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Establishment of data mining-based public education administrative work automation system and student activity analysis

Seung-Ryeol Joo, Jong-Chan Kim, Sung-Jun Kim

Abstract


There are several important factors in public education in Korea. Among them, it is very important to manage time to improve teachers’ educational capabilities and students’ grades. However, in Korea’s public education, the existing school administrative work system has to deal with miscellaneous procedures, hindering teachers from guiding students. As a result, students also give low trust in public education. This study introduces procedures for an integrated public education data management system to automate administrative tasks of teachers and increase students’ educational capabilities. By applying the Data Mining Problem Solving Methodology (ICAIS), we identified five stages in which data is processed. In addition, the activities required for students to go to college were processed with text mining techniques (from a simple word cloud to the construction of a neural network algorithm classification model), allowing students to check their grades themselves. Through this study, it reduces teachers’ chores, concentrates student education, and provides students with the educational purpose of a self-directed method that determines their career path.


Keywords


data mining; text mining; self-directed learning; administrative work system automation

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DOI: https://doi.org/10.32629/jai.v6i3.996

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Copyright (c) 2023 Seung-Ryeol Joo, Jong-Chan Kim, Sung-Jun Kim

License URL: https://creativecommons.org/licenses/by-nc/4.0/