Department of Computer Science

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A Critical Evaluation of the Environmental Effects of the Existing E-Waste Management Practices in Kenya
(2019) Simiyu, Peter Wamalwa; Wabwoba, Franklin; Ronoh, Richard
Information Communication Technology (ICT) gadgets and other electronics are extensively being used in the health, industries, education, homes, communication and trade sectors. With the expected introduction of use of laptops in primary schools in Kenya, the use of these electronics is expected to drastically increase, thus, leading to an increase in electronic waste. Although e-waste has parts and components of value, they contain many toxic components, which prompt a potential need of this research to assess the contents, qualities and impact of e-waste material. The purpose of this paper is to evaluate the environmental implications of the existing e-waste management practices. The study adopted survey research design. The sample population included 18 policy officers in County Government of Bungoma, 28 electronic shop repairs, and 61 institutions and collectors of e-waste material. The study is expected to provide guideline on Green ICT practices and e-waste management as a platform for evaluation, policy enforcement, guidelines and further research on electronic waste management.
Students Selection for University Course Admission at the Joint Admissions Board (Kenya) Using Trained Neural Networks
(2011) Wabwoba, Franklin; Mwakondo, Fullgence M.
Every year, the Joint Admission Board (JAB) is tasked to determine those students who are expected to join various Kenyan public universities under the government sponsorship scheme. This exercise is usually extensive because of the large number of qualified students compared to the very limited number of slots at various institutions and the shortage of funding from the government. Further, this is made complex by the fact that the selections are done against a predefined cluster subjects vis a vis the student’s preferred and applied for academic courses. Minimum requirements exist for each course and only students having the prescribed grades in specific subjects are eligible to join that course. Due to this, students are often admitted to courses they consider irrelevant to their career prospects and not their preferred choices. This process is tiresome, costly, and prone to bias, errors, or favour, leading to disadvantaging innocent students. This paper examines the potential use of artificial neural networks at the JAB for the process of selecting students for university courses. Based on the fact that Artificial Neural Networks (ANNs) have been tested and used in classification, the paper explains how a trained neural network can be used to perform the students’ placement effectively and efficiently. JAB will be able, therefore, to undertake the students’ placement thoroughly and be able to accomplish it with minimal wastage of time and resources respectively without having to utilise unnecessary effort. The paper outlines how the various metrics can be coded and used as input to the ANNs. Ultimately, the paper underscores the various merits that would accompany the adoption of this technique. By making use of neural networks in the university career choices, student placement at JAB will enhance the chances of students being placed into courses they prefer as part of their career choice. This is likely to motivate the students, making them work harder and leading to improved performance and improved completion rate. The ANN application may also reduce the cost spend on the application processing and the time the applicants have to wait for the outcome. The ANN application could further increase the chances of high quality applicants getting admission to career courses for which they qualify.
Classifying Program Visualization Tools to Facilitate Informed Choices: Teaching and Learning Computer Programming
(2012) Mutua, Stephen; Wabwoba, Franklin; Ogao, Patrick; Anselmo, Peter; Abenga, Elizabeth1
Program Visualization (PV) is a technique that has been found useful in teaching computing programming. This has seen proliferation in development of PV tools with an aim of enhancing teaching/learning programming over the last two decades. However, the tools usage has remained minimal. Perhaps because it becomes challenging to ascertain the appropriate tool for the right task. This paper presents a classification of program visualization tools with the focus of aiding teachers and students in choosing the most appropriate tool for an interesting experience in the classroom. The paper is based on six various PV tools evaluated over a period of two consecutive academic years in a Kenyan public University. The classification augments the Price’s taxonomy of software visualization arm of PV by presenting four basic levels which are further subdivided into lower levels. Index Terms– Classification, Pedagogy, Program Visualization and Taxonomy
Virtual reality in education trends and issues
(2013-01-01) Omieno, Kelvin K.; Wabwoba, Franklin; Matoke, Nahason
common form of education in institutions of higher learning (IHL). Many IHL in developing nations, such as Kenya, have greatly experienced an increase in demand for higher education. On the other hand, the ability to connect people with required sets of skills, regardless of their location in the world has been enabled by advances in information technology over the past 20 years. Use of virtual learning systems (VLS) has rapidly emerged as a very promising technology that will probably match the innovation of technologies such as multimedia/hypermedia. These VLS have the potential to provide opportunities for active, flexible, and increasingly individualized learning experiences. It also explains virtual reality principle, describes the interactive educational environment, highlights the challenges higher education face in the traditional mode of delivery and discusses educational benefits of implementing virtual learning environments in IHL. The paper makes a number of recommendations for successful adoption of VLS in higher education

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