Research on the System Optimization Model for Talent Cultivation in Higher Education under the Background of Digital Economy

Abstract

This study addresses the demand for talent cultivation in higher education under the Background of Digital Economy by designing and implementing a systematic optimization model. The model consists of four interrelated subsystems: cultivation objectives, curriculum system, teaching methods, and evaluation feedback. Using the Delphi method and the Analytic Hierarchy Process (AHP), the key elements and weights of the model were determined. The implementation process adopted modular design and an intelligent learning platform, integrating blended learning and diversified evaluation methods. To validate the effectiveness of the model, a year-long controlled experiment was conducted. The results showed that the experimental group using the optimized model outperformed the control group in learning efficiency, knowledge mastery, innovation capability, and employability. The model demonstrated excellent functionality, performance, and adaptability, receiving high recognition from both students and employers.