Framework for Performance Measurement of Public and Private Sector Higher Education Institutions in Pakistan using Machine Learning Algorithms


Authors : Muhammad Zulqarnain Siddiqui, Dr. Sellappan Palaniappan.

Volume/Issue : Volume 4 - 2019, Issue 2 - February


Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/pamjzn

Thomson Reuters ResearcherID : https://goo.gl/KTXLC3


Abstract : This study proposes the mechanism to collect real time data relating to education sector into a centralize repository and then to process specific portion of collected data using machine learning algorithms to compare performance of public and private sector higher education systems in Pakistan. Data of selected batch of students from colleges and universities are interlinked through a central repository that organizes and processes data to monitor the overall performance in terms of student retention gives trends of admissions and drop outs. A framework to that will facilitate the stakeholders including Government, Students and institutions to overview the progress at any level and can be sliced to any institution as well.

Keywords : Machine Learning, Repository, Distributed Systems, Data Sharing, Algorithms.

This study proposes the mechanism to collect real time data relating to education sector into a centralize repository and then to process specific portion of collected data using machine learning algorithms to compare performance of public and private sector higher education systems in Pakistan. Data of selected batch of students from colleges and universities are interlinked through a central repository that organizes and processes data to monitor the overall performance in terms of student retention gives trends of admissions and drop outs. A framework to that will facilitate the stakeholders including Government, Students and institutions to overview the progress at any level and can be sliced to any institution as well.

Keywords : Machine Learning, Repository, Distributed Systems, Data Sharing, Algorithms.

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