Journal Articles

Permanent URI for this collectionhttp://erepository.kibu.ac.ke/handle/123456789/9624

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Feasibility, acceptance, and workflow integration of an AI- enabled clinical decision support system for non- communicable diseases in Kiambu County, Kenya: A mixed- methods implementation evaluation
(Open Research Africa, 2026-02-28) Kamau, David; Mbuguah, Samuel Mungai; Omondi, Protus; Kamau, Gideon; Mbugua, George; Ngugi, Rosslyn; Ngure, Jane; Ngaruiya, Njeri; Wamaitha, Nicole; Munene, Joan; Maina, Njogu; Gitaka, Jesse
Background Non-communicable diseases (NCDs), particularly hypertension and diabetes, impose a growing burden on health systems in low- and middle- income countries like Kenya. Artificial intelligence (AI)-driven Clinical Decision Support Systems (CDSS) may enhance diagnostic accuracy and adherence to clinical guidelines, yet their feasibility and acceptability among frontline clinicians in real-world settings underexplored. Methods We conducted a mixed-methods implementation study in 10 health facilities in Kiambu County, Kenya. The evaluation comprised three components. First, a retrospective review of 1,929 patient records established baseline NCD prevalence and care patterns. Second, we assessed the clinical acceptance of the NCDAI platform, an AI-CDSS using a Large Language Model with Retrieval-Augmented Generation, through 300 independent expert physician reviews of its recommendations. Third, we captured clinician perspectives via a cross-sectional Knowledge, Attitudes, and Practices (KAP) survey (n=29) and key-informant interviews (n=11). Results The baseline cohort demonstrated a substantial NCD burden: 72.8% had a history of hypertension and 43.1% had diabetes. Expert validation showed high acceptance of AI-generated recommendations, with 67.0% “Agreed,” 26.3% “Partially Agreed,” and only 6.7% “Disagreed,” yielding 93.3% overall (partial or full) agreement. Most disagreements arose in medication and treatment plan recommendations. Clinicians demonstrated strong digital readiness; 86% reported moderate or good IT proficiency, and 69% were already aware of AI in healthcare. Patient-related factors were the most commonly cited barriers to NCD care (33%). Qualitative findings identified operational challenges particularly duplicative data entry arising from parallel paper-based workflows as the main impediment to NCDAI adoption amid high patient volumes. Conclusions An AI-driven CDSS for NCD management is feasible and highly acceptable to expert physicians and frontline clinicians in Kenya. The key barrier is not reluctance toward AI but workflow friction. Effective scale-up will require investment in digital infrastructure to enable seamless integration and replacement of paper-based systems
Modeling User Experience with Universities Websites Based on Webometric Ranking User Analysis
(International Journal of Computer Trends and Technology (IJCTT), 2020-04-27) Mukanda, Adeline; Mbuguah, Samuel Mungai; Wabwoba, Franklin; Aselemo, Peters Ikoha
The paper sets posits that Universities are ranked globally based on their web presence. The web crawler accesses the universities websites to collect data on presence, visibility, openness, and excellence. These data is then used to rank the Universities based on set criteria. The paper identifies design issues that may affect website ranking. The paper identifies as a gap lack of user analysis model for university website and recommends a study of the same.
