DEVELOPMENT OF COMMUNICATIVE COMPETENCE OF STUDENTS BY MEANS OF PSYCHOLOGICAL TRAINING

Keywords: verbal consciousness, future psychologists, active Internet users, communicative attitudes, communicative and social competence

Abstract

The article presents the theoretical substantiation of the psycholinguistic category communicative competence, which is one of the main professionally important qualities of forming the personality of a future specialist psychologist. Mental reality and speech communication of modern students are mediated by new ways of perceiving information that determine a new type of communicative behavior of its carriers. Based on the analysis of authoritative sources it is found out that the virtual communication space as a whole and the active use of the Internet in particular significantly affect the features of communicatively mediated communication of young people, deforming its verbal component. The purpose of the article is to theoretically substantiate and empirically study the development of communicative competence of future psychologists by means of psychological training. The study used a set of methods, namely theoretical analysis of works devoted to virtual discourse in scientific publications of the last two decades. Also, in order to study the effectiveness of the developed training program, a number of empirical methods were applied – observation, experiment, testing, method of studying products of activity, method of expert evaluation.

Results. In order to develop communicative competence, the psychological training “Formation of Communicative Competence” was developed and implemented in the educational process. The algorithm for designing and applying assignments for lessons is characterized. The study was attended by 107 respondents, who form 4 academic groups of students of 1 and 2 courses of the Kiev National Trade and Economic University specializing in psychology. To test the effectiveness of training the development of communicative competence of students in control groups, the method “Diagnosis of communicative setting V.V. Boyko” and the methodology “Diagnosis of communicative social competence (CSC)”. The results obtained were processed using statistical methods.

Conclusions. The effectiveness of the influence of psychological training “Formation of communicative competence” on the development of personality-oriented speech communication of active Internet users has been proved, which as a whole is a predictor of more effective communication strategies. The prospect of further research with the involvement of students of other professional fields (future philologists, managers), as well as the study of gender differences in virtual communication and their influence on the mental development of the individual, are offered.

