CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS Cover Image

CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS
CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS

Author(s): Citra Kurniawan, Punaji Setyosari, Waras Kamdi, Saida Ulfa
Subject(s): Education, Higher Education
Published by: Scientia Socialis, UAB
Keywords: self-efficacy; visual-verbal preferences;, data mining;

Summary/Abstract: 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.

  • Issue Year: 77/2019
  • Issue No: 3
  • Page Range: 349-363
  • Page Count: 15
  • Language: English
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