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LLMs for Coding and Robotics Education

9 February 2024
Peng Shu
Huaqin Zhao
Hanqi Jiang
Yiwei Li
Shaochen Xu
Yi Pan
Zihao Wu
Zheng Liu
Guoyu Lu
Le Guan
Gong Chen
Xianqiao Wang Tianming Liu
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Abstract

Large language models and multimodal large language models have revolutionized artificial intelligence recently. An increasing number of regions are now embracing these advanced technologies. Within this context, robot coding education is garnering increasing attention. To teach young children how to code and compete in robot challenges, large language models are being utilized for robot code explanation, generation, and modification. In this paper, we highlight an important trend in robot coding education. We test several mainstream large language models on both traditional coding tasks and the more challenging task of robot code generation, which includes block diagrams. Our results show that GPT-4V outperforms other models in all of our tests but struggles with generating block diagram images.

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