Ways to use big data technologies in the practice of vocational guidance of schoolchildren for teaching activities
DOI: 10.23951/2307-6127-2025-1-56-65
The paper presents current trends in the career guidance of schoolchildren for the teaching profession related to big data technologies, artificial intelligence and the personification of career trajectories. The possibilities of a basic data analysis source are shown using the example of the VKontakte social network, which can be used to identify the identification features of the pedagogical community and predict the propensities of schoolchildren to the teaching profession. The article presents the results of an empirical study, during which an organizational and pedagogical model of the use of big data technologies in the regional system of professional orientation of schoolchildren to teaching activities based on the methods of predictive analytics was formed. The model allows us to identify the key factors influencing the choice of a teaching profession and form personalized recommendations for career path building for schoolchildren. The results of the study can be used to develop new tools and methods of career guidance aimed at improving the effectiveness of choosing a future profession and reducing the risk of professional maladjustment. The materials of the article are prepared based on the use of methods of theoretical and structural analysis, focus groups, expert method, search modeling method, theoretical research (idealization, modeling, schematization,), methods of theoretical and structural analysis, structural semiotic analysis, predictive analytics and simulation based on neural network data and parsing.
Keywords: big data, professional orientation, pedagogical activity, machine learning, forecasting, education personalization
References:
1. Smyshlyayeva L. G., Titova G. Yu. Razvitiye regional’noy praktiki professional’noy oriyentatsii shkol’nikov na pedagogicheskuyu deyatel’nost’: strategiya i resursy [Development of regional practice of professional orientation of schoolchildren to teaching activities: strategy and resources]. Vestnik Tomskogo gosudarstvennogo pedagogicheskogo universiteta – Tomsk State Pedagogical University Bulletin, 2016, vol. 5 (170), pp. 36–41 (in Russian).
2. Malakhov V. V., Smyshlyayeva L. G. Big Data kak sredstvo povysheniya effektivnosti uchebnykh zanyatiy v kontekste razvitiya lichnostnogo potentsiala obuchayushchikhsya SPO [Big Data as a means of improving the effectiveness of training sessions in the context of the development of the personal potential of students]. Nauchno-pedagogicheskoye obozreniye – Pedagogical Review, 2022, vol. 4 (44), pp. 72–80 (in Russian). DOI: 10.23951/2307-6127-2022-4-72-80
3. Grigor’yev S. G., Anik’yeva M. A. Povysheniye effektivnosti primeneniya tekhnologiy generativnogo iskusstvennogo intellekta v obrazovatel’noy deyatel’nosti [Improving the effectiveness of the use of generative artificial intelligence technologies in educational activities]. Informatika i obrazovaniye, 2024, no. 3, pp. 5–15 (in Russian).
4. Fiofanova O. A. Big Data v rossiyskom obrazovanii: metody analiza dannykh ob obrazovanii i razvitii cheloveka, tsifrovyye servisy dannykh [Big Data in Russian education: methods of analyzing data on education and human development, digital data services]. Digital Society, 2020, no. 3, pp. 89–96 (in Russian).
5. Esin R. V., Kustitskaya T. A., Noskov M. V. Prognozirovaniye uspeshnosti obucheniya po distsipline na osnove universal’nykh pokazateley tsifrovogo sleda LMS moodle [predicting the success of learning in a discipline based on universal indicators of the LMS moodle digital footprint]. Informatika i obrazovaniye, 2023, no. 3, pp. 20–35 (in Russian).
6. Fiofanova O. A. Analiz bol’shikh dannykh v sfere obrazovaniya: metodologiya i tekhnologii [Big Data Analysis in education: methodology and technology]. Moscow, Delo Publ., 2020. No. 1. Pp. 123–140 (in Russian).
7. Osipovskaya E. A. Trendy obrazovatel’nykh tekhnologiy v Rossii i mire v 2020 g.: analiz poiskovykh zaprosov v Google Trends [Trends in educational technologies in Russia and the world in 2020: analysis of search queries in Google Trends]. Vestnik Rossiyskogo universiteta druzhby narodov – RUDN Journal, 2021, no. 4, pp. 291-304 (in Russian).
