Abstract:

The rapid development of network technology in distance education makes it possible for personalized learningIn this paper, we use the Kmeans algorithm to cluster students based on attribute data and the corresponding student’s course achievement for data mining and find the characteristics of the learner groupsThen, the characteristics and differences of the clustering results can provide guidance for curriculum resources establishment and teaching process improvement

Key words: Kmeans algorithm, personalized teaching, distance learning, distance education