The issue of educational evaluation has long been a research hotspot. Using big data analysis method to conduct educational evaluation can improve the pertinence and effectiveness of education. Conventional Apriori algorithm has certain limitations in the application of educational evaluation. This paper introduces an improved Apriori-Gen algorithm and describes its application in evaluation of actual effectiveness of ideological and political course of colleges and universities. Through conducting correlation analysis of network questionnaire data, the study requirements of college students can be acquired, so as to improve the teaching effectiveness of ideological and political course. Results show that it is effective to apply the proposed study method in educational evaluation.
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Chen-lei et al. (2017) studied this question.
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