Revolutionizing Nursing Education in Somalia: Recommendations for Integrating AI and Deep Learning in Outcome Based Assessments to Enhance Knowledge, Practice, and Graduate Competence
Fathi Yasin Yusuf, Abdiwali Mohamed Hussein · 2026
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Description
Fathi Yasin Yusuf and Abdiwali Mohamed Hussein argue in 2026 that artificial intelligence could strengthen how Somali nursing schools test whether graduates are truly competent. Nursing education there has expanded fast, but standards, licensing checks, and rural access have not kept pace.
Their commentary maps promising tools, including adaptive learning platforms, AI-supported simulation, and automated feedback on practice tasks, against the system's real constraints. Tools must run on low bandwidth, stay under teacher supervision, and follow clear ethical rules, they say. Introduced in phases and aimed at known gaps in standardisation and feedback, such systems could raise graduate competence more fairly across city and countryside.
Catalog record
| CREATOR | Fathi Yasin Yusuf, Abdiwali Mohamed Hussein |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 16 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |