The prediction model of higher vocational students' classroom participation based on the fusion of deep learning and support vector machine

Key Points

• Classroom participation can be effectively predicted using a combined model with deep learning and support vector machine.
• The model indicates significant predictive power by integrating artificial intelligence techniques, enhancing student engagement.
• Observational analysis applies advanced computing methodologies to assess participation trends in vocational education settings.
• The findings highlight the potential for AI-driven models to inform teaching strategies, requiring further validation in diverse educational environments.