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《Computer Knowledge and Technology》 2018-24
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Student Performance Prediction based on Campus Card Data and Curriculum Classification

ZHOU Qing;WANG Wei-fang;GE Liang;XIAO Yi-feng;TAI-Dai;College of Computer Science, Chongqing University;  
Aiming at the academic risk of College students and the difficulty of Teaching Management in Universities,this paperpresented a method based on campus card data and the idea of curriculum classification to predict whether students can pass thecourse examination. First of all, preprocessing the data of students' campus card data and course performance, and extracting thefeatures, Secondly, using Pearson's correlation coefficient and Apriori algorithm to analyze not only the correlation between thecourse results of different semesters, but also the relevance between breakfast time and course performance. Then, combining thenumber of breakfast with the results of the same type of course, a variety of classifiers were used to predict whether the students' fu-ture performance was passed. The result shows that this method can predict whether there is a risk of failure in a student's course,and it is convenient for teachers to help students with academic difficulties in time.
【Fund】: 国家自然科学基金资助项目(61472464);; 重庆市前沿与应用基础研究计划(cstc2016jcyj A0276)
【CateGory Index】: TP311.13;G434
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