Research on the Construction and Practice of an AI-Enhanced Blended Teaching Model for Econometrics

Abstract

Artificial intelligence (AI) has emerged as a key driver of curriculum reform in higher education. For econometrics—a discipline that emphasizes both theoretical rigor and methodological application—the integration of AI into blended teaching models is a pressing issue in contemporary pedagogy. This study investigates the development of an AI-enhanced instructional framework for econometrics, focusing on students majoring in International Economics and Trade at Sichuan International Studies University. By incorporating tools such as ChatGPT and machine learning into a blended learning environment that combines online platforms with in-person instruction, the course adopts a “Technology Integration–Project-Based Learning–Practice Orientation” approach. In the practical process, the course focuses on strengthening students’ comprehensive abilities in data processing, empirical modeling, and economic problem analysis, promoting their transition from theoretical learning to research and practice. Research has shown that AI empowerment can effectively enhance the teaching efficiency of econometrics courses and improve students’ practical application skills, providing a viable pathway for curriculum reform.