Mining Educational Data for Academic Accreditation: Aligning Assessment with Outcomes
Document Type
Article
Source of Publication
Global Journal of Flexible Systems Management
Publication Date
3-1-2017
Abstract
© 2016, Global Institute of Flexible Systems Management. 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.
DOI Link
ISSN
Publisher
Global Institute of Flexible Systems Management
Volume
18
Issue
1
First Page
51
Last Page
60
Disciplines
Computer Sciences
Keywords
Big Data, Educational data mining, Higher education, Learning analytics
Scopus ID
Recommended Citation
Hussain, Mohammed; Al-Mourad, Mohamed; Mathew, Sujith; and Hussein, Abdullah, "Mining Educational Data for Academic Accreditation: Aligning Assessment with Outcomes" (2017). All Works. 2400.
https://zuscholars.zu.ac.ae/works/2400
Indexed in Scopus
yes
Open Access
no