LLMs for Coding and Robotics Education

2024/02/09 by Peng Shu, Huaqin Zhao, Shu, Peng +21 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Digital Rights Management and Security #FOS: Computer and information sciences #Open Education and E-Learning #Robotics (cs.RO)

paper · pdf · doi:10.48550/arxiv.2402.06116

openalex publication_date 2024/02/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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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