Author(s)

Yu Zhu ¹

Affiliation(s)

¹ School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

Corresponding Author

Yu Zhu

ABSTRACT

With the rapid development of artificial intelligence (AI) technology, mechanical engineering education is facing a historic opportunity to transform from a standardized training model to a personalized learning paradigm. This paper systematically explores the application value and technical framework of AI-driven personalized learning path planning in the teaching of mechanical engineering majors. First, the study analyzes the characteristics of the knowledge system of mechanical engineering and the diversity of students' learning needs and then constructs a personalized learning path planning model integrating knowledge graph, learning analytics, and intelligent recommendation as a trinity. The paper elaborates on the implementation mechanisms of core modules such as learner model construction, knowledge state diagnosis, and dynamic path optimization, and discusses the specific application scenarios of personalized learning paths in theoretical teaching, virtual simulation, and practical links in combination with the curriculum system of mechanical engineering majors. Finally, the study probes into the transformation path of teachers' roles under the background of human-machine collaboration and the ethical boundaries faced by technological application. This paper aims to provide theoretical reference and practical guidance for mechanical engineering educators to understand and apply AI technology, realize teaching students in accordance with their aptitudes, and improve the quality of talent cultivation.

KEYWORDS

Artificial Intelligence, Personalized Learning, Path Planning, Mechanical Engineering Education, Intelligent Tutoring System

CITE THIS PAPER

Yu Zhu. Application of Artificial Intelligence-Driven Personalized Learning Path Planning in Mechanical Engineering Education. Curriculum and Teaching Methodology (2026). Vol. 9, No.1, 119-127. DOI: http://dx.doi.org/10.23977/curtm.2026.090116.

REFERENCES

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Sponsors, Associates, and Links

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• Advances in Educational Technology and Psychology
  
  
• Transactions on Comparative Education
  
  
• Applied & Educational Psychology
  
  
• Advances in Vocational and Technical Education
  
  
• Adult and Higher Education