An Analysis of Course Factor Correlation Causing Undergraduate Student Withdrawals Using the Apriori Algorithm and Data Mining Methods; Department of Civil Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang (KMITL) - Uthaiwattananon, Phubade (วารสารนวัตกรรมการศึกษาและการวิจัย, 2024)
This research employing a quantitative approach, aimed to investigate correlation between course variable factors and students’ status of being terminated of King Mongkut’s Institute of Technology Ladkrabang (KMITL) using Association Rules, Data Mining, and Apriori Algorithm. The sample were 90 Civil Engineering students of KMILT who were active from academic year 2007 to 2020. The research revealed that there was a significant factors of termination status within different groups of courses that the students enrolled. For 63.33% of first and second year students, failing (F) or obtaining low grades (D and D+) in fundamental science courses were consequently a cause of termination status. For 10% of third year students (a degree continuation of study from diploma certificate), failing or obtaining low grades in fundamental science were also a cause of termination status. For 26.67% of fourth year students, failing or obtaining low grades in specific engineering mandatory courses were consequently a cause of termination status.