Understanding Topic Mastery with Bayesian Networks

2012-03-28 17:50:12 GMT

Jace Kohlmeier is the scientist studying our statistics to figure out how Khan Academy users learn best.

He’s working to answer questions like:
  • What are the underlying concepts that relate mastery of our hundreds of exercises to each other?
  • Can we predict the best ordering of topic for a user to minimize time spent and maximize success?
  • What instructional interventions can an intelligent learning system make to best aid the user?
To learn about the software behind answering these questions, check out Jace’s new post about building Bayesian networks in Python for Khan Academy.