Development of Predictive Models for Quality Assurance of Local Higher Education Institutions

Abstract

Quality Assurance in local higher education institutions (LHEIs) to determine its performance based on set standards is necessary as to ensure that quality education is enforced holistically. However, due to the myriad of services that the institution is providing, this task could often be overlooked. However, with the availability of Information Technology systems, and Mathematics, the regular evaluation of the LHEIs can be managed and monitored consistently. This paper discusses the development of a basic framework to allow LHEIs monitor their performance across ten (10) areas to determine quality assurance of services in an institution. This study combines the application of Data Mining Models as well as Statistical Methods to develop a Predictive Model to determine the quality assurance levels of a local higher education institution. Moreover, it provides a model in which the institution can look into in determining whether it provides quality service to its students. The developed model was tested for accuracy using existing historical data.