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August 16, 2026Advanced ElectromagneticsOpen Access

Research on the Construction and Application of New Business Education Integration Teaching Model Empowered by Artificial Intelligence

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Authors

YCY. L. CuiLML. Ma

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Overview

Controlled experiment demonstrates improved curriculum alignment and practical skills in business students, indicating the efficacy of AI-driven adaptive educational frameworks.

Key Points

  • Develop and evaluate an artificial intelligence-driven framework that dynamically aligns business curricula, enterprise project allocation, and practical decision training with real-time industry demands.
  • Extracted entities from 45,600 job postings using BERT and BiLSTM-CRF to build an industry-skill knowledge graph and semantic mapping system for curriculum updates.
  • Deployed a multi-agent reinforcement learning scheduler to optimize student-to-project allocation alongside a cGAN- and LLM-powered market simulation sandbox.
  • Conducted a 16-week controlled experiment to evaluate curriculum alignment, resource utilization, and student performance metrics.
  • AI-driven semantic mapping increased syllabus-to-industry alignment to a score of 0.89.
  • The multi-agent reinforcement learning matching system reduced the project-resource idle rate to 5.7%.
  • Generative sandbox training improved students' strategy innovation and risk-prediction scores by over 23 points.

Cite This Study

Cui et al. (2026) studied this question.

synapsesocial.com/papers/6a817ab4f2fb91fc834aeb99https://doi.org/10.7716/aem.v15i3.3994
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