@article{darcan2012student,
  title = {Student Profiling on Academic Performance Using Cluster Analysis},
  author = {Osman N. Darcan and Bertan Y. Badur},
  year = 2012,
  url = {https://ibimapublishing.com/articles/JELHE/2012/622480/},
  journal = {Journal of e-Learning and Higher Education},
  volume = (2012),
  pages = 8,
  doi = 10.5171/2012.622480,
  abstract = {This study is carried out in Management Information System (MIS) department which accepts students from general and vocational high schools with widely varying range of educational backgrounds. As an emerging interdisciplinary field, MIS education demands both technical and managerial skills from its students. However, students with different backgrounds have to pursue the same diversified set of courses. The aim of this study is to investigate students’ segments and profiles based on the various dimensions of academic abilities they possess, by performing cluster analysis. The data set consists of the student official grade for the required courses. First, dimensionality of the course grades is reduced to a few independent abilities by performing factor analysis. The summed scales representing the independent factors are then used in the cluster analysis to obtain student segments. Finally, variation of the student background measured by high school type is profiled for each segment. The students from general high schools have been more successful in MIS education compared to students from vocational schools where only the basic knowledge on management or computer skills is offered. The results of this analysis are also utilized in shaping various macro and micro level strategies in our MIS department.},
  keywords = {Educational data mining, factor analysis, cluster analysis},
  note = Article ID: 622480
}