Title :
The Estimation of Students´ Academic Success by Data Mining Methods
Author :
Goker, Hanife ; Bulbul, Halil I. ; Irmak, Erdal
Author_Institution :
Inst. of Informatic, Gazi Univ., Ankara, Turkey
Abstract :
Data mining is a process of getting out useful information from data stacks. One of the most common application areas is to use classification of algorithms that estimate the future events by past experiences. In this context, in order to predict future events, a data warehouse is created by using the background of students which includes demographic, personal, school, and course information of students. On this data warehouse by using classification algorithms, new applications which can make inferences for the future could be developed. Aims of this study are to create student data warehouse which can be used data mining algorithms, to improve an early warning system that may estimate students´ the future academic successes for students and also for their families and to find out primary factors affecting their academic success.
Keywords :
data mining; data warehouses; educational administrative data processing; educational courses; inference mechanisms; pattern classification; algorithm classification; course information; data mining methods; data stacks; demographic information; early warning system improvement; future event prediction; personal information; school information; student background; student data warehouse; students academic success estimation; Classification algorithms; Data mining; Data preprocessing; Data warehouses; Databases; Educational institutions; classification; data mining; data warehouse; feature selection; naive bayes; weka;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location :
Miami, FL
DOI :
10.1109/ICMLA.2013.173