Clustering scholarship programs using educational data mining techniques

Abstract

Major colleges and state universities assess students’ quality and set different rewards for the various level in order to stimulate students’ interest to study and participate in extracurricular activities. The main reward system that is used is the providing of financial incentives such as scholarship grants. In this paper, several data mining techniques such as clustering and time series analysis was integrated to discover and assess future outcomes and matters concerning scholarship offerings in Surigao State College of Technology (SSCT). The Student Financial Assistance Unit (SFAU) of SSCT holds all the records of scholarship grants and its grantees from June 2014 which was used as datasets. The study segmented every scholarship grants in SSCT to find patterns as to the scholarship grants and use it for the proliferation of data. It is suggested that the output of this study may be used as input and avenue for future researches using other data mining techniques.