Dataset of student level prediction in UAE

Shatha Ghareeb; Abir J. Hussain; Wasiq  Khan; Dhiya Al-Jumeily; Thar Baker; Rawaa  Al-Jumeily

doi:10.1016/j.dib.2021.106908

Dataset of student level prediction in UAE

Shatha Ghareeb, Abir J. Hussain, Wasiq Khan, Dhiya Al-Jumeily, Thar Baker, Rawaa Al-Jumeily

Department of Computing & Games

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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 di- verse educational backgrounds that might be useful for auto- mated student levelling, i.e., at which level the student needs to be entered when moved from a different school with different international curriculum.

Original language	English
Article number	106908
Journal	Data in Brief
Volume	35
DOIs	https://doi.org/10.1016/j.dib.2021.106908
Publication status	Published - 24 Feb 2021

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title = "Dataset of student level prediction in UAE",

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{\textquoteright} information and prepared to be used for pattern analysis and prediction of student grading based on di- verse educational backgrounds that might be useful for auto- mated student levelling, i.e., at which level the student needs to be entered when moved from a different school with different international curriculum.",

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AU - Hussain, Abir J.

AU - Khan, Wasiq

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AU - Baker, Thar

AU - Al-Jumeily, Rawaa

PY - 2021/2/24

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AB - 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 di- verse educational backgrounds that might be useful for auto- mated student levelling, i.e., at which level the student needs to be entered when moved from a different school with different international curriculum.

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M3 - Article

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VL - 35

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Dataset of student level prediction in UAE

Abstract

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