If we could design a ‘fitbit’ for education, what would it look like? Join a panel of leading researchers and instructional designers to discuss what we know about student-facing learning analytics including current research, instructional design challenges, and where our current rate of innovation will likely lead in the next 5 years.
What evidence do we have that student-facing analytics work?
- Students earning a D or an F used Bb 40% less than their peers UMBC. “Predicating and Supporting Student Success“
- We do have to be careful with how we reveal data to students. We need to be careful with predictive vs prescriptive recommendations with data.
- Self-directed learning, the ability to self judge ones performance is a sign of maturity and life-long learning. Students need to have the data.
- ”Study finds alerts promote action at high rates – Students interact with LMS notifications at high rates…”
“Learning theory is what we need with analytics – not just counting clicks.” – John Fritz
- Dashboards provide a ladder for students on their way to success and ultimately graduation.
- Data democratization provides actionable information to the needs at the time of needs.
- A focus on training preparing faculty and other professionals is important to help students use analytics effectively.