Adaptive Learning Model for English Classroom Based on Artificial Intelligence

Abstract

: This paper proposes an artificial intelligence-based adaptive learning model for English classrooms. By analyzing multidimensional learning data, including students' learning styles, learning states, and academic abilities, the model enables real-time prediction of learning performance and automatic adjustment of teaching strategies and learning content to sustain students' learning engagement and concentration. Specifically, the system can generate personalized learning paths, dynamically adapt learning content and difficulty levels, and realize student-oriented personalized instruction. Educational practice indicates that AI-driven adaptive learning possesses prominent advantages in classroom teaching. It can closely integrate with conventional teaching procedures, monitor learning progress continuously, and deliver tailored learning experiences through intelligent strategy adjustment. Furthermore, the system accumulates massive learning data to provide reliable educational evidence for teachers, helping them accurately perceive students' learning conditions, optimize teaching methods in a timely manner, and better satisfy students' diverse personalized learning demands.