Research on the Innovation of Practical Teaching Mode in Marketing Specialty Empowered by Artificial Intelligence

Wang Zhongjie

Loughborough University

Abstract：

The rapid proliferation of MarTech architectures and generative artificial intelligence has restructured corporate marketing practices, generating urgent demand for graduates equipped with high-order analytical and algorithmic competencies. Nonetheless, prevailing practical teaching models in university marketing curricula continue to suffer from deterministic simulation boundaries, instructional latency, and fragmented summative assessments. Grounded in experiential learning and constructivist educational paradigms, this study designs an artificial intelligence-empowered practical teaching model structured across an infrastructure tier, an intelligent simulation engine tier, and multi-scenario operational modules. By embedding synthetic consumer personas, dynamic advertising sandboxes, and intelligent tutoring systems into business laboratory instruction, the framework bridges conceptual theory and volatile market realities. Furthermore, the paper establishes a multidimensional evaluation mechanism that converts qualitative and telemetry metrics into an integrated appraisal of student strategy, human-machine synergy, operational agility, and ethical discernment. This research delivers an actionable blueprint for higher education institutions striving to modernize business curricula, align pedagogical outcomes with modern industrial workflows, and safeguard critical inquiry.

Key Words：

marketing education; practical teaching; Artificial Intelligence; generative AI; pedagogical innovation; synthetic personas; higher education reform