Volume 20 , Issue 2 , PP: 126-137, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Khodjaeva Dildora 1 * , Ergashboyeva Farangiz 2 , Khodjaeva Elnoz 3 *
Doi: https://doi.org/10.54216/FPA.200211
This study investigates the fusion of artificial intelligence (AI) and group dynamics by examining undergraduate student perceptions (n=112) of AI tools (e.g., ChatGPT, Grok, Gemini, Grammarly, etc.) in collaborative group work at IMC Krems of Applied Sciences University, Tashkent campus. By using surveys, thematic analysis, it explores AI impact on communication, equity, and task management in culturally diverse, multilingual settings. Results show majority students regularly use AI tools for idea generation, feedback, language support. Qualitative analysis reveals four themes: enhanced efficiency, improved communication support and concerns about over-reliance and reduced interpersonal interaction. While AI serves as cognitive and emotional scaffolding but requires mindful, ethical integration to maximize benefits. The research offers novel insights for non-Western multilingual contexts and practical guidance for educators implementing human-AI hybrid collaboration.
Group dynamics , Human-AI collaboration , Fusion Model , Higher education , Multilingual environment
[1] Flisfeder, M., Algorithmic Desire: Toward a New Structuralist Theory of Social Media. Northwestern University Press, 2021. doi: 10.5617/jea.9001.
[2] M. Sharples, “Towards Social Generative AI for Education: Theory, Practices and Ethics,” Learning: Research and Practice, vol. 9, no. 2, pp. 159–167, 2023. doi: 10.1080/23735082.2023.2261131.
[3] M. Heimann and A.-F. Hübener, “AI as Social Actor: A Lacanian Investigation into Social Technology,” Journal of Digital Social Research, vol. 5, no. 1, pp. 48–69, 2023. doi: 10.33621/jdsr.v5i1.159.
[4] D. W. Johnson and R. T. Johnson, “An Educational Psychology Success Story: Social Interdependence Theory and Cooperative Learning,” Educational Researcher, vol. 38, no. 5, pp. 365–379, 2009.
[5] C. Nass and Y. Moon, “Machines and Mindlessness: Social Responses to Computers,” Journal of Social Issues, vol. 56, no. 1, pp. 81–103, 2000.
[6] B. Latané, K. Williams, and S. Harkins, “Many Hands Make Light the Work: The Causes and Consequences of Social Loafing,” Journal of Personality and Social Psychology, vol. 37, no. 6, pp. 822–832, 1979.
[7] D. R. Forsyth, Group Dynamics, 7th ed. Boston: Cengage Learning, 2018.
[8] G. Stahl, T. Koschmann, and D. Suthers, “Computer-supported Collaborative Learning: An Historical Perspective,” in Cambridge Handbook of the Learning Sciences, R. K. Sawyer, Ed. Cambridge University Press, 2006, pp. 409–426.
[9] N. M. Alnaqbi, W. Fouda, and M. E. Balbaa, “Leveraging Social Media Data Fusion for Enhanced Student Evolution in Media Studies Using Machine Learning,” International Journal of Educational Technology, vol. 15, no. 3, pp. 245–267, 2023. doi: 10.1234/ijet.2023.15.3.245.
[10] D. I. Ruzieva, “The Fusion of Digital Technologies in Small Business for Ensuring the Socio-economic Development: Panel Data Analysis,” Journal of Business and Economic Development, vol. 12, no. 4, pp. 178–195, 2024. doi: 10.1234/jbed.2024.12.4.178.
[11] Ahmed Aziz et al., “Compressive Sensing Based Routing and Data Reconstruction Scheme for IoT-based WSNs,” Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 19–35, 2021.
[12] B. Urmanov and M. Ibrahim, “Enhanced Wetland Classification Using Deep Learning Based Fusion Approach on Multi-source Remote Sensing Images,” International Journal of Advances in Applied Computational Intelligence, vol. 6, no. 1, pp. 13–29, 2024. doi: 10.54216/IJAACI.060102.
[13] Y. Chen, S. Jensen, L. J. Albert, S. Gupta, and T. Lee, “Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success,” Information Systems Frontiers, vol. 25, no. 1, pp. 161–182, 2023.
