|
|
Diagnostics basing on testing paths: the method of patterns 643
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 Yuryev G.A.
PhD in Physics and Matematics, Associate Professor, Head of Scientifi c Laboratory, Moscow State University of Psychology and Education, Moscow, Russia
ORCID: https://orcid.org/0000-0002-2960-6562
e-mail: g.a.yuryev@gmail.com Ushakov D.V.
PhD in Psychology, Head of the Laboratory, “Psychology and Psychophysiology of Creativity”, Moscow, Russia
e-mail: dv.ushakov@gmail.com Yuryeva N.E.
PhD in Engineering, Research Fellow, Center for Computer Science Faculty for Psychological Research, 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 Valueva E.A.
PhD in Psychology, Research Fellow, The Laboratory of the Psychology and Psychophysiology of Creativity, Institute of Psychology of RAS, Moscow, Russia
ORCID: https://orcid.org/0000-0003-3637-287X
e-mail: ekval@mail.ru Lapteva E.M.
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
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.
-
Baker F.B. The Basics of Item Response Theory. ERIC
Clearinghouse on Assessment and Evaluation, University of Maryland, College
Park, MD, 2001.
-
Borg I., Groenen P.J.F. Modern Multidimensional Scaling
Theory and Applications. Springer. 2005, p. 140.
-
Gregory R.J. Psychological testing: History,
principles, and applications (5th edition). New York, Pearson, 2007.
-
Gulliksen H. Theory of Mental Tests. John Wiley
& Sons Inc, 1950.
-
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
-
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)
-
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.).
-
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.).
-
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.).
-
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.).
-
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.).
-
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.).
-
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.).
-
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.).
-
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.).
-
Neal Phillip Grieb. Multiresolution Analysis for
Adaptive Refinement of Multiphase Flow Computations. University of Iowa,
2010, pp. 116.
-
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.
-
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)
-
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.
-
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.
-
Trevor F. Cox, M.A.A. Cox. Multidimensional Scaling,
Second Edition. Chapman & Hall CRC, 2001, 299 p.
-
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.).
-
Wright B.D., Masters G.N. Rating scale analysis. Rasch
measurements. Chicago, MESA Press, 1982.
-
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)
-
Young F. MDS: History, Theory, and Applications.
Psychology Press, 2013, 317 p.
|
|
