Yu Xue1,2,*, Jiafeng Qin1, Shoubao Su2, Adam Slowik3
Computer Systems Science and Engineering, Vol.39, No.2, pp. 211-219, 2021, DOI:10.32604/csse.2021.016693
Abstract 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… More >
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