<![CDATA[Learning Management Systems (LMS) are extensively utilized to enhance teaching and learning in higher education institutions. These platforms provide invaluable insights into users' usage data and behavior within the online environment. Therefore, evaluating users' activity on these platforms is essential to maximize their effectiveness. This study aims to evaluate usage reports and engagement patterns and analyze online student learning activity using Moodle's tracking features. To achieve this, statistical and visualization techniques were employed to analyze student data from a year-long module delivered in a blended mode during the first semester at a South African university. The study utilized LMS log data to evaluate students' and instructors' usage patterns and engagement levels on the online platform, focusing on module-related activities. The data mining analysis revealed that LMS usage was significantly higher when students were on campus during the first semester and relatively lower when off-campus or in residence. In addition, no significant differences were observed in the type of LMS tools used or module activities across the eight months of the first semester. In conclusion, this data-driven approach and its findings underscore the importance of monitoring LMS activity.]]>
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