The Generating Algorithm Of Individualized Courses Based On Clustering Analysis

In the context of education informatization 2.0,individualized education has received widespread attention.With the promotion of liberal education and complete credit system,students have greater autonomy in the course selection,and they can combine the individualized characteristics,such as professions,interests,knowledge,ability and others,to select courses that meet their individualized development.However,limited by the understanding of professions and future employment,it is often difficult for students to make the right choice.Therefore,it is of great significance to use information technology to assist students to select individualized coursed based on the big data of students.On the basis of reviewing the relevant literature of individualized education,combing the data sets related to students and quantifying the key indicators,this paper has put forward the hypothesis of individualized characteristics that affects the course selection,and verified the validity ofthe recommendation results and recommendation accuracy in the hypothesis through experiments,and finally proposed a generating algorithm of individualized courses in colleges and universities based on clustering analysis.In terms of specific technology,through the K-means algorithm to cluster the data sets of students,combined with the individualized factors such as hobbies and interests,learning ability and learning objectives,the paper has proposed an approximate sorting algorithm to deal with the problem of sorting among target students.This paper has also proposed course recommendation index(CRI)to analyze the matching degree between the courses in the objective of cultivation and the characteristics of student.Based on the requirement research of individualized course recommendations for teachers,counselors,and students,this paper has found that students prefer to choose easy courses and avoid choosing difficult key courses during the process of course selection.In order to avoid the adverse effects of such tendencies on the professional cultivation of students,this paper has conducted a deep analysis of the specific indicators,and improved the clustering algorithm in a targeted manner,which makes the recommendation result not cater to the pleasure of students,but really guide the good development of students.According to the analysis of experiment result,the paper has proposed the generating algorithm of individualized courses based onK-means clustering analysis,which has certain validity,and the accuracy of recommendation is acceptable.In addition,this paper has specifically conducted experiments and analysis on the guiding effect,and compared with the recommendation effect of students with different scores.It is found that the improved algorithm in this paper is more accurate for relatively excellent students,the accuracy drops off for the students of lower-middle class.The results of this experiment show that the improved algorithm in the paper is more in line with the characteristics of course selections among excellent students,and helps to guide the students of lower-middle class to adjust the courses appropriately,so as to better complete their professional cultivation.