The Assessment of Students Self-Learning Styles through Learning Analytics in the Implementation of Mooc Manhaj Qirā’āt

Abstract

This study aims to look into student self-learning styles in learning Qirā’āt through Massive
Open Online Course (MOOC) using learning analytics. This study conducted to explore online
learning trends in MOOCs as the real-time data from learning analytics was evaluated.
Respondents of this study included 296 participants that come from a variety of fields and
backgrounds who had registered for the Qirā’āt MOOC. Findings show that there consist
various types of student self-learning styles based on four trends in a learning activity that have
groups of active students, observers, lurkers, and inactive students. Meanwhile, active students
are divided into two categories those who have completed the course and those who have not
yet completed the course. This study is salient for students and educators to gain a better
understanding of student learning activity trends. Educators can assess the performance of their
students in understanding a topic presented. In addition, the information obtained from the data
analysis process is used to determine the appropriate method that needs to be used in the
teaching process as it also can identify at-risk students such as failure or dropout.