Behavior Analysis And Application In Intelligent Learning Environment Based On IPv6

With the rapid development of the Internet of Things,the Internet and cloud computing technologies,smart classrooms in a smart environment have gradually become the target of informatization construction in major universities.Due to the emerging development of smart classrooms,the research and use of smart classrooms are still being explored.How to give full play to the advantages of smart classrooms to improve teachers' teaching quality and improve students' learning efficiency lacks clear indicators and effective programs.Through field research and demand analysis,this thesis proposes an analysis of user interaction behavior based on IPv6 smart learning environment,and implements an Internet-based interactive behavior analysis platform based on IPv6 and Web Service.The platform analyzes the teaching process behavior and learning interaction behavior by acquiring intelligent classroom equipment operation data,monitoring and analyzing data,intelligent recording and broadcasting data,supervising the management process of the management personnel,managing the classroom equipment,and how to improve the teaching quality and achieve Personalized education has certain reference significance.The work of this thesis is mainly reflected in the following three points.:(1).This thesis proposes an interactive behavior analysis scheme and implementation ideas based on the smart learning environment.The smart classroom obtains the dynamic data of teachers and students through the object-aware technology and video recording technology.The program obtains the teacher operating equipment data,student attendance data,class emotional data,device status data,etc.through the interface protocol and Web service interface of the Internet of Things.The data is stored in a data warehouse to support user decision making and analysis.(2).This thesis aims to promote the application of IoT in the future,and the problem of insufficient IPv4(Internet Protocol Version 4)address when deploying smart devices.This thesis proposes a solution based on IPv6 hardware deployment and dual protocol stack,which can implement dual stack.The communication method of the network address device.(3).Based on the ID3 algorithm in the decision tree and the K-means algorithm in cluster analysis,this thesis implements multi-angle statistics and analysis of teaching behavior,learning behavior and equipment usage data,including the use of smart classrooms for teachers of different disciplines and ages.And intelligent recording and data analysis,data analysis of student attendance,online answering and class expressions,and analysis of equipment usage time,equipment energy consumption and equipment loss warning,and finally visualize the analysis results.