Blended Learning Fellowship on Learning Analytics announced

The recent adoption of a campus framework for learning analytics provides an opportunity to explore one approach to evidence-based teaching. The Blended Learning Fellowship on Learning Analytics will continue to examine the emerging practice of learning analytics and how it can be integrated into courses by delving deeply into a learning analytics functional taxonomy. The outcomes of this fellowship will be an expansion of the Learning Analytics Functional Taxonomy (explored last spring by the Blended Learning Fellowship on Evidence-Based Teaching) to include local case studies and ideas for incorporating learning analytics approaches locally, across the various categories from the taxonomy. The fellows will also help design a curriculum for a learning analytics program that would support instructors as they incorporate learning analytics into their own courses. The taxonomy includes these learning analytics approaches:

  • Access to learning behavior
  • Evaluate social learning
  • Improve learning materials and tools
  • Individualize learning
  • Predict student performance
  • Visualize learning activities

Faculty and instructional staff who are interested in learning analytics or have experimented with learning analytics processes in their teaching are invited to apply for the program. Participants will receive a $500 stipend for their time, which includes 60-90 minutes prep time each week along with a weekly 90-minute face-to-face session.

Dates: Tuesdays | Feb. 5 – April 16
Time: 11:30am–1pm
Location: 302 Middleton Building, 1305 Linden Drive
Stipend: $500 | Lunch provided each week

Apply now