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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

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A new approach to computerized adaptive testing 53

Kuravsky L. S., Doctor in Technical Sciences, Dean of the Department of Information Technologies, Moscow State University of Psychology & Education, Moscow, Russia, l.s.kuravsky@gmail.com
Artemenkov S.L., Ph.D. in Technical Sciences, Chair of applied informatics and multimedia technologies, department of information technology, head of laboratory of mathematical psychology and applied software, Moscow State University of Psychology and Education, Moscow, Russia, slart@inbox.ru
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
Grigorenko E.L., Doctor in Psychology, Professor, Head of Laboratory of Behavoir Genetics, Chair of Psychology of Education and Pedagogics, member of the editorial board of scientific journal "Experimental Psychology", Lomonosov Moscow State University, Moscow, Russia, elena.grigorenko@yale.edu
Abstract
A new approach to computerized adaptive testing is presented on the basis of discrete-state discrete-time Markov processes. This approach is based on an extension of the G. Rasch model used in the Item Response Theory (IRT) and has decisive advantages over the adaptive IRT testing. This approach has a number of competitive advantages: takes into account all the observed history of performing test items that includes the distribution of successful and unsuccessful item solutions; incorporates time spent on performing test items; forecasts results in the future behavior of the subjects; allows for self-learning and changing subject abilities during a testing procedure; contains easily available model identification procedure based on simply accessible observation data. Markov processes and the adaptive transitions between the items remain hidden for the subjects who have access to the items only and do not know all the intrinsic mathematical details of a testing procedure. The developed model of adaptive testing is easily generalized for the case of polytomous items and multidimensional items and model structures.

Keywords: Markov processes, adaptive testing, IRT, computerized adaptive testing

Column: Research Methods

DOI: http://dx.doi.org/10.17759/exppsy.2017100303

A Part of Article

Testing procedures are increasingly used in many contemporary applications requiring assessment of people or machine’s behavior. According to conventional models of testing based on classical test theory for measuring the examinee’s level in a specific skill or ability as preciselyas possible these procedures usually should implement a big number of items that makes testing difficult to use.

For Reference

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