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

Journal Title: Problems of Education in the 21st Century - Year 2019, Vol 77, Issue 3

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.

Authors and Affiliations

Citra Kurniawan, Punaji Setyosari, Waras Kamdi, Saida Ulfa

Keywords

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  • EP ID EP590726
  • DOI 10.33225/pec/19.77.349
  • Views 133
  • Downloads 0

How To Cite

Citra Kurniawan, Punaji Setyosari, Waras Kamdi, Saida Ulfa (2019). CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS. Problems of Education in the 21st Century, 77(3), 349-363. https://europub.co.uk/articles/-A-590726