Flipped Classroom 2.0 Integration of AI Assistants into the Model of Student Independent Preparation

Munavvarkhon Mukhitdinova

doi:10.59022/IRSHAD-ujldp.9

Authors

Munavvarkhon Mukhitdinova Tashkent State University of Law Author

DOI:

https://doi.org/10.59022/IRSHAD-ujldp.9

Keywords:

Flipped Classroom, Generative Artificial Intelligence, Independent Preparation, Self-Regulated Learning, Academic Integrity, Legal Education, Student Autonomy

Abstract

Artificial intelligence assistants are changing how students prepare before class. This shift raises questions about effort, depth, and independent reasoning. This study examines AI assistants within the flipped classroom preparation stage specifically. It aims to identify how preparation time, self-regulation, and understanding change under this influence. A qualitative doctrinal design guided the research, supported by document analysis. Materials included legal sources, institutional policies, and recent scholarly literature. Results show faster preparation, stronger self-regulation among weaker students, and reduced reasoning depth. They also reveal an emerging division of responsibility between students and AI tools. The study recommends structured task design that preserves independent judgment alongside efficiency gains. Institutions should require justification steps that reveal genuine student reasoning during preparation. These findings support balanced, rule-based integration rather than unrestricted or prohibited AI use. The research contributes a structural framework for responsible preparation design. Legal education particularly benefits from protecting reasoning practice within this evolving preparation model.

References

Adamakis, M., & Rachiotis, T. (2025). Artificial intelligence in higher education: A state-of-the-art overview of pedagogical integrity, artificial intelligence literacy, and policy integration. Encyclopedia, 5(4), 180. https://doi.org/10.3390/encyclopedia5040180

Ahmad Radzuan, F. A., Mohd Arif, M., & Ab. Rahman, N. K. (2026). Artificial intelligence in flipped class-rooms for enhancing vocabulary acquisition and retention in primary ESL education. Arab World English Journal, 17(2), 32–48. https://doi.org/10.24093/awej/vol17no2.3

Allah Rakha, N. (2023). The impacts of Artificial Intelligence (AI) on business and its regulatory challenges. International Journal of Law and Policy, 1(1). https://doi.org/10.59022/ijlp.23

AllahRakha, N. (2025). AI and corruption: Legal liability in algorithmic decision-making. Access to Justice in Eastern Europe, 8(3), 303–326. https://doi.org/10.33327/AJEE-18-8.3-a000120

Asad, M. M., Soomro, S., Nawab, A., & Almusharraf, N. (2026). Impact of artificial intelligence driven flipped classroom to enhance students' self-regulated learning: Innovative practices from the context of Pakistan. Learning Futures and Emerging Technologies. Advance online publication. https://doi.org/10.1108/LFET-03-2025-0029

Bach, N. D., & Le, H. T. (2026). Artificial intelligence-supported flipped learning in information technology education: Quasi-experimental evidence on programming performance, learning autonomy, reflective learning, and digital competence. Frontiers in Education, 11, 1907387. https://doi.org/10.3389/feduc.2026.1907387

Belda-Medina, J., & Calvo-Ferrer, J. R. (2022). Using chatbots as AI conversational partners in language learning. Applied Sciences, 12(17), 8427. https://doi.org/10.3390/app12178427

Civit, M., Escalona, M. J., Cuadrado, F., & Reyes-de-Cozar, S. (2024). Class integration of ChatGPT and learning analytics for higher education. Expert Systems, 41(12), e13703. https://doi.org/10.1111/exsy.13703

Deng, Y., et al. (2026). A systematic review of design thinking implementations in higher education: Fostering self-directed learning and AI integration. European Journal of Engineering Education, 51(1), 45–67. https://doi.org/10.1080/03043797.2026.2640060

Diwanji, P., Hinkelmann, K., & Witschel, H. F. (2018). Enhance classroom preparation for flipped classroom using AI and analytics. In Proceedings of the 20th International Conference on Enterprise Information Systems (pp. 477–483). SciTePress. https://doi.org/10.5220/0006807604770483

