ArticleJournal of multidisciplinary healthcare2026
Revolutionizing Nursing Education in Somalia: Recommendations for Integrating AI and Deep Learning in Outcome Based Assessments to Enhance Knowledge, Practice, and Graduate Competence.
Article in Journal of multidisciplinary healthcare, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Artificial intelligence (AI) and deep learning hold significant potential to strengthen outcome-based assessment in Somali nursing education. Somalia's nursing education system faces critical challenges including inadequate standardization, uneven competency assessment, urban-rural disparities in access, limited faculty capacity, and weak governance. Outcome-based education offers a governance mechanism to define and measure graduate competencies, but its full benefit depends on robust assessment tools. This commentary examines how AI and deep learning can strengthen outcome-based assessment frameworks in Somali nursing schools, identifies the most impactful applications including adaptive learning platforms, AI-enhanced simulation, and automated formative assessment, maps these to Somalia's documented structural constraints, and proposes context-adapted recommendations for phased, faculty-supervised, and ethically governed implementation. The central argument is that AI and deep learning add the most value when introduced as low-bandwidth, contextually appropriate tools that directly address existing gaps in standardization, feedback, and equitable access rather than as stand-alone technologies.
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