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<PublisherName>ejsss</PublisherName>
<JournalTitle>ELECTRONIC JOURNAL OF SOCIAL AND STRATEGIC STUDIES</JournalTitle>
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<EISSN/>
<Volume-Issue>Volume 6 Issue 1</Volume-Issue>
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<IssueTopic>Multidisciplinary</IssueTopic>
<IssueLanguage>English</IssueLanguage>
<Season>Apr-May 2025</Season>
<SpecialIssue>N</SpecialIssue>
<SupplementaryIssue>N</SupplementaryIssue>
<IssueOA>Y</IssueOA>
<PubDate>
<Year>2025</Year>
<Month>05</Month>
<Day>31</Day>
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<ArticleType>Political Science</ArticleType>
<ArticleTitle>Integrating Artificial Intelligence in Regional Education: A Holistic Framework for Inclusive, Adaptive, and Community-Centric Learning</ArticleTitle>
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<ArticleLanguage>English</ArticleLanguage>
<ArticleOA>Y</ArticleOA>
<FirstPage>26</FirstPage>
<LastPage>45</LastPage>
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<Author>
<FirstName>Sandeep</FirstName>
<LastName>Lopez</LastName>
<AuthorLanguage>English</AuthorLanguage>
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<CorrespondingAuthor>N</CorrespondingAuthor>
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<DOI>10.47362/EJSSS.2025.6102 </DOI>
<Abstract>This research explores the integration of Artificial Intelligence (AI) into regional education through a holistic framework designed to address challenges of inclusivity, cultural relevance, and accessibility. The study emphasizes a multidimensional approach incorporating localized content development, adaptive learning systems, teacher support tools, inclusion features, and community engagement. Guided by educational theories like constructivism, Universal Design for Learning (UDL), and community-based participatory research (CBPR), the model proposes leveraging AI-driven technologies such as natural language processing, adaptive algorithms, and assistive tools to create culturally aligned and personalized learning pathways. The study highlights the transformative potential of AI to bridge systemic educational gaps, particularly in marginalized and under-resourced regions. Pilot programs are proposed to evaluate the feasibility of AI-driven localized education in multilingual and low-tech settings. Ethical considerations, such as algorithmic bias and data privacy, are addressed to ensure equity and sustainability. Key findings indicate that integrating AI with community-led initiatives significantly enhances learner engagement, retention, and inclusivity. The study concludes with recommendations for policy frameworks, scalable implementation strategies, and future research avenues to refine the integration of AI into global education systems. By aligning cutting-edge AI capabilities with cultural and societal contexts, the proposed framework aspires to make education truly inclusive, equitable, and accessible for all.</Abstract>
<AbstractLanguage>English</AbstractLanguage>
<Keywords>AI in education,adaptive learning systems,inclusive education,community engagement,localized content,educational equity</Keywords>
<URLs>
<Abstract>https://ejsss.net.in/ubijournal-v1copy/journals/abstract.php?article_id=15740&title=Integrating Artificial Intelligence in Regional Education: A Holistic Framework for Inclusive, Adaptive, and Community-Centric Learning</Abstract>
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<References>
<ReferencesarticleTitle>References</ReferencesarticleTitle>
<ReferencesfirstPage>16</ReferencesfirstPage>
<ReferenceslastPage>19</ReferenceslastPage>
<References>Arya, R., and; Verma, A. (2024). Role of Artificial Intelligence in Education. International Journal of Advanced Research in Science, Communication and Technology. http://doi.org/10.48175/ijarsct-19461
Bilous, V. (2019). Basic principles for developing an adaptive learning system. Open Educational E-Environment of Modern University. http://doi.org/10.28925/2414-0325.2019s3
Chevalier, J. M., and; Buckles, D. J. (2013). Participatory action research: Theory and methods for engaged inquiry. Routledge.
