ANSPOLY Journal of Advanced Research in Science & Technology (AJARST)
ANSPOLY Journal of Advanced Research in Science & Technology (AJARST) is an interdisciplinary annual open access, peer-reviewed International Journal published by the Anambra State Polytechnic, Mgbakwu.
ARTIFICIAL INTELLIGENCE (AI) FOR SUSTAINABLE DEVELOPMENT IN MULTILINGUAL CONTEXTS: INSIGHTS FROM ENGLISH USAGE IN ANAMBRA STATE RELIGIOUS SETTINGS
This paper explores the integration of Artificial Intelligence (AI) in education for sustainable development within multilingual contexts, drawing insights from the usage of English in religious settings (Catholic, Anglican, Pentecostal) in Anambra State, Nigeria. In Nigeria, Christian religion plays integral roles In the lives of the people. It helps to inculcate good moral values in the lives of the members of the community through the use of language. The study examines how AI can enhance language education and promote inclusivity in diverse cultural settings. By analyzing English language dynamics in these religious contexts, the research identifies pathways for AI to support sustainable education goals through tailored language learning and teaching strategies. Findings highlight the potential of AI to bridge language gaps, foster cultural sensitivity, and contribute to sustainable development in multilingual educational environments. Implications for AI implementation in similar contexts are discussed.
Copyright (c) 2026 Anthony Ogugua Obiesili, Peace Adaobi Ike (Author)
ARTIFICIAL INTELLIGENCE IN THE NIGERIAN BUSINESS ENVIRONMENT: ADOPTION, CHALLENGES, AND FUTURE PROSPECTS
Artificial Intelligence (AI) has emerged as a transformative force in the global economy, changing the way businesses operate, their productivity, and competitiveness. However, the adoption of AI and its integration in business, vary by regions due to factors such as differences in regulatory environments, business climates, and infrastructural readiness. Thus, this paper analyzed the historical background of AI, the regulatory environment of Nigeria, and the prevailing business climate that informs its adoption. Grounded on the Diffusion of Innovation Theory, the study employed a qualitative exploratory strategy and founded its results on secondary information gleaned from government policy documents, scholarly books and articles, and industry reports, complemented by case findings from some Nigerian firms adopting AI. The report revealed that while Nigeria has achieved remarkable strides through national digital economy policies and emerging AI regulations, regulatory gaps remain, particularly in areas under data protection, ethical standards, and enforcement capacity. The Nigerian business landscape, founded on entrepreneurial drive, fintech technological innovation, and growing start-up ecosystems, is full of potential for AI integration. Yet, barriers such as weak digital infrastructure, lack of technical expertise, weak policy enforcement, ethical considerations and costly business operations deter large-scale adoption. Despite these limitations, Nigeria's prospects for AI opportunities are bright, with its potential applications in finance, healthcare, agriculture, and logistics to enhance efficiency, innovation, and competitiveness. The study concludes that AI penetration into Nigeria's business environment requires regular regulatory frameworks, improved infrastructure, and targeted capacity-building interventions.
Artificial Intelligence, Regulation, Business Environment, Adoption, Nigeria
Copyright (c) 2026 Anthonia Onyinye Ilodigwe (Author)
ARTIFICIAL INTELLIGENCE AND SUSTAINABLE DEVELOPMENT IN AGRICULTURAL ENGINEERING: A SYSTEMATIC REVIEW ON PRECISION AGRICULTURAL TECHNOLOGIES. (SMART FARMING)
This study investigates the transformative role of Artificial Intelligence (AI) in promoting sustainable development within agricultural engineering. By applying the PRISMA methodology, we systematically review literatures from 2018 to 2024, focusing on AI applications that align with the three pillars of sustainability: economic viability, environmental stewardship, and social responsibility. The findings reveal that AI technologies; such as smart farming, machine learning, computer vision and predictive analytics are reshaping agricultural practices through precision farming, climate-resilient strategies, and smart resource management. The paper concludes with recommendations for future research and policy frameworks to enhance AI integration in sustainable agriculture.
