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@article{194565,
        author = {Prof. Dr. Shaikh Imran Shaikh Ramzan},
        title = {Integrating Artificial Intelligence into Flipped Classrooms for Personalized, Data-Informed Active Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {5013-5021},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194565},
        abstract = {The flipped classroom model has emerged as a significant pedagogical innovation that relocates direct instruction to pre-class individual learning while allocating in-class time to collaborative, higher-order cognitive activities. Despite its documented benefits, the model continues to encounter notable challenges, including variability in student preparedness, limited opportunities for individualized learning pathways, and insufficient access to real-time learning analytics to inform evidence-based instructional decision-making.
This article proposes and elaborates a comprehensive conceptual model, the AI-Augmented Flipped Learning (AAFL) Framework designed to address key structural challenges of the traditional flipped classroom within diverse Indian educational settings through the systematic integration of Artificial Intelligence (AI) technologies across all stages of the teaching–learning process.
Based on a synthesis of recent empirical studies, established theories of learning, and emerging AI applications in education relevant to large and heterogeneous classrooms, the study develops a multi-phase framework that aligns specific AI-supported interventions with each stage of flipped learning: pre-class preparation, in-class collaborative engagement, and post-class reinforcement. Particular attention is given to issues of digital access, multilingual learners, and varied learner readiness commonly observed in Indian schools and higher education institutions.
The AAFL Framework identifies five key domains of pedagogical improvement, they are 
•	personalized learning support, 
•	Real-time feedback, 
•	enhanced learner engagement, 
•	Accessibility and Inclusion
•	teacher empowerment 
The AAFL Framework offers a practical and scalable roadmap for educators, teacher-training institutions, and universities seeking to implement AI-enabled flipped learning effectively across varied educational environments. Evidence indicates that AI-supported flipped learning can improve student preparedness, increase classroom participation in large class settings, and provide teachers with actionable analytics for data-informed and inclusive instructional practices. AI integration has the potential not only to enhance flipped classroom practices but also to address systemic challenges such as large class sizes, diverse learner needs, and limited instructional time prevalent in the Indian context.},
        keywords = {Flipped Classroom, Artificial Intelligence, Personalized Learning, Data-Driven Instruction, Active Learning, Adaptive Technology, Educational Technology},
        month = {March},
        }