Jing Geng1,*, Huali Yang2, Shengze Hu3
Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1311-1324, 2023, DOI:10.32604/iasc.2023.038481
Abstract Educational data mining based on student cognitive diagnosis analysis can provide an important decision basis for personalized learning tutoring of students, which has attracted extensive attention from scholars at home and abroad and has made a series of important research progress. To this end, we propose a noise-filtering enhanced deep cognitive diagnosis method to improve the fitting ability of traditional models and obtain students’ skill mastery status by mining the interaction between students and problems nonlinearly through neural networks. First, modeling complex interactions between students and problems with multidimensional features based on cognitive processing theory can enhance the interpretability of… More >
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