Review of Deep Learning-Based Personalized Learning Recommendation
Ling Zhong, Yantao Wei, Huang Yao, Wei Deng, Zhifeng Wang, Mingwen Tong
Abstract
Online learning has become a significant way for learners to acquire knowledge, which enables anybody to learn anywhere and anytime. However, how to choose appropriate content for learning is an interesting issue, especially when one faces massive online learning resources. With this regard, deep learning-based personalized learning resources recommendation has become an effective approach to handle this problem. In this paper, deep learning-based personalized learning recommendation technology in the field of education is thoroughly analyzed, and some limitations of recent studies as well as future works, then, are reported and predicted respectively. The study would provide suggestions for future research on deep learning-based personalized learning recommendations.