DEVELOPMENT OF THE PROCEDURE OF TESTING WITH THE APPLICATION OF THE EXPERT EVALUATION METHOD IN PSYCHOPHYSIOLOGY

Main Article Content

Svetlana V. Igrunova
Elena V. Nesterova
Orest D. Ivaschuk
Valery G. Nesterov
Alexandr V. Lomazov
Konstantin K. Igrunov

Keywords

Information Technology, Information System Design, Functional Models, Testing, Expert Evaluation

Abstract

Purpose: This article provides a detailed description of the stages of development of an information system of personalized psychophysiological testing using expert evaluation. The process of the information system design is presented, the developed functional models, database and algorithm of testing by students-experts are demonstrated.


Methodology: As a result of the analysis, the features of commercial educational institutions in the field of practical psychology, as the main influencing factor can be identified as the amount of practical training in the direction of «Psychology», which is very different from the standard curriculum.


Result: In the learning process, students, who acts experts, face following problems: absence of a clear structured hierarchy of indicators (test questions) in the evaluation of tests; lack of a procedure for formalization and evaluation of various qualitative and quantitative indicators (certain types of tests; lack of an effective tool that provides support for decision-making on the selection of personality type. The proposed system will solve these problems.


Applications: This research can be used for universities, teachers, and students.


Novelty/Originality: In this research, the model of Development of the Procedure of Testing with the Application of the Expert Evaluation Method in Psychophysiology is presented in a comprehensive and complete manner.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...
Abstract 43 | PDF Downloads 28 XML Downloads 2 ePUB Downloads 6

References

1. Dmitriev, M. G., & Lomazov, V. A. (2014). Sensitivity of linear convolution from expert judgments. Procedia Computer Science ”2nd International Conference on Information Technology and Quantitative Management, ITQM 2014", 802-806 (In Russian). https://doi.org/10.1016/j.procs.2014.05.330
2. Igrunova, S. V., Chursina, O. V., & Igrunov, K. K. (2018). On the stages of development of an automated testing subsystem. Theory and practice of modern science, 1(31). Website: http://www.modern-j.ru (In Russian).
3. Loewenthal, K., & Lewis, C. A. (2018). An Introduction to Psychological Tests and Scales. Psychology Press: 25-46. https://doi.org/10.4324/9781315782980
4. Munoz, M. A., Tromp, J. G., & Zhushun, C. (2018). Review of Virtual Reality Evaluation Methods and Psychophysiological Measurement Tools. Emerging Technologies for Health and Medicine: Virtual Reality, Augmented Reality, Artificial Intelligence, Internet of Things, Robotics, Industry, 4.0, 69-86. https://doi.org/10.1002/9781119509875.ch6
5. Petrosov, D. A., Lomazov, V. A., Dobrunova, A. I., Matorin, S. I., & Lomazova, V. I. (2015). Large Discrete Systems Evolutionary Synthesis Procedure. Biosciences Biotechnology Research Asia, 12(2), 1767-1775 (In Russian). https://doi.org/10.13005/bbra/1841
6. Petrosov, D.A., Lomazov, V.A., Dobrunova, A.I., Matorin, S.I., Lomazova, V.I., 2015. Large Discrete Systems Evolutionary Synthesis Procedure. Biosciences Biotechnology Research Asia. 12(2): 1767-1775 (In Russian). https://doi.org/10.13005/bbra/1841
7. Putivtseva, N. P., Igrunova, S. V., & Nesterova, E. V. (2017). Comparative analysis of the use of multicriteria methods. Scientific Result. Information technology, 2(1), 40-47 (In Russian). https://doi.org/10.18413/2518-1092-2016-1-1-39-47
8. Tarabayeva, V. B. (2016). New technologies. City Management: Theory and Practice, 1, 25-30 (In Russian).
9. Vagramenko, Ya. A., & Yalamov, G. Yu. (2015). Automated Information Systems for Educational Purposes. Actual problems of the implementation of e-learning and distance learning technologies. Book IM: Publishing House of SSU: 14-26 (In Russian).
10. Wagman, M. (2018). Computer Psychotherapy Systems: Theory and Research Foundations. Routledge: 71-84. https://doi.org/10.4324/9781351062909
11. Troland, L. T. (1929). The principles of psychophysiology. Vol. 1.
12. Gobel, M., Springer, J., & Scherff, J. (1998). Stress and strain of short haul bus drivers: psychophysiology as a design oriented method for analysis. Ergonomics, 41(5), 563-580. https://doi.org/10.1080/001401398186757
13. Troland, L. T. (1930). The principles of psychophysiology: A survey of modern scientific psychology, Vol 2: Sensation. https://doi.org/10.1037/13374-000
14. Cardone, D., Pinti, P., & Merla, A. (2015). Thermal infrared imaging-based computational psychophysiology for psychometrics. Computational and mathematical methods in medicine, 2015. https://doi.org/10.1155/2015/984353
15. Golubeva, E. A. (1972). The driving reaction as a method of study in differential psychophysiology. In Biological bases of individual behavior (pp. 11-28). Academic Press New York. https://doi.org/10.1016/B978-0-12-515350-8.50007-7
16. Lehrer, P. (2003). Applied psychophysiology: Beyond the boundaries of biofeedback (mending a wall, a brief history of our field, and applications to control of the muscles and cardiorespiratory systems). Applied Psychophysiology and Biofeedback, 28(4), 291-304. https://doi.org/10.1023/A:1027330909265
17. Miller, J., Patterson, T., & Ulrich, R. (1998). Jackknife-based method for measuring LRP onset latency differences. Psychophysiology, 35(1), 99-115. https://doi.org/10.1111/1469-8986.3510099
18. Bagiella, E., Sloan, R. P., & Heitjan, D. F. (2000). Mixed-effects models in psychophysiology. Psychophysiology, 37(1), 13-20. https://doi.org/10.1111/1469-8986.3710013
19. Cacioppo, J. T., Tassinary, L. G., & Berntson, G. (Eds.). (2007). Handbook of psychophysiology. Cambridge University Press. https://doi.org/10.1017/CBO9780511546396
20. Bach, D. R., & Friston, K. J. (2013). Model‐based analysis of skin conductance responses: Towards causal models in psychophysiology. Psychophysiology, 50(1), 15-22. https://doi.org/10.1111/j.1469-8986.2012.01483.x
21. Honts, C. R. (2004). The psychophysiological detection of deception. The detection of deception in forensic contexts, 103-126. https://doi.org/10.1017/CBO9780511490071.005
22. Kivikangas, J. M., Nacke, L., & Ravaja, N. (2011). Developing a triangulation system for digital game events, observational video, and psychophysiological data to study emotional responses to a virtual character. Entertainment Computing, 2(1), 11-16. https://doi.org/10.1016/j.entcom.2011.03.006