Fine-grained causal effect estimation of learning resources via dynamic causal heterogeneous graph neural networks

Abstract Effect evaluation of learning resources in online education platforms is crucial for optimizing instructional strategies and enabling personalized learning. However, conventional methods struggle to address the inherent challenges posed by the heterogeneous graph structure of student-resour...

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Autors principals:	Yuan Ren, Zhanfang Chen, Xiaoming Jiang, Zeming Du
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2026-01-01
Col·lecció:	Scientific Reports
Matèries:	Causal inference GNN Doubly robust estimator Heterogeneous graph
Accés en línia:	https://doi.org/10.1038/s41598-025-34421-5
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