Clustering of Management Information Systems’ Students Using Data Mining

Abstract:

In Turkey, students have to participate a nationwide entrance exam to study at a university. As a direct consequence of this, students from general and vocational high schools with widely varying range of educational backgrounds are admitted to our Management Information Systems (MIS) department. As an emerging interdisciplinary field, MIS demands both technical and managerial skills from its graduates. Therefore, our students with different backgrounds have to pursue the same diversified set of courses such as programming, managerial, quantitative as well as analysis and design. The aim of this study is to investigate the profiles of students in our department by performing cluster analysis on various dimensions of academic abilities. Student official grade data for the required courses are used in this study. First factor analysis is applied to the course grades in order to reduce the dimensionality to a few independent abilities. The summed scales representing the independent factors are then utilized in the cluster analysis to obtain student profiles. Characteristics of students in each cluster are examined to gain inside about how such attributes as educational background and high school types are distributed over each segment. The results of the analysis will be utilized to revise our MIS curriculum, to design elective tracks and guide students while they are selecting departmental electives more appropriately, and to intervene with the composition of student groups in course projects.