Conference Agenda

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.