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Digital Innovation Pathways in the Design of Macroeconomics Courses in the Era of Artificial Intelligence

Author(s)

Lingshan Li*, Liqin Nie, Zhiyan Li

Affiliation(s)

School of Management, Hubei University of Chinese Medicine, Wuhan, Hubei, China *Corresponding Author.

Abstract

The advent of the artificial intelligence (AI) era presents significant challenges to traditional education, necessitating innovative approaches to teaching methods. Integrating artificial intelligence into classroom instruction to enhance course quality has become a pressing concern. This study explores the design of macroeconomics courses in the context of artificial intelligence, addressing the limitations of traditional teaching methods and highlighting the potential benefits of AI integration. These advantages include personalized learning experiences, increased teaching efficiency, enhanced interactivity, real-time feedback, and access to expanded teaching resources. Building on these insights, the research proposes a comprehensive framework for innovating macroeconomics courses design. First, it emphasizes content innovation, which involves integrating AI-related economic phenomena and frontier developments in the discipline. Second, it focuses on methodological innovation, leveraging AI-powered tools to facilitate teaching and incorporating practical, hands-on learning experiences. Finally, it advocates for assessment reform, emphasizing process-oriented evaluations and introducing diverse, multi-dimensional assessment methods. These innovative strategies are shown to enhance the quality of macroeconomics education, improve student learning outcomes, and better align educational programs with the demands of a rapidly evolving economy in the AI era.

Keywords

Artificial Intelligence; Macroeconomics; Course Design; Digitalization; Innovation

References

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