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Machine Learning Adoption Among Technopreneurs in Gweru, Zimbabwe
(Great Zimbabwe University, 2025) Chapwanya Natsai; Munthali Akim
This paper explored the present condition, operating challenges and facilitators of Artificial Intelligence (AI) and Machine Learning (ML) among Technopreneurs at Gweru, a secondary city in Zimbabwe. The research incorporated the use of qualitative exploratory design and Technology-Organization-Environment (TOE) framework in which semi-structured interviews were held with 23, purposely sampled, Technopreneurs in different fields. The results showed that there is a young-adoption environment, with merely 26 percent of Technopreneurs already taking action with AI/ML, and 35 percent are still in the investigative stages. The sectoral analysis showed that there was more implementation in fintech (37.5) and strong exploration in agritech (30%). The greatest impediments identified were infrastructural constraints which were common and presented as an untrustworthy power, an expensive and slow internet, and expensive cloud service. The other impediments were critical knowledge gaps that require informal learning and lack of familiarity with AI/ML ventures by investors. On the other hand, collaborative peer learning networks, resource sharing and incremental adoption models became some of the important enablers. Specifically, the paper has emphasized the exponential nature of an "AI divide" necessitated by computational needs and suggested locally based suggestions, such as the creation of AI hubs, the development of local cloud infrastructure, formalizing training and mentorship, and training investors on how to faster accelerate AI-based Technopreneurship. This study bridged a significant gap in the
knowledge on AI/ML adoption outside of main sources of innovation in emerging economies.
Framework for the Upskilling for the 4th Industrial Revolution: Challenges, Curriculum and the Way Forward
(Great Zimbabwe University, 2025) Mafukidze Harry D.; Sadock Brian; Chitiza Kennedy; Nechibvute Action
The Fourth Industrial Revolution (4IR or Industry 4.0) presents a significant shift in the operation of industries and economies. It is a manufacturing paradigm that integrates cyber-physical systems, artificial intelligence (AI), robotics, and the Internet of Things (IoT) to create more intelligent, connected industrial systems. Unlike previous industrial revolutions, 4IR offers unprecedented advances, enabling machines to learn, adapt, and make decisions in manufacturing environments. However, operating, maintaining, and integrating these emerging technologies requires dedicated skill sets to thrive in this new landscape. The purpose of this work is to develop a pedagogical framework to promote key skills needed for the fourth industrial revolution and the implementation of its curriculum in tertiary education institutions in Zimbabwe. Quantitative and qualitative data were collected via stakeholder engagements, online surveys, and interviews with educators and captains of industry. This study developed a comprehensive framework for 4IR education within tertiary institutions from four skill sets: general, soft skills, hard skills, and critical skills. The framework will play a key role in the effective upskilling of communities in the 4IR, especially those in low-resource Sub Saharan regions
Towards a comprehensive framework for enablers and inhibitors of bad news reporting on software projects in state universities in Zimbabwe
(Great Zimbabwe University, 2025) Maseko Melody; Tsokota Theo
Software project status reporting is critical in software project management, yet team members often find it easier to report positive news than negative progress. This research investigates the ‘mum effect’, which refers to the reluctance to report bad news on software projects by project team members. Silence on project bad news has remained a major contributor to project failure in higher learning institutions. This study, therefore, aimed to come up with a framework for the inhibitors and enablers of bad news reporting by project team members on specific academic and administrative software projects within state universities in Zimbabwe. Naturally, it is easier to report positive news than negative progress encountered during the software project life cycle. Following a qualitative, multiple-holistic case study approach, this research employed focus group discussions and key informant interviews with project managers, team members, and system users from three state universities in Zimbabwe. The findings indicate that the main enablers of bad news reporting include open communication, a positive organisational culture, and feedback and motivation to achieve. On the other hand, the results suggest that the main inhibitors of bad news reporting include a lack of communication, fear of punishment, an unfair distribution of work, and a lack of skills. The findings of this study can help institutions understand the
dynamics at play in status reporting for software projects. Results from this study contribute to the body of knowledge theoretically and, practically, to status reporting on software
project development in institutions of higher learning. This reduces the chances of software project failure and escalation.
Introduction: Computational Intelligence and Mathematical Modelling for Industry and Commerce
(Great Zimbabwe University, 2025) Nyawo Zvidenga Vongai
g/0000-0003-2603-2273
Abstract - Between July 29 and July 31, 2025, GreatZimbabwe University’s School of Natural Sciences hosted its second International Conference on Computational Intelligence and Mathematics Modelling for Industry and Commerce, themed ‘Unlocking the Potential of the Fourth Industrial Revolution in Knowledge Work.’ The conference venue was the Victoria Falls Safari Lodge in Victoria Falls, Zimbabwe. The Minister of Higher and Tertiary Education, Honourable Dr Fredrick Shava, was the guest of Honour. The theme of the conference reflected the imperative to recalibrate the intellectual framework to respond to technological disruptions in the educational space. Great Zimbabwe University, as a Zimbabwean institution, is alert to the urgency of contextualizing the disruption within the national development agenda. The government of Zimbabwe, through flagship policies such as Heritage Based Education 5.0 and National Development Strategy 1, repositioned universities as engines of industrial transformation and national development. What this means is that institutions of higher learning go beyond teaching and learning, embrace innovation and industrialization. It is in this breath that the 2025 conference was relevant and apt. The fields of Computational Intelligence and Mathematical Modelling are emergent foundational academic disciplines to the implementation of Education 5.0.
Human Anatomy and Physiology TSPE122-2
(Great Zimbabwe University, 2025) GZU Past Examination Paper