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Deep Knowledge Tracing Based on Spatial and Temporal Representation Learning for Learning Performance Prediction
2022
Applied Sciences
Knowledge tracing (KT) serves as a primary part of intelligent education systems. Most current KTs either rely on expert judgments or only exploit a single network structure, which affects the full expression of learning features. To adequately mine features of students' learning process, Deep Knowledge Tracing Based on Spatial and Temporal Deep Representation Learning for Learning Performance Prediction (DKT-STDRL) is proposed in this paper. DKT-STDRL extracts spatial features from students'
doi:10.3390/app12147188
fatcat:mllasvaou5au5n6cbuhrgaqys4