A Comprehensive Literature Review on AI-Enhanced Autonomous Learning Mechanisms in Vocational Education
Abstract
The rapid advancement of artificial intelligence (AI) is transforming education, particularly vocational institutions, which play a vital role in producing technically skilled professionals. Vocational colleges face challenges in modernizing teaching methods and addressing deficiencies in self-directed learning mechanisms, such as disparities in students' abilities, technological acceptance issues, and limited teacher support. This study aims to develop AI-based strategies to enhance autonomous learning among vocational students, focusing on intelligent systems, feedback mechanisms, and optimized learning environments while redefining the role of educators. A comprehensive literature review was conducted to analyze existing self-directed learning mechanisms and challenges in vocational education. The findings reveal that integrating AI technologies into vocational education significantly improves learning outcomes. Intelligent learning systems enable personalized pathways and adaptive feedback, while optimized learning environments and educator training address student disparities and motivational issues. The study concludes that adopting AI-supported autonomous learning strategies not only resolves current challenges but also provides a roadmap for innovation in vocational education. Future efforts should focus on refining these mechanisms and ensuring their scalability to nurture self-reliant and innovative professionals.
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References
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