Framework for Evaluation of Effectiveness of Integrated Financial Management Information Systems Architecture Implemented in Public Hospitals in Kenya
(International Journal of Scientific Research in Science, Engineering and Technology, 2020-12-12) Afwande, Margaret; Mbuguah, Samuel Mungai; Kilwake, Juma
Integrated Financial Management Information System (IFMIS), is an enterprise resource planning application that captures all functional processes and relevant financial flows within Public expenditure management. IFMIS is being adopted by the Public hospitals to promote efficiency, effectiveness, accountability, transparency, security of data management and comprehensive reporting. However the Public hospitals are loosing a lot of money through scandals and this has compromised service delivery to the Public. Therefore, the purpose of this study was to investigate the effectiveness of IFMIS as used in Public procurement services in Public Hospitals in Kenya and come up with an enhanced secure technical architecture. The objectives of the study were: to asses the extent to which IFMIS has been implemented in Public procurement services in Public hospitals in Kenya, to evaluate the effectiveness of IFMIS in enforcing logical access and technical controls in Public procurement services in Public Hospitals in Kenya and to develop a framework that will evaluate the effectiveness of IFMIS architecture that is implemented in Public procurement services in Public hospitals in Kenya .The study used mixed method research design targeting users of IFMIS. Stratified sampling was used to select the target population of 132 in 4 hospitals in Kenya. The target population was from 5 homogeneous stratum comprising of 44 Procurement Assistants, 36 Finance Assistants, 12 Audit Assistants, 28 Medical Practioneers and 12 ICT Staff. Proportional allocation method was used to calculate the sample size which was 99 respondents. The data was collected through questionnaires and direct observation. Content validity was done to ascertain the validity of the research instruments. Reliability of the instruments was carried out using test- retest technique. Internal consistence of data was computed using Cronbach Alpha Computation. Analysis of Quantitative and qualitative data was through descriptive and inferential statistics methods and content analysis respectively. The study developed a framework of enhanced technical architecture of IFMIS that would streamline procurement services in Public hospitals and improve provision of quality health care.
Webometrics User Ranking Analysis Model Development and Validation
(International Journal of Computer and Organization Trends, 2022-04-26) Mukanda, Adeline; Mbuguah, Samwel Mungai; Wabwoba, Franklin
The webometrics user ranking analysis model was developed and validated. The need for the model arose as directorates of ICT in Kenyan Universities were assigned the challenge of improving their university's webo ranking. Webo ranking is the preferred method of the universities to showcase their niche and what they do to the global community. There are no published models for webometrics ranking. This leads to each university taking different approaches. In this paper, a model has been developed and validated.
Leveraging P2P Architecture and Semantic Web for Enhanced Resource Discovery
(International Journal of Scientific Research in Science, Engineering and Technology, 2024-05-18) Kirui, Leonard K.; Mbuguah, Samuel Mungai; Ronoh, Richard K.
Web 4.0, also known as the next generation, intelligent internet, possesses the potential to become a widely and universally used communication medium for various types of information. However, its decentralized architecture lacks strong semantic support, resulting in an internet that is disorganized. The current system lacks the capacity to facilitate users' effective information discovery, extraction, and integration from multiple sources. Additionally, it fails to give consumers efficient tools for manipulating and turning acquired data into knowledge that is useful. Peer-to-peer (P2P) overlay technologies have recently come to light as a way to improve resource discovery on the internet. In dynamic and large- scale situations, these technologies provide a scalable framework for allocating, sharing, and gaining access to resources. The purpose of this research is to discuss on semantically enabled web architecture that makes use of P2P overlay technology. This architecture aims to facilitate structured and precise access to internet resources and promote knowledge sharing among community members who share similar interests. The paper examines the core elements of the semantic web architecture, which encompass the services and protocols responsible for resource advertising, discovery, and management, methods and material. It then delve into the hybrid peer-to-peer (P2P) overlay structure, specifically focusing on indexing and resource location, and explores the mechanisms necessary to facilitate scalable routing within a distributed environment.
A Fuzzy Ontological Model for Semantic Interoperability in Distributed Healthcare Information Systems
(International Journal of Research and Innovation in Applied Science, 2025-01-17) Okemwa, Joshua; Owoche, Patrick Oduor; Mbuguah, Samuel Mungai
The exchange of patient or care data across heterogeneous health systems is crucial in the modern healthcare ecosystem yet remains daunting. Integration and interoperability in siloed health applications require robust health information exchange (HIE) and a pragmatic ontological model to be successful. This paper details a prototype development endeavor and systematic review of literature that has pioneered the development of a robust, practical, and tested fuzzy ontological model to enhance semantic interoperability in siloed, distributed health systems. Leveraging the tenets, standards, LOINC codes, and developed model from this study will enable robust and flexible data mapping and sharing health data in an environment marred with ambiguities and uncertainties but requiring the sophistry of interoperability
Evaluating AI-Blockchain–IoT Capabilities and Effects on Transparency in Kenyan Seed Supply Chain
(International Journal of Scientific Research in Science, Engineering and Technology, 2025-09-06) Ronoh, Lilian Cherotich; Mbuguah, Samuel Mungai; Ronoh, Richard K.
