Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology

Abstract

As new directions of development, Industry 5.0 and Education 5.0 emphasize human-machine
collaboration, personalized services, and the application of intelligent technologies. This paper
aims to explore how intelligent technology can transform vocational education to enhance the
effectiveness of vocational training and meet the demands of the modern economy. By
analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary
integration, and long-term learning behavior analysis, the paper proposes four
improved algorithms: the adaptive learning path generation algorithm, the emotion-driven
personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the
long-term learning behavior prediction algorithm. The research demonstrates that these
innovative approaches effectively address the limitations of current personalized learning
systems, providing theoretical and practical support for the intelligent transformation of
vocational education.