Kenyatta University Repository
Kenyatta University Institutional Repository is a digital archive that collects, preserves and disseminates scholarly outputs of the Institution
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Digital Learning Materials in Teaching and Their Influence on Learners’ Performance in Biology: A Case of Kalawa Secondary School, Kitui County, Kenya
(Kenyatta University, 2025-09) Kavoso, Emmanuel Mumo
Use of technology has influenced education sector by enabling teachers to allow repetition and variation in presentation of complex content in class easily. Other than motivation, use of Digital learning materials ensures high content retention. Kalawa Secondary (KS) had been recording consistent low performance in Biology between year 2014 and 2022. The school benefited from equipped computer laboratory through Economic Stimulus Package (ESP) by the government. Science teachers were taken through in-service training for ICT skills. This study investigated use of digital learning materials in teaching and its influence on learners’ performance in Kalawa Secondary. The study objectives were: (a) to identify available digital learning resources for the use in teaching Biology; (b) to explore challenges facing teachers of Biology during integration of technology; and (c) to establish influence of digital learning materials integration on learners’ performance. The research used descriptive research design. Qualitative and quantitative data was collected using checklists, Biology teacher questionnaires, Principal interview schedule and Lesson observation sheets research instruments. The study was grounded on Vygotsky social constructivist learning theory. A target population of eight (8) teachers of Biology and 750 students taking Biology was used. Purposive sampling was done to pick six (6) teachers of Biology, four (4) Form II Biology classes and the principal. Piloting was done with two (2) teachers of Biology at neighboring school of equal status. Statistical package for social sciences (SPSS) was used in data analysis based on study objectives. The study revealed that the school had insufficient Biology ICT resources. In addition, 75% of teachers of Biology used technology in at least a single lesson per week while 25% never did. The study revealed a strong positive relationship between use of digital learning materials and students’ performance in Biology (r=0.652). The findings will benefit curriculum developers at the Kenya Institute of Curriculum Development (KICD), ICT and QAS departments in MOE to evaluate the significance of technology use in secondary schools.
Assessment of Kenya’s Counter-Terrorism Strategies and Their Implications on National Security, 2011–2019
(Kenyatta University, 2025-11) Meroka, B. Onsinyo
Global terrorism has grown to be a threat and a common problem that countries face in the 21st century. Following Kenya's incursion in Somalia in 2011, the country has become a soft target for terror attacks that have challenged its national security, prompting the government to undertake various counter-terrorism strategies to mitigate the vice. This study examined Kenya's counter-terrorism strategies and their impact on national security from 2011 to 2019. The following objectives guided the research: to analyse the nature of Kenya's counter-terrorism strategies during this period; to explore the implications of these strategies on its national security; as well as to evaluate the challenges faced by security agencies in implementing Kenya's counter-terrorism measures from 2011 to 2019. The study relied on Securitization Theory as a tool of analysis. To achieve the study objectives, the researcher employed a descriptive survey research design. The research was conducted in Nairobi City County, utilizing purposive and snowball sampling techniques to identify interview respondents. The study sampled key informants that were drawn from the Ministry of Defence, the National Counterterrorism Centre, the Ministry of Interior and National Administration, the Director of Public Prosecution, Judiciary, security experts, Horn Institute for Strategic Studies and the Institute of Security Studies. The study employed Primary data derived from in-depth key informant interview guides. Secondary data was obtained from textbooks, journals, newspaper articles, scholarly magazines, publication press, libraries and different research-related organizations on security studies. The study revealed that the government was using military interventions as its key strategy for counter-terrorism. The study noted the government was implementing security measures in response to increasing radicalization and levels of extremism in Kenya. The study also revealed that lack of integrity in various security institutions weakened their capabilities to handle terrorism. Terrorist organizations were also using a variety of socioeconomic reasons to infiltrate the Kenyan community and breed terrorism. The study recommended the need for proper multiagency security coordination, particularly in the zones of comprehensive intelligence information gathering, analysing and sharing data. According to the study, these problems have significantly and extensively impacted Kenya's national security
Effects of Grassland Edges and Plot Sizes on Distribution, Nesting and Occurrence of Grassland-Dependent Birds in Kinangop Plateau, Nyandarua County, Kenya
(Kenyatta University, 2025-07) Mwangi, Martin W.
