College English Teaching Model and Discussion Based on Big Data Technology

This paper explores the integration of big data technology into college English teaching models to enhance educational outcomes. We developed a Self-Organizing Feature Map (SOFM) neural network-based model for evaluating English teaching quality, aiming to identify factors that improve teaching effectiveness. The model was tested for its training and generalization capabilities, demonstrating fast convergence, high classification accuracy, and robust generalization. Our experimental results indicate that the proposed evaluation model effectively classifies teaching quality by analyzing the competitive layer’s winning neurons. This approach not only advances the assessment of teaching quality but also provides innovative pathways for enhancing university English education, aligning with modern educational needs and technological advancements.