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.
Learning Analytics (LA) is evolving learning into a new era of analyzing student’s participation and engagement in order to gain some insights. The implementation of LA in a university helps the administration and faculty associates to observe the progress of the students alongside their rate of success. The purpose of this study is to develop a student’s engagement model for holistic involvement in the Learning Management System (LMS). The model was developed from an initial model that was derived from the review of literature and existing model of engagement in LMS. The data were collected from the online learning management system of one public University in Malaysia. From the data analysis, it was found that the strong engagement and interaction between the students, lecturers and the content in LMS, led to boost up the usage of the LMS as long as the student participation in the learning environment is accepted, which in return prepared the students to be evaluated anytime. The model that will be developed from this study can help increase the interaction and engagement between lecturers and students in LMS. Unlike the engagement of students in higher education LMS, which has been discussed already in the literature, this research integrated the role of trace data in shaping the learning environment communication and participation of the users.
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