An Association Rule-Based Multiresource Mining Method for MOOC Teaching

Abstract

The selection of MOOC teaching resources is influenced by diversified resource positioning methods, which leads to low index efficiency of resource mining. Therefore, this paper proposes a multiresource mining method based on association rules to collect the learning behavior data of MOOC users and establish the MOOC teaching resource warehouse. Aiming at the attribute set of information association positioning, the association rules of teaching resources are designed. In addition, the association rules are combined with the shortest path scheduling scheme of teaching resources to establish the location and mining of diversified MOOC teaching-associated resources. Finally, the clustering method is used to process the results of teaching resource mining and complete the clustering of diversified teaching resources. Experimental results show that the index time required by the proposed mining method is 0.1 s, which is only 1/6 of other resource mining methods.