This study focuses on developing a personalized teaching model for English learners

supported by big data technology. Addressing the limitations of traditional teaching methods in adapting to individual differences

the study integrates situational learning theory and educational equity theory to design a core framework comprising four dimensions. A personalized diagnostic system based on learner profiles enables precise assessment of abilities; a flexible resource supply system provides multimodal learning materials on demand; a real-time intervention system dynamically adjusts teaching strategies through learning situation alerts; and an evolutionary assessment system continuously optimizes model parameters through machine learning. Through a triple operational mechanism of initial adaptation

dynamic adjustment

and ecological evolution

the system achieves intelligent iteration of teaching pathways.