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http://dx.doi.org/10.22156/CS4SMB.2022.12.03.252

Clustering Analysis of Science and Engineering College Students' understanding on Probability and Statistics  

Yoo, Yongseok (Department of Electronics Engineering, Incheon National University)
Publication Information
Journal of Convergence for Information Technology / v.12, no.3, 2022 , pp. 252-258 More about this Journal
Abstract
In this study, we propose a method for analyzing students' understanding of probability and statistics in small lectures at universities. A computer-based test for probability and statistics was performed on 95 science and engineering college students. After dividing the students' responses into 7 clusters using the Robust PCA and the Gaussian mixture model, the achievement of each subject was analyzed for each cluster. High-ranking clusters generally showed high achievement on most topics except for statistical estimation, and low-achieving clusters showed strengths and weaknesses on different topics. Compared to the widely used PCA-based dimension reduction followed by clustering analysis, the proposed method showed each group's characteristics more clearly. The characteristics of each cluster can be used to develop an individualized learning strategy.
Keywords
College students; Probability and statistics; Clustering analysis; Robust PCA; Learning strategy;
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Times Cited By KSCI : 3  (Citation Analysis)
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