Author(s)

Jiang Huiming ¹, Yuan Jing ¹, Zhao Qian ¹, Ding Zishan ¹, Shen Hangming ¹, Chu Zhenzhong ¹

Affiliation(s)

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

Corresponding Author

Jiang Huiming

ABSTRACT

Fundamentals of Thermal Engineering is a compulsory foundational course for mechanical engineering majors. Under a schedule of only 32 class hours, the course covers a large body of fine-grained knowledge points spanning engineering thermodynamics and heat transfer. Although both parts offer clear paths of knowledge extension, students frequently find the content difficult to absorb, which weakens teaching effectiveness. This paper investigates how course design can be improved in the context of artificial intelligence. Drawing on an AI-enabled course development practice, a design framework is proposed that maps the capabilities of AI onto four concrete difficulties of the course: dense content, fine-grained knowledge points, clear but under-absorbed extension paths, and low student receptivity. The framework is built on a "basic theory teaching—AI-empowered engineering application" dual-track progressive architecture and rests on four pillars: knowledge-graph-based atomization and dynamic reconstruction of knowledge points, a progressive AI-assisted engineering case library, an intelligent teaching analysis platform for precise learning diagnosis, and a knowledge-ability-value multi-dimensional evaluation system. The paper further argues that the application of AI in course design must adhere to the principles of teacher leadership, value guidance, data security, and appropriate use of technology. The proposed framework offers design ideas and guiding principles for foundational engineering courses with insufficient teaching hours in the AI era.

KEYWORDS

Artificial intelligence; Course design; Fundamentals of Thermal Engineering; Knowledge graph; Teaching effectiveness

CITE THIS PAPER

Jiang Huiming, Yuan Jing, Zhao Qian, Ding Zishan, Shen Hangming, Chu Zhenzhong. AI-Empowered Design of the "Fundamentals of Thermal Engineering" Course for Mechanical Engineering Majors under Insufficient Teaching Hours. Advances in Educational Technology and Psychology (2026). Vol. 10, No. 4, 77-84. DOI: http://dx.doi.org/10.23977/aetp.2026.100411.

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