Open Academics Analytics Initiative talk. The goal of this study was the creation of an early alert system to predict at risk students in the initial weeks of a course, and then to deploy intervention strategies to enhance student chances of success. Used SAT scores, demographics, Sakai log data and Sakai grade book as indicators.
Ran various pilots over 70+ courses over 2 semesters. They also wanted to find what intervention strategies were most effective. The model appears to be portable and scalable. once identified, needed to make an intervention with students thought to be at risk. The test included a control group who received no intervention, one group received an academic alert and the other group received similar messages and access to online resources. No real difference between the 2 groups who received contact of some sort. In the intervention groups, there was also a higher withdrawal rate which suggested that students made aware that they were at risk could use that information to make an informed decision.
- Early feedback is important
- despite poor grades, some students do not recognise that they are at risk
- Typically, students in large groups do not receive as much attention as students in small groups, therefore this system was helpful in identifying students needing help