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КОНЦЕПЦИЯ ПСИХОЛОГИЧЕСКОГО МОНИТОРИНГА, ПРОГНОЗИРОВАНИЯ И УПРАВЛЕНИЯ ПСИХИЧЕСКИМ РАЗВИТИЕМ ДЕТЕЙ В ИГРОВОЙ АДАПТИВНОЙ СРЕДЕ НА ОСНОВЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ДОШКОЛЬНОЙ ОБРАЗОВАТЕЛЬНОЙ ОРГАНИЗАЦИИ

Vol. 5 No. 24 (2026): Innovative Research in the Modern World 76-83

DOI: 10.5281/zenodo.21786417 2026-07-31 Articles Open Access

Authors

  • Д. Ж. Камолдинова В.д. доцент PhD (доктор философии по педагогическим наукам) Преподаватель кафедры педагогики, психологии и физической культуры Андижанский филиал «Кокандского университета», Республика Узбекистан

Abstract

В статье представлена целостная теоретико-методологическая концепция психологического мониторинга, прогнозирования и управления психическим развитием детей дошкольного возраста в условиях адаптивной игровой среды, функционирующей на базе технологий искусственного интеллекта (ИИ). Актуальность исследования обусловлена необходимостью преодоления фрагментарности традиционных диагностических подходов и переходом к непрерывному, экологичному и персонализированному отслеживанию когнитивного, эмоционально-волевого и социального развития ребенка. На основе системного, деятельностного и субъектного подходов разработана концептуальная архитектура интеллектуальной платформы, интегрирующей адаптивный игровой контент с алгоритмами машинного обучения для динамической оценки зоны ближайшего развития. В работе детально описаны механизмы непрерывной экспрессивной и поведенческой диагностики, методы предиктивного моделирования траекторий развития, а также алгоритмы выработки управленческих решений для педагогов-психологов и воспитателей.

Keywords:

References

Baker, R. S., & Inventado, P. S. (2024). Educational data mining and learning analytics: Applications to early childhood and adaptive systems. Journal of Educational Technology & Society, 27(1), 45–62.

Holmes, W., Bialik, M., & Fadel, C. (2023). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.

Kulkarni, S., et al. (2023). Multimodal machine learning for assessing early childhood development in interactive environments. Computers & Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2023.100118

Luckin, R., et al. (2022). Intelligence Unleashed: An argument for AI in education. EdTech Review, 15(3), 112–129.

OECD. (2022). Smart Data in Childhood Education: Opportunities and Challenges. OECD Publishing, Paris.

OECD. (2025). Fostering Social-Emotional Skills in the Digital Age. OECD Education Working Papers, No. 312.

UNESCO. (2021). AI and Education: Guidance for Policy-Makers. UNESCO Publishing. https://doi.org/10.54675/PYAN1256

UNESCO. (2023). Guidance on Generative AI in Education and Research. UNESCO, Paris.

UNICEF. (2021). Policy Guidance on AI for Children. UNICEF Office of Global Insight and Policy.

UNICEF. (2024). Digital Futures: Ethical Frameworks for AI in Early Childhood. UNICEF Innocenti Research Centre.

American Psychological Association (APA). (2022). Guidelines for the use of technology in psychological assessment and evaluation. American Psychologist, 77(8), 912–928.

American Psychological Association (APA). (2024). Ethical considerations in AI-driven developmental tracking for children. Developmental Psychology, 60(4), 541–555.

Al-Emran, M., et al. (2023). The role of artificial intelligence in shaping the future of early childhood education: A systematic review. Education and Information Technologies, 28(6), 7215–7244. https://doi.org/10.1007/s10639-022-11456-w

Bers, M. U. (2021). Beyond Coding: How Children Learn Human Values through Technology. MIT Press. https://doi.org/10.7551/mitpress/13511.001.0001

Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510

Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications.

Dede, C., & Richards, J. (2020). The 60-Year Curriculum: A Strategic Response to a Changing World. Routledge. https://doi.org/10.4324/9781003050964

Edwards, L., et al. (2023). Young children's interactions with AI-enabled toys and learning environments: A developmental perspective. British Journal of Educational Technology, 54(2), 410–428. https://doi.org/10.1111/bjet.13280

Flowerdew, J. (2022). Academic Discourse. Routledge.

Hyland, K. (2019). Discourse and Knowledge: A Sociocognitive Approach to Academic Discourse. Cambridge University Press. https://doi.org/10.1017/9781108649353

Johnson, J. E., Christie, J. F., & Wardle, F. (2022). Play, Development, and Early Education (2nd ed.). Pearson.

Khodadadi, M., et al. (2024). Predictive modeling in early childhood interventions using machine learning techniques. Computers in Human Behavior, 150, 107982. https://doi.org/10.1016/j.chb.2023.107982

Livingstone, S., & Stoilova, M. (2021). The digital childhood: Designing digital environments for children's rights and well-being. New Media & Society, 23(11), 3241–3258. https://doi.org/10.1177/14614448211029272

McTigue, E. M., & Ricketts, J. (2023). Conceptual frameworks in educational and psychological research. Educational Psychologist, 58(2), 89–104.

National Association for the Education of Young Children (NAEYC). (2022). Technology and Interactive Media as Tools in Early Childhood Programs Serving Children from Birth through Age 8. NAEYC Position Statement.

Puentedura, R. R. (2020). SAMR and Beyond: Transforming Educational Technology Integration. Academic Press.

Resnick, M. (2020). Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play. MIT Press. https://doi.org/10.7551/mitpress/11799.001.0001

Selwyn, N. (2021). Education and Technology: Key Issues and Debates (3rd ed.). Bloomsbury Academic.

Shvets, I., et al. (2023). Intelligent adaptive systems in preschool pedagogy: Theoretical framework and practical implications. International Journal of Child-Computer Interaction, 36, 100570. https://doi.org/10.1016/j.ijcci.2023.100570

Smuha, N. A. (2021). From ethics to policy: Turning artificial intelligence ethics into EU law. The Oxford Handbook of Ethics of AI, 53–78. https://doi.org/10.1093/oxfordhb/9780198857853.013.3

Vygotsky, L. S. (2020). Mind in Society: The Development of Higher Psychological Processes (New ed. with commentary by M. Cole et al.). Harvard University Press (Original work published 1978).

Williamson, B., & Eynon, R. (2020). Historical trajectories, epistemic futures: Speculative data futures in education. Learning, Media and Technology, 45(4), 318–332. https://doi.org/10.1080/17439884.2020.1793386

Zimmerman, B. J. (2021). Attaining self-regulation: A social cognitive perspective. In Handbook of Self-Regulation (pp. 13–39). Academic Press.

Zosh, J. M., et al. (2022). Learning through play: A review of evidence and a proposed conceptual framework. Oxford Review of Education, 48(5), 624–644. https://doi.org/10.1080/03054985.2022.2045437

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2026-07-31

How to Cite

Камолдинова, Д. Ж. (2026). КОНЦЕПЦИЯ ПСИХОЛОГИЧЕСКОГО МОНИТОРИНГА, ПРОГНОЗИРОВАНИЯ И УПРАВЛЕНИЯ ПСИХИЧЕСКИМ РАЗВИТИЕМ ДЕТЕЙ В ИГРОВОЙ АДАПТИВНОЙ СРЕДЕ НА ОСНОВЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ДОШКОЛЬНОЙ ОБРАЗОВАТЕЛЬНОЙ ОРГАНИЗАЦИИ. Innovative Research in the Modern World, 5(24), 76-83. https://doi.org/10.5281/zenodo.21786417
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