This study develops a process that helps admission committees of higher education institutions select interested and qualified students. This enables institutions to maintain their financial viability by reaching the quota given by the Education Administration of Taiwan. We aimed to predict the decision-making behavior of students in terms of enrollment. A logistic regression analysis was conducted on publicly and inexpensively accessible data; the selection criteria of the model are based on metrics from a confusion matrix comprising predicted and observed data. The results indicate a matching rate of close to 80% between the training data of a target university from 2018 to 2020 and the testing data from 2021. This system outputs a probability that the student will enroll and thus helps admission committees more effectively select students.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.