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<p>The rapid expansion of AI in education is driving a significant transformation in higher education and workforce development by enabling personalized learning and skill building. However, synthesised evidence on how Generative Artificial Intelligence (GenAI) tools are implemented, experienced, and contested across diverse institutional contexts—particularly higher education in developing countries—remains fragmented. Addressing this gap, this study conducts a meta-synthesis of empirical research to investigate the role of GenAI tools in supporting personalized learning and transformative skill development, the socio-technical challenges that constrain equitable adoption, and the strategies that enable inclusive and sustainable integration. Following PRISMA guidelines, a systematic search of major databases identified peer-reviewed qualitative studies. Thematic synthesis was employed to integrate findings across diverse institutional and country contexts. The findings indicate that GenAI can enhance learner-driven personalization, cognitive and affective skill development, and perceived employability when embedded within intentional pedagogical designs and supported by human–AI collaboration. However, the findings also reveal persistent challenges, including overreliance and cognitive offloading, ethical ambiguity, academic integrity concerns, institutional inertia, professional strain, and structural inequalities related to infrastructure, access, and AI literacy. Building on these insights, the study advances an inclusive and equity-driven, layered framework for GenAI integration that conceptualizes infrastructure as a foundational condition, governance as a facilitating layer, and pedagogy as the application layer. The study concludes that GenAI’s educational impact is not only technologically determined but also socially and institutionally facilitated. Sustainable and equitable GenAI adoption depends on aligning technological innovation with ethical governance, professional capacity building, and pedagogically grounded human–AI collaboration.</p>

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Harnessing generative artificial intelligence for personalized learning and transformative skill development in higher education in developing-country contexts

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月6日

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  • Shouket Ahmad Tilwani,
  • Yalalem Assefa,
  • Anas Ali Alhur,
  • Isa Spahiu,
  • Bekalu Tadesse Moges,
  • Suzana Ejupi,
  • Huda Majeed

摘要

The rapid expansion of AI in education is driving a significant transformation in higher education and workforce development by enabling personalized learning and skill building. However, synthesised evidence on how Generative Artificial Intelligence (GenAI) tools are implemented, experienced, and contested across diverse institutional contexts—particularly higher education in developing countries—remains fragmented. Addressing this gap, this study conducts a meta-synthesis of empirical research to investigate the role of GenAI tools in supporting personalized learning and transformative skill development, the socio-technical challenges that constrain equitable adoption, and the strategies that enable inclusive and sustainable integration. Following PRISMA guidelines, a systematic search of major databases identified peer-reviewed qualitative studies. Thematic synthesis was employed to integrate findings across diverse institutional and country contexts. The findings indicate that GenAI can enhance learner-driven personalization, cognitive and affective skill development, and perceived employability when embedded within intentional pedagogical designs and supported by human–AI collaboration. However, the findings also reveal persistent challenges, including overreliance and cognitive offloading, ethical ambiguity, academic integrity concerns, institutional inertia, professional strain, and structural inequalities related to infrastructure, access, and AI literacy. Building on these insights, the study advances an inclusive and equity-driven, layered framework for GenAI integration that conceptualizes infrastructure as a foundational condition, governance as a facilitating layer, and pedagogy as the application layer. The study concludes that GenAI’s educational impact is not only technologically determined but also socially and institutionally facilitated. Sustainable and equitable GenAI adoption depends on aligning technological innovation with ethical governance, professional capacity building, and pedagogically grounded human–AI collaboration.