The impact of AIGC on simulating realistic human movement for immersive learning in film and television education
Abstract
This study investigates the impact of Artificial Intelligence Generated Content (AIGC) on teaching realistic human movement simulation in film and television education, with a focus on biomechanical principles. Through a 12-week randomized controlled study involving 46 students from three leading Chinese film academies, we examined the effectiveness of AIGC-based motion simulation systems compared to traditional teaching methods. Using a mixed-method approach, the study evaluated learning outcomes, technical accuracy, and user experience, emphasizing the biomechanical accuracy of simulated movements. Results demonstrated significantly higher performance in the AIGC group across multiple metrics, including motion accuracy (94.3% vs. 82.5%, p < 0.001), skill acquisition rates (improvement rate: 46.1% vs. 33.8%, p < 0.001), and knowledge retention (96.4% vs. 91.1%, p < 0.001). The AIGC system showed superior technical performance with 99.7% uptime and motion-to-photon latency below 20 ms, ensuring real-time responsiveness crucial for biomechanical training. Student engagement levels were notably higher in the AIGC group (92.4% vs. 78.6%, p < 0.001), with improved system usability scores (SUS: 87.3/100) compared to industry benchmarks. This research provides empirical evidence supporting the integration of AIGC technologies in film and television education, particularly in simulating realistic human movements grounded in biomechanical principles. The findings offer valuable insights for curriculum development and educational technology implementation in creative fields.
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