AI-Enabled Teaching Reform and Practical Exploration of Compressor Courses
Abstract
Against the background of the comprehensive advancement of emerging engineering construction and the deepening of industrial intelligent transformation, compressor courses, as core courses for majors such as Energy and Power Engineering, Mechanical Engineering, and Chemical Process Machinery, assume the important task of cultivating students’ engineering practice capabilities and innovative thinking. However, traditional teaching models face problems such as the use of abstract theories and a disconnection from practice, which make it difficult to meet the talent training requirements of the new era. Taking the in-depth integration of AI technology and education as the core concept, this paper systematically sorts out the teaching status and reform needs of compressor courses, and constructs an overall framework for “AI + Compressor” course teaching reform from three dimensions: teaching content reconstruction, teaching model innovation, and practical system optimization. By introducing various carriers such as virtual simulation experiments, intelligent teaching platforms, personalized learning systems, and AI innovative practice projects, it promotes the concretization of theoretical teaching, the scaling of practical teaching, and the precision of the teaching process. The paper also discusses the guarantee mechanism for the implementation of the reform, providing a feasible path for cultivating compound talents with engineering practice capabilities, innovative thinking, and intelligent technology application capabilities, as well as a reference paradigm for the intelligent transformation of engineering professional courses in China.
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