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Psychological Science and Education
2016. Vol. 21, no. 2, 84–95
doi:10.17759/pse.2016210210
ISSN: 1814-2052 / 2311-7273 (online)

Mathematical Aspects of the Concept of Adaptive Training Device

993

L.S. Kuravsky, A.A. Margolis, P.A. Marmalyuk, A.S. Panfilova, G.A. Yuryev

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Abstract

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.

General Information

Keywords: adaptive training, Markov process, adaptive training device

Journal rubric: Pedagogical Education

DOI: https://doi.org/10.17759/pse.2016210210

For citation: Kuravsky L.S., Margolis A.A., Marmalyuk P.A., Panfilova A.S., Yuryev G.A. Mathematical Aspects of the Concept of Adaptive Training Device. Psikhologicheskaya nauka i obrazovanie = Psychological Science and Education, 2016. Vol. 21, no. 2, pp. 84–95. DOI: 10.17759/pse.2016210210. (In Russ., аbstr. in Engl.)

References

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  2. 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).
  3. 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.
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Information About the Authors

Lev S. Kuravsky, Doctor of Engineering, professor, 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

Arkadiy A. Margolis, 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

Pavel A. Marmalyuk, PhD in Engineering, Head of the Laboratory of Psychology and Applied Software, Moscow State University of Psychology & Education, associate professor, Department of Information Technologies, Moscow State University of Psychology & Education, Moscow, Russia, e-mail: ykk.mail@gmail.com

Anastasya S. Panfilova, PhD in Engineering, Researcher, Institute of Psychology, Russian Academy of Sciences, Moscow, Russia, ORCID: https://orcid.org/0000-0003-1892-5901, e-mail: panfilova87@gmail.com

Grigory A. Yuryev, PhD in Physics and Matematics, Associate Professor, Head of Department of the Computer Science Faculty, Leading Researcher, Youth Laboratory Information Technologies for Psychological Diagnostics, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-2960-6562, e-mail: g.a.yuryev@gmail.com

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