8. Bozieva A. M., Tseeva F. M., Khatukhova D. V. Primeneniye metodov mashinnogo obucheniya pri otsenke deyatel’nosti obrazovatel’noy organizatsii vysshey shkoly [The use of machine learning methods in evaluating the activities of an educational organization of a higher school]. Izvestiya Kabardino-Balkarskogo nauchnogo tsentra RAN – News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2023, no. 2, pp. 10–35 (in Russian).
9. Zabokritskaya L. D., Oreshkina T. A., Obabkov I. N., Chepurov E. G. Primeneniye algoritma mashinnogo obucheniya dlya proforiyentatsii abituriyentov vysshego uchebnogo zavedeniya [Application of a machine learning algorithm for career guidance of university applicants]. Vestnik Tomskogo gosudarstvennogo universiteta – Tomsk State University Journal, 2022, no. 2, pp. 57–72 (in Russian).
10. Strekalova N. B. Riski vnedreniya tsifrovykh tekhnologiy v obrazovaniye [The risks of introducing digital technologies into education]. Vestnik Samarskogo universiteta – Vestnik of Samara State University, 2019, no. 2, pp. 84–88 (in Russian).
11. Kolesova A. S., Sarayeva O. N. Perspektivy primeneniya iskusstvennogo intellekta v proforiyentatsionnoy deyatel’nosti [Prospects for the use of artificial intelligence in career guidance]. Kreativnaya ekonomika, 2023, vol. 17, no. 7, pp. 2475–2490 (in Russian).
12. Internet zhurnal Skillbox [Online magazine Skillbox] (in Russian). URL: https://skillbox.ru/media/business/onlayn_obrazovanie_posle_2020_goda_kakim_ono_budet_i_pochemu_eto_rabotaet/ (accessed 10 September 2024).
13. Prokhorov A. V. Sovremennyye podkhody k professional’noy oriyentatsii shkol’nikov [Modern approaches to the professional orientation of schoolchildren]. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnyye nauki, 2022, no. 2, pp. 102–114 (in Russian).
14. Pozdeeva S. I. Razrabotka kontseptsii otkrytogo professionalizma pedagoga kak issledovatel’skaya zadacha [Development of the concept of open professionalism of a teacher as a research task]. Vestnik Tomskogo gosudarstvennogo pedagogicheskogo universiteta – Tomsk State Pedagogical University Bulletin, 2016, vol. 1 (166), pp. 88–90 (in Russian).
15. Kalinyuk Yu. V., Smyshlyayeva L. G., Matveev D. M. Proyektirovaniye izmeneniy v sisteme professional’nogo obrazovaniya regiona: klasternyy podkhod [Designing changes in the region’s vocational education system: a cluster approach]. Nauchno-pedagogicheskoye obozreniye – Pedagogical Review, 2021, vol. 6 (40), pp. 84–94 (in Russian) DOI: 10.23951/2307-6127-2021-6-84-94
16. Zhurnal global’nogo analiza rynka obrazovaniya Holon IQ [Holon IQ Journal of Global Education Market Analysis] (in Russian). URL: https://www.holoniq.com/edtech/10-charts-that-explain-the-global-educationtechnology-market/ (accessed 10 September 2024).
17. Programma personalizirovannogo obucheniya Century [Century Personalized Learning Program] (in Russian). URL: https://www.century.tech/ (accessed 10 September 2024).
18. Programma adaptivnogo obrazovaniya Squirrelai [Squirrelmail Adaptive Education Program] (in Russian). URL: http://squirrelai.com/ (accessed 12 September 2024).
19. Poryadok upravleniya dannymi “VKontakte” [The procedure for managing VKontakte data] (in Russian). URL: https://vk.com/data_protection?section=principles (accessed 12 September 2024).
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Issue: 1, 2025
Series of issue: Issue 1
Rubric: METHODOLOGY AND TECHNOLOGY OF PROFESSIONAL EDUCATION
Pages: 56 — 65
Downloads: 133