Ghareeb, S, Hussain, A, Khan, W, Al-Jumeily, D, Baker, T and Al Jumeily, R (2021) Dataset of student level prediction in UAE. Data in Brief, 35. ISSN 2352-3409

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Abstract

A primary dataset is presented comprising student grading records and educational diversity information. The dataset is collected from two international schools, a British curriculum, and an American Curriculum schools based in Abu Dhabi, United Arab Emirates. Following the ethical approval from Liverpool John Moores University (19/CMS/001), the data is collected through gatekeepers. A permission letter was granted from the Ministry of Education and Knowledge in Abu Dhabi, UAE to provide access to the schools. The dataset is anonymised by eliminating sensitive and identifiable students' information and prepared to be used for pattern analysis and prediction of student grading based on diverse educational backgrounds that might be useful for automated student levelling, i.e., at which level the student needs to be entered when moved from a different school with different international curriculum.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence; Education; Levelling; School curriculum; Student grade prediction; Student tracking
Subjects:	L Education > L Education (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Computer Science & Mathematics
Publisher:	Elsevier
Related URLs:	https://www.ncbi.nlm.nih.gov/pubmed/33732825
Date Deposited:	21 Apr 2021 10:01
Last Modified:	04 Sep 2021 05:34
DOI or ID number:	10.1016/j.dib.2021.106908
URI:	https://researchonline.ljmu.ac.uk/id/eprint/14844

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