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Experimental Psychology (Russia)

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 2072-7593

ISSN (online): 2311-7036

DOI: http://dx.doi.org/10.17759/exppsy

License: CC BY-NC 4.0

Started in 2008

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Comparative analysis of two new concepts of adaptive training

Kuravsky L.S., Doctor in Technical Sciences, Dean of the Computer Science Faculty , Moscow State University of Psychology and Education , Moscow, Russia, l.s.kuravsky@gmail.com
Yuryev G.A., Ph.D. in Physics and Matematics, associate professor, Deputy Dean of the Department of Information Technologies, Moscow State University of Psychology & Education, Moscow, Russia, g.a.yuryev@gmail.com
Dumin P.N., head of laboratory of quantitative psychology, faculty of information technologies, MSUPE
Pominov D.A., Junior Researcher, Moscow State University of Psychology & Education, Moscow, Russia, necrofallen@gmail.com
Abstract
Two new concepts of adaptive learning are presented. The first of them is based on a self-learning probabilistic model, the second one uses multivariate statistical analysis of wavelet representations for task execution trajectories as well as a matrix of recommended transitions. A comparative analysis of various aspects of their practical application has been carried out.

Keywords: adaptive training, IRT, method of patterns, Markov random processes, wavelet analysis, self-learning systems.

Column: Mathematical Methods

DOI: http://dx.doi.org/10.17759/exppsy.2019120213

Funding

This work has been supported by the Russian Foundation for Basic Research (Project No 17-29-07034).

For Reference

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