Enhancing Quality Assurance Mechanism through Data Analysis Approach

Abstract

Quality assurance is a holistic approach utilized in higher education
institutions which covers all the elements of educational processes. It is
aimed at providing better services to students and other stakeholders
ensuring that these services meet certain quality standards. This study
sought to develop an enhanced quality assurance mechanism intended
to expedite the process of a state university’s leveling by developing
an information system that incorporated the useful functions of
data consolidation and clustering and supported by data analytics
technologies. The study utilized the descriptive mixed methods research
design and included fifteen (15) participants who are involved in the
operation of the leveling instrument tool for the State Universities and
Colleges (SUCs). Relevant data were gathered using questionnaires
and through observations and interviews. The developed SUCs
Leveling tool has a high level of validity as assessed by the information
technology experts. The overall results of the participants’ evaluation,
the enhanced SUC Leveling Tool for SUCs were found to be compliant to
a very great extent with the quality standard characteristics defined by
ISO/IEC 9126-1 in terms of functionality, reliability, usability, efficiency,
maintainability and portability. The developed system has the ability
to extract knowledge hidden in complex and varied sources of data
and visualize them in human-readable form. The data mining and
analytics tool is freely available for academic use and uses the data
sets generated by the developed system as its input.