Conference Agenda
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Agenda Overview |
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D236: AI-ENHANCED LEARNING IN DESIGN EDUCATION
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More AI means less design? Empirical insights from design education 1TUM School of Engineering and Design, Technical University of Munich, Germany; 2Hilti Entwicklungsgesellschaft mbH, Germany Product development increasingly integrates generative AI tools to enhance creativity and efficiency. However, their actual impact on structured design work, particularly on method application and resulting designs, is not well understood. This study examines the effect of (1) method application quality on (2) product concept quality, influenced by (3) potential confounders like AI usage. Statistical analysis reveals that method application quality correlates positively with product concept quality, while higher AI usage correlates negatively with both, indicating limitations in AI usefulness. Generative AI adoption in engineering: a cluster analysis of student profiles for designing personalized learning support College of Engineering, University of Georgia, United States of America The integration of Generative AI in engineering education requires a deeper understanding of diverse student adoption patterns. This study applies cluster analysis grounded in the Technology Acceptance Model and extended constructs on survey data to create different user profiles. Four distinct user profiles emerged: Empowered Optimizers, Mainstream Pragmatists, Skeptical Minimalists, and Ethical Achievers. The findings challenge one-size-fits-all approaches, providing a student-centred framework for designing tailored instructional strategies, GenAI training, and ethical guidelines. Drivers and barriers of learning MBSE: design and validation of a RAG-based AI chatbot leveraging smart views 1ISEM - Institute for Smart Engineering and Machine Elements, Hamburg University of Technology, Germany; 2TRUMPF SE + Co. KG, Germany; 3Technische Universität Berlin, Germany; 4Einstein Center Digital Future, Germany Learning MBSE is hindered by abstraction and complex tools. This paper identifies barriers via literature review and interviews to design a RAG-based chatbot acting as a "smart view" for contextual guidance. Evaluated through a semester-long field study and a controlled experiment, the prototype shows high usability and reduces cognitive load. While performance is comparable to traditional e-books, the RAG-enabled system effectively mitigates entry-level barriers and aids authentic project work through stepwise tutoring, offering a scalable, interactive complement to MBSE education. Intelligent narratives: rethinking design education through the use of generative AI as a storytelling tool Iowa State University, United States of America This study explores how AI workflows and prompt engineering reshape storytelling in design education. Students utilized tools such as ChatGPT, Midjourney, Runway, and Meta Glasses to reframe existing projects through iterative scripting, image generation, and reflection. Analysis of 88 visual projects and over 80 videos showed a shift from static documentation to multimodal narratives. Findings suggest AI enhances communication fluency, engagement, and reflective practice through adaptive, platform-native storytelling. | ||
