Dropout Situation of Business Computer Students, University of Phayao

Pratya Nuankaew

Abstract


This paper aims to study the problem of the dropout situation of students in the business computer program at the University of Phayao. It consists of three sub-goals: 1) identifying the factors, 2) studying the relationship of factors, and 3) testing the relationship model. Data collected 389 students from the Department of Business Computer at University of Phayao from the academic year 2012-2019.
The tools used in the research are statistical data analysis and machine learning. It consists of percentages, decision tree algorithms, cross-validation methods, and the confusion matrix performance. The results showed that the dropout rate of learners in business computer program tended to increase even though the number of new students decreased. In addition, it was found that factors affecting the dropout consisted of seven courses: 221110, 221120, 001103, 128221, 005171, 122130 and 128221.
The model obtained as a high performance level of prediction with accuracy is equal to 87.21%. Based on the research results, the researcher found that the academic results had a significant influence on dropout, which were mostly obvious with the students in their first academic year.

Keywords


student dropout prediction; educational data mining; learning model; student model

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Copyright (c) 2019 Pratya Nuankaew


International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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