The Research On Students' Online Learning Behavior Based On Hadoop

In the large data era,the amount of data in various industries is growing rapidly,including the education.As the continuous development of information technology,cloud technology,the Internet of Things and the big data technology based on both are promoting education to change.For learners,the model of learning has gradually transformed from traditional face-to-face teaching to a combination of traditional teaching and online learning style,so the amount of data is also increasing during the online learning.Extracting effective data from massive data to analyze the learners'learning behavior and find the valuable information,which is beneficial to analyze the learners' learning behavior model,optimize the learning website structure and promote the educational information to develop better.This article take the log data of online learning behavior in distance learning network of open education college in East China Normal University for example,using Hadoop--tool of large data analysis,to extract the learner's effective information from log data of online learning behavior,analyze online learning behavior characteristics,and do correlation analysis combined with the learner's performance data to study the impact of learner's learning style on learning outcomes,and explore the optimization strategies of online learning platform.