Online Behavior Analysis‐Based Student Profile for Intelligent E‐Learning
K Liang, Y Zhang, Y He, Y Zhou… - Journal of Electrical …, 2017 - Wiley Online Library
K Liang, Y Zhang, Y He, Y Zhou, W Tan, X Li
Journal of Electrical and Computer Engineering, 2017•Wiley Online LibraryWith the development of mobile platform, such as smart cellphone and pad, the E‐Learning
model has been rapidly developed. However, due to the low completion rate for E‐Learning
platform, it is very necessary to analyze the behavior characteristics of online learners to
intelligently adjust online education strategy and enhance the quality of learning. In this
paper, we analyzed the relation indicators of E‐Learning to build the student profile and
gave countermeasures. Adopting the similarity computation and Jaccard coefficient …
model has been rapidly developed. However, due to the low completion rate for E‐Learning
platform, it is very necessary to analyze the behavior characteristics of online learners to
intelligently adjust online education strategy and enhance the quality of learning. In this
paper, we analyzed the relation indicators of E‐Learning to build the student profile and
gave countermeasures. Adopting the similarity computation and Jaccard coefficient …
With the development of mobile platform, such as smart cellphone and pad, the E‐Learning model has been rapidly developed. However, due to the low completion rate for E‐Learning platform, it is very necessary to analyze the behavior characteristics of online learners to intelligently adjust online education strategy and enhance the quality of learning. In this paper, we analyzed the relation indicators of E‐Learning to build the student profile and gave countermeasures. Adopting the similarity computation and Jaccard coefficient algorithm, we designed a system model to clean and dig into the educational data and also the students’ learning attitude and the duration of learning behavior to establish student profile. According to the E‐Learning resources and learner behaviors, we also present the intelligent guide model to guide both E‐Learning platform and learners to improve learning things. The study on student profile can help the E‐Learning platform to meet and guide the students’ learning behavior deeply and also to provide personalized learning situation and promote the optimization of the E‐Learning.
Wiley Online Library
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