ISSN online: 2221-1616

Bulletin of the Institute of Sociology (Vestnik instituta sotziologii)

Research Article

Александра А Филипова Doctor of Sociology
Professor, Far Eastern Federal University
alexgen77@list.ru
ORCID ID=0000-0002-7475-1961
Алёна А Высоцкая
Acting Head of the Department "Information Systems", Komsomolsk-na-Amure State University
Al-w-buaa@rambler.ru
ORCID ID=0000-0001-7048-028X
The method for imitation model structuring (Using the unified state exam average score in Russian regions as an example).
Vestnik instituta sotziologii. 2017. Vol. 8. No. 4. P. 71-89


This Article is downloaded: 484 times
Topic: To the methodology of scientific research

For citation:
Филипова А. Г., Высоцкая А. В. The method for imitation model structuring (Using the unified state exam average score in Russian regions as an example). Vestnik instituta sotziologii. 2017. Vol. 8. No. 4. P. 71-89
DOI: https://doi.org/10.19181/vis.2017.23.4.481


Abstract

This article presents a method for modeling situations in terms of unified state exam average scores in Russian regions. A system dynamics approach was chosen out of three imitation-modeling approaches, which allows working with insufficient data, monitoring changes to the model in time, as well as constructing causations between various factors and evaluating the power of their mutual influences. Stages of work include substantiating the methodology of system dynamics, constructing a conceptual model of unified state exam average score system dynamics, simplifying the established model, determining the causations using mathematical and statistical methods, implementing the model within AnyLogic software environment, and playing out scenarios for its development. Using the language of imitation modeling allowed for expressing elements of the modeled system via pathways and means of storage. Unified state exam average scores were chosen as a means of storage, which links within itself resources of the general education system (personnel, technological, financial). Three levels of analysis were highlighted in the conceptual model: demographical, institutional, economic-infrastructural, and an according set of 17 control factors was created, which impact unified state exam performance (the target factor). The control factors within the system dynamics model were transformed into “pathways” and “parameters”. The 2013–2014 academic year was chosen as the observation period. Statistical data for examination was sourced from “Russian regions” compilations, the unified interagency information and statistical system (UIISS), as well as informational-analytical reports from regional information processing centers. The final sample is comprised of 78 Russian regions, while 5 constituent entities of the Russian Federation did not undergo any examination due to a lack of statistical data on various factors. Utilizing correlation and regression analysis methods allowed for reducing the amount of control factors to just three – the level of urban population, the amount of well-furnished schools and the amount of evening schools. These factors became the parameters which determine the pathways in the system dynamics model. The influence of the first two has a positive effect on the growth of a certain parameter in the pathway quality of the unified state exam average score. The third parameter generates a reverse direction pathway, which decreases the storage means’ value. According to the coefficients in the regressive equation, it has a stronger influence than the previous two. The “unified state exam average score in Russian regions” model which was constructed in AnyLogic includes one means of storage (unified state exam level), one parameter with an unregulated value (level of urban population), and two with regulated values (well-furnished school and evening schools levels). Two series of experiments were conducted within the software environment.

Keywords

General education, unified state exam, constituent entities of the Russian Federation, unified state exam average score, regional factors, imitation modeling, correlation analysis, regression analysis, system dynamics model, means of storage, pathways, parameters.

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