Evaluating the Performance of AI-Based Software Tools in Intelligent Decision-Making Systems

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   Trusted digital identities sit at the heart of any modern, inclusive financial system. This paper investigates Somalia’s transition from a fragmented digital landscape to a secure, integrated ecosystem through the lens of a “Three Pillars” framework: Robust Digital Identity, Comprehensive ICT Policy, and Proactive Cybersecurity Safeguards. Utilizing a qualitative multi-method approach, the study triangulates fifteen semi-structured interviews with regulators, financial experts, and civil society against a rigorous analysis of foundational policies, including the Data Protection Act (2023) and the Cybersecurity Law (2026). Results indicate that Somalia’s digital identity ecosystem—comprising e-Aqoonsi, HUBIYE, and the Certificate Delivery System (CDS)—serves as a technical anchor for financial inclusion, significantly bolstered by a July 2025 Central Bank mandate requiring National IDs for all banking transactions. These tools are supported by legal scaffolding under the Data Protection Authority and proactive security guardrails provided by the Somalia Computer Incident Response Team (SOMCIRT). However, comparative analysis reveals that while Somalia has achieved technical parity with East African Community (EAC) peers in biometric capabilities, it remains an outlier due to its reliance on foreign data hosting, which poses risks to national data sovereignty. To realize Somalia’s Centennial Vision 2060, the study concludes that the nation must bridge implementation gaps in rural digital literacy and technical capacity while transitioning toward local data infrastructure. The paper proposes a strategic roadmap for regional harmonization and enhanced institutional coordination to sustain

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2. Journal article2026Published PDF

   Self-efficacy and instructor support as determinants of ChatGPT effectiveness in student learning

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   The rapid integration of generative artificial intelligence (AI) tools, such as ChatGPT, is reshaping learning experiences in higher education. However, the psychological and instructional conditions under which these tools enhance academic success remain insufficiently understood, particularly in low resource contexts. Using survey data from 286 university students in Somalia, this study investigates how ChatGPT usage influences students’ academic performance and learning outcomes, with particular attention to the mediating roles of academic self-efficacy and cognitive engagement (mental effort), and the moderating role of instructor support. Drawing on the Technology Acceptance Model, Social Cognitive Theory, and Cognitive Load Theory, eight hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that ChatGPT usage significantly enhances learning outcomes, self-efficacy, and cognitive engagement; however, its direct effect on academic performance is not statistically significant, suggesting that performance gains do not occur automatically from AI use. Mediation analysis reveals that self-efficacy significantly mediates the relationship between ChatGPT usage and academic performance, whereas cognitive engagement does not. Furthermore, instructor support significantly moderates the relationship between cognitive engagement and academic performance, strengthening the translation of mental effort into achievement. Overall, the findings highlight the critical role of psychological empowerment and instructional support in unlocking the educational benefits of generative AI, particularly in resource constrained higher education contexts.

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3. Journal article2025Published PDF

   The role of over-reliance on AI in the negative consequences of student learning: The moderating effects of ethical concerns and institutional policies

   Abubakar S., Jeilani A., Yusuf M. — Cogent Education, Volume 12, Issue 1, Article 2591503, 2025

   This study investigates the impact of over-reliance on artificial intelligence (AI) in educational settings and its negative consequences on student learning, focusing on the moderating effects of ethical concerns and institutional policies. As students increasingly depend on AI tools, potential risks to critical thinking and engagement may arise. Understanding these dynamics is essential for educators and policymakers to develop strategies that mitigate the adverse effects of AI dependence. The research utilizes a quantitative approach, surveying undergraduate and postgraduate students from major universities in Mogadishu. A sample size of 226 participants was determined using G*Power for a linear multiple regression analysis. Findings reveal significant relationships between AI over-reliance, ethical concerns, and institutional policies, indicating that while AI can enhance educational experiences, its misuse poses risks, including diminished analytical skills and ethical dilemmas such as academic dishonesty and data privacy issues. The study highlights a gap between existing institutional policies and student confidence in their effectiveness, suggesting the need for improved communication and implementation. The regression analysis confirms that robust ethical frameworks and comprehensive policies can alleviate some adverse impacts of AI reliance. This research offers a novel contribution by empirically examining the moderating roles of ethics and institutional governance in a post-conflict higher education context, where AI policy infrastructure is still developing. Recommendations include promoting a balanced integration of AI tools, enhancing ethical awareness through workshops, and establishing clear institutional policies regarding AI usage. Furthermore, continuous evaluation of AI’s impact on learning outcomes is vital for fostering responsible educational practices and ensuring that technology enhances, rather than hinders, student learning.

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