Browsing by Author "Muhoza, B. Gloria"

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    A Mobile Based Technology to Improve Male Involvement in Antenatal Care.
    (Kabale University, 2024) Muhoza, B. Gloria; Ssemaluulu, Paul Mukasa; Mabirizi, Vicent
    The World Health Organization Technical Working Group on maternal health unit recommended a minimum level of care to be four visits throughout the pregnancy for pregnant mothers [1]. The first visit which is expected to screen and treat anaemia, and syphilis, screen for risk factors and medical conditions that can be best dealt with in early pregnancy and initiate prophylaxis if required (e.g., for anaemia and malaria) is recommended to be made before the end of the fourth month of pregnancy. The second, third and fourth visits are scheduled at 24–28, 32 and 36 weeks, respectively. Male involvement in Antenatal health care has been described as a process of social and behavioural change that is needed for men to play more responsible roles in maternal health care to ensure women's and children’s wellbeing. A study by Okoth [1] reported that, in Uganda, male involvement in antenatal care stands at only 6% and this has been attributed to social, economic and cultural related factors. The situation worsens with the lack of an effective coordinated platform for males sharing their experience in taking part in ANC and this has affected the process of antenatal care service delivery. Objective. To assess the role of mobile technology in improving male involvement in antenatal care by developing a mobile-based technology which sends SMS reminders to male partners encouraging them to escort their pregnant wives for antenatal care services. Research questions. What are the challenges towards the limited antenatal care-seeking behaviours among pregnant mothers? What are the causes of limited male involvement in antenatal care? What roles do ICTs play in enhancing Antenatal Care seeking behaviours among pregnant mothers and in increasing the male involvement in Antenatal Care? Method. We purposively selected pregnant mothers whose phones, had been receiving antenatal care services from Kabale General Hospital and reported staying with their male partners. The recruited participants were interviewed together with their male partners. STATA 13 software was used to define participants’ demographics while qualitative data were analysed using content analysis to come up with classes describing participants’ perceptions. Results. Participants reported that reminding them of their next antenatal visit via SMS reminder plays a significant role towards their antenatal care-seeking behaviour. Conclusion. Mobile health could be a potential approach to improving male involvement in antenatal care through sending timely SMS reminders to both the expectant mother and her male partner reminding them of their next antenatal visit.
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    Assessing the Effectiveness of Tools Used for Lecturer and Course Evaluation in Institutions of Higher Learning: A Case Study from Ugandan Universities.
    (Kabale University, 2024) Mabirizi, Vicent; Karungi, Monica; Murangira, Jones; Muhoza, B. Gloria; Mutebi, Michael; Mbago, Ronald; Kohabohebwa, John Ivan; Birungi, Ruth
    Blended learning, a pedagogical method integrating face-to-face and online instructions methodologies, has been identified as a strategic educational approach since its inception in the late 1990s. Moreover, its adoption especially in developing countries such as Uganda was widely recognized during the COVID-19 pandemic’s acceleration of digital learning adoption. However, this adoption has paused many challenges in evaluating learning content, teaching methodologies, and their impact on student progress. This study therefore, explores the critical role of quality assurance in higher education, focusing on the assessment of lecturer performance and course content. Apparently, paper-based mode of evaluation is the commonly used method in Ugandan universities, posing issues of privacy, delayed analytics, and ever-increasing operational costs. To address these challenges, this research proposes the development of an automated assessment system, informed by a benchmarking study across four universities. By adopting insights from existing evaluation practices, the proposed system aims to enhance the efficiency, accuracy, and students’ privacy during lecturer and course assessment. The implementation of this automated system at Kabale University promises to streamline evaluation process, ultimately enhancing teaching quality and academic outcomes.
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    Masked and unmasked Face Recognition Model Using Deep Learning Techniques. A case of Black Race.
    (Kabale University, 2023) Mabiriz,I, Vicent; Ampaire, Ray Brooks; Muhoza, B. Gloria
    Currently, many institutions of higher learning in Uganda are faced with major security threats ranging from burglary to cyber threats. Consequently, the institutions have recruited and deployed several trained personnel to offer the desired security. As human beings, these personnel can make errors either by commission or omission. To overcome the limitation of trained security personnel, many face recognition models that detect masked and unmasked faces automatically to allow access to sensitive premises have been developed. However, the state-of-the-art models are not generalizable across populations and probably will not work in the Ugandan context because they have not been implemented with capabilities to eliminate racial discrimination in face recognition. This study therefore developed a deep learning model for masked and unmasked face recognition based on local context. The model was trained and tested on 1000 images taken from students of Kabale University using a Nikon d850 camera. Machine learning techniques such as Principal Component Analysis, Geometric Feature-Based Methods, and double threshold techniques were used in the development phase while results were classified using CNN pre-trained models. From the results obtained, VGG19 achieved a higher accuracy of 91.2% followed by Inception V 3 at 90.3% and VGG16 at 89.69% whereas the developed model achieved 90.32%.