The challenges of integrating technology in global design classes have been published in the literature, but it is unclear if this knowledge makes its way back to the classroom. This paper investigates knowledge transfer by documenting the results of four workshops across two institutions and two distributed design classes. Participants were asked to identify the challenges of distributed design, the functionality of technologies to overcome the challenges and guidance on how best to perform distributed design to best help future students. 17 challenges, 10 functionalities and 8 guidelines were developed. The identification of challenges, functionalities and subsequent guidance created can be utilised to assist future students and educators of distributed design. Analysis of gaps in the knowledge identify where theories have not been transferred from literature to the classroom and will help to identify how best to fill the gaps in knowledge. The workshops also present a novel way to engage students in analysing their own collaborative work practices.

Selection of suitable computer-supported collaborative design (CSCD) technologies is crucial to facilitate successful projects. This paper presents the first systematic method for engineering design teams to evaluate and select the most suitable CSCD technologies comparing technology functionality and project requirements established in peer-reviewed literature. The paper first presents 220 factors that influence successful CSCD. These factors were then systematically mapped and categorised to create CSCD requirement statements. The novel evaluation and selection method incorporates these requirement statements within a matrix and develops a discourse analysis text processing algorithm with data from collaborative projects to automate the population of how technologies impact the success of CSCD in engineering design teams. This method was validated using data collected across 3 years of a student global design project. The impact of this method is the potential to change the way engineering design teams consider the technology they use and how the selection of appropriate tools impacts the success of their CSCD projects. The development of the CSCD evaluation matrix is the first of its kind enabling a systematic and justifiable comparison and technology selection, with the aim of best supporting the engineering designers collaborative design activity.

This work highlights the phenomenon of pareidoliathe tendency to see faces in the environment, buildings and objects that surround usand establishes its relevance for design contexts. In reviewing literature on anthropomorphism and the use of faces in design embodiment, we have shown that it is a compelling and prevalent facet of how we interpret products. By surveying 2,309 images from across the internet, we provide the first systematic investigation of product types and face characteristics (size, composition, emotion) that are manifest in this phenomenon. The most common instances were shown to be in medium-sized products, where part of the product was interpreted as a face, and that conveyed a happy emotion. The effects of culture and self-congruence are identified as important aspects of our interpretation of facial emotion. It is concluded that the fundamental geometric elements of products should be considered with respect to facial morphology, whether it be the intention to utilise its effects or not, and set out case for more quantified guidelines on the use of pareidolia and anthropomorphism in design.

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Artificial intelligence (AI) capable of generating images from a text prompt are becoming increasingly prevalent in society and design. The general public can use their computers and mobile devices to ask a complex text-to-image AI to create an image which is in some cases indistinguishable from that which a human could create using a computer graphics package. These images are shared on social media and have been used in the creation of art projects, documents and publications. This exploratory study aimed to identify if modern text-to-image AI (Midjourney, DALL-E 2, and Disco Diffusion) could be used to replace the designer in the concept generation stage of the design process. Teams of design students were asked to evaluate AI generated concepts from 15 to a final concept. The outcomes of this research are a first of its kind for the field of engineering design, in the identification of barriers in the use of current text-to-image AI for the purpose of engineering design. The discussion suggests how this can be overcome in the short term and what knowledge the research community needs to build to overcome these barriers in the long term.