Research on Personalized Service Path of Learning Resources by Data Driven

Abstract

In the digital age, the trend of personalized learning requires learning resources to provide learners with more accurate and intelligent personalized services. However, current research is inadequate in meeting the need for personalized, intelligent, and accurate digital learning resource services for learners. This study is based on a large number of learning analytics and learning resources relevant to the analysis of literature studies and the corresponding theoretical framework, using over 1.4 million learner data collected and stored by H Publishing from real-life contexts and natural learning conditions as the basis of the study. This study uses learning analytics and artificial intelligence technologies to analyze learners' personalized learning needs and construct intelligent adaptive service path for learning resources. On the one hand, it reduces the unreasonable use of digital learning resources, saves learner's time costs, and improves learning efficiency. On the other hand, it provides effective references for digital learning resources can better serve learners.