3. Faculty and Staff Publications

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A Biblical Assessment of Luther’s View on Priesthood of All Believers and the Office of Ministry.
(The American Journal of Biblical Theology, 2021-05-30) Davidson Razafiarivony, Ph.D
Based on the biblical teaching that we are a universal priesthood and members are priests, many infers all members can be Pastors. The endless debate on the women ordination to ministry calls for a correct biblical understanding of pastoral ministry within the priesthood of all believers. Luther’s view can be of help when it has been assessed from the biblical perspective.
A Conceptual Design of a Generative Artificial Intelligence System for Education
(International journal of research and innovation in applied science (IJRIAS), 2024-05-24) Lossan Bonde
Artificial Intelligence (AI) and, more specifically, Generative Artificial Intelligence (GenAI) are among the most trending disruptive technologies, offering unprecedented possibilities for innovation in education by customising learning paths, fostering creativity, and bridging knowledge gaps. Gen AI is a subfield of AI which generates content (text, image, audio or video) that is comparable to human-generated content. It uses complex Machine Learning (ML) models and Neural Networks (NN) trained on large datasets. The launch of ChatGPT in November 2022 has significantly raised the standards for generative artificial intelligence capabilities. Since then, researchers and practitioners have extensively investigated the potential applications of this technology. Consequently, GenAI has been applied in various sectors, including business and marketing, media and entertainment, arts and design, research and innovation, and education. While it is evident that GenAI has a high potential transformative power on education, its actual application in classical educational settings such as schools and universities remains limited to individual (student or teacher) trials without institutional guidance and support. The aim of this is expressed in two points: (1) to explore the advances in GenAI and provide guidelines on leveraging the technology in the context of learning and teaching. (2) to identify the main barriers to adopting GenAI in education and how to address them when building a Gen AI application for education. The paper’s main contribution is conceptualising a Gen AI system for learning and teaching. Such a system produces course content, exercises, and supplementary materials tailored to the curriculum and each student’s learning pace and style. This system will enhance comprehension and retention, making education more accessible and effective. Secondarily, the research addresses the ethical issues and other barriers to adopting GenAI in education.
A Generative Artificial Intelligence Based Tutor for Personalized Learning
(IEEE Xplore, 2024) Lossan Bonde
Personalized learning refers to a system of teaching and learning where the content, methods, and assessment are tailored to each learner’s needs, capacities/skills/competencies, and pace. There is abundant literature about personalized learning, describing its advantages, challenges, and approaches to implementing it. This study has explored the abundant literature and realized that while there are substantial proposed ways to achieve personalized learning, these proposals are not implemented into actionable products. This research aims to construct a Generative Artificial Intelligence (Gen AI) tutor that implements personalized learning and teaching in a higher education level course. The research methodology involved exploring literature to determine the requirements for personalized learning and designing a tutor system. The resultant system uses Custom GPT technology, Application Programming Interface (API), a repository for storing content, learners’ profile information, and performance metrics. Out of the six components that make the proposed system, only the “Custom GPT” component has been implemented and tested on a course named “Applied Cryptography” in a postgraduate program. Though the preliminary results are promising, an effective assessment of the system will be made when the full implementation is completed. Further, issues related to ethics, scaling and integration with learning management systems should also be considered. Subsequent work to this study will focus on those issues.
A Machine Learning Based Framework forCollecting and Using Social Media for Real-timeTerrorist Attacks Prediction
(International Conference on Artificial Intelligence and its Applications, 2023) Lossan Bonde; Severin Dembele
Terrorism has become a global plague causing insecurity and jeopardizing the development of many countries. In the past few years, terrorism has exploded in Burkina Faso, affecting education, national security, health, and the economy. There is a great need for solutions to detect and stop terrorist attacks before they occur. This research project seeks to use Artificial Intelligence (AI) to mine social media and detect probable future terrorist attacks. This article describes the design of a framework, its partial implementation, and an experiment to validate the technique. The system consists of five steps: taking social media as input, converting it to text, validating it, extracting essential information, predicting its class, and storing it in a dataset. The modest size of the manually produced dataset utilized in the original experiment is a key drawback of the work discussed in this research. The modest size proved inconvenient for Deep Learning algorithms, which operate best with massive datasets. When we complete the entire system, inserting increased data from social media into the dataset will resolve this limitation. The other limitation is the partial implementation of the framework, which does not provide a comprehensive picture of the proposed approach. Our future works will address the remainder parts of the proposed framework.
