2017
DOI: 10.17759/exppsy.2017100303
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A new approach to computerized adaptive testing

Abstract: A new approach to computerized adaptive testing is presented on the basis of discrete-state discrete-time Markov processes. This approach is based on an extension of the G. Rasch model used in the Item Response Theory (IRT) and has decisive advantages over the adaptive IRT testing. This approach has a number of competitive advantages: takes into account all the observed history of performing test items that includes the distribution of successful and unsuccessful item solutions; incorporates time spent on perf… Show more

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Cited by 18 publications
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“…Probabilistic models represented by Markov random processes with discrete states and continuous time [6,[18][19][20][21][22][23][24][25]32] for each pattern cluster are created using the identification procedure to represent probabilistic dynamics for each operator skill class to forecast probabilistic class behavior. This step is implemented in two ways: via distribution of probabilities of being in model states and via dynamics of mathematical expectations for each independent parameter determined with the aid of the Principal Components Analysis (correspondingly, these parameters are considered approximately as independent ones).…”
Section: Basic Approach: Analysis Of Activity Parameters Represented mentioning
confidence: 99%
“…Probabilistic models represented by Markov random processes with discrete states and continuous time [6,[18][19][20][21][22][23][24][25]32] for each pattern cluster are created using the identification procedure to represent probabilistic dynamics for each operator skill class to forecast probabilistic class behavior. This step is implemented in two ways: via distribution of probabilities of being in model states and via dynamics of mathematical expectations for each independent parameter determined with the aid of the Principal Components Analysis (correspondingly, these parameters are considered approximately as independent ones).…”
Section: Basic Approach: Analysis Of Activity Parameters Represented mentioning
confidence: 99%