It is essential to track the progress of learners and identify problems that arise in learning programmes. This becomes more difficult for MOOCs delivered asynchronously with large numbers of students. Course designers and moderators need to utilize user activity data to track and analyse the learners’ behaviour and progress to identify any possible issues or bottlenecks. Obtaining this data can be difficult due to the number of students. Due to the asynchronous nature of the courses, it becomes difficult to get direct feedback from the learner population. Modern learning management systems have in-built tools and features that automatically track learners’ interactions with the course generating millions of data samples.

open.uom.lk is an online learning platform with courses in information technology and project management that was launched in early 2022 and currently has over 300,000 registered users. open.uom.lk is built on Moodle, which is an open-source course management system. Moodle has a collection of useful features to track user interactions and activities. It automatically generates reports on each user and each lesson/module. This paper outlines the methods by which these records and reports can be utilized to measure the course progression of individual students as well as track the behaviour of an entire cohort.

This allows teachers, course creators, and researchers to get information on the students' behaviour and course participation with minimal impact on the students. The academic and research team behind open.uom.lk uses these reports as analysis tools to identify lessons in modules in which a significant proportion of students have trouble with allowing issues to be addressed and the course to be amended. Additionally, when conducting research, these reports can be used to track the change in the student’s behaviour to various prompts and changes in the course. This data was also used to develop predictive models to forecast course completions.

open.uom.lk consists of lectures that are delivered online and quizzes that must be completed sequentially. A lesson can only be accessed if the previous lesson is completed. For courses that do not have a clear sequential structure of quizzes and submissions, tracking participation using data reports might be complicated. When creating a platform or course on Moodle, administrators and content creators need to consider if and how they want to track student performance and utilize the data tracked by Moodle to improve the course and understand learner behaviour. This paper outlines methods that use activity logs from the learning management system to track students' progress, identify bottlenecks, and measure the impact of corrective measures.

Keywords: MOOCs, Technology, data analysis, learner completion rate.