Ust.edu.my (S.M.) Division of Computing, Middle East College, Know-how Oasis Muscat, P.B. No. 79, Al Rusayl 124, Oman; [email protected] School of Informatics and Applied Mathematics, University Malaysia Terengganu, Kuala Terengganu 21030, Malaysia; ku_sarker@yahoo Correspondence: [email protected] to.edu.my; Tel.: 968-9819-Citation: Hasan, R.; Palaniappan, S.; Mahmood, S.; Abbas, A.; Sarker, K.U. Dataset of Students’ Functionality Employing L-Cysteic acid (monohydrate) medchemexpress student Info Technique, Moodle and also the Mobile Application “eDify”. Data 2021, six, 110. https:// doi.org/10.3390/data6110110 Academic Editors: Leonardo Grilli, Carla Rampichini, Maria Cecilia Verri and Donatella Merlini Received: 10 August 2021 Accepted: 19 October 2021 Published: 22 OctoberAbstract: The information presented in this write-up comprise an educational dataset collected from the student data program (SIS), the finding out management technique (LMS) named Moodle, and video interactions from the mobile application named “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 L-Gulose Protocol characteristics in total, like the students’ academic info from SIS (which has 24 features), the students’ activities performed on Moodle within and outdoors the campus (comprising ten features), and the students’ video interactions collected from eDify (consisting of six capabilities). The dataset is useful for researchers who wish to explore students’ academic performance in on line learning environments, and will assistance them to model their educational datamining models. Moreover, it may serve as an input for predicting students’ academic efficiency inside the module for educational datamining and studying analytics. In addition, researchers are very encouraged to refer to the original papers for more facts. Dataset: https://zenodo.org/record/5591907 (accessed on 18 October 2021). Dataset License: CC-BY 4.0. Search phrases: educational datamining; understanding management system; prediction; student academic functionality; student information and facts system1. SummaryPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.Copyright: 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is definitely an open access short article distributed under the terms and conditions with the Creative Commons Attribution (CC BY) license (licenses/by/ four.0/).Greater educational institutions (HEIs) employ a variety of studying approaches primarily based on information and communications technology (ICT). These approaches involve different understanding environments to facilitate the teaching and mastering procedure with ease and dissemination of know-how to their learners. Moreover, these environments retain track from the customers and their interactions within these environments for auditing and recovery purposes. The logs can help stakeholders with beneficial understanding data, and when analyzed properly, can assist to provide a much better studying expertise to learners. Reports creating distinctive users/courses could be employed to evaluate the efficacy of the courses and also the progress on the learners. Insights can assist cater diverse learning styles, which helps to determine the complexity of courses, identifying specific components of your content that result in complications in understanding the ideas and gaining insights into the future performance of learners. Many HEIs use machine mastering (.