Agricultural sector plays a very crucial role in Kenyan national economy and within it, is the seed sector which is it’s driver and sustainer. Despite the strides that have been made towards digitalization of the seed sector, still, there are challenges facing it, one of them being lack of transparency. This has resulted in farmers purchasing counterfeit seeds which have adverse effects on the overall crop yields and great financial losses to farmers. This study sought to evaluate the capabilities and the effects of integrating AI-Blockchain-IoT technologies to improve transparency within the seed supply chain. Data was collected from KALRO and KSC staff, farmers and agro-dealers through questionnaires and interviews and data analyses carried out were both descriptive and inferential. Findings revealed varying perceptions on the capabilities of these technologies which show that more awareness needs to be done to enlighten the stakeholders on the benefits of these technologies as well as benefits of their integration. In addition, the findings on the effects revealed that integration of AI-Blockchain-IoT technologies has a statistically significant positive effect on transparency in the seed supply chain. This study contributes to practice by providing insights into technologies that can enhance transparency so that all stakeholders can have clear visibility and access to information on the entire seed supply chain operations.
Map of the Various Configuration Attributes from IPv4 to IPv6 Networks for Dual Stack, 6to4 Tunnelling and NAT: Modelling Designs in OPNET Modeller
(International Journal of Computer Science and Mobile Computing, 2018-07-26) Barasa, Samuel W.; Mbuguah, Samuel Mungai; Karume, Simon M.
This paper presents a performance evaluation study of dual stack, 6to4 tunnelling, and Network Address Translation transition schemes on simulative method in IPv4/IPv6 networks. This research aims to find out what IPv4/IPv6 transition scheme performs better in terms of performance parameters packet losses, delays, segment delays, query response times, packet delay variations, packet end-to-end delays, jitters, mean opinion score value, and traffic sent and received for data, voice and video traffic. An equal capacity of network load in terms of probes for the three scenarios is considered and benchmarked to ascertain the impact on the performance parameters on IPv4/IPv6 networks. The scenarios are basically network models configured and simulated using Optimized Network Engineering Tool modeler. The core model designed represents an Internet Service Provider network deployed to form an ideal choice of IP domain corresponded to a realistic network topology running both IPv4 and IPv6 connections. The dual stack, 6to4 tunnelling, and NAT network models are defined which allow the researcher to compare the simulated results. This paper shows that automated 6to4 tunnelling has better performance since it requires only one IPv4 address per tunnel for unlimited number of concurrent sessions though not suitable for voice perhaps because of the encryption overhead
Cyber-Security Vulnerability Assessment Model for County Governments in Kenya
(International Journal of Science and Research, 2021-07-26) Kadima, Victor Chitechi; Omieno, Kelvin K.; Mbugua, Samuel Mungai
Computerization of county government daily activities enables faster and better services to their clients. The integration of Information and Communications Technology by the CG into their systems has led to new advancements in technology. The adoption of ICT into the Kenya’s County Governments has contributed to faster growth and output in better client service delivery. The benefits has also encouraged serious attacks to such systems causing risks due to easier penetration in the systems because of vulnerabilities. The attacks have costed county governments more resources and time in case of managing such risks. As a country, we need to ensure that all our systems are well safeguarded from attacks. This paper sought to address the above issue by developing a cyber-security vulnerability assessment model for County Governments in Kenya, The model can be applied as a better approach that will manage and reduce the attacks and risks. The Model was developed from a study that targeted a total population of 170 staff grouped as end users and ICT Experts working in county governments of Kakamega and Bungoma. The study adopted an exploratory research design. Stratified random sampling technique was used to group the counties while purposive sampling was used to identify the correspondence with the required information. A sample size of 98 end users and 37 ICT experts was obtained using Yamane’s formula. Questionnaires and interview schedules were used in data collection. The data was analyzed using SPSS where descriptive statistics of frequencies, charts, percentages and mean regression analysis were used and a null hypothesis was tested at 5% level of significance. Study results showed that there is a positive association between preparedness and awareness, support and funding, policies and regulations, and technology; hence influencing cyber-security. The developed model will be used as a guide to manage cyber security matters in Kenya’s County governments.
