Cloud-Based Institutional Quality Assurance Model for a Local Higher Education Institution Using Data Mining Techniques
DOI:
https://doi.org/10.69478/JITC2024v6n002a08Keywords:
Data-Driven Decision Making, Data Models, Data Mining, Institutional Quality AssuranceAbstract
This study presents a Cloud-Based Institutional Quality Assurance Model for Local Higher Education Institutions (LHEIs). It utilizes advanced data mining techniques and custom data models that enhance the monitoring, assessment, and improvement of quality assurance processes through the utilization of cloud computing infrastructure in a developed system that offers scalability, flexibility, and accessibility, empowering policymakers to make data-driven decisions and to efficiently analyze vast amounts of data collected from various sources and be guided by algorithms. The findings advance quality assurance methodologies and offer valuable insights for practitioners, policymakers, and researchers in higher education.
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Copyright (c) 2024 Sharmaine Justyne R. Maglapuz, Jenny Lyn V. Abamo
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
