Моделирование и анализ данных
2012. Том 2. № 1. С. 70–81
ISSN: 2219-3758 / 2311-9454 (online)
Probabilistic artifact filtration in adaptive testing
Ключевые слова: Adaptive testing, Markov models, Kalman filter
Рубрика издания: Научная жизнь
Тип материала: научная статья
Для цитаты: Куравский Л.С., Юрьев Г.А. Probabilistic artifact filtration in adaptive testing // Моделирование и анализ данных. 2012. Том 2. № 1. С. 70–81.
Estimation of probabilities for various skill levels is performed basing on test results obtained with the aid of parametric mathematical models described by Markov random processes with discrete states and continuous or discrete time. Further discussion applies to the models with continuous time only. Directly observable quantity is the difficulty of task being executed, measured in logit. The valid range of this quantity is divided into several intervals, each of them is considered as a separate state xi, i=0,1,,n, in which a testee may be with certain probability, transferring from one state to another according to certain rules. The length of these intervals determines the discrimination of estimates obtained in the testing process. In turn, the number of states is determined by the desired discrimination of estimates and available sample size.
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