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Mathematical Aspects of the Concept of Adaptive Training Device 941
Kuravsky L.S.
Doctor of Engineering, Dean of the Computer Science Faculty , Moscow State University of Psychology and Education , Moscow, Russia
ORCID: https://orcid.org/0000-0002-3375-8446
e-mail: l.s.kuravsky@gmail.com Margolis A.A.
PhD in Psychology, Rector, Professor, Chair of Pedagogical Psychology, Moscow State University of Psychology & Education, Moscow, Russia
ORCID: https://orcid.org/0000-0001-9832-0122
e-mail: margolisaa@mgppu.ru Marmalyuk P.A.
PhD in Engineering, Head of the Laboratory of Psychology and Applied Software, Moscow State University of Psychology & Education, Moscow, Russia
e-mail: ykk.mail@gmail.com Panfilova A.S.
PhD in Engineering, Head of the Laboratory of Quantitative Psychology, Moscow State University of Psychology & Education, Moscow, Russia
e-mail: panfilova87@gmail.com Yuryev G.A.
PhD in Physics and Matematics, Associate Professor, Head of Scientifi c Laboratory, Moscow State University of Psychology & Education, Moscow, Russia
ORCID: https://orcid.org/0000-0002-2960-6562
e-mail: g.a.yuryev@gmail.com
The paper presents a concept of an adaptive training system implied for electronic learning that supports the choice of tasks according to parametric models. This approach is an alternative to the adaptive technologies based on item response theory (IRT). The features of the diagnostic methods underlying the choice of tasks presented in tests include, firstly, the account of the dynamics in an individual’s levels of performance and in the time s/he needs to complete the test, and, secondly, the lesser amount of tasks required to be presented in the training session.
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- Kuravsky L.S., Kulik S.D., Marmalyuk P.A., Yuryev G.A. Patent na poleznuyu
model’ №118095, Rossiiskaya Federatsiya (RU), kl. MPK G 09 B 23/02. Ustroistvo
dlya modelirovaniya adaptivnogo testirovaniya kognitivnykh sposobnostei
ispytuemogo [A device for modeling subject’s cognitive abilities adaptive
testing procedure] / L.S. Kuravsky, S.D. Kulik, P.A. Marmalyuk, G.A. Yuryev
(Rossiya). Zayavka №2012105993/08, 21.02.2012; Zaregistr. 10.07.2012;
Opublikovano 10.07.2012 Byul. №19; Prioritet ot 21.02.2012. (ROSPATENT).
- Kuravsky L.S., Margolis A.A., Marmalyuk P.A., Yuryev G.A., Dumin P.N.
Obuchaemye markovskie modeli v zadachakh optimizatsii poryadka pred”yavleniya
psikhologicheskikh testov [Trained Markov models to optimize the order of tasks
in psychological testing]. Neirokomp’yutery: razrabotka i primenenie
[Neurocomputers: development and application], 2013, no. 4, pp.
28–38.
- Kuravsky L.S., Margolis A.A., Marmalyuk P.A., Yuryev G.A., Dumin P.N.,
Kulik S.D. Patent na poleznuyu model’ №122796, Rossiiskaya Federatsiya (RU) kl.
MPK G09B 31/07. Sistema podderzhki prinyatiya reshenii dlya psikhologicheskogo
i pedagogicheskogo testirovaniya [Decision support system for psychological and
pedagogical testing]. / L.S. Kuravsky, A.A. Margolis, P.A. Marmalyuk, G.A.
Yuryev, P.N. Dumin, S.D. Kulik (Rossiya). Zayavka №2012132684/08, 31.07.2012;
Opublikovano 10.12.2012, Byul. №34; Prioritet ot 31.07.2012 (ROSPATENT).
- Kuravsky L.S., Margolis A.A., Yuryev G.A. Psikhologicheskii trening na
osnove neirosetevoi tekhnologii [Psychological training based on neural network
technology]. Neirokomp’yutery: razrabotka i primenenie
[Neurocomputers: development and application], 2009, no. 9, pp.
20–26.
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rezul’tatov testirovaniya [Using a Markov models in the test results
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Technique for the Identification of Discrete-State Continuous-Time Markov
Models. Applied Mathematical Sciences, Vol. 9, 2015, no. 8, pp. 379–391.
URL: https://doi.org/10.12988/ams.2015.410882
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Probabilistic Modeling of a Testing Procedure. Applied Mathematical
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