Involvement in the Use of Mobile Devices as a Factor in Adolescents' Perception of Artificial Intelligence Capabilities
https://doi.org/10.18384/2949-5105-2025-1-109-128
Abstract
Aim. To find the relationship between engagement in mobile technology use and adolescents' perceptions of artificial intelligence (AI) capabilities.
Methodology. The study involved 385 adolescents aged 11 to 18 years (50.9% were girls). The methods used were the questionnaire of identifying the forms of mobile device use, the phubbing scale, the author's questionnaire of perception of AI capabilities, and methods of descriptive, comparative, correlation and factor analysis.
Results. The study found that adolescents' interactions with new digital technologies are mediated by gender, stage of schooling, and age of first gadget ownership. It was revealed that adolescent engagement in gadget use is associated with the perception of a wider range of opportunities to interact with AI technologies.
Research implications. The value of findings is conditioned by the possibility of taking the results into account when developing programs to support digital socialization of schoolchildren
Keywords
involvement,
perception,
gadgets,
artificial intelligence,
mobile devices,
adolescents,
digital behavior
Supporting agencies: This work has been supported by the Russian Science Foundation (RSF), grant no. 23-28-00412, https://rscf.ru/project/23-28-00412.
About the Authors
Yu. L. Proekt
Herzen State Pedagogical University of Russia
Russian Federation
Russian Federation
Yulia L. Proekt – Cand. Sci. (Psychological Sciences), Assoc. Prof., Department of Psychology of Professional Activity and IT in Education
Moika Embankment, 48, Saint Petersburg, 191186
E. B. Spasskaya
Herzen State Pedagogical University of Russia
Russian Federation
Russian Federation
Elena B. Spasskaya – Cand. Sci. (Pedagogical Sciences), Assoc. Prof., Department of Preschool Pedagogy
Moika Embankment, 48, Saint Petersburg, 191186
References
1. Bogacheva N. V., Sivak E. V. [Myths about “Generation Z”] In: Sovremennaya analitika obrazovaniya [Modern Analytics of Education], 2019, no. 1, pp. 2–64.
2. Duggan S. Artificial Intelligence in Education: Changing the Pace of Learning. UNESCO IITE Policy Brief (Rus. ed., Parshakov A. V., transl. Iskusstvennyj intellekt v obrazovanii: Izmenenie tempov obucheniya. Analiticheskaya zapiska IITO YUNESKO. Moscow, UNESCO Institute for Information Technologies in Education, 2020. 45 p.).
3. Konstantinova L. V., Vorozhihin V. V., Petrov A. M. [Generative Artificial Intelligence in Education: Theory and Forecasts]. In: Otkrytoe obrazovanie [Open Education], 2023, vol. 27, no. 2, pp. 36–48. DOI: 10.21686/1818-4243-2023-2-36-48.
4. Koroleva D. O. [Study of everyday life of modern teenagers: connection to social networks as a recording component of communication]. In: Sovremennaya zarubezhnaya psihologiya [Modern Foreign Psychology], 2016, vol. 5, no. 2, pp. 55– 61. DOI: 10.17759/ jmfp.2016050207.
5. Koroleva D. O. [Always online: use of mobile technologies and social networks by modern teenagers at home and at school]. In: Voprosy obrazovaniya [Education Issues], 2016, no. 1, pp. 205–224. DOI: 10.17323/1814-9545-2016-1-205-224.
6. Panov V. I., Borisenko N. A., Mironova K. V. [Teenager's behavior in a digital education environment: defining concepts and posing problems]. In: Izvestiya Saratovskogo universiteta. Novaya seriya. Seriya: Akmeologiya obrazovaniya. Psihologiya razvitiya [Bulletin of the Saratov University. New series. Series: Acmeology of education], 2021, no. 3 (39), pp. 188–196. DOI: 10.18500/2304-9790-2021-10-3-188-196.
7. Svetlichnyj E. G., Hamgokov M. M., Shabaev V. V. [Improving the educational process at school using digital platforms based on artificial intelligence]. In: Problemy sovremennogo pedagogicheskogo obrazovaniya [Problems of modern pedagogical education], 2022, no. 74-2, pp. 207–209.
8. Soldatova G. U., Chigarkova S. V., Ilyuhina S. N. [Technologically extended personality: development and testing of the measure of the principle of digital everyday life]. In: Vestnik Moskovskogo universiteta. Seriya 14. Psihologiya [Bulletin of Moscow University. Series 14. Psychology], 2024, no. 47 (2), pp. 175–200. DOI: 10.11621/LPJ-24-20.
