From Digital Apprentice to Data-Driven Strategist: A Situated Learning Approach to E-Commerce Education

Abstract

In response to the growing demand for data-driven competencies in the digital economy, this study develops and implements the “E-commerce Operations and Statistical Analysis Virtual Simulation Experiment” under the framework of China's “New Business Disciplines” initiative. Built on a B2B2C high-fidelity architecture, the platform integrates business operations with statistical modeling through a closed-loop “operate–generate–analyze–decide” data sandbox. Grounded in situated learning and Legitimate Peripheral Participation (LPP), it establishes a digital apprenticeship pathway that guides students from peripheral operational tasks toward central roles as data-driven strategists. A dual-phase design combining case-based and project-based learning provides scaffolding for this progression. Mixed-methods evaluation demonstrates significant improvements in students’ data literacy, model application, and strategic interpretation skills, with both process and outcome assessments showing strong results. The study contributes a replicable simulation–analysis integration paradigm that effectively bridges the gap between academic theory and practical industry requirements. It offers a scalable pedagogical model for digital curriculum reform and industry–university collaboration, providing robust evidence for cultivating data-fluent business professionals in the era of digital transformation.