Analysis of Teaching Reform Pathways for Engineering Economics in the Era of Artificial Intelligence

DOI: https://doi.org/10.62517/jhet.202615102

Author(s)

Pinjie Xie*

Affiliation(s)

School of Economics and Management, Shanghai University of Electric Power, Shanghai, China *Corresponding Author

Abstract

The rapid emergence of generative artificial intelligence has fundamentally challenged the traditional teaching model of Engineering Economics, which has long focused on computational modeling and analysis. This paper seeks to develop a coherent reform framework for the course in the AI era, aiming to shift the educational paradigm from “instrumental rationality” toward “value rationality”. The goal is to move beyond training mere “computational technicians” and instead cultivate “decision analysts” capable of effectively leveraging AI technologies. The proposed comprehensive reform framework addresses four key dimensions: teaching objectives, content, methods, and evaluation. Specifically, teaching objectives should be redefined to emphasize the development of advanced economic decision-making capabilities; teaching content must be simultaneously streamlined and enriched, with a stronger focus on uncertainty analysis and the integration of AI ethics; teaching methods should transition to AI-enabled blended and project-based learning approaches; and evaluation systems need to evolve into process-oriented, multifaceted evaluations that incorporate “human-AI collaboration”. Finally, the paper discusses the challenges inherent in implementing these reforms and proposes practical measures to ensure their success, providing both theoretical foundations and actionable guidance for curriculum innovation in the AI-driven era.

Keywords

Engineering Economics; Artificial Intelligence; Teaching Reform; AI Empowerment; Value Rationality

References

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