Mining Educational Data for Academic Accreditation: Aligning Assessment with Outcomes

Author First name, Last name, Institution

Mohammed Hussain, Zayed University
Mohamed Al-Mourad, Zayed University
Sujith Mathew, Zayed University
Abdullah Hussein, University of Sharjah

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

10.1007/s40171-016-0143-3

ISSN

0972-2696

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

85011562555

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