Research on a Dual-Loop Artificial Intelligence Model Based on Employability Cultivation and Industry Alignment

Abstract

This study proposes a dual-loop AI model to enhance college students' competency development through systematic industry alignment. The first loop leverages modular skill tracking, long short-term memory–attention networks, and Shapley additive explanations to deliver real-time, personalized feedback during learning. The second loop integrates enterprise job role profiles to align training with labor market demands. Deployed across multiple institutions in China, the system served 500 students and achieved sub-120ms latency with transparent visualizations. Results show the intervention group improved by 18.7 percentage points in employment competency, significantly exceeding the control group's 5.9-point gain (p