Reframing artificial intelligence and learning analytics in emerging higher education: towards a human-centred and contextually responsive future

Source raw items (1)

• Semantic Scholar2026-08-02 07:15:28
  Reframing artificial intelligence and learning analytics in emerging higher education: towards a human-centred and contextually responsive future

  Artificial intelligence (AI) and learning analytics (LA) are increasingly used to enhance student outcomes and support institutional decision-making in higher education. However, evidence from emerging economies remains fragmented and unevenly distributed across regions. This critical scoping review synthesises current evidence on AI and LA implementation across higher education institutions in Latin America, Sub-Saharan Africa, South Asia, and the Middle East. The review followed the Joanna Briggs Institute Population-Concept-Context (PCC) framework and was reported in accordance with the PRISMA-ScR guidelines. Systematic searches of eight academic databases and selected grey literature sources identified 31 eligible publications published between 2019 and 2026. The evidence base comprised 20 empirical studies, 6 conceptual papers, and 5 policy or grey literature sources. To enhance transparency, studies were classified using a structured evidence-grading framework ranging from Grade A (high evidence) to Grade D (conceptual and policy evidence). Four dominant application areas emerged: predictive early-warning systems, adaptive learning platforms, generative AI tools, and institutional analytics dashboards. Considerable regional variation was identified. Latin America demonstrated comparatively greater implementation maturity, while Sub-Saharan Africa placed greater emphasis on governance, ethics, and data justice. South Asia showed strong technical sophistication but limited pedagogical integration, whereas evidence from the Middle East reflected predominantly early-stage implementation. Across all regions, evaluation focused primarily on technical performance, with comparatively limited attention given to educational impact, equity outcomes, and long-term sustainability. Through a three-stage analytical synthesis, the review develops the Human-Centred AI and Learning Analytics Implementation Framework (HCAI-LIF), comprising four interdependent dimensions: Governance, Pedagogy, Equity, and Sustainability. The review reframes AI and LA as socio-technical systems that require context-sensitive adaptation and responsible implementation rather than technology-driven adoption alone. The proposed framework provides an evidence-informed foundation for policymakers, institutional leaders, and researchers seeking to promote equitable, sustainable, and human-centred digital transformation in higher education across emerging economies.