Research on the Visualization of Users' Online Learning Behavior by Big Data Intelligent Analysis

Abstract

Big Data has significant prospects for virtually every company and sector, including finance, stock trading, agriculture, telecommunications, healthcare, and education. This wide-open door brings with it a lot of problems and obstacles. Opportunities are growing along with the volume of Big Data, which is expected to grow significantly as a result of the technological revolution, which includes but is not limited to various mobile devices. As educational institutions have sensitive data that are dispersed across departments in various configurations and need to be processed to gain knowledge and create future predictions, we studied several Big Data usages, approaches, and a Learning Examination Model based on Big Data. By studying the patterns from the available verified data, prediction models may be created. The emergence of the mobile stage, including smart phones and cushions, has accelerated the development of the e-learning paradigm. In this article, we analyzed e-learning-related signals, created student profiles, and suggested countermeasures. In addition, we provide an intelligent leadership model and e-learning her platform to guide learners and improve learning outcomes in line with learning behaviors and e-learning materials. A detailed examination of three interrelated factors: Learning effect correlation analysis, individual course recommendation analysis by page rank calculation, clustering analysis of learning behavior by k-means calculation.