A Survey of Awareness of Social Engineering Attacks to Information Security Management Systems: The Case of Kibabii University Kenya
(International Journal of Computer Applications Technology and Research, 2022-03-26) Mbuguah, Samwel Mungai; Otibine, Tobias Okumu
Computer based systems are socio-technical systems in nature. The security of the system depends both on technical aspect and also social aspect. The social aspect refers to people in contact with system commonly referred to as wetware. To attack the system you may consider to target the technical or wetware. Social engineering is based on exploiting human traits that make human susceptible to these attacks. The aim of this paper was establish how aware the staff of Kibabii University were of these attributes and how these attributes could be used by social engineers to penetrate the Information Security Management systems at the institution. A survey research was adopted with a questionnaire being developed using Google application, and was administered online to all staff members of Kibabii University. A descriptive analysis was carried out on feedback. The finding was that to a large extent the sampled staff are aware of these traits but there is need for awareness training to enhance the information security management system of Kibabii University
Association between Metabolic Syndrome and Substance Dependence: A Cross-Sectional Study in Kenya
(European Journal of Medical and Health Sciences, 2022-06-28) Mbuguah, Samuel Mungai; Mecha, Ezekiel; Kirira, Peter; Njoroge, Margaret; Malala, Boniface; Gitaka, Jesse; Makokha, Francis; Mwenda, Catherine
Metabolic syndrome and its defining components remain an understudied area of human health research in Kenya and Africa. Understanding the relationship between substance dependence and the occurrence of metabolic syndrome is critical in prevention and clinical management of the related complications. This was a cross-sectional study in 6 rehabilitative centers in 3 counties in Kenya with a conveniently selected sample size of 166 participants. A signed informed consent was obtained from each participant following which anthropometric and biochemical measurements were obtained. Descriptive statistics and chi-square test were used to describe the prevalence of metabolic syndrome and the relationship of the defining criteria with the substance of dependence. A quarter of the respondents were overweight and 6% obese. Fasting blood glucose was elevated in 62% of the sampled population with triglycerides having a significant variation with a mean of 216.95mg/ dL and a standard deviation of 151.107. A prevalence rate of 4.8% was established based on the Harmonized Joint Scientific Statement on Metabolic syndrome for the African region. 87.34% of the population showed at least one elevated defining criteria with alcohol as the most prevalent substance of dependence. There was statistical difference of fasting blood glucose and triglycerides with alcohol use. The findings indicate that alcohol use resulted to elevated levels of fasting blood glucose and triglycerides. There is need for emphasis on a multidisciplinary approach to substance dependence and metabolic syndrome management integrating physical activity interventions, dietary modifications and psychotherapeutic approaches.
Performance Evaluation of Machine Learning Algorithms in Smart Agriculture
(International Journal of Advanced Research in Computer and Communication Engineering, 2024-08-26) Gichuki, Dennis Karugu; Owoche, Patrick Oduor; Mbuguah, Samuel Mungai
This study explores the integration of Wireless Sensor Networks (WSN) and Machine Learning (ML) in smart farming to address critical agricultural challenges. By leveraging real-time data collection and advanced analytical tools, the research demonstrates the potential of ML algorithms—Decision Trees, Naive Bayes, Support Vector Machines (SVM), Logistic Regression, and Random Forests—in enhancing crop management, including yield prediction, soil quality assessment, and pest and disease detection. The study finds that Naive Bayes achieves the highest accuracy and balanced precision-recall metrics, while ensemble methods like Random Forests effectively reduce overfitting and improve prediction accuracy. Despite the promising results, the research identifies challenges such as data accessibility, model integration, and user interface design that must be addressed to fully realize the potential of smart farming technologies. Overall, the findings provide valuable insights into optimizing resource utilization, reducing crop losses, and promoting sustainable farming practices, thereby supporting global food security and economic stability.
