Dataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”

The data presented in this article comprise an educational dataset collected from the student information system (SIS), the learning management system (LMS) called Moodle, and video interactions from the mobile application called “eDify.” The dataset, from the higher educational institution (HEI) in...

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Autores principales:	Raza Hasan, Sellappan Palaniappan, Salman Mahmood, Ali Abbas, Kamal Uddin Sarker
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	educational datamining learning management system prediction student academic performance student information system Bibliography. Library science. Information resources Z
Acceso en línea:	https://doaj.org/article/b25b7d2ba3854daf9d51a3298fecef2b
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spelling	oai:doaj.org-article:b25b7d2ba3854daf9d51a3298fecef2b2021-11-25T17:19:49ZDataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”10.3390/data61101102306-5729https://doaj.org/article/b25b7d2ba3854daf9d51a3298fecef2b2021-10-01T00:00:00Zhttps://www.mdpi.com/2306-5729/6/11/110https://doaj.org/toc/2306-5729The data presented in this article comprise an educational dataset collected from the student information system (SIS), the learning management system (LMS) called Moodle, and video interactions from the mobile application called “eDify.” The dataset, from the higher educational institution (HEI) in Sultanate of Oman, comprises five modules of data from Spring 2017 to Spring 2021. The dataset consists of 326 student records with 40 features in total, including the students’ academic information from SIS (which has 24 features), the students’ activities performed on Moodle within and outside the campus (comprising 10 features), and the students’ video interactions collected from eDify (consisting of six features). The dataset is useful for researchers who want to explore students’ academic performance in online learning environments, and will help them to model their educational datamining models. Moreover, it can serve as an input for predicting students’ academic performance within the module for educational datamining and learning analytics. Furthermore, researchers are highly recommended to refer to the original papers for more details.Raza HasanSellappan PalaniappanSalman MahmoodAli AbbasKamal Uddin SarkerMDPI AGarticleeducational datamininglearning management systempredictionstudent academic performancestudent information systemBibliography. Library science. Information resourcesZENData, Vol 6, Iss 110, p 110 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	educational datamining learning management system prediction student academic performance student information system Bibliography. Library science. Information resources Z
spellingShingle	educational datamining learning management system prediction student academic performance student information system Bibliography. Library science. Information resources Z Raza Hasan Sellappan Palaniappan Salman Mahmood Ali Abbas Kamal Uddin Sarker Dataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”
description	The data presented in this article comprise an educational dataset collected from the student information system (SIS), the learning management system (LMS) called Moodle, and video interactions from the mobile application called “eDify.” The dataset, from the higher educational institution (HEI) in Sultanate of Oman, comprises five modules of data from Spring 2017 to Spring 2021. The dataset consists of 326 student records with 40 features in total, including the students’ academic information from SIS (which has 24 features), the students’ activities performed on Moodle within and outside the campus (comprising 10 features), and the students’ video interactions collected from eDify (consisting of six features). The dataset is useful for researchers who want to explore students’ academic performance in online learning environments, and will help them to model their educational datamining models. Moreover, it can serve as an input for predicting students’ academic performance within the module for educational datamining and learning analytics. Furthermore, researchers are highly recommended to refer to the original papers for more details.
format	article
author	Raza Hasan Sellappan Palaniappan Salman Mahmood Ali Abbas Kamal Uddin Sarker
author_facet	Raza Hasan Sellappan Palaniappan Salman Mahmood Ali Abbas Kamal Uddin Sarker
author_sort	Raza Hasan
title	Dataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”
title_short	Dataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”
title_full	Dataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”
title_fullStr	Dataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”
title_full_unstemmed	Dataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”
title_sort	dataset of students’ performance using student information system, moodle and the mobile application “edify”
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b25b7d2ba3854daf9d51a3298fecef2b
work_keys_str_mv	AT razahasan datasetofstudentsperformanceusingstudentinformationsystemmoodleandthemobileapplicationedify AT sellappanpalaniappan datasetofstudentsperformanceusingstudentinformationsystemmoodleandthemobileapplicationedify AT salmanmahmood datasetofstudentsperformanceusingstudentinformationsystemmoodleandthemobileapplicationedify AT aliabbas datasetofstudentsperformanceusingstudentinformationsystemmoodleandthemobileapplicationedify AT kamaluddinsarker datasetofstudentsperformanceusingstudentinformationsystemmoodleandthemobileapplicationedify
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Dataset of Students’ Performance Using Student Information System, Moodle and the Mobile Application “eDify”

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