Moodle Analytics Models

This walkthrough video provides an overview of main analytics models available in Moodle LMS (version 4.0.1):
- Upcoming activities due
- Courses at risk of not starting
- Students who have not accessed the course recently
- Students who have not accessed the course yet
- Students at risk of dropping out

Key takeaways from this: Moodle Analytics capabilities are well designed and implemented with the following advantages
- Explainability (why a course not analysable, how prediction made with indicator values)
- Actionable (send message, “Go-to-activity” link)
- Ability to provide feedback of the generated predictions
- Tracking model’s performance / effectiveness
- Model clarity and customizable
- Complete control of model training and deployment

However, it appears that the model training and deploying may consume a lot of server resources, and the model accuracy is not as high as expected (due to the algorithm used, and/or the amount and quality of data available). As a result, these capabilities are often overlooked and disabled altogether by system administrators.