27 min listen
LM101-046: How to Optimize Student Learning using Recurrent Neural Networks (Educational Technology)
LM101-046: How to Optimize Student Learning using Recurrent Neural Networks (Educational Technology)
ratings:
Length:
23 minutes
Released:
Feb 23, 2016
Format:
Podcast episode
Description
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
www.learningmachines101.com and follow us on Twitter at: @lm101talk
Released:
Feb 23, 2016
Format:
Podcast episode
Titles in the series (85)
LM101-022: How to Learn to Solve Large Constraint Satisfaction Problems: In this episode we discuss how to learn to solve constraint satisfaction inference problems. by Learning Machines 101