LM101-046: How to Optimize Student Learning using Recurrent Neural Networks (Educational Technology)
Learning Machines 101 - Un pódcast de Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
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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