A Machine Learning Model for Prediction of Malaria from Microscopic Blood Cell Images
(IEEE Xplore, 2024) Samson Otieno Ooko; Charles Theuri Kagwi
Machine learning (ML), a pivotal subset of artificial intelligence (AI), has been instrumental in developing systems that learn from and enhance their performance based on data. This technology has facilitated the creation of predictive models for a range of diseases, including pneumonia, heart disease, and COVID-19, allowing for diagnosis based on specific data parameters. Traditionally, malaria detection has relied on the microscopic examination of blood cells, a method that is not only time-consuming but also prone to misdiagnosis, leading potentially to the incorrect treatment of patients. This study introduces a machine-learning model designed to identify patterns in microscopic images of blood cells to differentiate between healthy and malaria-infected cells. Utilizing publicly available datasets from Kaggle for both training and testing, we evaluated the performance of K-Nearest Neighbor (KNN) and Convolutional Neural Network (CNN) algorithms. Our findings show that the CNN model significantly outperformed the KNN model, achieving an accuracy of 94%, and requiring less memory and computational time. Therefore, the CNN model is recommended for further development and use. The implementation of this model represents a significant step forward in achieving the sustainable development goals related to health and wellness, offering a more reliable, efficient, and scalable tool for malaria diagnosis.
A Unified Generative Artificial Intelligence Approach for Converting Social Media Content
(IEEE Explore, 2024) Lossan Bonde; Severin Dembele
Social media content is relevant for many applications, including applications that assist in fighting the plague of terrorism through Artificial Intelligence (AI). However, social media content is diverse in its form - text, image, audio, and video. Depending on the nature of the applications, it may be desirable to convert all these forms into a unique format to ease processing. Once the data is converted into text, it is then possible to organize it into structured tabular data to feed Machine Learning (ML) algorithms for real-time terrorist attack detections. This paper explores using the emerging Generative Artificial Intelligence (Gen AI) tools for converting social media content (text, image, audio or video) into text format suitable for applying machine learning algorithms. The methodology of this research consisted of studying existing Gen AI tools, evaluating and selecting the best among those that offer API or code integration to implement a tool for converting all forms of social media content into text. The main limitation of this work is the small size of the datasets used in the tools’ evaluation. The design and implementation of the proposed solution have been completed, and the tool is ready for use and integration into a framework for collecting and analysing social media content to fight against terrorism.
Achieving Organizational Performance in Profit-Oriented Businesses Through the Use of Artificial Intelligence
(Pan-African Journal of Education and Social Sciences (PAJES), 2023) Lossan Bonde; Prof Musa Nyakora
Artificial Intelligence (AI) is undoubtedly one of the most evolving technologies, finding its application in almost every aspect of human activity. At the individual, business, and corporate organization levels, AI transforms lives and business processes and affects how people work. There is extensive literature on AI’s potential positive contribution to organizational performance. However, there is a lack of research on how to leverage AI to effectively achieve organizational performance. This paper seeks to fill that gap by 1) identifying the AI components driving organizational performance and then 2) designing a conceptual framework for integrating AI into an organization to achieve higher performance. A significant limitation of this work is the lack of implementation and testing of the framework, which we will address in future research.