ElGamal, H. (2025). Towards a flipped learning ecosystem: A generative artificial intelligence-enabled framework. European Journal of Open, Distance and E-Learning, 28(1), 151. https://doi.org/10.65043/eurodl.151

Fütterer, T., Bardach, L., Kuhn, J., & Scheuer, C. (2026). Enhancing school students' self-regulated learning through generative AI support: A randomized controlled trial. Educational Psychology Review, 38(4), 42. https://doi.org/10.1007/s10648-026-10133-8

Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI in education. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692

Han, I., Ji, H., Jin, S., & Choi, K. (2025). Mobile-based artificial intelligence chatbot for self-regulated learning in a hybrid flipped classroom. Journal of Computing in Higher Education. Advance online publication. https://doi.org/10.1007/s12528-025-09434-8

Hilliger, I., et al. (2026). A GAI-based chatbot for scaffolding self-regulated learning. Journal of Learning Analytics, 13(1), 1–20. https://doi.org/10.18608/jla.2026.9143

Hu, Y. H. (2025). Advancing asynchronous pre-class learning in flipped classrooms: Generative AI compan-ions in business ethics. Education and Information Technologies, 30(10), 25853–25880. https://doi.org/10.1007/s10639-025-13379-x

Khalil, H., Alfazari, S., Eid, M., Hassan, A. M., Kamal, A. A., & Khatiry, A. (2026). Human and AI support in higher education: A hybrid model for an enhanced learning experience. Frontiers in Education, 11, 1772646. https://doi.org/10.3389/feduc.2026.1772646

Kwan, P., Kadel, R., Memon, T. D., & Hashmi, S. S. (2025). Reimagining flipped learning via Bloom's taxonomy and student–teacher–GenAI interactions. Education Sciences, 15(4), 465. https://doi.org/10.3390/educsci15040465

Lee, Y. F., Hwang, G. J., & Chen, P. Y. (2025). Technology-based interactive guidance to promote learning performance and self-regulation: A chatbot-assisted self-regulated learning approach. Educational Technology Research and Development, 73, 2279–2304. https://doi.org/10.1007/s11423-025-10478-x

Lo, C. K., & Hew, K. F. (2023). A review of integrating AI-based chatbots into flipped learning: New possibilities and challenges. Frontiers in Education, 8, 1175715. https://doi.org/10.3389/feduc.2023.1175715

López-Villanueva, D., et al. (2024). Flipped learning and artificial intelligence. Electronics, 13(17), 3424. https://doi.org/10.3390/electronics13173424

Moulavinafchi, A., Alhaideri, S. A. A., & Alfawwaz, S. N. M. (2026). The impact of an AI-powered flipped classroom on grammar competence and language anxiety in EFL learners. International Journal of In-struction, 19(1), 105–130. https://doi.org/10.29333/iji.2026.1916a

Namaziandost, E. (2025). Integrating flipped learning in AI-enhanced language learning: Mapping the effects on metacognitive awareness, writing development, and foreign language learning boredom. Computers and Education: Artificial Intelligence, 9, 100446. https://doi.org/10.1016/j.caeai.2025.100446

Nguyen, H., et al. (2026). Supporting self-regulated learning in the age of artificial intelligence: A chatbot-fueled metalinguistic guidance approach. Journal of Educational Computing Research, 64(2), 145–168. https://doi.org/10.1177/07356331261450647

Peng, Y., Awang, M. M., & Yaccob, N. S. (2026). AI literacy in English language education: A systematic review from a social ecological perspective. Education Sciences, 16(8), 1182. https://doi.org/10.3390/educsci16081182

Perakaki, E., & Doi, C. (2025). Exploring flipped learning practices in piano and music theory: Fostering self-directed learning and AI integration. Research Studies in Music Education, 47(1), 88–105. https://doi.org/10.1177/1321103X251342708

Qassrawi, R., & Al Karasneh, S. (2026). AI-supported interactive flipped learning in language education: A multidimensional perspective. Education Sciences, 16(8), 1304. https://doi.org/10.3390/educsci16081304

