Digital Intelligence Empowerment in Business Education: Strategies for Enhancing Experimental Teaching Quality in the Era of Digital Transformation

Abstract

Amid the global acceleration of digital educational transformation, business experimental teaching in higher education faces three
critical challenges: outdated infrastructure, insufficient digital competencies among faculty, and slow curriculum iteration. This study employs
a mixed-methods approach, combining field research and meta-analysis of relevant studies over the past five years, to construct the DigitalTeaching-Intelligence Empowerment Pyramid (DTIEP) model. Findings reveal that AI simulations significantly enhance learning engagement, while real-time data-integrated courses shorten skill acquisition cycles. Through international benchmarking (e.g., the Wharton Schools
AI Lab with 92% student satisfaction) and domestic case studies (e.g., Zhejiang Universitys Fintech Sandbox reducing decision errors by
40%), this research proposes three strategic interventions: phased cloud laboratory development, faculty micro-certification in digital pedagogy, and dynamic curriculum updating mechanisms. The implementation of the DTIEP framework demonstrates a 73% potential improvement
in teaching quality, offering a systematic solution to address the digital disconnection in business education. This study provides actionable
insights for higher education institutions navigating digital transformation.