Hybrid Teaching Model of College English Based on Collaborative Filtering Recommendation Algorithm

Abstract

A recommendation system is a powerful tool that analyzes user preferences and behaviors to provide personalized suggestions or recommendations. By leveraging algorithms and data analysis techniques, recommendation systems help users discover relevant content, products, or services tailored to their individual interests and needs. Whether recommending movies, music, books, or products, these systems enhance user experience by minimizing the effort required to find relevant information or items. Additionally, recommendation systems benefit businesses by increasing customer engagement, satisfaction, and sales through targeted recommendations. The recommendation systems play a crucial role in optimizing decision-making processes and enhancing user satisfaction in various domains. This paper introduces a novel hybrid teaching model for college English, integrating the Collaborative Filtering Recommendation Algorithm with Hybrid Ant Whale Optimization Collaborative Filtering (HAWO-CF). The proposed model aims to personalize English language instruction by leveraging collaborative filtering techniques to recommend tailored learning materials and activities to students. Through simulated experiments and empirical validations, the efficacy of the HAWO-CF-enhanced hybrid teaching model is evaluated. Results demonstrate significant improvements in student engagement, comprehension, and learning outcomes compared to traditional methods. For instance, students using the HAWO-CF model exhibited a 25% increase in vocabulary retention and a 30% improvement in reading comprehension scores. Additionally, the model enabled instructors to optimize teaching strategies based on real-time feedback and performance data, leading to more effective and adaptive instruction. These findings underscore the potential of hybrid teaching models with HAWO-CF in revolutionizing college English education, and fostering personalized and impactful learning experiences.