Saydullayeva, S. (2025). The impact of artificial intelligence on personalized learning in a flipped classroom model. The Eurasia Proceedings of Educational and Social Sciences, 41, 44–52. https://doi.org/10.55549/epess.895

Silitonga, L. M., Wiyaka, Suciati, S., & Prastikawati, E. F. (2024). The impact of integrating AI chatbots and microlearning into flipped classrooms: Enhancing students' motivation and higher-order thinking skills. Lecture Notes in Computer Science, 14786, 184–193. https://doi.org/10.1007/978-3-031-65884-6_19

Suciati, S., Silitonga, L. M., & Anggara, A. A. (2026). Gender and AI in flipped classrooms: Unpacking the impact of chatbots on engagement, self-efficacy, writing performance, and technology affinity. SAGE Open, 16(1). https://doi.org/10.1177/21582440261420014

Tan, X., Cheng, G., & Ling, M. H. (2025). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education: Artificial Intelligence, 8, 100355. https://doi.org/10.1016/j.caeai.2024.100355

Tang, V. (2026). Integrating tailored generative AI into the flipped classroom: A pilot implementation in higher education. Innovative Higher Education. Advance online publication. https://doi.org/10.1080/14703297.2025.2523898

Tseng, Y. C., & Lin, Y. H. (2024). Enhancing English as a foreign language (EFL) learners' writing with ChatGPT: A university-level course design. Electronic Journal of e-Learning, 22(2), 78–97. https://doi.org/10.34190/ejel.21.5.3329

Villarosa, R. D., Jr. (2024). Exploring college students' awareness and use of AI-enhanced flipped classroom models: Impacts on learning outcomes and skills development. International Research Journal of Science, Technology, Education, and Management, 4(4), 99–113. https://doi.org/10.5281/zenodo.14744850

Wang, X., & Li, X. (2026). Designing a flipped AI-chatbot learning module to support students' environmental literacy development: A Fuzzy Delphi Method. PLoS ONE, 21(3), e0345027. https://doi.org/10.1371/journal.pone.0345027

Wiyaka, W., Silitonga, L. M., Sunardi, S., & Pramudi, Y. T. C. (2024). From nervous to fluent: The impact of AI chatbot-assisted assessment on English reading anxiety and performance in Indonesia. Theory and Practice in Language Studies, 14(12), 3851–3860. https://doi.org/10.17507/tpls.1412.20

Wu, X. Y., et al. (2025). Designing artificial intelligence chatbots for self-regulated learning in hybrid flipped classrooms. Interactive Learning Environments. Advance online publication. https://doi.org/10.1080/10494820.2025.256308

Yavuz, M., Balat, Ş., & Kayalı, B. (2025). The effects of artificial intelligence supported flipped classroom applications on learning experience, perception, and artificial intelligence literacy in higher education. Open Praxis, 17(2), 286–304. https://doi.org/10.55982/openpraxis.17.2.811

Yilmaz, M., Gauthier, A., & Cukurova, M. (2026). Supporting online learners' regulation skills with the help of learning analytics and generative artificial intelligence. Educational Technology Research and Development, 74(6), 1223–1252. https://doi.org/10.1007/s11423-026-10595-1

Youssef, E., et al. (2024). Examining the effect of ChatGPT usage on students' learning outcomes in flipped classrooms. Computers and Education: Artificial Intelligence, 7, 100250. https://doi.org/10.1016/j.caeai.2024.100250

Zarrinabadi, N., et al. (2026). Understanding the role of competition beliefs and learning motivation in self-directed flipped learning environments. European Journal of Psychology of Education, 41(2), 345–367. https://doi.org/10.1007/s10212-026-01157-3

Zhang, J. (2025). Integrating chatbot technology into English language learning to enhance student engagement and interactive communication skills. Journal of Computational Methods in Sciences and Engineering, 25(1), 1–12. https://doi.org/10.1177/14727978241312992

Zhang, J., Deng, X., Wu, T., & Wang, K. (2026). GenAI-supported flipped learning in preservice chemistry teacher education: Lesson-design performance, learning attitude, self-regulated learning, and critical thinking awareness. Behavioral Sciences, 16(4), 514. https://doi.org/10.3390/bs16040514