Addressing the Ten Commonly Asked Questions about Qualitative Research in the Philippines
(2017-12-25) Dr. Wa-Mbaleka, Safary
There is no doubt that the need for qualitative research has increased and has been felt all around the world. Once feared, detested, or even not much valued by some, qualitative research has now become the rare bird many people are trying to catch. Unfortunately, as more and more people and institutions try to embrace qualitative research, maybe more damage is being done in the process because of the lack of solid understanding of qualitative research. To pave a strong way to excellence in qualitative research conduct and dissemination, it is important to have an idea of the current state of qualitative research. This paper is based on content analysis of the input from 197 higher education professors, administrators, researchers, graduate and doctoral students from 40 higher education institutions in the Philippines. It is based on 10 most commonly asked questions about qualitative research. These questions are grouped into three major themes: the fundamentals, the methodology, and the trustworthiness of qualitative research. Understanding these commonly asked questions can help us pave better the way to quality capability training in qualitative research.
Adventists in politico-military strife and violence
(Ministry International Journal for Pastors, 9-12, 2016-02) Dr. Wa-Mbaleka, Safary
African Traditional Religion and Seventh-day Adventism in Africa: The Entanglement Debate
(Journal of Asia Adventist Seminary, 2024) Gabriel Masfa, PhD
Seventh-day Adventism in Africa finds itself in a complex context of maintaining its identity within traditional African religious systems. This identity struggle is partly linked to the failure of early Adventist missionar-ies who brought the gospel to Africa without much knowledge of African traditions. Some missionaries believed that no religious heritage existed prior to their arrival in Africa. Such an approach to missionary activities created a setback in the process of contextualizing the Christian message in the African continent. This article reflects on the identity crisis in African Seventh-day Adventism today by analysing the belief systems of African Traditional Religion and how and why many Seventh-day Adventists in Africa still find themselves entangled in traditions long after their conversion to the Adventist faith. The article presents some recommendations on how the Seventh-day Adventist Church can address the identity crisis in the de-nomination in Africa
An assessment of the effectiveness of records management practices in Adventist Health Institution in Ghana
(GE-International Journal of Management Research, 2016-08) Dr. Nwaomah, Angela E.
This paper is a report of a study that evaluated the practice of effective records management in the Seventh-Day Adventist Hospital in Kwadaso-Kumasi, Ghana. The study revealed that only 46.7 percentage of the records managers have professional qualifications/specialized training in records management. The findings also revealed that there is a positive level (51.1%) of effective records management practices in the hospital. However, those with the job title records manager faced some specific constrains that hinders the maximum achievement of records management effectiveness. The conclusion drawn is that, certain factors are responsible for the challenges. The paper then offers some recommendations that will help the hospital management and Ghana government deal with those challenges.
An Evaluation of Machine Learning Techniques for Crop Detection from Garden Images
(IEEE Xplore, 2023) Samson O. Ooko; Grace Kwagalakwe; Lossan Bonde
Agriculture is a major driver for different economies across the globe. With the continued advancement in technology, there is a move towards precision agriculture. A major area of research interest is the detection of crops by use of computer vision. Such can help in controlling pests and diseases and thus increase yields. However, given the wide range of techniques applied, there is a need to evaluate them to recommend the most suitable for the detection of different crops. This study was thus aimed at evaluating both traditional Machine Learning (ML) and Deep Learning (DL) techniques for the detection of banana and cassava crops from a set of garden images. First, a crop classification model was built using the traditional machine learning model with feature extraction algorithms being applied before training using K-Nearest Neighbor (KNN) and Naïve Bayes. Another crop classification model was also built using deep learning (CNN) on an annotated dataset. The performance of both models was evaluated with deep learning giving the best result. Deep learning is thus recommended as the best model for crop detection.
An Evaluative Study of Management Practices and the Effects on Employees Performance and Attitude
(International journal of research and innovation in social science (IJRISS), 2025-03-10) Dr. Angela Ewhonne Nwaomah
This evaluative study investigated the relationship between management practices and their consequences on employee outcomes within selected faith-based organizations. By examining a diverse range of management practices, including communication flow, Participatory decision making of lower cadre of staff, putting people before paper work and equality in workplace. The research aimed to identify the direct consequences of the management practices on the employees in relation to their Job performance and attitude or feelings on the job. Utilizing quantitative methods, data were collected from surveys of 104 employees representing 85% response rate across the selected faith- based organizations in Kenya. The findings revealed specific pattern of management practices regarding communication flow, participatory decision making of lower cadre of staff, putting paper work before people and as well as revealed unclear denominational policies as the primary cause of Inequality in workplace and the various ways inequality is evident in the organizations. The findings also revealed that effective management practices enhance employee engagement and productivity, while the ineffective management practices affect employees’ emotional and professional well-being. The study highlights the critical role of management in shaping workplace culture and suggests actionable recommendations for leaders to foster a more positive and productive work environment. Ultimately, this research contributes to a deeper understanding of how management practices affect employee performance and well-being, and organizational success.
