The association rule between college students' daily behavior and school records has been the focus of education. Firstly, this paper summarizes the previous research results on this kind of problem, and studies many factors that affect college students' performance. Secondly, as an example of Institute of Disaster Prevention in China, the data of school records, online time and library time were extracted in this paper. The association between school records and the average daily online time, the average daily network flow and the time staying in library are discussed qualitatively via statistical analysis. It is pointed out that there is a negative correlation between daytime online time and academic records, and a positive correlation between library stay time and academic records. Then, using K-means clustering mining algorithm to analyze the online time and academic records, the results show that the excellent students spend less time online than the poor students, especially in the daytime. And using Apriori association analysis mining algorithm to study the relationship between the length of stay in Library and academic records. The minimum support and minimum credibility are set at 60%, and three strong association rules are obtained, that is, the students with good academic records stay in library for the longest time, the students with general academic records take the second place, and the students with poor academic records stay in library for the shortest time, which is completely consistent with the actual situation. This shows that the results of statistical method and data mining algorithm are consistent, that is, students who study well spend less time on Internet (shorter in the day) and more time in library than those with average records. The conclusion can help teachers to guide students to improve their achievement, so that students can better complete their studies, which has important guiding significance.
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