9. Filkina O. M., Kocherova O. Yu., Boboshko A. V. [Gender features of adolescent internet activity and the relationship with health and wealth]. In: Vestnik Ivanovskoj medicinskoj akademii [Bulletin of the Ivanovo Medical Academy], 2023, no. 28 (4), pp. 16–22.
10. Chen C., Zhang K. Z., Gong X. Examining the effects of motives and gender differences on smartphone addiction. In: Computers in Human Behavior, 2017, no. 75, pp. 891–902. DOI: 10.1016/j.chb.2017.07.002.
11. Coll C. G., Szalacha L. A. The multiple contexts of middle childhood. In: The future of children, 2004, no. 14 (2), pp. 80–97. DOI: 10.2307/1602795.
12. Guan J., Zhang J., Zhang X. The Influence of Generative Artificial Intelligence on High School Students’ Academic Planning – ChatGPT. In: Lecture Notes in Education Psychology and Public Media, 2023, no. 24, pp. 205–210. DOI: 10.54254/2753-7048/24/20230705.
13. Hu X, Fang Y, Liang Y. Roles and Effect of Digital Technology on Young Children’s STEM Education: A Scoping Review of Empirical Studies. In: Education Sciences, 2024, no. 14 (4). Available at: https://www.mdpi.com/2227-7102/14/4/357 (accessed: 10.10.2024). DOI: 10.3390/educsci14040357
14. Humble N., Mozelius P. Artificial intelligence in education – a promise, a threat or a hype? In: P. Griffiths and M. N. Kabir, ed. Proceedings of the European Conference on the impact of artificial intelligence and robotics / 31 October – 1 November 2019. Oxford, EM-Normandie Business School, 2019. P. 149–156.
15. Ibabe I., Albertos A., Lopez-Del Burgo C. Leisure time activities in adolescents predict problematic technology use. In: European Child and Adolescent Psychiatry, 2023, no. 33, pp. 279–289. DOI: 10.1007/s00787-023-02152-5.
16. Lim W. M., Gunasekara A., Pallant J. L. Generative AI and the future of education: Ragnarok or reformation? A paradoxical perspective from management educators. In: The International Journal of Management Education, 2023, no. 21 (2). Available at: https://www. sciencedirect.com (accessed: 10.10.2024). DOI: 10.1016/j.ijme.2023.100790.
17. Nah F., Zheng R., Cai J. Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. In: Journal of Information Technology Case and Application Research, 2023, no. 25, pp. 277–304. DOI: 10.1080/15228053.2023.2233814.
18. Özer M. Potential Benefits and Risks of Artificial Intelligence in Education. In: Bartın University Journal of Faculty of Education, vol. 13, no. 2, pp. 232–244.
19. Rodríguez-Ruiz J. Marín-López I., Espejo-Siles R. Is artificial intelligence use related to self-control, self-esteem and self-efficacy among university students? In: Education and Information Technologies, 2024, pp. 2–18. DOI: 10.1007/s10639-024-12906-6.
20. Russell A. L. Six Stages for Learning To Use Technology. Research Report No. ED 397832). In: Proceedings of selected research and development and presentations at the 1996 national convention of the association for educational communications and technologies. Australia, Queensland University of Technology Publ., 1996, pp. 633–643.
21. Skavronskaya L., Hadinejad A., Cotterell D. Reversing the threat of artificial intelligence to opportunity: a discussion of ChatGPT in tourism education. In: Journal of Teaching in Travel & Tourism, 2023, no. 23 (2), pp. 253–258. DOI: 10.1080/15313220.2023.2196658.
22. Skilton M., Hovsepian F. The 4th Industrial Revolution: Responding to the Impact of Artificial Intelligence on Business. Cham, Springer Publ., 2017. 322 p.
23. Xia X., Qin S., Zhang S. Leisure experience and mobile phone addiction: Evidence from Chinese adolescents. In: Heliyon, 2024, no. 10 (3). Available at: 10.1016/j.heliyon.2024.e24834 (accessed: 10.10.2024).
24. Xiao W., Wu J., Yip J. The relationship between physical activity and Mobile phone addiction among adolescents and young adults: systematic review and Meta-analysis of observational studies. In: JMIR public health and surveillance, 2022, no. 8 (12). Available at: https://pmc. ncbi.nlm.nih.gov (accessed: 12.10.2024). DOI: 10.2196/41606.
25. Zhai X., Chu X., Chai C. S. A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. In: Complexity, 2021, no. 1, pp. 2–18. DOI: 10.1155/2021/8812542.
Supplementary files
Review
Views:
118
Email this article 