Evaluation Data of Poor College Students Based on Improved Apriori Algorithm

In recent years, with the continuous expansion of college enrollment in China, more and more students have the opportunity to enter the university. However, due to the reform of the charging system in colleges and universities, the number of poor students in colleges and universities is increasing. In this worrying situation, our government and universities have taken a series of measures and made many achievements. In this study, we use the Apriori algorithm to extract evaluation data from poor college students’ compositions. The purpose of this study is to examine how poor college students’ writing performance is evaluated by taking their compositions as samples. We also investigated whether there were differences between male and female students in assessing their own performance. The results show that, compared with other college students, Apriori algorithm can effectively evaluate the paper quality of students whose academic ability is at least at the middle level. This is especially useful for papers with poor evaluation ability.