Brain Storm Optimization Based Clustering for Learning Behavior Analysis  

作　　者：Yu Xue Jiafeng Qin Shoubao Su Adam Slowik 

机构地区：[1]School of Computer and Software,Nanjing University of Information Science and Technology,Nanjing,210044,China [2]Jiangsu Key Laboratory of Data Science and Smart Software,Jinling Institute of Technology,Nanjing,211169,China [3]Department of Electronics and Computer Science,Koszalin University of Technology,75-453,Koszalin,Poland

出　　处：《Computer Systems Science & Engineering》2021年第11期211-219,共9页计算机系统科学与工程（英文）

基　　金：This work was partially supported by the National Natural Science Foundation of China(61876089,61876185,61902281,61375121);the Opening Project of Jiangsu Key Laboratory of Data Science and Smart Software(No.2019DS301);the Engineering Research Center of Digital Forensics,Ministry of Education,the Key Research and Development Program of Jiangsu Province(BE2020633);the Priority Academic Program Development of Jiangsu Higher Education Institutions.

摘　　要：Recently,online learning platforms have proven to help people gain knowledge more conveniently.Since the outbreak of COVID-19 in 2020,online learning has become a mainstream mode,as many schools have adopted its format.The platforms are able to capture substantial data relating to the students’learning activities,which could be analyzed to determine relationships between learning behaviors and study habits.As such,an intelligent analysis method is needed to process efficiently this high volume of information.Clustering is an effect data mining method which discover data distribution and hidden characteristic from uncharacterized online learning data.This study proposes a clustering algorithm based on brain storm optimization(CBSO)to categorize students according to their learning behaviors and determine their characteristics.This enables teaching to be tailored to taken into account those results,thereby,improving the education quality over time.Specifically,we use the individual of CBSO to represent the distribution of students and find the optimal one by the operations of convergence and divergence.The experiments are performed on the 104 students’online learning data,and the results show that CBSO is feasible and efficient.

关 键 词：Online learning learning behavior analysis big data brain storm optimization CLUSTER 

分 类 号：H31[语言文字—英语]