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A study on data analysis of student achievement under adult education through association rule algorithm

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  • Yuan Dong

Abstract

Students receiving adult education must complete academic tasks while balancing work and life, which may cause poor learning results. The student learning situation can be better comprehended by analysing student performance data. In order to realise the analysis of students' course performance under adult education, this paper designed an improved Apriori algorithm based on the Boolean matrix for the problem of low efficiency. Through the experiments on the webdocs and mushroom datasets, it was found that when Supmin = 0.1, the running time of the improved Apriori algorithm for the webdocs dataset was 1123 s, which was 20.64% shorter than the FPGrowth algorithm and 26.17% shorter than the Apriori algorithm. The running time for the Mushroom dataset was 27.38 s, which was 76.73% shorter than the Apriori algorithm and 55.31% shorter than the FPGrowth algorithm.

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  • Yuan Dong, 2025. "A study on data analysis of student achievement under adult education through association rule algorithm," International Journal of Data Science, Inderscience Enterprises Ltd, vol. 10(2), pages 195-209.
    • Handle: RePEc:ids:ijdsci:v:10:y:2025:i:2:p:195-209
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