Title :
Use data warehouse and data mining to predict student academic performance in schools: A case study (perspective application and benefits)
Author :
Kurniawan, Yusuf ; Halim, Erwin
Author_Institution :
Sch. of Inf. Syst., Bina Nusantara Univ., Jakarta, Indonesia
Abstract :
The real facts in the education institute is the significant growth of the educational data. Basically the main goal of this paper is to propose a model that can be applied in data warehouse and data mining techniques to predict student performance (academic) in schools. Data mining techniques was used to extract the essential information from the data warehouse and to explore the relationships between variables stored in the data warehouse. In this study we will discuss how data mining and data warehouse model can help the low achiever students, evaluate the course or module suitability, and tailor the interventions to increase student academic performance in schools.
Keywords :
data mining; data warehouses; educational administrative data processing; educational courses; educational institutions; information retrieval; course suitability; data mining techniques; data warehouse model; data warehouse techniques; education institute; educational data; information extraction; module suitability; schools; student academic performance prediction; Data mining; Data models; Data warehouses; Databases; Decision making; Educational institutions; data mining; data warehouse; student performance;
Conference_Titel :
Teaching, Assessment and Learning for Engineering (TALE), 2013 IEEE International Conference on
Conference_Location :
Bali
DOI :
10.1109/TALE.2013.6654408