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Experimental Psychology (Russia)
2018. Vol. 11, no. 2, 77–94
doi:10.17759/exppsy.2018110206
ISSN: 2072-7593 / 2311-7036 (online)

Diagnostics basing on testing paths: the method of patterns

742

L.S. Kuravsky, G.A. Yuryev, D.V. Ushakov, N.E. Yuryeva, E.A. Valueva, E.M. Lapteva

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Abstract

Presented is the method of patterns to diagnose subjects basing on testing paths which represent results of completion of tasks in the order of their appearance. This method allows solving diagnostics tasks having limited observation results, building diagnostics conclusions only relying on the analysis of accumulated empirical data and changing adaptively both the number of presented testing tasks and their content to attain the given level of diagnostic assessment reliability.

General Information

Keywords: diagnostics of cognitive capabilities, diagnostics of operators of complex engineering systems, adaptive testing, IRT, method of patterns

Journal rubric: Mathematical Psychology

Article type: scientific article

DOI: https://doi.org/10.17759/exppsy.2018110206

For citation: Kuravsky L.S., Yuryev G.A., Ushakov D.V., Yuryeva N.E., Valueva E.A., Lapteva E.M. Diagnostics basing on testing paths: the method of patterns. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2018. Vol. 11, no. 2, pp. 77–94. DOI: 10.17759/exppsy.2018110206. (In Russ., аbstr. in Engl.)

