Shows improved educational outcomes in vocational education, highlighting the role of blockchain and AI for better skill development.
Labor education plays a vital role in higher vocational education by building students’ practical and professional skills. However, existing platforms suffer from weak industry–institution collaboration, lack of personalized training paths, and insecure management of learning records. To address these challenges, the research proposes a collaborative teaching mechanism integrating blockchain technology with a deep learning framework. The goal is to develop a transparent, secure, and intelligent vocational education system that encourages collaboration between students, teachers, and industry partners. Data on vocational education performance is collected from various sources, including student performance records, practical task diaries, and internship assessments. The dataset undergoes cleaning and Z-score standardization for analysis. Use a distributed ledger (DL) to securely maintain verifiable learning outcomes, internships, and certifications. Blockchain technology is being used to connect colleges, industries, and students to facilitate transparent data sharing. Applying a Residual Convo Memory Network (RCMNet) model allows the system to discover unknown skill gaps, measure development over time, and produce personalized recommendations for learning paths. The RCMNet model is implemented on the Python platform. Simulation results show that the proposed blockchain-based RCMNet framework achieves 98% accuracy, 97.43% recall, 97.16% precision, and 97.64% F1-score, outperforming existing methods. It also delivers strong educational outcomes, with 92% LOIR, 89% SGRI, 94% IPS, 98% DITS through blockchain, and 91% PLPAR, demonstrating both high analytical performance and practical impact in vocational education. Finally, integrating blockchain with deep learning offers a robust solution for collaborative vocational education by ensuring secure accountability and personalized skill development for learners.
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Lin et al. (2026) studied this question.
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