Teaching Reform of Graduate Game Theory to Cultivate Independent Thinking and Complex Decision-Making in the Digital Age

Abstract

This study proposes a digitally driven framework for graduate-level game theory teaching to cultivate higher-order competencies in the digital era. By integrating big data, AI agents, and simulation technologies, the reform shifts the pedagogical focus from mechanical equilibrium computation to strategic reasoning and complex decision-making. The proposed model reconstructs teaching through three dimensions: dynamic industry-oriented case repositories, human–AI strategic confrontation, and network-based evolutionary simulation environments. Through scenario-based practices, algorithmic auditing, and iterative decision simulations, the framework fosters independent thinking and cognitive autonomy. Furthermore, it introduces a trajectory-oriented evaluation system and reconceptualizes instructors as learning environment designers. This human–machine collaborative approach equips students to navigate uncertain strategic environments through reflective engagement with technological tools, providing both theoretical and practical guidance for advancing game theory education.