| The rapid development of information technology has promoted the transformation of teaching methods.Personalized learning,one of the basic characteristics of learning in the 21 st century,is a new learning trend that promotes the individualized development of students in the era of "Internet +".The main means to achieve personalized teaching is to use computer-aided tests to diagnose the student's knowledge structure,and then carry out targeted remedial teaching activities based on the diagnosis results,such as resource push and path planning.How to accurately diagnose the knowledge status of students is the core link to achieve personalized teaching.Grouping is an important part of cooperative learning.It can cultivate students' teamwork ability and improve the efficiency of students' cooperative learning.However,at present,cooperative learning is often grouped manually,and it is impossible to ensure that members of the group have high complementarity in knowledge structure.Therefore,the article proposes a grouping method based on cognitive diagnosis.The method firstly uses the multi-layer perceptron neural network to diagnose the student's knowledge state.Under the support of the diagnosis results,the knowledge state transition diagram is generated and the topological order is obtained by acquiring the dependence between the knowledge points.Finally,the student is sorted according to the knowledge state topology.Automated grouping makes members in the group highly complementary in knowledge structure.On this basis,the grouping method is applied to the cooperative learning teaching design,and it is applied to the teaching practice in the course of "C programming".The experimental data shows that this method can effectively improve the complementarity of team members in the knowledge structure,thereby improving the problem solving rate and improving the learning effect of students.The results of the survey showed that students participating in the experiment were more satisfied with the teaching method based on complementary grouping. |