LM101-046: How to Optimize Student Learning using Recurrent Neural Networks (Educational Technology) - a podcast by Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

In this episode, we briefly review Item Response Theory and Bayesian Network Theory methods for the assessment and optimization of student learning and then describe a poster presented on the first day of the Neural Information Processing Systems conference in December 2015 in Montreal which describes a Recurrent Neural Network approach for the assessment and optimization of student learning called “Deep Knowledge Tracing”. For more details check out:

www.learningmachines101.com and follow us on Twitter at: @lm101talk

 

 

Further episodes of Learning Machines 101

Further podcasts by Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

Website of Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.