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Peer-inspired Student Performance Prediction in Interactive Online Question Pools with Graph Neural Network
[article]
2020
arXiv
pre-print
Student performance prediction is critical to online education. It can benefit many downstream tasks on online learning platforms, such as estimating dropout rates, facilitating strategic intervention, and enabling adaptive online learning. Interactive online question pools provide students with interesting interactive questions to practice their knowledge in online education. However, little research has been done on student performance prediction in interactive online question pools. Existing
arXiv:2008.01613v1
fatcat:v7spnglvbfcvnltows7x6wvbbi