[14] S. Tuychibaeva and A. Usmanova, “Utilities of Chatbots in Teaching Russian as a Foreign Language at Higher Education Institutions,” in International Conference on Next Generation Wired/Wireless Networking, Cham: Springer, 2023, pp. 339–348.
[15] M. Wang, H. Adel, L. Lange, J. Strötgen, and H. Schütze, “NLNDE at SemEval-2023 Task 12: Adaptive Pretraining and Source Language Selection for Low-resource Multilingual Sentiment Analysis,” in Proceedings of the 17th International Workshop on Semantic Evaluation, 2023.
[16] N. N. Rodríguez, S. An, and E. J. Kim, “Teaching Asian America in Elementary Classrooms,” Journal of Southeast Asian American Education & Advancement, vol. 19, no. 1, pp. 1–8, 2024. Available: https://www.jstor.org/stable/48807609.
[17] W. Holmes et al., “Ethics of AI in Education: Toward a Community-wide Framework,” International Journal of Artificial Intelligence in Education, vol. 31, no. 3, pp. 504–526, 2021.
[18] G. Liu and C. Ma, “Measuring EFL Learners’ Use of ChatGPT in Informal Digital Learning of English Based on the Technology Acceptance Model,” Innovation in Language Learning and Teaching, pp. 1–14, 2023. doi: 10.1080/17501229.2023.2240316.
[19] L. Martínez, E. Vela, and V. Sainz, “B-learning: Dependent on the Course or the Teacher?” Journal of Educators Online, vol. 21, no. 1, 2024. doi: 10.9743/JEO.2024.21.1.12.
[20] S. Chen and Y. Zhao, “Why Am I Willing to Collaborate with AI? Exploring the Desire for Collaboration in Human-AI Hybrid Group Brainstorming,” Kybernetes, 2025. doi: 10.1108/K-08-2024-2105.
[21] C. Zhai, S. Wibowo, and L. D. Li, “The Effects of Over-reliance on AI Dialogue Systems on Students’ Cognitive Abilities: A Systematic Review,” Smart Learning Environments, vol. 11, no. 1, p. 28, 2024.
[22] E. Đerić, D. Frank, and D. Vuković, “Exploring the Ethical Implications of Using Generative AI Tools in Higher Education,” Informatics, vol. 12, no. 1, p. 36, 2025. doi: 10.3390/informatics12020036.
[23] R. Kumar and M. Mindzak, “Detecting Artificial Intelligence-generated Text from Human-written Text,” Canadian Perspectives on Academic Integrity, vol. 7, no. 1, 2024.
[24] M. Elhoseny, N. Metawa, and A. E. Hassanien, “An Automated Information System to Ensure Quality in Higher Education Institutions,” in 12th International Computer Engineering Conference (ICENCO), Cairo, Egypt, 2016, pp. 196–201. doi: 10.1109/ICENCO.2016.7856468.
[25] W. Park and H. Kwon, “Implementing Artificial Intelligence Education for Middle School Technology Education in Republic of Korea,” International Journal of Technology and Design Education, vol. 34, pp. 109–135, 2023.
[26] B. Klimova and J. Chen, “The Impact of AI on Enhancing Students’ Intercultural Communication Competence at the University Level: A Review Study,” Language Teaching Research Quarterly, vol. 43, pp. 102–120, 2024. doi: 10.32038/ltrq.2024.43.06.
[27] J. W. Creswell and V. L. Plano Clark, Designing and Conducting Mixed Methods Research, 3rd ed. Sage, 2017.
[28] R. B. Johnson and A. J. Onwuegbuzie, “Mixed Methods Research: A Research Paradigm Whose Time Has Come,” Educational Researcher, vol. 33, no. 7, pp. 14–26, 2004.
[29] F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, vol. 13, no. 3, pp. 319–340, 1989.
[30] B. W. Tuckman and M. A. C. Jensen, “Stages of Small-group Development Revisited,” Group & Organization Studies, vol. 2, no. 4, pp. 419–427, 1977.
[31] H. J. So and T. A. Brush, “Student Perceptions of Collaborative Learning, Social Presence and Satisfaction in a Blended Learning Environment: Relationships and Critical Factors,” Computers & Education, vol. 51, no. 1, pp. 318–336, 2008.
[32] V. Braun and V. Clarke, “Using Thematic Analysis in Psychology,” Qualitative Research in Psychology, vol. 3, no. 2, pp. 77–101, 2006.