From Tradition to Intelligence: Exploring the Pathways for Upgrading Marketing Curriculum Systems Towards Intelligence
DOI: https://doi.org/10.62381/H241916
Author(s)
Zhiming Tang
Affiliation(s)
School of management, Chongqing University of Science and Technology, Chongqing, China
Abstract
This study aims to explore the pathways for upgrading the marketing curriculum from traditional models to an intelligent framework. In response to the rapid advancements in digital and intelligent technologies, this research employs a literature review method to systematically analyze existing studies and trends related to the intelligent transformation of marketing education. Through qualitative analysis, the study clarifies the challenges present in traditional teaching frameworks and identifies the practical applications of intelligent technologies, such as artificial intelligence and big data analytics, within educational contexts. Findings indicate that intelligent upgrades necessitate not only the effective integration of technological tools but also the dynamic updating of course content and a transformation of teaching methodologies. Furthermore, the role of educators must evolve from unidirectional knowledge transmitters to facilitators of student learning and promoters of intelligent technologies. Students, in turn, should be nurtured as self-directed learners equipped with critical thinking and innovation capabilities, positioning them as lifelong learners. Ultimately, this research presents a series of optimization recommendations, including enhanced collaboration between academia and industry, the development of personalized learning plans, and the establishment of a supportive, intelligent environment for continuous learning, all aimed at ensuring the competitiveness of marketing education in the future. This paper provides valuable insights for both academics and practitioners regarding the journey of intelligent transformation in marketing education.
Keywords
Marketing Education; Intelligent Upgrading; Curriculum System; Artificial Intelligence; Digital Transformation
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