References

1. Zavinchenko, N. (2003). Osoblivosti rozvitku komunikativnoi kompetentnosti maybutnyoho psihologa sistemi osviti [Features of the development of communicative competence of the future psychologist of the education system]. Dis. ... kand. psihol. nauk. [dissertation PhD]. Кyiv, 2003, p. 41–42 [in Ukrainian].
2. Kaminska, O., Stezhko, U., Glebova, L. (2009). Psycholingvistyka virtualnoi komunikasii v konteksti zalezhnosti vid socialnih merezh [Psycholinguistics of virtual communication in the context of dependence on social networks]. Psycholingvistyka – Psycholinguistics, 25(1) [in Ukrainian].
3. Kirichenko, Т. (2016). Osoblivosty rozvitku mizhosobistisnoi movlenevoi komunikasii pidlitkiv [Features of development of interpersonal speech communication of adolescents]. Psycholingvistyka – Psycholinguistics. 20(1), 119–138. DOI: 10.5281/zenodo.1211177 [in Ukrainian].
4. Korniyaka, О. (2016). Komunikativna kompetentnist yak viznachalniy chinnik profesiynogo samozdiysnennya vikladacha vishoy shkoly [Communicative competence as the determining factor of professional self-realization of a teacher of higher education]. Aktualni problemi psychologiy – Actual problems of psychology. (VІ): Psychophysiology. Psychology prasi. Experimental psychology [Psychophysiology. Psychology of labor. Experimental psychology], 16, 82–92. Retrieved from: https://core.ac.uk/download/pdf/32305849.pdf [in Ukrainian].
5. Raygorodskiy, D. (2011). Diagnostika kommunikativnoy ustanovki V.V. Boyko [Diagnostics of communicative installation V.V. Boyko]. Practicheskaya psychodiagnostica: metodiky i testy [Practical psychodiagnostics: techniques and tests]. Moskva: Bahrah, 298–312 [in Russian].
6. Skulovatova, О. (2017). Doslidzhennya samopresentasii osobistosty v Internety (na osnovi analizu ii avatariv) [Self-presentation of the personality on the Internet (based on analysis of its avatars)]. Molodiy vcheniy: naukoviy zhurnal [Young scientist: scientific journal], 1(41), 249–253. Retrieved from: http://molodyvcheny.in.ua/files/journal/2017/1/58.pdf [in Ukrainian].
7. Fetiskin, N.P., Kozlov, V.V., Manuylov, G.М. (2002). Diagnosticа communicativnoy socialnoy competentnosty (CSC) [Diagnostics of communicative social competence (CSC). Socialno-psychologicheskaya diagnostica razvitiya lichnosty i malih grup [Socio-psychological diagnostics of personality development and small groups] Moskva: Bahrah, 139–149 [in Russian].
8. Boyle, E., Hainey, T., Connolly, T., Gray, G., Earp, J., & Ott, M. et al. (2016). An update to the systematic literature review of empirical evidence of the impacts and outcomes of computer games and serious games. Computers & Education, 94, 178–192. DOI: 10.1016/j.compedu.2015.11.003.
9. Chan, C. (2018). Analysing social networks for social work practice: A case study of the Facebook fan page of an online youth outreach project. Children and Youth Services Review, 85, 143–150. DOI :10.1016/j.childyouth.2017.12.021.
10. Coulson, M., Oskis, A., Meredith, J., & Gould, R. (2018). Attachment, attraction and communication in real and virtual worlds: A study of massively multiplayer online gamers. Computers in Human Behavior, 87, 49–57. DOI: 10.1016/j.chb.2018.05.017.
11. Felker, E., Klockmann, H., & Jong, N. (2018). How conceptualizing influences fluency in first and second language speech production. Applied Psycholinguistics, 40, 111–136. Retrieved from: https://doi.org/10.1017/S0142716418000474.
12. Gholamitooranposhti, M., Sabzaliani, H., & Aghaei, M. (2012). A New Attitude to Computer Games. Procedia – Social and Behavioral Sciences, 69, 1302–1308. DOI: 10.1016/j.sbspro.2012.12.066.
13. Cult Cogn Sci (2018). Cognitive Science and Cultural Transmission. Journal of Cognition and Culture (J Cognit Cult), 2018, DOI: ow.ly/C8wA30m22IC.
14. Huang, J., Heidergott, B., & Lindner, I. (2019). Naive learning in social networks with random communication. Social Networks, 58, 1–11. DOI: 10.1016/j.socnet.2019.01.004.
15. Litou, I., Boutsis, I., & Kalogeraki, V. (2017). Efficient techniques for time-constrained information dissemination using location-based social networks. Information Systems, 64, 321–349. DOI: 10.1016/j.is.2015.12.002.
16. Liu, C., & Chang, I. (2016). Model of online game addiction: The role of computer-mediated communication motives. Telematics and Informatics, 33(4), 904–915. DOI: 10.1016/j.tele.2016.02.002.
17. Peng, S., Yu, S., & Mueller, P. (2018). Social networking big data: Opportunities, solutions, and challenges. Future Generation Computer Systems, 86, 1456–1458. DOI: 10.1016/j.future.2018.05.040.
18. Ríos, S., Aguilera, F., Nuñez-Gonzalez, J., & Graña, M. (2019). Semantically enhanced network analysis for influencer identification in online social networks. Neurocomputing, 326–327, 71–81. DOI: 10.1016/j.neucom.2017.01.123.
19. Sapountzi, A., & Psannis, K. (2018). Social networking data analysis tools & challenges. Future Generation Computer Systems, 86, 893–913. DOI: 10.1016/j.future.2016.10.019.
20. Stria, I. (2015). Towards a Linguistic Worldview for Artificial Languages. Poznań.
21. Sumith, N., Annappa, B., & Bhattacharya, S. (2018). Influence maximization in large social networks: Heuristics, models and parameters. Future Generation Computer Systems, 89, 777–790. DOI: 10.1016/j.future.2018.07.015.
22. Tsai, C., & Liu, S. (2019). SEIM: Search economics for influence maximization in online social networks. Future Generation Computer Systems, 93, 1055–1064. DOI: 10.1016/j.future.2018.08.033.
23. Verheijen, G., Stoltz, S., van den Berg, Y., & Cillessen, A. (2019). The influence of competitive and cooperative video games on behavior during play and friendship quality in adolescence. Computers in Human Behavior, 91, 297–304. DOI: 10.1016/j.chb.2018.10.023.
24. Yang, Y. (2010). Web user behavioral profiling for user identification. Decision Support Systems, 49(3), 261–271. DOI: 10.1016/j.dss.2010.03.001.
25. Zhou, X., Wu, B., & Jin, Q. (2019). User role identification based on social behavior and networking analysis for information dissemination. Future Generation Computer Systems, 96, 639–648. DOI: 10.1016/j.future.2017.04.043
Published
2020-04-02
Pages
174-181
Section
SECTION 4 ORGANIZATIONAL PSYCHOLOGY