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.
- 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
- 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).
- Loewenthal, K., & Lewis, C. A. (2018). An Introduction to Psychological Tests and Scales. Psychology Press: 25-46. https://doi.org/10.4324/9781315782980
- 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
- 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
- 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
- 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
- Tarabayeva, V. B. (2016). New technologies. City Management: Theory and Practice, 1, 25-30 (In Russian).
- 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).
- Wagman, M. (2018). Computer Psychotherapy Systems: Theory and Research Foundations. Routledge: 71-84. https://doi.org/10.4324/9781351062909
- Troland, L. T. (1929). The principles of psychophysiology. Vol. 1.
- 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
- Troland, L. T. (1930). The principles of psychophysiology: A survey of modern scientific psychology, Vol 2: Sensation. https://doi.org/10.1037/13374-000
- 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
- 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
- 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
- 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
- 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
- Cacioppo, J. T., Tassinary, L. G., & Berntson, G. (Eds.). (2007). Handbook of psychophysiology. Cambridge University Press. https://doi.org/10.1017/CBO9780511546396
- 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
- 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
- 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