Kibuspace
Kibuspace is the institutional repository of Kibabii University, the repository preserves the University's research legacy and all aspects of knowledge generated by KIBU community for posterity
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The use of personal Computing devices for self-directed learning
(International Journal of Research in Information Technology, 2020-02-04) Barasa, Godliphas Mamati; Mbuguah, Samuel Mungai; Anselemo, Peters Ikoha
Covid 19 pandemic has disrupted education worldwide, affecting over 94% of the student population. One strategy to ensure seamless learning is the adoption of self-directed learning and personal computing devices. A survey was carried out in four public Universities in Kenya to assess the computing devices used by learners for self-directed learning. Five hundred seventy-two students pursuing either information technology or computer science students participated in the study. The findings revealed that over 90% of the students own a personal computing device. The most popular device was a smartphone, followed by a Laptop, a Personal computer and finally a Tablet. The majority of the students prefer using a laptop for self-directed because of the convenience of use. Over 90 % of students prefer using their computing devices to university-provided devices. Over 80% of the students are using their computing devices for learning. The findings will inform policy in the domain of technology-enhanced self-directed learning
A Model for Analyzing Usage Factors in Designing User Acceptance of Biometric Voter Registration Technology
(International Journal of Engineering and Applied Sciences, 2021-12-04) Nyakundi, Richard Kayanga; Mbuguah, Samuel Mungai; Makiya, Ratemo
Models leading to acceptance of the technology remain largely unrealized in economically transitioning countries due to low adoption of appropriate and acceptable electronic technology models. This is because electoral bodies focus on the technical supply-side factors with little emphasis
on acceptable biometric technology systems. While a number of adoption models have been applied to the developed countries, they require domestication in order to address the specific client-based needs of developing nations. This study therefore was meant to provide A Model for User Acceptance of BVR Technology. This model sought to explain the low acceptance level of biometric technology acceptance that led to
development of a model which best support free, fair and credible election process. A Model for Adoption and Acceptance of Successful BVR Technology is developed and validated. The findings affirm that the model can be adopted and applied in both developing and developed countries to fast track the voting process.
Determination of User Factor Requirements for Acceptable of Biometric Voter Registration Technology
(International Journal of Engineering and Applied Sciences, 2021-12-04) Nyakundi, Richard Kayanga; Mbuguah, Samuel Mungai; Makiya, Ratemo
Voting systems around the world are transitioning from the manual voting practices to electronic systems for better service delivery. However, even with electronic systems, credibility of the technology has been a challenge to many countries around the world. This is because of Electoral bodies
focus on the technical supply-side factors with little emphasis on acceptable biometric technology systems. There has been inadequate research and development in IT models particularly leading to adoption and acceptance of BVR Technology to inform the publics’ uptake of acceptable election outcomes. While a number of adoption models have been and applied to the developed countries, they require domestication in order to address the specific client-based needs of developing nations. This study therefore was meant to establish the valid user factors that determine easy adoption
and wide acceptability of the BVR Technology. Analyzing the existing BVR Technology and determination of usage factors for adoption of BVR Process formed the objectives of this study. Questionnaires and interview schedules were used as research instruments to collect data. Data was then arranged and coded for analysis. Descriptive statistics was used to analyze the collected data. Data presentation was done using tables and logical analysis. The study affirmed that paybacks, lack of reliance, negative exactitudes of technology users, inadequacy of government policy, lack of preparation in BVR technology and lack of edification in internet use led to low usage rate of BVR Technology.
Technology-Enabled Self-directed Learning in Developing countries: Adoption Framework
(International Journal of Computer Applications Technology and Research, 2022-05-03) Barasa, Godliphas Mamati; Mbuguah, 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.
Remote Data Centre Monitoring System Based On The Arduino Microcontroller.
(International Journal of Engineering Research and Applications, 2022-08-26) Mungai, Teresia Muthoni; Nderu, Lawrence; Mbuguah, Samuel Mungai
COVID 19 forced most workers to work from home to stem the tide of infections. Data centers environment requires continuous monitoring by the technical personnel hence the need for system that could allow remote working. Most institutions desire to reduce cost and better management of the available resources including energy that contribute immersely in running data centers. Moreover grid power is not always reliable hence the need to use generators as backup in case of power outages which consume fossil fuels. The aim of the research was to design and implement a sensor based data centre management system using the Arduino microcontroller.. The research methodology adopted was an engineering approach. The output is a
prototype of data center monitoring system that enable the data center workers to work from their homes and meet the desired COVID-19 Protocol of
social distancing