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http://dx.doi.org/10.5392/JKCA.2022.22.03.105

An Analysis for the Student's Needs of non-face-to-face based Software Lecture in General Education using Text Mining  

Jeong, Hwa-Young (경희대학교 후마니타스칼리지)
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Abstract
Multiple-choice survey types have been mainly performed to analyze students' needs for online classes. However, in order to analyze the exact needs of students, unstructured data analysis by answer for essay question is required. Big data is applied in various fields because it is possible to analyze unstructured data. This study aims to investigate and analyze what students want subjects or topics for software lecture in general education that process on non-face-to-face online teaching methods. As for the experimental method, keyword analysis and association analysis of big data were performed with unstructured data by giving a subjective questionnaire to students. By the result, we are able to know the keyword what the students want for software lecture, so it will be an important data for planning and designing software lecture of liberal arts in the future as students can grasp the topics they want to learn.
Keywords
Big Data; Text Mining; Student's Needs; Software Lecture; Online Learning;
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Times Cited By KSCI : 4  (Citation Analysis)
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