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Моделирование и анализ данных

Издатель: Московский государственный психолого-педагогический университет

ISSN (печатная версия): 2219-3758

ISSN (online): 2311-9454

DOI: https://doi.org/10.17759/mda

Лицензия: CC BY-NC 4.0

Издается с 2011 года

Периодичность: 4 номера в год

Язык журнала: русский

Доступ к электронным архивам: открытый

 

Probabilistic artifact filtration in adaptive testing 733

Куравский Л.С., доктор технических наук, декан факультета информационных технологий, Московский государственный психолого-педагогический университет, Москва, Россия, l.s.kuravsky@gmail.com
Юрьев Г.А., кандидат физико-математических наук, зам. декана, доцент, факультет информационных технологий, ФГБОУ ВО МГППУ, Москва, Россия, g.a.yuryev@gmail.com

Аннотация

Computerized testing is widely used for diagnostics and estimation of professional skills including CM education quality control. Both quality of testing and reliability of its results depend on a selected test technology that was a scientific research object during last years. Numerous problems following applications of tra¬ditional testing techniques inspired creation of the adaptive testing technology under consideration, which is based on application of trained structures in the form of continuous-time Markov models. Its peculiarities, in particular, are revealing and using test solution capability changes in quantitative evaluation of their time-domain dynamics as well as taking into account timetable of testing process. The approach suggested has certain advantages over the testing techniques, which were used before, owing to its greater information capability and acceleration of a test procedure. The main subject under consideration is elimination of artifacts conditioned by certain forms of illegal purposeful interference in testing procedure. It is carried out on the basis of comparing observed and expected subject responses with the aid of the Kalman filter adapted to the peculiarities of the problem in question.

Ключевые слова: Adaptive testing, Markov models, Kalman filter

Рубрика: Научная жизнь

Тип: научная статья

Ссылка для цитирования

Фрагмент статьи

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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