Research on the course relations based on granular computing

There exists certain relevance between many different courses generally, and usually a course is also a prerequisite for other courses. However, under current credit system, students have many choices in taking courses and arranging the course sequences, generally resulting in different achievements for students of different course sequences and different teaching efficiency. Based on the method of granular computing and analysis of association rules, this paper aims to provide students with reasonable suggestions on their course choices by studying the affecting relationship between different courses and their knowledge association rules. The simulation and the actual score data analysis are presented.