Heterogeneous teaching evaluation network based offline course recommendation with graph learning and tensor factorization

•Student attributes, relations and comment are used to construct feature network.•The network provides students’ personalization and their mastery of knowledge.•With network feature, a “user-item-personalization” rating tensor is constructed.•The rating tensor is decomposed by tensor factorization methods via learning.•A course recommendation model is proposed based on aforementioned processes.