Deep Learning-Based Modeling Methods in Personalized Education  

作　　者：Qiang SUN 

机构地区：[1]North China University of Technology

出　　处：《Artificial Intelligence Education Studies》2025年第1期15-30,共16页人工智能教育研究(英文)

摘　　要：Deep learning has significantly transformed personalized education by enabling intelligent adaptation to indi-vidual learning needs.This study explores deep learning-based modeling methods that enhance personalized learning experiences,optimize instructional content,and predict student progress.We examine key techniques,including recurrent neural networks(RNNs),transformers,reinforcement learning,and multimodal learning analytics,to demonstrate their roles in personalized learning path recommendations and adaptive content gen-eration.Case studies of AI-driven tutoring systems and learning management platforms illustrate real-world applications.Additionally,we address challenges related to data privacy,algorithmic bias,and model inter-pretability.The paper concludes with future directions for deep learning in education,emphasizing its potential for enhancing immersive and intelligent learning environments.

关 键 词：Deep Learning Personalized Learning Adaptive Education Learning Analytics Artificial Intelligence 

分 类 号：H31[语言文字—英语]