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LM101-037: How to Build a Smart Computerized Adaptive Testing Machine using Item Response Theory

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Manage episode 230297565 series 2497400
Content provided by Richard M. Golden, M.S.E.E., and B.S.E.E.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Richard M. Golden, M.S.E.E., and B.S.E.E. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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 .

  continue reading

85 episodes

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iconShare
 
Manage episode 230297565 series 2497400
Content provided by Richard M. Golden, M.S.E.E., and B.S.E.E.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Richard M. Golden, M.S.E.E., and B.S.E.E. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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 .

  continue reading

85 episodes

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