Kinangop Plateau is an Important Bird Area (IBA) hosting globally threatened bird species and lies west of Aberdare Ranges and east of Lake Naivasha, in Kenya. Fragmentation of the grassland since human occupation in the 1960s has created grassland edges with forest, road, and cultivated areas, yet little was known about how these edges affect bird distribution, nesting behavior, density and occurence. The study investigated the effects of habitat fragmentation on grassland-dependent birds, focusing on three umbrella species: Sharpe’s Longclaw (Macronyx sharpei Jackson 1904), Jackson’s Widowbird (Euplectes jacksoni Sharpe 1891), and Long-tailed Widowbird (Euplectes progne Boddaert 1783). Using purposive sampling of 23 plots covering 573.2 acres, bird population surveys, nest searches and nest monitoring were conducted along edges via belt transects and rope-drag methods. Results showed that birds preferred cultivated edges most (38%), followed by road edges (35%), with forest edges (27%) least preferred. Only 1 individual Sharpe’s Longclaw was recorded from a Forest-edged grasslands out of 44 individuals recorded during the study. Jackson’s Widowbird nested predominantly in cultivated edges (61%), with nest predation highest at road edges (75%) and lower (57%) in both Forest and Cultivated-edged grasslands. Plot size influenced Sharpe’s Longclaw occurrence strongly, with 75% found in large plots (>20 acres), while Long-tailed and Jackson’s Widowbirds were unaffected by plot size. The study recommends prioritizing conservation of large cultivated-edged grasslands, promoting medium to large - sized plots (medium = 5–20 acres and larger = >20acres) for Sharpes Longclaw, limiting forest encroachment into grasslands, protection and restoration of native tall grass species such as Themeda triandra, Hyparrhenia filipendula, Andropogon amethystinus and Pennisetum cladestinum used for nesting. Further research should be carried on Sharpe’s Longclaw breeding and nest predation factors as well as engaging local communities in bird-friendly practices to reduce grassland fragmentation.
Social Media Analytics and Market Performance of Commercial Banks in Nairobi City County, Kenya
(Kenyatta University, 2025-11) Kiptoo, Kipkorir Samuel
The ability of a firm to generate business insight from social media data and to exploit it to improve business processes and decision-making is vital for market performance. However, it is a challenge for many commercial businesses in Kenya to analyze and use this data appropriately for instance, big data. The social media has become more innovative and interactive compared to the conventional print or audio/video media. However, due to unstructured and dispersed nature of this data, it is difficult to extract information that is meaningful and applicable. The firms’ inability to utilize the social media analytics in generation of business insights has limited their efforts to take advantage of this new marketing channel to make sound business decisions. The aim of this study was to establish the influence of social media analytics on the market performance of commercial banks in Nairobi City County. The specific objective of this research is to assess the influence of news analytics, opinion mining, sentiment analysis, and social media scraping on the market performance of commercial banks in Nairobi City County; while ascertaining the moderating effect of organizational capabilities on the relationship between social media analytics and the market performance of commercial banks in Nairobi County. The study is founded upon four major theories: resource-based view, dynamic capability theory, holistic theory and systems theory. The study adopted a stratified random sampling technique used to choose respondents, with structured questionnaires being used to collect data. The data collection tool was pre-tested for validity and reliability analysis was conducted. The target population for the study was 39 licensed commercial banks in Nairobi City County from which a sample of 156 respondents from these banks was sought. Descriptive and inferential statistics utilized to analyse the research data. The analysis techniques comprised means, standard deviation, regression statistics, and beta-coefficients. Multiple regression analysis was employed in this study to determine the influence of the four independent variables on the dependent variable. The study found that social media analytic, opinion mining, sentiment analytic and social media scrapping have positive statistically significant impact on the market performance of commercial banks in Nairobi City County, Kenya. Further, the study revealed a moderating effect of organization capability on the relationship between social media analytics and the market performance of commercial banks. The study concludes that news analytic enable invaluable insights into market performance. Opinion mining helps in keeping trends and events that act as warning signs for supply-chain risks. Sentiment analysis helps in gathering data and feedback on problems with products and services. Social media scraping allows banks to gather valuable insights into current market trends and organizational capabilities pinpoints a bank’s strengths and weaknesses. Further, the study further concludes that applying social media analytics in an environment of organization capability improves the positive impact on the market performance of commercial bank. The study recommends that banks should establish high social media performance standards, and their employees should strive to meet or exceed them. Further, stakeholders in the banking sector should improve their participation by offering feedback in social media to be able to inform decision making.
