Mining survey data on university students to determine trends in the selection of majors

Abstract

The main objective of higher education institutions is to provide quality education to their students. One way to achieve the highest level of quality in a higher education system is to discover knowledge for predictions regarding enrollment of students on a particular course, alienation of traditional majors based on students' performance and so on. This knowledge is hidden in the educational data set and it is extractable through data mining techniques. The present paper is designed to justify the capabilities of data mining techniques in the context of higher education by offering a data mining model for the higher education system at Sebha University. In this research, association rules are used to evaluate students' performance by applying the apriori algorithm on survey data. In this task we extract knowledge that describes students' performance, which helps in identifying earlier trends in the choices of major and in helping new students to select their major.