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LM101-037: How to Build a Smart Computerized Adaptive Testing Machine using Item Response Theory
LM101-037: How to Build a Smart Computerized Adaptive Testing Machine using Item Response Theory
ratings:
Length:
35 minutes
Released:
Oct 12, 2015
Format:
Podcast episode
Description
In this episode, we discuss the problem of how to build a smart computerized adaptive testing machine using Item Response Theory (IRT). Suppose that you are teaching a student a particular target set of knowledge. Examples of such situations obviously occur in nursery school, elementary school, junior high school, high school, and college. However, such situations also occur in industry when top professionals in a particular field attend an advanced training seminar. All of these situations would benefit from a smart adaptive assessment machine which attempts to estimate a student’s knowledge in real-time. Such a machine could then use that information to optimize the choice and order of questions to be presented to the student in order to develop a customized exam for efficiently assessing the student’s knowledge level and possibly guiding instructional strategies. Both tutorial notes and advanced implementational notes can be found in the show notes at: www.learningmachines101.com .
Released:
Oct 12, 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