Learning of design for environment with large language models: An interactive system using GPT-4

This study explores a large language model (LLM)-based system enhancing design methodology education, focusing on design for environment (DfE). By integrating GPT-4 with DfE guidelines and a dual-loop structured learning workflow, we developed an interactive system addressing persistent challenges in design method learning. Through personalised exercises and systematic feedback, our system guided beginners in applying DfE strategies while fostering self-directed learning. Experiments involving 30 participants revealed significant improvements across Bloom's taxonomy domains, particularly when learners demonstrated sustained or developing proactiveness. This study analysed how LLM-based systems can support education for various design for X methodologies through generalizable interaction frameworks.