SA-FEM: Combined Feature Selection and Feature Fusion for Students’ Performance Prediction

SA-FEM: Combined Feature Selection and Feature Fusion for Students’ Performance Prediction

Around the world, the COVID-19 pandemic has created significant obstacles for education, driving people to discover workarounds to maintain education. Because of the excellent benefit of cheap-cost information distribution brought about by the advent of the Internet, some offline instructional activ...

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Bibliographic Details
Main Authors: Mingtao Ye, Xin Sheng, Yanjie Lu, Guodao Zhang, Huiling Chen, Bo Jiang, Senhao Zou, Liting Dai
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Sensors
Subjects:
e-learning behavior classification
feature selection
feature fusion
prediction of learning performance
prediction and analysis
Online Access:https://www.mdpi.com/1424-8220/22/22/8838

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https://www.mdpi.com/1424-8220/22/22/8838

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