Mining Educational Data for Academic Accreditation: Aligning Assessment with Outcomes

Mohammed Hussain (), Mohamed Al-Mourad (), Sujith Mathew () and Abdullah Hussein ()
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Mohammed Hussain: Zayed University
Mohamed Al-Mourad: Zayed University
Sujith Mathew: Zayed University
Abdullah Hussein: University of Sharjah

Global Journal of Flexible Systems Management, 2017, vol. 18, issue 1, No 5, 60 pages

Abstract: Abstract Institutions in higher education generate terabytes of data that has great value to shape future of nations. This Big Data is in heterogeneous formats, very current, and in large volumes. We propose a framework to collect, scope and verify this large amount of data. The analysis of the data is used to evaluate the institution against a standard set by an accreditation body, for the purpose of the academic accreditation of higher education programs. Therefore, the framework reduces human involvement in accreditation. The paper provides the detailed design of the process of aligning assessment with student learning outcomes.

Keywords: Big Data; Higher education; Learning analytics; Educational data mining (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40171-016-0143-3

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