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@article{197202,
        author = {Amruta Kusumkar and Shravani Mulik and Shruti Bhoi and Srushti Mhaisane},
        title = {AI-Powered Personalized Learning: A Review of Intelligent Adaptive Educational Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {15827-15832},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197202},
        abstract = {Artificial Intelligence (AI) is transforming the global educational ecosystem through intelligent personalization. Unlike traditional educational systems that rely on rigid curricula and generalized teaching models, AI-powered personalized learning adapts content delivery, pacing, and assessments dynamically to individual learner needs. By integrating recommendation systems, conversational AI, multimodal learning analytics, and ethical frameworks, modern adaptive systems address pedagog- ical, technological, and social challenges simultaneously. This paper provides an extensive theoretical and technical review of intelligent adaptive educational systems (IAES), tracing their pedagogical roots, mapping their technical components, analyzing key literature, and outlining a vision for equitable and scalable future learning ecosystems. The work emphasizes the convergence of pedagogy and AI, underscoring how human-centered design, ethical safeguards, and AI-driven intelligence can reshape how knowledge is acquired and applied globally.},
        keywords = {Personalized Learning, Adaptive Systems, Recom- mendation, Transformer Chatbot, Learning Analytics, Educational Technology, Cognitive Theory, Fairness in AI},
        month = {April},
        }