A Balanced Clustering Grouping Model Based on Cognitive States
Grouping is a key step in collaborative learning.A balanced clustering model based on cogni-tive diagnosis is proposed to address the problems of quantization of student characteristics and dispro-portion in group size and learning ability in student grouping.Firstly,the cognitive diagnostic model is used to obtain the cognitive states of students,and the cognitive states are quantified;then the grouping goals are defined as functions,and students are clustered using an improved balanced clustering algo-rithm;finally,the final grouping scheme is obtained based on the grouping goals and the students'knowl-edge characteristics.Three existing grouping methods were compared and contrasted within nine datasets.The experiments verified the effectiveness of the balanced clustering based on cognitive states of two indi-cators:the rate of intra-group knowledge complementarity and the rate of knowledge balance between groups.
NETL
NSTL
万方数据
维普
