate how this affected the working process, their learning outcome and the final product, the scientific report.

This study uses survey data from the students in ING101 to investigate the positive and negative perceptions of using AI in engineering education. By looking at the results from the survey and the reported experiences from the students we can evaluate how AI can assist in higher education. This information can be used to influence the way we let our students work on projects, reports, and exams, and if AI should be(come) a learning tool in engineering education.