References

  1. Baker F.B. The Basics of Item Response Theory. ERIC Clearinghouse on Assessment and Evaluation, University of Maryland, College Park, MD, 2001.
  2. Borg I., Groenen P.J.F. Modern Multidimensional Scaling Theory and Applications. Springer. 2005, p. 140.
  3. Gregory R.J. Psychological testing: History, principles, and applications (5th edition). New York, Pearson, 2007.
  4. Gulliksen H. Theory of Mental Tests. John Wiley & Sons Inc, 1950.
  5. Kuravsky L.S., Marmalyuk P.A., Baranov S.N., Alkhimov V.I., Yuryev G.A. and Artyukhina S.V. A New Technique for Testing Professional Skills and Competencies and Examples of its Practical Applications. Applied Mathematical Sciences, 2015, vol. 9, no. 21, pp. 1003—1026, https://doi.org/10.12988/ ams.2015.411899
  6. Kuravsky L.S., Marmalyuk P.A., Yuryev G.A. and Dumin P.N. A Numerical Technique for the Identification of Discrete-State Continuous-Time Markov Models. Applied Mathematical Sciences, 2015, vol. 9, no. 8, pp. 379—391. URL: https://doi.org/10.12988/ams. 2015.410882 (Accessed: 16.06.2018)
  7. Kuravskiy L.S., Artemenkov S.L., Yur’yev G.A., Grigorenko Ye.L. Novyy podkhod k komp’yuterizirovannomu adaptivnomu testirovaniyu [A novel approach towards computerized testing]. Eksperimental’naya psikhologiya [Experimental Psychology]. 2017. vol. 10, no. 3, pp. 33—45. DOI: 10,17759/ exppsy.2017100303 (In Russ.).
  8. Kuravskiy L.S., Margolis A. A., Marmalyuk P. A., Yur’yev G. A., Dumin P.N. Obuchayemyye markovskiye modeli v zadachakh optimizatsii poryadka pred”yavleniy psikhologicheskikh testov [Markov models in optimization of the order problems in psychological tests]. Neyrokomp’yutery: razrabotka i primeneniye [Neurocomputers: development and usage], 2013. no 4, pp. 28—38. (In Russ.).
  9. Kuravskiy L.S., Margolis A.A., Marmalyuk P.A., Panfilova A.S., Yur’yev G.A. Matematicheskiye aspekty kontseptsii adaptivnogo trenazhera [Mathematical aspects of the adaptive training concept]. Psikhologicheskaya nauka i obrazovaniye [Psychological science and education], 2016, vol. 21, no. 2, pp. 84— 95. doi: 10.17759 / pse.2016210210 (In Russ.).
  10. Kuravskiy L.S., Margolis A.A., Yur’yev G.A., Marmalyuk P.A. Kontseptsiya sistemy podderzhki prinyatiya resheniy dlya psikhologicheskogo testirovaniya [Conception of a system of support of decision making for psychological testing]. Psikhologicheskaya nauka i obrazovaniye [Psychological science and education], 2012, no 1, pp. 56—65. (In Russ.).
  11. Kuravskiy L.S., Yur’yev G.A. Adaptivnoye testirovaniye kak markovskiy protsess: modeli i ikh identifikatsiya [Adaptive testing as a markovsky process: models and their identification]. Neyrokomp’yutery: razrabotka i primeneniye [Neurocomputers: development and usage], 2011, no. 2, pp. 21—29. (In Russ.).
  12. Kuravskiy L.S., Yur’yev G.A. Veroyatnostnyy metod fil’tra artefaktov pri adaptivnom testirovanii [Probability method of filtring artefacts in adaptive testing]. Eksperimental’naya psikhologiya [Experimental Psychology], 2012, vol. 5, no. 1, pp. 119—131. (In Russ.).
  13. Kuravskiy L.S., Yur’yev G.A. Ispol’zovaniye markovskikh modeley pri obrabotke rezul’tatov testirovaniya [Using markovsky models in analyzing testing results]. Voprosy psikhologii [Psychology questions], 2011, no. 2, pp. 98—107. (In Russ.).
  14. Kuravskiy L.S., Yur’yev G.A. Ob odnom podkhode k adaptivnomu testirovaniyu i ustraneniyu yego artefaktov [About an approach towards adaptive testing and eliminating its artefacts]. Neyrokomp’yutery: razrabotka i primeneniye [Neurocomputers: development and usage], 2012, no 1. (In Russ.).
  15. Markovskiye modeli v zadachakh diagnostiki i prognozirovaniya: ucheb. posobiye [Markov models in diagnostics and prognostics: a manual]. Ed. L.S. Kuravsky. Moscow, MGPPU, 2017, 203 p. (In Russ.).
  16. Neal Phillip Grieb. Multiresolution Analysis for Adaptive Refinement of Multiphase Flow Computations. University of Iowa, 2010, pp. 116.
  17. Rasch G. Probabilistic models for some intelligence and attainment tests. Copenhagen, Danish Institute for Educational Research, expanded edition (1980) with foreword and afterword by B.D. Wright. Chicago, The University of Chicago Press. 1960/1980.
  18. René Vidal, Yi Ma, Shankar Sastry. Generalized Principal Component Analysis. Springer-Verlag New York, 2016. URL: http://www.springer.com/ us/book/9780387878102 (Accessed: 16.06.2018)
  19. Thompson N.A., Weiss D.J. A framework for the development of computerized adaptive tests. Practical Assessment, Research & Evaluation, 2011, vol. 16, no. 1, pp. 1—9.
  20. Torre J. de la, Patz R.J. Making the Most of What We Have: A Practical Application of Multidimensional Item Response Theory in Test Scoring. Journal of Educational and Behavioral Statistics, 2005, vol. 30, np. 3, pp. 295—311. doi:10.3102/10769986030003295.
  21. Trevor F. Cox, M.A.A. Cox. Multidimensional Scaling, Second Edition. Chapman & Hall CRC, 2001, 299 p.
  22. Valuyeva Ye.A., Ushakov D.V. Empiricheskaya verifikatsiya modeley sootnosheniy predmetnykh i emotsional’nykh sposobnostey [Empitical verification of the emotional abilities models]. Psikhologiya. Zhurnal Vysshey shkoly ekonomiki [Psychology. Journal of the Higher School of Economics], 2010, vol. 7, no 2, pp. 103—114. (In Russ.).
  23. Wright B.D., Masters G.N. Rating scale analysis. Rasch measurements. Chicago, MESA Press, 1982.
  24. Xiangyu Kong, Changhua Hu, Zhansheng Duan. Principal Component Analysis Networks and Algorithms. Springer, 2017. URL: http://www.springer.com/us/book/9789811029134 (Accessed: 16.06.2018)
  25. Young F. MDS: History, Theory, and Applications. Psychology Press, 2013, 317 p.

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

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

Dmitry V. Ushakov, Doctor of Psychology, Head of the Scientific and Educational Center for Social Competencies and Intelligence, Moscow State University of psychology and education (MSUPE), First Vice-President of Eurotalent, Head of the Center for Research and Development of Giftedness, Moscow University of Psychology and Education, Moscow, Russia, e-mail: dv.ushakov@gmail.com

Nataliya E. Yuryeva, PhD in Engineering, Head of Laboratory, Youth Laboratory Information Technologies for Psychological Diagnostics, Research Fellow, Information Technology Center for Psychological Studies of the Computer Science Faculty, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0003-1419-876X, e-mail: yurieva.ne@gmail.com

Ekaterina A. Valueva, PhD in Psychology, Research Fellow, The Laboratory of the Psychology and Psychophysiology of Creativity, Institute of Psychology of RAS, Leading Research Fellow, Center of Applied Psychological and Pedagogical Studies, Moscow State University of Psychology & Education, Moscow, Russia, ORCID: https://orcid.org/0000-0003-3637-287X, e-mail: ekval@list.ru

Ekaterina M. Lapteva, PhD in Psychology, Researcher, Laboratory for Psychology and Psychophysiology of Creativity, Institute of Psychology of RAS, Moscow, Russia, ORCID: https://orcid.org/0000-0002-3051-6492, e-mail: ek.lapteva@gmail.com

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