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BIDTrainer: An LLMs-driven Education Tool for Enhancing the Understanding and Reasoning in Bio-inspired Design

Liuqing Chen, Zhaojun Jiang, Duowei Xia, Zebin Cai, Lingyun Sun, Peter R. N. Childs, Haoyu Zuo

2024Year
23Citations
8Top-tier citations

Abstract

Bio-inspired design (BID) fosters innovations in engineering. Learning BID is crucial for developing multidisciplinary innovation skills of designers and engineers. Current BID education aims to enhance learners’ understanding and analogical reasoning skills. However, it often heavily relies on the teachers’ expertise. When learners pursue independent learning using some educational tools, they face challenges in understanding and reasoning practice within this multidisciplinary field. Additionally, evaluating their learning outcomes comprehensively becomes problematic. Addressing these challenges, we introduce a LLMs-driven BID education method based on a structured ontology and three strategies: enhancing understanding through LLMs-enpowered "learning by asking", assisting reasoning by providing hints and feedback, and assessing learning outcomes through benchmarking against existing BID cases. Implementing the method, we developed BIDTrainer, a BID education tool. User studies indicate that learners using BIDTrainer understood BID knowledge better, reason faster with higher interactivity than the baseline, and BIDTrainer assessed the learning outcomes consistent with experts.

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