An inquiry into the historicity of the Tabernacle in ancient Israel
(The American journal of biblical theology, 2019-01-20) Melak A. Tsegaw, PhD
The historicity of the passage that narrates the construction of the tabernacle, also called the tabernacle account, has been highly debated. Was there a tabernacle in ancient Israel? What are the evidences that validate the historicity of the tabernacle? This paper attempts to answer these questions by employing the historical-descriptive method, following the procedural steps proposed by V. Philips Long for the historical exploration of biblical texts. Hence, the study concludes that the tabernacle account makes a truth claim based on a closer investigation of its content and context. Also, the truth value of this claim is affirmed by examining the internal as well as the external consistency of the account.
Analysis of Students’ Knowledge, Attitudes and Behavior towards Sustainability and Sustainable Lifestyle: Implications for the Sustainable Future of Africa
(2020-12) Dr. Ganu, Josephine; Ocansey, Evans
Sustainable development has become a critical concern in the 21st Century. While a number of players are actively engaged in the delivery of the SDGs,the unique contribution of educational institutions of higher learning is key to achieving the SDGs. Apart from the fact that quality education can break the shackles of poverty and hunger (SDG 1 & 2), spur economic growth and decent jobs (SDG 8), we argue that quality educational institutions of higher learning play a critical role in grooming future leaders and workers to develop global social consciousness, positive sustainable development mind-set and adopt a sustainable lifestyle.Therefore,this empirical study utilized a cross-sectional descriptive research design and surveyed 422 respondents to examine the level of students’ awareness of sustainability issues, their attitudes towards sustainability and their current lifestyle in selected countries in Africa. The results suggest that generally, students have a fair idea of sustainability issues. They seem to know a lot about pollution and deforestation, however, they lack a deep understanding of other key sustainability-related concepts that confront our world today. More so, they appear to have positive attitudes towards the multi-dimensions of environmental sustainability. Nevertheless,their daily actions and lifestyle do not powerfully support what they profess. Implications of the study results are therefore discussed.
Application of Tiny Machine Learning in Predicative Maintenance in Industries
(Journal of computing theories and applications, 2024-08-02) Samson O. Ooko; Simon M. Karume
The advancements in the Internet of Things (IoT) and Machine Learning (ML) have enabled significant improvements in Predictive Maintenance (PdM) in industries, providing economic benefits by reducing equipment downtime and maintenance costs. Traditional ML approaches, however, re-quire more computational resources and are often limited to cloud-based processing, leading to in-creased costs and high latencies. Tiny Machine Learning (TinyML) offers a novel solution by enabling ML models to run on low-power, resource-constrained devices at the edge, facilitating real-time, on-device inference. This review analyzesTinyML applications in PdM, highlighting the technology's po-tential to transform industrial maintenance practices. We explore the differences between TinyML and standard ML, discuss the economic and operational advantages of adopting PdM, and present practical case studies where TinyML has been successfully implemented. In addition, we address the challenges facing TinyML, including hardware limitations and the need for specialized algorithms. Our findings indicate that while TinyML is a promising technology for PdM, further research is needed to overcome these challenges and fully realize its potential. This review contributes to understandingTinyML's role in industrial PdM and outlines a roadmap for future research and development in this emerging field.
