Abstract:
Financial aid allocation is one of the keys to the success of admission management in
universities and institutes. The financial aid policy plays an important role to attract
prospective applicants and enhance graduation quality. Therefore, a decision making on
financial aid allocation is quite critical and complicated in order to reach administrators’
objectives. This study is proposed to help administrators make rational decisions on
financial aid allocation more easily and effectively. Analytic network process and casebased
reasoning are the two primary methods used to evaluate the characteristics of
applicants and recommend the number of fellowships offered to them. In addition, a data
visualization function is provided in order to view and understand historical admission data
in meaningful ways, in which the method of drilling down from stacked column charts is
applied. Using those methods, the system of this study can support to improve the
administrators’ decision making on financial aid allocation. The achievements of the study
have contributed to decision support technology a framework for recommendation
systems, especially for educational management areas.
