Overview of Online Learning Behavior Analysis in the Context of Big Data

Abstract

Under the Internet era, various technologies such as big data and cloud computing are becoming more and more a hot issue of concern. Big data provides a large number of network resources with great economic as well as social value, which has a certain impact on various fields in society, and its use in education has received more attention from scholars. After the outbreak of the new crown epidemic, online learning has become a normalized way of learning, online learning platform records a large number of learners' learning data, through the processing and analysis of these massive data, not only is conducive to the realization of students' personalized learning, but also helps teachers to understand and master the current situation of students' learning, and then adjust their teaching. In order to have a clear understanding of the current research status of online learning behavior analysis in the context of big data, the article uses the visual analysis software CiteSpace to analyze the literature selected from the China Knowledge Network (CKN), from which the current status of the research, research hotspots, and future research trends in this field are obtained. The analysis results show that the number of publications has gradually decreased in the past two years, and there is less cooperation and communication between the core publication authors as well as the publication institutions; the analysis of learning behavior data on MOOC platforms has become a research hotspot at this stage, and in-depth learning, multi-scenario, and focusing on the students' learning experience are the future research trends.