Applications Of Goal-Setting Theory On Students’ Take-Home Assignments Using Content Analysis Approach
(International Journal of Humanities and Social Science Invention (IJHSSI), 2018-03) Okezie, Goodlucknwokoma; Prof. Nyakora, Musa O
The Information and Communication Technology (ICT) and Social Media have kept most of the typical university students very busy, but not in aid to their academic exercises. Experiences in years of University teaching and observations showed that many of these students are unable to meet up with the stipulated time for take-home assignments. The attempt of this study is to use goal setting theory to develop a process by which an average University student will be equipped to complete and submit such assignments. The Directed Method of Content Analysis was adopted. It is a deductive process, which correlate theory with data. Qualitative codes were generated from selected articles using the Search Project dialogue box of ATLAS. ti, version 8. Themes such as learning orientation, performance orientation, goal-setting, learning, effectiveness, task complexity, feedback, action, motivation and result, were generated and grouped into five models. The coefficients for the five models were 0.002, 0.380, 0.006, 0.131 and 0.326, respectively, while their t coefficients were 0.190, 0.710, 0.204, 0.289 and 0.204 for each model. The c- and t- coefficients of model 1 showed that combinations of learning orientation and performance were not strong. Model 2 revealed a very strong congruency between goal setting and performance. If the typical University student sets goals that are focused on a take-home assignment, this will direct energy on activities that will lead to the completion and submission of the assignments
Biblical Foundations of Giving Insights Through the Seven WH Questions
(Steward Ministries magazine, 2024) Melak Alemayehu Tsegaw, PhD
Giving is a fundamental aspect of God’s kingdom, rooted deeply in the foundation of love. As the saying goes, “You can give without love, but you cannot love without giving.” This principle is woven throughout Scripture, illustrating how God designed His kingdom to operate on the principle of receiving in order to give. Understanding and embracing the concept of giving is crucial for anyone who desires to be part of His kingdom. This article explores the biblical foundation of giving, structured around seven key questions: What?, Why?, Who?, To Whom?, Which?, When?, and Where? From a biblical perspective, we will uncover the importance of giving in the Christian faith and how it should be practiced according to biblical principles.
Biblical Narratives of Steadfast Grit: A Select Example in Cultivating Psychological Fortitude
(Pan-African Journal of Theology, 2024) Dr. Mahlon, Juma
Psychological grit is credited to Angela Duckworth. Psychologists have investigated grit as a personality trait, educators as a character trait, and economics as a non-cognitive competence or soft skill. Additionally, it has been translated into Russian, Japanese, German, Korean, Turkish, and Spanish. However, the attributes associated with grit, such as courage, conscientiousness, excellence, resilience, and optimism, are similar to Bible terminology. However, the literature is scarce, and there is a knowledge gap about these characteristics from a biblical standpoint. Critics have proposed that future studies look into the useful applications of grit in educational contexts and other languages. In response, the story investigated the following issues: (1) What words do the New and Old Testaments use to describe grit’s courage, conscientiousness, excellence, resilience, and optimism? (2) Who are the Biblical characters who demonstrated these virtues? The analysis revealed that grit is an abundant biblical attribute in both the New and Old Testaments. Countless Bible characters demonstrated grit. Distressing end-times call on Christians to display grit.
A Brief Ethnography on Philippine English
(2014-04) Dr. Wa-Mbaleka, Safary; Blath, Claudia; Lloren, Janice; Duan, Wenwan
The Philippines is a nation with a rich culture and heritage that reflects the indigenous diversity of the islands. Its present identity and unique features are not whimsical. They are mainly the result of a combination of events throughout its history. Its linguistic diversity and cultural uniqueness— e.g., being the only Asian Christian country—are clear evidence of several colonial influences (Hechanova, 2012; Miller, 2014). Using an ethnographic approach, this paper examines English, Taglish, and pragmatic aspects in a suburb and a metropolitan area of the Philippines. This study reveals that socioeconomic status, educational attainment and background go hand in hand with the level of exposure and usage of the English language. It also shows that the interactional and speech acts that nine participants demonstrated during the interviews, together with the artifacts found on the research sites, are reflections of their culture. The study also led to the conclusion that code-switching or Taglish is common among English-speaking Filipinos. Finally, more English proficiency was evidenced with people who had attended private schools more than those who attended public education.

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