LM101-037: How to Build a Smart Computerized Adaptive Testing Machine using Item Response Theory
Learning Machines 101 - A podcast by Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
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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 .
