Author(s)

Xiankun Lin ¹, Wenhui Bian ¹

Affiliation(s)

¹ School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China

Corresponding Author

Xiankun Lin

ABSTRACT

The rapid advancement of robotic technology has broadened its applications across diverse fields, making it increasingly important for students, even those not specializing in robotics, to acquire a fundamental understanding of robot design technology. However, traditional teaching methods, which often rely on conventional lecture formats, may not effectively cater to the diverse educational backgrounds of non-robotics majors. This paper proposes the application of the large language model-inferred approach as an innovative pedagogical strategy to enhance the learning outcomes of these students. Four primary pillars build the proposed teaching model: Reasoning assistance for basic knowledge, visualized comprehension for robotic mechanism, support via similar case studies and performance feedback. Through detailed discussion and analysis, this study demonstrates that integrating these elements into a cohesive, iterative teaching process improves theoretical comprehension and fosters critical thinking, practical problem-solving, and creative innovation.

KEYWORDS

Teaching methods; Robot design technology; Non-robotics major students; Large language model

CITE THIS PAPER

Xiankun Lin, Wenhui Bian, Teaching Non-Robotics Major Students Robot Design Technology with Aids of Large Language Model-Inferred Approach. Advances in Educational Technology and Psychology (2025) Vol. 9: 107-112. DOI: http://dx.doi.org/10.23977/aetp.2025.090216.

REFERENCES

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