Assessing Preparedness for Smart Farming and Technology Adoption among Kenyan Farmers
(International Journal of Research and Innovation in Applied Science, 2024-09-16) Gichuki, Dennis Karugu; Mbuguah, Samuel Mungai; Owoche, Patrick Oduor; Oyile, Paul Oduor
Agriculture is crucial in reducing poverty, promoting economic prosperity, and ensuring food security for the world’s growing population, which is expected to reach 9.7 billion by 2050. This sector is vital to the global economy, contributing significantly to GDP and providing jobs for a large workforce. Precision agriculture and e-commerce advances have proven beneficial, boosting crop yields and rural incomes. Sub-Saharan Africa faces similar agricultural challenges as it anticipates a population of 2.1 billion by 2050. Although the region has made strides in expanding farmland and labour, improvements in crop yields have been limited. The digital revolution offers new opportunities to tackle issues such as undernutrition by improving access to information and technology. In Kenya, with a population projected to reach 95 million by 2050, expanding food production is a pressing challenge. Significant hurdles include declining soil fertility, inadequate water management, and a lack of technical support. While technologies like Wireless Sensor Networks (WSNs) and Machine Learning (ML) have the potential to enhance agricultural productivity, their adoption is constrained by infrastructure issues, high costs, and a shortage of technical expertise. Addressing these barriers and improving farmer education is essential to fully realising these technologies' benefits.
Unraveling the ‘community effects’ of interventions against malaria endemicity: a systematic scoping review
(BMJ Public Health, 2024-10-29) Ko, Yura K; Kagaya, Wataru; Chan, Chim W; Kanamori, Mariko; Mbugua, Samuel Mungai; Rotich, Alex K; Kanoi, Bernard N.; Ngara, Mtakai; Gitaka, Jesse; Kaneko, Akira
Objectives There is an urgent need to maximise the effectiveness of existing malaria interventions and optimise the deployment of novel countermeasures. When assessing the effects of interventions against malaria, it is imperative to consider the interdependence of people and the resulting indirect effects. Without proper consideration of the effects, the interventions’ impact on health outcomes and their cost-effectiveness may be miscalculated. We aimed to summarise how the indirect effects of malariainterventions were and reported. Design We conducted a scoping review. Data sources We searched PubMed, Web of Science and EMBASE. Eligibility criteria We included studies that were conducted to quantify the indirect effects of any interventions for all species of Plasmodium infection. Data extraction and synthesis We used a standardised data collection form to obtain the following information from each record: title, name of authors, year of publication, region, country, study type, malaria parasite species, type of interventions, type of outcomes, separate estimated indirect effect for different conditions, pre-specified to measure indirect effect, secondary analysis of previous study, methods of indirect effects estimation, terms of indirect effects, and if positive or negative indirect effects observed. Results We retrieved 32 articles and observed a recent increase in both the number of reports and the variety of terms used to denote the indirect effects. We further classified nine categories of methods to identify the indirect effects in the existing literature and proposed making comparisons conditional on distance to account for mosquito flight range or intervention density within that range. Furthermore, we proposed using the words community effects or spillover effects as standardised terms for indirect effects and highlighted the potential benefits of mathematical models in estimating indirect effects. Conclusions Incorporating assessment of indirect effects in future trials and studies may provide insights to optimise the deployment of existing and new interventions, a critical pillar in the current fight against malaria globally.
