Applications of Artificial Intelligence Methods in Digital Modeling within Vocational and Pedagogical Education: Optimization, Applications, and Ethical Approaches
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Alishov Monsum Adil oglu
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This study explores the integration of artificial intelligence (AI) methods into digital modeling specifically for vocational and pedagogical education, with a focus on technical specialties widely taught in Azerbaijan. A three-stage framework (Design → AI-Driven Optimization → Ethical Validation) is proposed to embed digital twins and hybrid AI algorithms into vocational training curricula. The framework combines hyperparameter-optimized deep neural networks, reinforcement learning, and human-in-the-loop feedback from experienced instructors to create adaptive, high-fidelity training simulators. Two illustrative cases are presented: (1) an AI-enhanced virtual welding simulator and (2) a predictive digital twin of a CNC machining center. Preliminary implementation results from pilot courses at Azerbaijani vocational colleges demonstrate a 34 % reduction in material consumption, a 29 % decrease in practical training duration, and a significant improvement in skill retention rates. The paper further introduces a 5E ethical integration model (Explain–Explore–Experiment–Evaluate–Embed) to address fairness, transparency, and the digital divide in resource-limited educational settings. The proposed approaches provide practical, scalable solutions for modernizing vocational education in developing countries, directly supporting UN SDG 4 and SDG 8.
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Authors
Alishov Monsum Adil oglu
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References:
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