Chisom, O. N., Unachukwu, C. C., and; Osawaru, B. (2024). Review of AI in Education. International Journal of Applied Research in Social Sciences. http://doi.org/10.51594/ijarss.v5i10.725
Ejjami, R. (2024). The Future of Learning: AI-Based Curriculum Development. International Journal For Multidisciplinary Research. http://doi.org/10.36948/ijfmr.2024.v06i04.24441
Elifas, T. N., and; Simuja, C. (2024). The Pedagogical Insights of Mathematics Teachers Integrating AI in Rural Schools. Interdisciplinary Journal of Education Research. http://doi.org/10.38140/ijer-2024.vol6.37
Er-Radi, H., Aammou, S., and; Jdidou, A. (2023). Personalized learning through adaptive content modification. Conhecimento and; Diversidade. http://doi.org/10.18316/rcd.v15i39.11153
Guskey, T. R. (2002). Professional development and teacher change. Teachers and Teaching: Theory and Practice, 8(3/4), 381-391.
Hollan, J., Hutchins, E., and; Kirsh, D. (2000). Distributed cognition: Toward a new foundation for human-computer interaction research. ACM Transactions on Computer-Human Interaction (TOCHI, 7(2), 174-196.
Holman, K., Marino, M., Vasque, T., Taub, M., Hunt, J., and; Tazi, Y. (2024). Navigating AI-powered personalized learning in special education. Journal of Special Education Preparation. http://doi.org/10.33043/5b2xqcb3
Israel, B. A., Schulz, A. J., Parker, E. A., and; Becker, A. B. (1998). Review of community-based research: Assessing partnership approaches to improve public health. Annual Review of Public Health, 19(1), 173-202.
Khamis, M. A. (2015). Adaptive e-learning environment systems and technologies.
Khosravi, H., Sadiq, S., and; Gaand;scaron;evi?, D. (2020). Development and adoption of an adaptive learning system. Proceedings of the 51st ACM Technical Symposium on Computer Science Education. http://doi.org/10.1145/3328778.3366900
Luckin, R. (2018). Machine Learning and Human Intelligence. UCL Press.
Majki?, Z., and; Vranjeand;scaron;, D. (2024). The Integration of Artificial Intelligence Across Educational Levels. 10th International Scientific Conference Technics, Informatic, and Education. http://doi.org/10.46793/tie24.391m
Maravanyika, M., Dlodlo, N., and; Jere, N. (2017). An adaptive recommender-system-based framework for personalized teaching and learning. 2017 IST-Africa Week Conference (IST-Africa). http://doi.org/10.23919/ISTAFRICA.2017.8102297
Meadows, D.H. (2008) Thinking in systems: A primer. Chelsea Green, White River Junction.
Meyer, A., Rose, D. H., and; Gordon, D. (2014). Universal design for learning: Theory and practice. CAST Professional Publishing. http://castpublishing.org
Onesi-Ozigagun, O., Ololade, Y. J., and; Eyo-Udo, N. L. (2024). Revolutionizing education through AI. International Journal of Applied Research in Social Sciences. http://doi.org/10.51594/ijarss.v6i4.1011
Osadcha, K., Osadchyi, V., and; Semerikov, S. (2020). The review of the adaptive learning systems.
Piaget, J. (1950). The psychology of intelligence. London: Routledge.
Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. Simon and Schuster. http://simonandschuster.com
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning.
Simonsen, J., and; Robertson, T. (2012). Routledge international handbook of participatory design. Routledge.
Shershneva, V., Vainshtein, Y., and; Kochetkova, T. (2019). Technological approach to development of adaptive e-learning system. SHS Web of Conferences. http://doi.org/10.1051/SHSCONF/20196601014
UNESCO. (2023). Global education monitoring report.
Vainshtein, J., Esin, R., and; Tsibulsky, G. (2021). Learning content model: From concept structuring to adaptive learning. Open Education. http://doi.org/10.21686/1818-4243-2021-1-4-28-39
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Van Dijik, AGM. (2006) Digital divide research, achievements and shortcomings. Poetics, 34, 221-235. https://doi.org/10.1016/j.poetic.2006.05.004
Wiener, N. (1948). Cybernetics: Or control and communication in the animal and the machine. MIT Press.</References>
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