Prospects for Ontological Modeling as a Verifying Method of the Psychological Research results (on Example of Game Analysis)
DOI:
https://doi.org/10.29038/2227-1376-2024-44-khaiKeywords:
verification, empiricism, rationalism, ontology, ontological modeling, game, game modeling, model, taxonomy, experiment, categorical matrix, standardAbstract
Purpose. Methodological differences in the verification standards for the results of scientific knowledge between individual psychological branches represented in the domestic and global scientific space, the peculiarities of extremely complex psychological knowledge objects indicates the need to modernize the relevant standards and choose the optimal methodological platform for the verification of the results of modern psychological research. This paper discusses the feasibility of choosing such a ontological modeling platform, which is a special descriptive methodology and an alternative to the naturalistic experimental approach in verifying the results of psychological research. Ontological modeling provides the possibility for a more objective verification of the achievements for the study of intelligible objects, which have a distinct cultural and historical meaning, extremely complex structure and functionality, an ancient and diverse history of their own empirical representations. The purpose of the article is a theoretical study of ways to modernize the standards of verification of the results of modern psychological research using the example of the verification of the promising theory of game modeling of human vital activity in uncertainty conditions.
Methods.The research uses the methods of analysis and systematization for psychological and interdisciplinary approaches in the study of verification patterns for the psychological knowledge results, comparison and optimization for the content of its standards on the study example of game modeling of human vital activity in uncertainty conditions.
Results. According to the results of the study, the expediency of choosing ontological modeling (the names "conceptual modeling", "formal ontology", "formal ontology" and "ontological engineering" are also used synonymously) as a perspective basis for the verification of the psychological research results, a new universal methodological tool of Ukrainian psychology, has been proven using the example for game modeling of human vital activity in uncertainty. The existing scientific approaches that argue for the choice of ontological modeling as the basis for the verification of new psychological knowledge are specified. The methodological perspective of the modernization for the verification norms of psychological theories and concepts based on the ontological approach has been updated and substantiated. Modern scientific ideas are generalized and fundamental approaches to the verification of the results of knowledge of unlimited generality objects, i.e. ultra-complex simultaneously intelligible and empirical objects, are deepened. It has been established that ontological modeling has a universal scientific purpose and is able to overcome the shortcomings of the naturalistic experimental method for verification of research products, to be the optimal methodological platform for the verification of the modern psychological research results.
Conclusions. The results of the study allow us to conclude about the relevance of the above issues and the expediency of choosing ontological modeling as a prospective basis for the verification of the psychological research results using the example for game modeling of human vital activity in uncertainty. A well-founded description of the standards and the process for verification of the psychological research results for game modeling of human vital activity in uncertainty conditions is considered promising.
References
1. Basiuk T. M. (2017). Ontolohichnyi inzhynirynh [Ontological engineering]. Lviv : Vydavnytstvo Lvivskoi politekhniky. [in Ukrainian].
2. Blikhar, V.S., Tsymbaliuk, M.M., Haivoroniuk, N.V., Levkulych, V.V., Shandra, B.B., Svyshcho, V.Iu. (2021). Filosofiia [Philosophy]. Uzhhorod: Vyd-vo UzhNU “Hoverla”. [in Ukrainian].
3. Bocheliuk V.I., & Bocheliuk V.V. (2008). Metodyka ta orhanizatsiia naukovykh doslidzhen iz psykholohii [Methodology and organization of scientific research in psychology]. Kyiv : Tsentr uchbovoi literatury. [in Ukrainian].
4. Halian O. (2018). Tested models of the development of the subjectivity of students' personality as an empirical verification of the effectiveness of a humanitarian-oriented educational environment. [Aprobovani modeli rozvytku subiektnosti osobystosti uchniv yak empirychna veryfikatsiia rezultatyvnosti humanitarno-oriientovanoho osvitnoho seredovyshcha]. Molod i rynok. 12, 12–18. Rezhym dostupu: http://nbuv.gov.ua/UJRN/Mir_2018_12_4 [in Ukrainian].
5. Heizinha Y. (1994). Homo Ludens. [Homo Ludens]. Kyiv : Osnovy. [in Ukrainian].
6. Danylova, T., Zhovtianska, V., Kukharuk, O., Malkhazov, O., Sushyi O. (2023). Psykholohichne zabezpechennia prohnozuvannia sotsialnykh protsesiv. [Psychological support for forecasting social processes]. Kropyvnytskyi : Imeks-LTD. [in Ukrainian].
7. Ivanova, N. V. (2017). Dukhovno-ontolohichni stratehii myslennia: sotsialno-filosofskyi analiz. [Spiritual and ontological strategies of thinking: socio-philosophical analysis]. Doctor’s thesis. Odesa. [in Ukrainian].
8. Komakha, L.H. (2015). Lohichni zasady arhumentatsii u filosofskomu znanni. [Logical principles of argumentation in philosophical knowledge]. Kyiv : Tsentr uchbovoi literatury. [in Ukrainian].
9. Lovka, O. V., Borysenko, L. L., Kolesnichenko L. A., Muzychko, L. V. Timakova A. V., Lavrynenko, D. H. (2019). Zahalna psykholohiia. Teoretyko-metodolohichni osnovy nauky.[General Psychology. Theoretical and methodological foundations of science]. K.: KNEU. [in Ukrainian].
10. Furman, A.V., Shandruk, S.K. (2014). Sutnist hry yak uchynennia. [The essence of the game as practice]. Ternopil : TNEU. [in Ukrainian].
11. Furman, A.B. (2016). Ideia i zmist profesiinoho metodolohuvannia. [The idea and content of professional methodology]. Ternopil : TNEU. [in Ukrainian].
