The concept of Decision Support System for psychological testing

Kuravsky L.S.; Margolis A.A.; Yuriev G.A.; Marmalyuk P.A.

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Psychological Science and Education

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 1814-2052

ISSN (online): 2311-7273

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

License: CC BY-NC 4.0

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Psychological Science and Education
2012. Vol. 17, no. 1, 56–65
ISSN: 1814-2052 / 2311-7273 (online)

The concept of Decision Support System for psychological testing ⁸⁷²

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

Yuriev G.A.
Programmer, Chair of Applied Computer Informatics, Information Technologies faculty, Moscow State University of Psychology and Education, Moscow, Russia, Moscow, Russia
e-mail: grinch89@mail.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

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RUIn Russian

The concept of a decision support system designed to optimize the order of tasks during psychological testing and based on trained continuous-time Markov models is presented. Diagnostic conclusions are derived using probabilistic estimates of being in different subject’s classes. These estimates are improved during testing procedure. Selection of a regular task is carried out for each subject individually, with previous testing outcome and forecasting the discriminating fineness of future tasks being in use.

Keywords: Markov models, psychological testing, identification of Markov models, decision support system

Column: Psychological Diagnostics

For Reference

Kuravsky L.S., Margolis A.A., Yuriev G.A., Marmalyuk P.A. The concept of Decision Support System for psychological testing. Psikhologicheskaya nauka i obrazovanie = Psychological Science and Education, 2012. Vol. 17, no. 1, pp. 56–65. (In Russ., аbstr. in Engl.)

Galushkin A.I. Nejronnye seti. Osnovy teorii. M., 2010.
Golovko V. A. Nejronnye seti: obuchenie, organizacija i primenenie: Ucheb. posobie. M., 2001.
Dzhekson P. Vvedenie v jekspertnye sistemy: Ucheb. posobie. M., 2001.
Dzhons M.T. Programmirovanie iskusstvennogo intellekta v prilozhenijah. M., 2004.
Kramer G. Matematicheskie metody statistiki. M., 1976.
Kuravskij L.S., Baranov S.N. Primenenie nejronnyh setej dlja diagnostiki i prognozirovanija ustalostnogo razrushenija tonkostennyh konstrukcij // Nejrokomp'jutery: razrabotka i primenenie. 2001. № 12.
Kuravskij L.S., Baranov S.N. Sintez setej Markova dlja prognozirovanija ustalostnogo razrushenija // Nejrokomp'jutery: razrabotka i primenenie. 2002. № 12.
Kuravskij L.S., Baranov S.N., Kornienko P.A. Obuchaemye mnogofaktornye seti Markova i ih primenenie dlja issledovanija psihologicheskih harakteristik // Nejrokomp'jutery: razrabotka i primenenie. 2005. № 12.
Kuravskij L.S., Baranov S.N., Jur'ev G.A. Sintez i identifikacija skrytyh markovskih modelej dlja diagnostiki ustalostnogo razrushenija // Nejrokomp'jutery: razrabotka i primenenie. 2010. № 12.
Kuravskij L.S., Margolis A.A., Jur'ev G.A. Psihologicheskij trening na osnove nejrosetevoj tehnologii // Nejrokomp'jutery: razrabotka i primenenie. 2009. № 9.
Kuravskij L.S., Jur'ev G.A. Ispol'zovanie markovskih modelej pri obrabotke rezul'tatov testirovanija // Voprosy psihologii. 2011. № 2.
Ljuger Dzh. F. Iskusstvennyj intellekt: strategii I metody reshenija slozhnyh problem. M., 2003.
Ovcharov L.A. Prikladnye zadachi teorii massovogo obsluzhivanija. M., 1969.
Psihodiagnostika v Rossii cherez 5 let // Psihologija. Zhurn. Vysshej shkoly jekonomiki. T. 5. 2008. № 4.
Saati T.L. Jelementy teorii massovogo obsluzhivanija i ejo prilozhenija. M., 2010.
Kuravsky L.S. and Baranov S.N. Condition monitoring of the structures suffered acoustic fatigue failure and forecasting their service life. Proc. Condition Monitoring 2003, Oxford, United Kingdom, July 2003.
Kuravsky L.S. and Baranov S.N. Neural networks in fatigue damage recognition: diagnostics and statistical analysis // Proc. 11th International Congress on Sound and Vibration, St.-Petersburg, July 2004.
Kuravsky L.S. and Baranov S.N. The concept of multifactor Markov networks and its application to forecasting and diagnostics of technical systems // Proc. Condition Monitoring 2005, Cambridge, United Kingdom, July 2005.
Kuravsky L.S., Baranov S.N. and Yuryev G.A. Synthesis and identification of hidden Markov models based on a novel statistical technique in condition monitoring // Proc. 7th International Conference on Condition Monitoring & Machinery Failure Prevention Technologies, Stratford-upon-Avon, England, June 2010.
URL: http:// www.solver.com.