A Study of Student Behavioral Pathways in Gen AI-Enabled Economics and Management Courses Teaching and Learning

<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> In the digital intelligence era, generative artificial intelligence, particularly ChatGPT, has seen rapid development. Numerous studies have confirmed that generative AI can provide efficient and personalized intelligent services and technical support for education Yet, few researchers have delved into the underlying mechanisms by which ChatGPT enhances student performance. This study employs Economics and Management Courses instruction as a case study, utilizing lag series analysis from a student behavior perspective. It describes the effects of exam answering on 24 college students in the experimental and control groups under different learning conditions of ChatGPT-assisted instruction versus traditional methods. By contrasting their behavioral networks, the study seeks to uncover the fundamental principle through which ChatGPT boosts student performance. The results of the study showed that the integration of ChatGPT into the teaching of economics and management courses significantly increased the level of student achievement . This enhancement is primarily attributed to its ability to spark students' curiosity and foster an exploratory spirit, thereby elevating their cognitive capabilities and broadening their knowledge base, leading to marked improvements in academic performance