Faculty of Engineering, Design and Technology

Permanent URI for this communityhttps://hdl.handle.net/20.500.11951/793

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Browsing Faculty of Engineering, Design and Technology by Subject "Uganda"

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    A Framework for Improving Document Submission in Digital Institutional Repositories: A Case Study of Uganda Christian University
    (Uganda Christian University, 2025-05-26) Drake Tamale
    Digital institutional repositories (DIRs) serve as critical platforms for the preservation and dissemination of academic and research outputs. However, the document submission process in these repositories is often fraught with challenges such as manual data entry, system inefficiencies, and limited user training. This study aims to develop a comprehensive framework to enhance the document submission process in DIRs, addressing these challenges and improving overall user experience and system effectiveness. The primary objective of this study is to develop a framework for improving the document submission process in digital institutional repositories. Specific objectives include assessing the current state of document submission processes, determining the factors for improvement, and developing a framework based on these requirements. The study employed quantitative data collection techniques. A total of 158 questionnaires were distributed to participants, with a response rate of 94.9%. The demographic analysis revealed a diverse participant pool, with a majority holding bachelor's degrees (49%) and having some level of experience with DIRs. The assessment of the current submission process highlighted significant time spent on submissions, guided primarily by institutional policy (62%). System quality and information quality were identified as critical areas for improvement, with participants indicating the need for enhanced metadata workflows and effective error handling mechanisms. User satisfaction and individual impact metrics underscored the importance of training and system updates to improve performance and save time. The findings suggest that improving system quality, information quality, and user satisfaction can significantly enhance the document submission process in DIRs. The designed framework incorporates components such as metadata management, security and privacy measures, automated data entry, and error handling. These improvements are expected to streamline the submission process, reduce errors, and increase user efficiency and satisfaction. This study provides a comprehensive framework for improving document submission in digital institutional repositories. By addressing system inefficiencies and enhancing user experience, the proposed framework aims to facilitate more effective and efficient document management.
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    CONTEXTUALIZING AI ETHICS IN UGANDA’S MICROCREDIT WITH ADAPTIVE SENSITIVE REWEIGHTING
    (Uganda Christian University, 2025-08-12) Isabirye Emmanuel
    This research tackles the pressing ethical concerns of using Artificial Intelligence (AI) in Uganda’s microcredit sector, namely to develop an Adaptive Sensitive Reweighting (ASR) model to mitigate algorithmic bias and promote equitable access to credit. Traditional credit scoring models - and AI algorithms trained on Western-biased data - discriminate against marginalized groups because they are based on formal financial records, reinforcing structural disadvantages. By iterative engagement with Ugandan policymakers, lenders, borrowers, and AI experts, we identify the most significant ethical concerns and specify context-specific fairness metrics. The ASR approach adaptively adjusts weights for sensitive features like collateral values and transaction history during model training to enhance fairness. Experimental outcomes on a typical credit scoring dataset demonstrate ASR’s success: the inclusion rate of disadvantaged borrowers is enhanced by 15% with predictive accuracy maintained, and significant improvements on key fairness metrics. The research provides actionable policy recommendations on implementing ASR-based AI systems in Uganda’s microfinance sector to drive financial inclusion and sustainable development. This study contributes to emerging Majority World scholarship on AI ethics by demonstrating the necessity of situating ethical frameworks and valuing stakeholder perspectives to develop equitable, inclusive AI systems. Our findings offer valuable insights for policymakers, microfinance institutions, and AI practitioners who aim to implement responsible AI in Uganda’s Microcredit sector.