This paper examines AI's role in integrating physical and academic education, focusing on sports injury prevention (via real-time monitoring and personalized plans) and academic burnout intervention. It constructs integration paths through curriculum design, AI-driven teaching tools, and resource optimization. Challenges include data ethics and uneven tech access, with solutions like regulation and tech popularization to […]

This study explores AI's role in revolutionizing film and television performance education, covering intelligent assessment, virtual practice, and personalized guidance. It highlights significant improvements: 53% better student performance, 70% less teacher repetitive work, and enhanced training efficiency via technologies like motion capture and virtual scenes. Challenges like emotional computation limits and ethical issues are addressed, […]

This study systematically reviews the research progress on the impact of educational leadership on student academic achievement from 2000 to 2024. It finds that the theoretical connotation of educational leadership has continuously evolved, shifting from an early focus on formal leaders to perspectives such as distributed leadership and teacher leadership. As a research hotspot, teacher […]

This study focuses on the mechanism for cultivating innovative music talents in higher vocational colleges under the "Double High" background. It analyzes current dilemmas such as the disconnection between courses and the market, insufficient innovation capability of teachers, and lack of practical platforms. Drawing on experiences from domestic and foreign institutions, it systematically constructs a […]

This study explores the interaction mechanism between educational expectations and social pressures in college students' families from a theoretical perspective. By analyzing relevant theories in sociology, psychology, and education, it reveals how families' high educational expectations for college students are influenced by the social environment, and how these expectations interact with social pressures to affect […]

This study constructs an intelligent classroom teaching evaluation system integrating multimodal deep learning. Based on models such as computer vision (ResNet+Pose Estimation), speech processing (CNN+LSTM), and natural language processing (BERT+Transformer), the system comprehensively analyzes multimodal data including students' facial expressions, speech emotions, and classroom speaking content, to accurately quantify student focus, classroom interaction index, and […]