Research on Teaching Model Innovation and Job Adaptation in the Digital-Intelligent Finance and Business Industry-Education Integration Training Center

Abstract

The competency requirements for digital-intelligent finance and business are shifting towards a multi-dimensional and dynamic structural transformation, and the training center needs to construct an appropriate teaching model and job matching mechanism. This study proposes a three-layer framework that includes a teaching paradigm transformation, a job adaptation mechanism, and a collaborative adaptation path. By deconstructing the competency domain into four sub-domains of data perception, logical deduction, decision response, and value evaluation, this study achieves a modular reorganization of training elements and constructs a task-driven immersive framework. This study adopts dynamic job profiling, a virtual-real collaborative task chain, and personalized path generation to form a job adaptation mechanism. By optimizing the mapping between modules and functions, designing dynamic resource scheduling rules, and establishing an effectiveness and competency calibration model, this study achieves the coordination of teaching elements and job requirements. This research provides a theoretical basis and a technical path for the teaching model design of the training center.