Guideline for Academic Support of Student Career Path Using Mining Algorithm
Maleerat Sodanil, Saranlita Chotirat, Lap Poomhiran, Kanchana Viriyapant · 2019
In general, higher education is an important step in preparing a career for students in the future. Graduates should have qualifications that are recognized by both entrepreneurs and society. Therefore, every higher educational institution should make an effort to consider how to assist students' performance. This research aims to analyze the relationships between courses that are likely to produce a future career for students using the Apriori algorithm. The data used in the operation of the association rule was the student's grades from 25 main courses in the field of information technology, Department of Information Technology, Faculty of Science and Technology, Suan Sunandha Rajabhat University. This data was recorded between 2011 and 2019 and stored in the registration and graduate career system. The 14 association rules were determined from the operation by using the Weka 3.8.3 data mining software, this indicated that there were a few courses in which students could have future careers. Most importantly, the results can contribute to guidelines for the academic support of students' future career.