Faculty of engineering students´ success analysis with clustering methods

Author

Saygili, A. ; Albayrak, Sahin

Author_Institution

Bilgisayar Muhendisligi Bolumu, Namik Kemal Univ., Tekirdağ, Turkey

fYear

2013

fDate

24-26 April 2013

Firstpage

1

Lastpage

4

Abstract

In this study, data clustering analysis for the student of faculty of engineering carried out. Cluster analysis, using the different characteristics or similar properties of objects in the data set, aims at creating in the same cluster homogeneous and between different clusters heterogeneous groups. This is the process of analyzing students´ demographic data, and settlement in University Entrance Exam scores success percentages weighted grade point average information gained will be used. In addition, examining the general characteristics of the clusters formed and the regions and school types of the students have interpreted. Hard and fuzzy clustering algorithms are used in study and their performances are compared. Outlier detection was performed for the clusters with Box-Plot analysis which used as a tool to measure the success of the methods in the study.

Keywords

educational institutions; engineering education; pattern clustering; box-plot analysis; clustering algorithms; data clustering analysis; engineering students faculty success analysis; outlier detection; student demographic data; university entrance exam scores; Algorithm design and analysis; Clustering algorithms; Data mining; Educational institutions; Engineering students; Indexes; Knowledge discovery; Clustering Analysis; Fuzzy C-Means; K-Means; Student Datas;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2013 21st

Conference_Location

Haspolat

Print_ISBN

978-1-4673-5562-9

Electronic_ISBN

978-1-4673-5561-2

Type

conf

DOI

10.1109/SIU.2013.6531253

Filename

6531253