Trends in Software Architecture Designs: Evolution and Current State
(International Journal of Innovative Science and Research Technology, 2025-03-26) Agwenyi, C.A; Mbuguah, Samuel Mungai
Software architecture combines architectural style and quality attributes with the high-level structure of software system abstraction through composition and breakdown. In addition to meeting the system's primary functionality and performance needs, a software architectural design must also meet non-functional requirements including availability, scalability, portability, and dependability. The set of components, their relationships, how they interact, and how each component is deployed must all be described in a software architecture. There are numerous approaches to characterizing software architecture, including object-oriented modeling with UML (Unified Modeling Language), the Architecture View Model (4+1 view model), and ADL (Architecture Description Language). With an emphasis on microservices, serverless architecture, event-driven architecture, domain-driven design, cloud-native applications, zero trust security, and artificial intelligence integration, this paper reviews the latest developments in software architectural concepts, comparing their trends and contributions to modern computing. This paper reviews the evolution and current trends in software architecture designs from 2016 to 2024. It highlights key shifts, emerging paradigms, and factors influencing architectural decisions. The study is based on a systematic desktop review of existing literature, focusing on industry and academic contributions. Findings indicate a shift towards cloud-native architectures, microservices, event-driven models, and AI-enhanced frameworks. The paper synthesizes these trends and discusses their implications for future software development
ICT Personnel Maturity Towards Green ICT in Kenya
(International Journal of Computers & Technology, 2014-04-23) Wabwoba, Franklin; Mbugua, Samuel Mungai; Anselemo, Peters Ikoha; Shisoka, Dorcus Arshley
Though ICT is contributing to the economy associated with innovations, inventions and rapid development in almost all aspects of human life, is responsible for climatic degradation. The rapid increase of ICT usage means more costs of doing business, energy consumption, and more environmental challenges. The rapid changing technology reaching Kenya and lack of their understanding has put a lot of pressure on both management and ICT personnel to implement them on a trial and error manner. This has limited the gains meant to be obtained from green ICT despite its technologies availability. The lack of ICT personnel capacity readiness challenges the reaping of green ICT benefits. The study was informed by the G-readiness model and the enhanced G-readiness model. This study purposed to determine the personnel capacities readiness towards green ICT in Kenya. The study was undertaken using the interpretive, inductive multi-case survey study on a population of four data centres and 116 ICT managerial, technical and user personnel that were purposively sampled. Interview, observation, questionnaire and document analysis methods were used to gather data that was triangulated to increase the reliability and validity. The study established the ICT personnel’s G-readiness was very low on both training and professional development perspectives in Kenya. The study’s findings are useful towards the strategic planning for green ICT implementation, cutting down running costs, improving environmental performance of organisations and contribution to the world of knowledge. The findings provide data for informed ICT personnel and workplace readiness alignment, decision making and ICT curriculum development. The study recommends application of green ICT based on established ICT personnel capacity, inclusion of green ICT training in the curriculum, creation of green ICT responsibilities, provision for a green ICT budget and investment into the development of green ICT personnel
Interface Features, Program Complexity and Memorability as Indicators of Learnability of Mobile Social Software
(International Journal of Science and Research, 2017-10-26) Masese, Nelson Bogomba; Muketha, Geoffrey Muchiri; Mbuguah, Samuel Mungai
Social Computing aims to support the tendency of humans to interact with mobile devices. Technology reinforces this interaction by producing appropriate responses that then lead to improved communication between humans and computational devices. Although latest in mobile phone technologies have opened the way for a new generation of mobile social applications that allow users to interact and share information, there is still very limited user support information on how to use different applications. This problem either increases the learning curve of the users, thereby adversely affects their overall efficiency. The main purpose of this paper is to analyze factors that affect the learnability of mobile social software. A sample of 361 respondents was selected, with 345 respondents returning feedback. Primary data was collected through the use of questionnaires and interviews targeting mobile social users in Nakuru County Kenya. Three social networks were used, namely, WhatsApp, Facebook and Twitter. Data analysis was done using descriptive statistics. Findings indicate that interface features affect learnability across the three social networks, with learnability of WhatsApp turning out to be higher than that of compared to Facebook and Twitter. Findings also indicate that more than 60% program supports compatibility with other applications while 59.4% of the respondents agreed that maintaining language is cheap across the three social networks. Other findings indicate that WhatsApp’s memorability is easy to execute compared to that of Facebook and Twitter.
