Volume 94

Artificial intelligence (AI) technology injects new impetus into education reform, and its functions, such as personalized learning and intelligent evaluation, are expected to solve the problems of low efficiency and unequal resources in the traditional teaching mode. However, there are still significant bottlenecks in the practical feasibility and effectiveness of AI in the teaching classroom and its deep integration with traditional education, which restrict the full release of its educational value. Through empirical analysis, this paper reveals the current three core issues. First, the lack of support for educational resources and the gap in AI infrastructure between regions exacerbated the inequity of education; Second, there are differences in teaching feedback. AI tools are difficult to adapt to complex teaching scenes due to low adaptability of algorithms and data deviation; The third is the lack of teachers' information awareness and ability, and the dual lack of technology application ability and curriculum integration strategy. Given the above problems, this paper puts forward targeted countermeasures from three aspects: improving educational resources, improving educational feedback, and improving teachers' information awareness and ability, to provide reference for the effective application of AI technology in classroom teaching practice.

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Under the background of the rapid, continuous development of global technology, electronic equipment and programming, artificial intelligence is gradually moving from theory to application, and exerting significant influence on various aspects of people's life, which including the field of professional sports training. This paper analyzes whether the volleyball training plans generated by generative artificial intelligence align to the sports training principles, and the attitudes and differences of professional coaches and volleyball athletes towards the plans generated by AI. This paper concludes that coaches and athletes unanimously agree that the training scheme formulated by generative AI conforms to the principles of sports training, and coaches' recognition is higher. Additionally, There are great differences in the attitudes of athletes and coaches. Based on this, this paper puts forward the following suggestions: improving the customization ability of AI, developing adaptive artificial intelligence training system, applying reinforcement learning, and promoting multi-disciplinary and interdisciplinary cooperation.

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Vocational education plays a pivotal role in fostering economic growth, social advancement, and individual development in China. Against the backdrop of rapid digital transformation and industrial upgrading, this study examines the current status, challenges, and future trends of China’s vocational education system. By conducting a systematic literature analysis of peer-reviewed articles from CNKI and Web of Science, government policies, and international reports, this research identifies critical barriers such as outdated educational philosophies, insufficient integration of emerging technologies, and regional disparities in resource allocation. Thematic coding and comparative analysis reveal persistent contradictions between policy rhetoric and implementation, particularly the elitist bias favoring general education over vocational training. Key findings emphasize the necessity of adopting a people-oriented approach, deepening industry-education collaboration, modernizing curricula with AI and IoT, and enhancing teacher competencies through enterprise partnerships. The study concludes that proactive strategies, including policy reinforcement, curriculum innovation, and equitable resource distribution are essential to align vocational education with the demands of digital transformation. Limitations include insufficient exploration of rural vocational schools’ digital readiness, suggesting future research directions.

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