CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODSJournal: Problems of Education in the 21st Century (Vol.77, No. 3)
Publication Date: 2019-06-21
Authors : Citra Kurniawan; Punaji Setyosari; Waras Kamdi; Saida Ulfa;
Page : 349-363
Keywords : self-efficacy; visual-verbal preferences; data mining;
The purpose of this research was to build a classification model and to measure the correlation of self-efficacy with visual-verbal preferences using data mining methods. This research used the J48 classifier and linear projection method as an approach to see patterns of data distribution between self-efficacy and visual-verbal preferences. The measurement of the correlation of engineering students' self-efficacy with visual-verbal preferences using the data mining method approach gets the result that self-efficacy does not correlate with visual-verbal preferences. However, engineering students' self-efficacy influences the achievement of initial learning outcomes. Visual-verbal preference is more influenced by students' interest in images so it can be concluded that self-efficacy affects the initial results of learning but does not have a correlation with visual-verbal preferences. The results of the decision tree provide the results that are easily understood and present a correlation between self-efficacy and visual-verbal preferences in a visual form.
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Last modified: 2019-06-25 15:39:22