31 min listen
LM101-038: How to Model Knowledge Skill Growth Over Time using Bayesian Nets
LM101-038: How to Model Knowledge Skill Growth Over Time using Bayesian Nets
ratings:
Length:
24 minutes
Released:
Oct 27, 2015
Format:
Podcast episode
Description
In this episode, we examine the problem of developing an advanced artificially intelligent technology which is capable of tracking knowledge growth in students in real-time, representing the knowledge state of a student a skill profile, and automatically defining the concept of a skill without human intervention! The approach can be viewed as a sophisticated state-of-the-art extension of the Item Response Theory approach to Computerized Adaptive Testing Educational Technology described in Episode 37. Both tutorial notes and advanced implementational notes can be found in the show notes at: www.learningmachines101.com.
Released:
Oct 27, 2015
Format:
Podcast episode
Titles in the series (85)
LM101-006: How to Interpret Turing Test Results: Episode Summary: In this episode, we briefly review the concept of the Turing Test for Artificial Intelligence (AI) which states that if a computer.s behavior is indistinguishable from that of the behavior of a thinking human being, by Learning Machines 101