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Journal Neurocomputers №2 for 2011 г.
Article in number:
Adaptive testing as a Markov process: models and their identification
Keywords: adaptive testing Markov models identification of Markov models classical theory of testing IRT
Authors:
L. S. Kuravsky, G. A. Yuryev
Abstract:
Presented is a new technology of adaptive testing, which is based on application of trained structures in the form of discrete- and continuous-time Markov models. Its peculiarities, in particular, are revealing and using test solution capability changes in quantitative evaluation of their time-domain dynamics as well as taking into account timetable of testing process. The approach suggested has certain advantages over the testing techniques which were used before owing to its greater information capability and acceleration of a test procedure.
Pages: 21-29
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. Gregory, R. J., Psychological testing: History, principles, and applications (5th edition). New York: Pearson. 2007.
  3. Gulliksen, H., Theory of Mental Tests. John Wiley & Sons Inc. 1950.
  4. Haberman, S. J., Analysis of qualitative data: new developments. N.Y. 1988.
  5. 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. P. 256-279. July 2003.
  6. 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. Russia. P. 2929-2944. July 2004.
  7. 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. P. 111-117. July 2005.
  8. 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
  9. URL: http://www.solver.com
  10. URL: http://www.matlab.mgppu.ru/work/0015.htm
  11. Wright, B. D., Stone, M.N. Best Test Design. Chicago: MESA Press. 1979.
  12. Wright, B. D., Masters, G. N., Rating scale analysis. Rasch measurements. Chicago: MESAPress. 1982.
  13. Аванесов В. С. Педагогическое измерение латентных качеств // Педагогическая диагностика. 2003. № 4. С. 69-78.
  14. Заочников Б. И., Найденова Н. Н., Никифоров С. В., Челышкова М. Б. Шкалирование и выравнивание результатов педагогических измерений. М.: Логос. 2003.
  15. Карданова Е. Ю.Моделирование и параметризация тестов: основы теории и приложения. ФГУ «Федеральный центр тестирования». 2008.
  16. Крамер Г. Математические методы статистики. М.: Мир. 1976.
  17. Куравский Л. С., Баранов С. Н., Малых С. Б. Нейронные сети в задачах прогнозирования, диагностики и анализа данных: Учеб. пособие. М.: РУСАВИА. 2003.
  18. Куравский Л. С., Баранов С. Н. Применение нейронных сетей для диагностики и прогнозирования усталостного разрушения тонкостенных конструкций // Нейрокомпьютеры: разработка и применение. 2001. № 12. С. 47-63.
  19. Овчаров Л. А. Прикладные задачи теории массового обслуживания. М.: Машиностроение. 1969.
  20. Тюменева Ю. А.Психологическое измерение. М.: Аспект-Пресс. 2007.