Open Access

ARTICLE

Developing Engagement in the Learning Management System Supported by Learning Analytics

Suraya Hamid¹, Shahrul Nizam Ismail¹, Muzaffar Hamzah^2,*, Asad W. Malik³

1 Department of Information System, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia
2 Faculty of Computing and Informatics, Universiti Malaysia Sabah, Sabah, Malaysia
3 Department of Computing, School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, Pakistan

* Corresponding Author: Muzaffar Hamzah. Email:

(This article belongs to the Special Issue: Application of the Information Technology During the Complex Pandemic Times Especially in the Education Sector)

Computer Systems Science and Engineering 2022, 42(1), 335-350. https://doi.org/10.32604/csse.2022.021927

Received 19 July 2021; Accepted 20 August 2021; Issue published 02 December 2021

Abstract

Learning analytics is an emerging technique of analysing student participation and engagement. The recent COVID-19 pandemic has significantly increased the role of learning management systems (LMSs). LMSs previously only complemented face-to-face teaching, something which has not been possible between 2019 to 2020. To date, the existing body of literature on LMSs has not analysed learning in the context of the pandemic, where an LMS serves as the only interface between students and instructors. Consequently, productive results will remain elusive if the key factors that contribute towards engaging students in learning are not first identified. Therefore, this study aimed to perform an extensive literature review with which to design and develop a student engagement model for holistic involvement in an LMS. The required data was collected from an LMS that is currently utilised by a local Malaysian university. The model was validated by a panel of experts as well as discussions with students. It is our hope that the result of this study will help other institutions of higher learning determine factors of low engagement in their respective LMSs.

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