12. Furman, A. V. (2023). Katehoriina matrytsia vitakulturnoi metodolohii: vid myslevchynennya do kanonu [Categorical matrix of vitacultural methodology: from thinking to the canon]. Psykholohiia i suspilstvo, 2, 6-50 [in Ukrainian]. DOI: https://doi.org/10.35774/pis2023.02.006
13. Khairulin, O.M. (2023). Ontological modeling of the psychological playing field. [Ontolohichne modeliuvannia psykholohichnoho polia hry]. Psykholohiia i suspilstvo. №2. 106-141. [in Ukrainian]. DOI: https://doi.org/10.35774/pis2023.02.106
14. Khairulin, O.M. (2024a). Game modeling of human life as a subject of psychological research. [Ihrove modeliuvannia zhyttiediialnosti liudyny yak predmet psykholohichnoho doslidzhennia]. Naukovyi zhurnal «Habitus». Vyp. 57. 73–79. [in Ukrainian]. DOI: https://doi.org/10.32782/2663-5208.2024.57.11
15. Khairulin, O.M. (2024b). Prospects for theory of game modeling human life activities as canonical psychology component/ [Perspektyvy teorii ihrovoho modeliuvannia zhyttiediialnosti liudyny yak skladnyka kanonichnoi psykholohii]. Zhurnal suchasnoi psykholohii. №3. 39-50. DOI: https://journalsofznu.zp.ua/index.php/psych/article/view/4276 [in Ukrainian].
16. Aarseth, E., Calleja, G. (2015). The Word Game: The ontology of an indefinable object. 10th International Conference on the Foundations of Digital Games (FDG 2015). Pacific Grove. CA, USA.
17. Bogost, I. (2006). Unit Operations. An Approach to Videogame Criticism. Cambridge, MA: MIT Press. http://dx.doi.org/10.7551/mitpress/6997.001.0001 DOI: https://doi.org/10.7551/mitpress/6997.001.0001
18. Bogost, I. (2007). Persuasive games: the expressive power of videogames. Cambridge, MA: MIT Press. http://dx.doi.org/10.7551/mitpress/5334.001.0001 DOI: https://doi.org/10.7551/mitpress/5334.001.0001
19. Carnap, R. (1967). The logical structure of the world. London : Routledge & K. Paul.
20. Corea, C.; Delfmann, P. (2017): Detecting Compliance with Business Rules in Ontology-Based Process Modeling. Leimeister, J.M.; Brenner, W. (Hrsg.): Proceedings der 13. Internationalen Tagung Wirtschaftsinformatik (WI 2017), St. Gallen.
21. Fellmann, M., Hogrebe, F., Thomas, O., Nüttgens, M. (2010). An ontology-driven approach to support semantic verification in business process modeling. In Proceedings of the Modellierung Betrieblicher Informationssysteme (MobIS 2010), Modellgestütztes Management, Dresden, Germany.
22. Garanina, N., Anureev, I., Borovikova, O. (2018). Verification Oriented Process Ontology. Modeling and Analysis of Information Systems, 25(6), 607-622. http://dx.doi.org/10.18255/1818-1015-2018-6-607-622 DOI: https://doi.org/10.18255/1818-1015-2018-6-607-622
23. Gruber, T. R. (1993). A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 5(2), 199-220. http://dx.doi.org/10.1006/knac.1993.1008 DOI: https://doi.org/10.1006/knac.1993.1008
24. Gruber, T. R. (2009). Ontology. Entry in the Encyclopedia of Database Systems. Ling Liu and M. Tamer Özsu (Eds.), Springer-Verlag. DOI: https://doi.org/10.1007/978-0-387-39940-9_1318
25. He, H., Wang, Z., Dong, Q., Zhang,W., Zhu, W. (2013). Ontology-based semantic verification for uml behavioral models. Int. J. Softw. Eng. Knowl. Eng. 23. http://dx.doi.org/10.1142/s0218194013500010 DOI: https://doi.org/10.1142/S0218194013500010
26. Mosca, I. (2014). The Social Ontology of Digital Games. Handbook fo digital games. Wiley-IEEE. http://dx.doi.org/10.1002/9781118796443.ch23 DOI: https://doi.org/10.1002/9781118796443.ch23
27. Nguyen, T. H., Grundy, J. C., Almorsy, M. (2015). Ontology-based automated support for goal–use case model analysis. Software Quality Journal, 24 (3), 635–673. https://doi.org/10.1007/s11219-015-9281-7 DOI: https://doi.org/10.1007/s11219-015-9281-7
28. Rajab, А., Hafeez, A., Shaikh, A., Alghamdi, A., Al Reshan, M.S., Hamdi, M., Rajab, K. (2022). UCLAONT: Ontology-Based UML Class Models Verification Tool. Appl. Sci., 12, 1397. https://doi.org/10.3390/app12031397 DOI: https://doi.org/10.3390/app12031397
29. Searle, J. R. (1995). The Construction of Social Reality. Simon and Schuster, London.
30. Searle, J.R. (2006). Social ontology: Some basic principles. Anthropological Theory, 6 (1). https://doi.org/10.1177/1463499606061731 DOI: https://doi.org/10.1177/1463499606061731
31. Sun, J.; Wang, H.; Hu, T. (2011). Design Software Architecture Models using Ontology. In Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering, Miami, FL, USA.
32. Wartofsky, M.W., (1979). Models: Representation and the Scientific Understanding. Dordrecht/Boston/London : D. Reidel. DOI: https://doi.org/10.1007/978-94-009-9357-0_10
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