Facilitating Factors for Cybersecurity Vulnerabilities in Kenyan County Governments
(Asian Journal of Research in Computer Science, 2018-11-13) Kadima, Victor Chitechi; Mbuguah, Samuel Mungai; Omieno, Kelvin
Globally, ICT is regarded as a driver and enabler; thus, organisations which have integrated ICT in their systems have had immense growth and output. The adoption of ICT into the Kenyan County Governments, therefore, promises equal growth and output. These benefits notwithstanding, integration of ICT systems into County Governments is faced with a number of challenges in terms of vulnerabilities and other cybersecurity risks. This paper sought to identify the key facilitators of cybersecurity vulnerabilities in Kenyan County Governments only. The exploratory research design was used as a methodology. Questionnaires and interview schedules were the main instruments of data collection. The data was analysed using descriptive and inferential statistics. The findings indicate that there is a need for County Governments in Kenya to prepare for cybersecurity related challenges through policy formulations, End-users and ICT experts awareness on cybersecurity-attacks, Management support through resources funding and cybersecurity infrastructure is key to any system controls. The solutions to cybersecurity vulnerabilities in Kenyan County governments can be solved when these keys are implemented
Technology-Enabled Self-directed Learning in Developing countries: Adoption Framework
(International Journal of Computer Applications Technology and Research, 2022-03-26) Barasa, Godliphas Mamati; Mbugua, Samuel Mungai; Anselemo, Peters Ikoha
21st century-learning approach is characterized by self-directedness and the ability to learn anytime, anywhere. Self-directed learning heavily depends on Technology to be effective. Most universities were used to conventional face-to-face learning, but uncertainties like the covid-19 pandemic have challenged this teaching and learning mode, thus pushing universities to explore innovative learning approaches to ensure seamless learning. One such approach is Technology-enhanced self-directed learning. Most developed countries are endowed with enabling infrastructure to actualize this learning approach. However, most developing countries like Kenya are still struggling to adopt self-directed learning due to technological, organizational, and environmental challenges. A framework is needed to guide its adoption. A survey research design using an online questionnaire with a sample size of 572 was used.Four Kenyan public university students participated in the study. Data was collected and analyzed using Exploratory Factor Analysis. Principle component analysis extracted seven factors explaining a total variance of 62.5%. The factors were renamed based on a shared theme, and the average factor loading for each construct was calculated. A percentage weight of each construct was also calculated. Key factors forming the constructs of Technology-enhanced self-directed learning were: E-learning infrastructure, bring your own device policy, Connectivity infrastructure, ICT Competencies, Information security, demographic factors, and laptop ownership program
Model Driven Architecture a Review of Current Trends
(International Journal of Computer Science and Mobile Applications, 2023-01-30) Onunga, Jeremiah; Mbugua, Samuel Mungai
The Object Management Group (OMG) adopted the Model Driven Architecture (MDA) approach from among the various Model Driven Engineering (MDE) methods. The MDA technique, which is based on the separation of concerns principle, aims to automate the software development process by using models rather than traditional coding. Model Driven Architecture (MDA) is a new technique to application modeling and creation that has gotten a lot of attention recently. Many organizations are now considering MDA as a way to organize and manage their application solutions, tool vendors are explicitly referring to their capabilities in terms of "MDA compliance," and the MDA lexicon of platform-specific and platform-independent models is now widely referenced in the industry. The OMG produced the second iteration of the MDA guide in June 2014 in an effort to implement the essential ideas and supplement the 2003 original with more precise specifications. Researchers' interpretations of the MDA words vary due to the 11-year difference and their respective perspectives and backgrounds. What causes uncertainty about what falls under and outside the MDA's scope. In this work, we present an overview of the current MDA trends simplifying integration challenges and enhancing business Information Technology (IT) alignment. This paper establishes boundaries around what constitutes MDA, positioning MDA in relation to other model-driven methods. It will also demonstrate its advantages over conventional software development and other model-driven methodologies. This paper highlights problems and difficulties that researchers have identified that affect the MDA. The paper also provides some insight into the MDA trends in research and directions, particularly with regard to the platforms that the MDA development process is aimed at and its automation

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