Browsing by Author "Maake, Benard"

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    Adopting Course Completion Tracking and Conditional Activities to Enhance Engagement in eLearning for University Students
    (IST-Africa Institute and IIMC, 2021-05) Wambua, Anthony; Maake, Benard
    Student engagement is an overarching problem in the learning context that instructors continue to grapple with. Several attempts that utilize features within the Learning Management Systems (LMSs) have been made to increase student engagement and motivation for online courses. This paper presents the findings of the adoption of completion tracking and conditional activities to enhance engagement in Moodle, a leading LMS. To investigate the effectiveness and the potential of completion tracking and conditional activities in enhancing engagement, data was collected from 90 students across four courses, further Moodle logs were examined. The research findings indicate completion tracking and conditional activities significantly increase learner engagement in online classes. These findings have significant implications on instructors conducting online classes and the development of student engagement for online courses. The present research fulfills the need to study how completion tracking and conditional activities features can be used to enhance learner engagement in Moodle LMS.
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    Characterizing Software Quality Assurance Practices in Kenya
    (INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING & COMPUTER SYSTEMS, 2022) Wambua, Anthony ; Maake, Benard
    Given the increased reliance on technology, Software Quality Assurance(SQA) has become a vital area in Software Engineering (SE). SQA practices require training, cost and often take more time than actual code writing. Owing to these requirements, software developers often ignore or partly implement SQA practices, leading to potentially poor quality software development. The goal of the study is to characterise SQA practices of software developers in Kenya. As such, quantitative empirical research was conducted. Seventy-seven (N=77) completed questionnaires were received and analysed to yield the required insights. The analysis of the findings indicates compliance with SQA practices. However, the research unearths concerns such as failure to comply with Software Development Life Cycle (SDLC) models as having the potential to lower the quality of software products. The assessment found that Unit testing was the most common type of software test. Based on the findings and literature, recommendations are made. The need to improve software engineering education and invest in software testing is underscored. The results can be generalised to most developing countries and used by software developers and trainers to identify areas in SQA that need strengthening
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    Water Quality Monitoring Using IoT & Machine Learning
    (ST-Africa.org/Conference2022, 2022) Omambia, Andrew; Maake, Benard; Wambua, Anthony
    Abstract: Safe water access is fundamental form of human survival and it is presented as a fundamental human right. As consumers use water, primarily sourced from pipes and springs located around towns, contamination, leakages, and pilferage happen. IoT and Machine Learning offer a promising solution to address these challenges. Premised on these technologies, the authors propose a system that monitors water quality and pilferage and wastage that uses machine learning algorithms for decision making