Improving Student Risk Predictions


Assessing the Impact of Learning Data Sources


Higher education students learning on computer

Does combining student activity data from multiple learning tools improve our ability to predict student achievement?

In partnership with University of Maryland Baltimore County and VitalSource, researchers from Blackboard used the IMS Caliper Analytics standard to combine student activity stream data from Blackboard Learn and VitalSource to see if it would improve predictions about student achievement.

The joint study describes the following major findings:

  1. Early activity in learning tools is a strong predictor of whether a student will pass a class
  2. Patterns of activity differ significantly between courses
  3. Learning activity data is a more powerful predictor of achievement than demographics and educational background
  4. Combining data from multiple learning tools (like Blackboard Learn and VitalSource) improves the accuracy of predictions about student achievement
  5. Students with high levels of activity in multiple learning tools can significantly increase their chances of successfully passing a class


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