Design and Fabrication of a Non-Invasive Near Infrared Meter for Glucose Monitoring
(Kenyatta University, 2025-06) Kirui, Julius
In the current times, there is an alarming increase of diabetes in the world, which has largely been linked to changes in lifestyle. Diagnosing and controlling blood sugar levels are necessary for people with diabetes. The reason is to ensure that adequate action is taken to maintain insulin at acceptable levels. The methods used currently to measure blood sugar levels are frequently invasive or minimally invasive. These methods are effective and successfully used, but they are painful, costly, and carry a risk of infection. Thus, non-invasive, painless, infection-free and cost-effective alternative methods are currently being pursued. Numerous non-invasive techniques have been thoroughly studied. Notwithstanding the challenges of accuracy, calibration and bulkiness, these techniques have shown promising results for the development of non-invasive glucose meters. Given these challenges, the primary objective of this study was to develop an accurate Near Infrared (NIR) meter for non-invasive glucose monitoring that can identify both high and low blood sugar levels. Specifically, the research endeavored to design, develop, test and validate a NIR blood sugar level detector system. The NIR meter utilizes the transmittance principle by using a low-power infrared light-emitting diode (LED) with an emission wavelength of 1150 nm as a transmitter and a photodiode as a receiver. The signal is then filtered, linearized, stabilized and passed to a microcontroller. The Microcontroller uses Arduino programming language fitted with a regression equation to transform the signal and give an output. The output of the detector was first passed through the trans-impedance amplifier, a filter circuit, amplifier and a linearizer before passing to a microcontroller. In order to compute glucose concentrations, a linear regression equation was fitted into the software to calculate equivalent glucose levels of the voltages obtained. The results were displayed on the liquid crystal display (LCD) and transmitted to a remote device for monitoring via the Global System for Mobile communication (GSM) for monitoring and storage. An In-vitro approach was adopted to test the system. Standard glucose concentrations within all the sugar levels were prepared for the test. The samples were then set between the probe beam and the detector. During system testing, it was observed that the output voltages directly vary with glucose concentrations. Therefore, the voltage output is directly proportional to glucose concentrations. Thus, the results proved that an 1150nm infrared LED can be used to measure glucose levels non-invasively. The system was validated using Clark Error Grid and Bland Altman analysis. It was ascertained from the Clark error grid that the glucose concentration of the tested system falls within region A and region B of the Clark’s Error Grid. The majority of the values fell within both limits of agreement when Bland Altman's analysis was used. It implies that the device is suitable for measuring glucose concentration non-invasively. The residual plot for 1150nm wavelength suggests that the model satisfies the requirements of linear regression and offers an acceptable fit to the data and the Pearson correlation coefficient suggests a very strong positive linear relationship within the data set, with the measurements showing high consistency and predictability. However, since the scope of the study was limited to in-vitro measurements, it is recommended that more validation be done on a large number of data samples specifically with the use of in-vivo measurements and compare the results with commercially available glucometers.