CONFERENCES
E&PDE 2026 - 28th International Conference on Engineering & Product Design Education
The Conference will bring together representatives from education and industry interested in sharing new perspectives on design education.
Knowledge Base Repository
In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.
AI – A PROBLEM SOLVER IN ENGINEERING EDUCATION? OPPORTUNITIES FOR MORE INCLUSIVE PRODUCT DEVELOPMENT TEACHING
Schmid, Niklas; Nutzmann, Marc
Type:
Year:
2026
Editor:
Buck, Lyndon; Brisco. Ross; Bohemia, Erik
Author:
Series:
E&PDE
Institution:
DHBW Baden-Wuerttemberg Cooperative State University, Germany
Page(s):
457 - 462
DOI number:
ISBN:
978-1-912254-24-8
ISSN:
3005-4753
Abstract:
Since the introduction of large-scale generative AI systems such as ChatGPT (GPT-3.5) in 2022, artificial intelligence has rapidly expanded across professional, educational, and societal domains. In engineering and product development, AI tools are increasingly integrated into engineering workflows, supporting tasks from early conceptual design to detailed development processes. However, their accelerating adoption raises critical questions: How can students be taught to use AI responsibly? How can ethical, democratic, and societal values be preserved when intelligent systems influence decision-making? This paper investigates the application of AI tools within engineering design and product development education, with a particular focus on inclusive teaching approaches. Through the exploration, testing, and analysis of various AI-supported methods and tasks across the product development process, the study evaluates the potential of AI to both enhance engineering outcomes and support diverse learners. The research identifies practical application fields - such as ideation, requirements engineering, concept evaluation, simulation assistance, and documentation - and examines how AI can be validated and verified as a supportive tool for engineering students. Moreover, the paper demonstrates how inclusive teaching strategies can foster students’ critical and reflective engagement with AI, helping them understand both its benefits and limitations.
Keywords:
