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Big data analytics framework for effective higher education Institutions

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dc.contributor.author Matto, George
dc.date.accessioned 2022-12-22T13:16:24Z
dc.date.available 2022-12-22T13:16:24Z
dc.date.issued 2022
dc.identifier.citation Matto, G., (2022). Big data analytics framework for effective higher education Institutions. Tanzania Journal of Engineering and Technology, 41(1), 10-18. en_US
dc.identifier.issn 2619-8789
dc.identifier.issn 1821-536X
dc.identifier.other https://doi.org/10.52339/tjet.vi.768
dc.identifier.uri http://repository.mocu.ac.tz/xmlui/handle/123456789/328
dc.description https://doi.org/10.52339/tjet.vi.768 en_US
dc.description.abstract There has been an increased dependency on Information and Communication Technologies (ICTs) in undertaking various activities in Higher Education Institutions (HEIs) ecosystems. Because of that, huge volumes of data have increasingly been generated. There have been, for instance, considerable amounts of data generated through electronic platforms involved in students’ admission and registration process, students’ academic records management, teaching and learning data, curriculum related data, and several other administrative data. Analysis of data generated from these platforms stands to give students, lecturers, HEIs Management, policy makers and implementers, and other stakeholder’s useful insights that would help in improving HEIs’ effectiveness. Unfortunately, literature has identified several challenges associated with existing big data analytics frameworks in HEIs. It was on this line that the present study, which was based on desk research, was carried out to propose an effective big data framework for analytics of such data. The proposed framework is composed of five stages; data collection, data pre-processing, data storage, data analytics, and data visualization. The stages were arranged systematically to address the identified challenges in the existing frameworks. Effective implementation of this framework will help HEIs to make a productive use of various data they generate. This will ultimately be beneficial to not only HEIs but also to aspired students, labor market, the government and the public at large. en_US
dc.language.iso en_US en_US
dc.publisher College of Engineering and Technology en_US
dc.relation.ispartofseries 41;1
dc.subject Higher Learning Institutions (HEIs) en_US
dc.subject ICTs en_US
dc.subject Big data en_US
dc.subject Analytical Framework en_US
dc.subject Learning Management System en_US
dc.subject Online Learning en_US
dc.title Big data analytics framework for effective higher education Institutions en_US
dc.title.alternative College of Engineering and Technolog en_US
dc.type Article en_US


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