|
|
Mathematical Aspects of the Concept of Adaptive Training Device 950
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 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 Panfilova A.S.
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 Yuriev 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
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.
- 1S: Elektronnoe obuchenie [Elektronnyi resurs] [1C: E-learning]. URL:
http://v8.1c.ru/elo (Accessed 06.02.2016).
- 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).
- 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.
- Kuravsky L.S., Margolis A.A., Marmalyuk P.A., Yuryev G.A., Dumin P.N.,
Kulik S.D. Patent na poleznuyu model’ №122796, Rossiiskaya Federatsiya (RU) kl.
MPK G09B 31/07. Sistema podderzhki prinyatiya reshenii dlya psikhologicheskogo
i pedagogicheskogo testirovaniya [Decision support system for psychological and
pedagogical testing]. / L.S. Kuravsky, A.A. Margolis, P.A. Marmalyuk, G.A.
Yuryev, P.N. Dumin, S.D. Kulik (Rossiya). Zayavka №2012132684/08, 31.07.2012;
Opublikovano 10.12.2012, Byul. №34; Prioritet ot 31.07.2012 (ROSPATENT).
- Kuravsky L.S., Margolis A.A., Yuryev G.A. Psikhologicheskii trening na
osnove neirosetevoi tekhnologii [Psychological training based on neural network
technology]. Neirokomp’yutery: razrabotka i primenenie
[Neurocomputers: development and application], 2009, no. 9, pp.
20–26.
- Kuravsky L.S., Yuryev G.A. Ispol’zovanie markovskikh modelei pri obrabotke
rezul’tatov testirovaniya [Using a Markov models in the test results
processing]. Voprosy psikhologii [Questions of psychology], 2011,
no. 2, pp. 98–107.
- Baker F.B. The Basics of Item Response Theory. ERIC Clearinghouse on
Assessment and Evaluation, University of Maryland, College Park, MD, 2001.
- Ebmodo [Elektronnyi resurs]. Connect with students and parents in your
paperless classroom. URL: https://www.edmodo.com (Accessed 03.02.2016).
- Kats, Y. Learning Management Systems and Instructional Design: Best
Practices in Online Education. IGI Global. 2013. ISBN 9781466639317.
- 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, Vol. 9, 2015, no. 8, pp. 379–391.
URL: https://doi.org/10.12988/ams.2015.410882
- Kuravsky L. S., Marmalyuk P. A., Yuryev G., Dumin P. N. and Panfilova A. S.
Probabilistic Modeling of a Testing Procedure. Applied Mathematical
Sciences, Vol. 9, 2015, no. 82, pp. 4053–4066. URL:
https://doi.org/10.12988/ams.2015.53234
- Moodle open-source learning platform [Elektronnyi resurs]. Moodle Pty Ltd.
URL:https://moodle.org (Accessed 03.02.2016).
- 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.
- Wolfram Alpha Webservice API [Elektronnyi resurs]. Wolfram Alpha LLC - A
Wolfram Research Company. URL:
http://products.wolframalpha.com/api/documentation.html (Accessed
21.01.2016).
- Wright B.D., Masters G.N. Rating scale analysis. Rasch measurements.
Chicago: MESA Press, 1982, р. 206.
|
|