Artificial Intelligence, technology, sustainability, precision agricultural practices, climate resilient strategies, smart farming,
Copyright (c) 2026 Obumneme O. Obieze, Omenogor Ikoko (Author)
INTEGRATING ARTIFICIAL INTELLIGENCE INTO RESEARCH IN BUSINESS AND ENTREPRENEURSHIP EDUCATION IN TERTIARY INSTITUTION IN SOUTH-EAST, NIGERIA.
This study investigated the integration of Artificial Intelligence (AI) into research in business and entrepreneurship education in tertiary institutions in South-East Nigeria. Three research questions and hypotheses were formulated for the study. The descriptive survey design was adopted, with a population of 5,000 lecturers and students across fifteen tertiary institutions. A multistage sampling technique was used to select a sample of 200 respondents. Data were collected using a validated and reliable questionnaire (Cronbach’s alpha = 0.83) and analyzed using descriptive statistics and independent t-tests. Findings revealed a moderate extent of AI integration into research activities (grand mean = 3.05), with limited utilization of advanced tools such as plagiarism checkers and predictive analytics. Major challenges identified included poor digital infrastructure, inadequate funding, limited digital literacy, weak institutional policies, and the high cost of AI tools (grand mean = 3.55). Respondents strongly agreed on strategies to enhance AI integration (grand mean = 3.67), emphasizing capacity-building, funding, infrastructure upgrades, curriculum reform, and industry collaboration. Hypotheses testing showed no significant differences between public and private institutions or between lecturers and students regarding integration, challenges, and strategies. The study concludes that while AI awareness is growing, systemic barriers hinder deeper adoption. It recommends policy support, increased funding, capacity-building, curriculum reforms, infrastructure investment, and stronger industry partnerships to fully harness AI’s potential in business and entrepreneurship education research.
Artificial Intelligence, Research, Business and Entrepreneurship Education and Tertiary Institutions.
Copyright (c) 2026 Chimezie Ada Ibezim (Author)
SMART INFRASTRUCTURE MONITORING FOR SUSTAINABLE PUBLIC FACILITY MAINTENANCE IN NIGERIA
Nigeria’s persistent public facility deficit is compounded by a weak maintenance culture, accelerating infrastructure deterioration and undermining returns on public investment. This study explores the potential of smart infrastructure monitoring systems: encompassing sensor networks, predictive analytics, and real-time reporting, to strengthen public facility maintenance in Nigeria. Using a documentary research design, 32 policy documents, peer-reviewed studies, and global case reports published between 2014 and 2024 were systematically reviewed and thematically analyzed to assess existing maintenance frameworks and the applicability of smart monitoring technologies. Findings indicate that more than 85% of current maintenance practices rely on manual inspections and reactive repairs, resulting in high life-cycle costs, prolonged service disruptions, and limited data for planning. Evidence from international best-practice cases demonstrates that continuous condition monitoring and predictive maintenance models can reduce downtime by up to 40% and extend asset lifespan by 20–30%. The study concludes that embedding smart monitoring systems within Nigeria’s public asset management framework is essential for enhancing service delivery, optimizing expenditure, and promoting infrastructure sustainability. Recommendations include targeted policy reforms, capacity-building programmes for public works agencies, and public–private partnerships with technology providers to institutionalize proactive, data-driven maintenance practices.
Predictive Analytics, Asset Management, Digital Governance, Infrastructure Sustainability, Service Delivery
Copyright (c) 2026 P. Chiamogu Amobi , P. Chiamogu Uchechukwu (Author)
AI-DRIVEN CURRICULUM DESIGN IN NIGERIAN POLYTECHNICS FOR INDUSTRY 4.0 SKILLS
The rapid transformation driven by the Fourth Industrial Revolution (4IR) demands a fundamental reorientation of technical and vocational education systems to equip graduates with industry-relevant skills. This study investigates the potential of integrating Artificial Intelligence (AI) into curriculum design in Nigerian polytechnics to foster adaptive and competency-based education. Adopting a documentary research design, we systematically reviewed 28 policy documents, academic studies, and industry reports published between 2015 and 2024, using thematic content analysis to assess existing curriculum frameworks and AI adoption patterns. Findings reveal that over 80% of current curricula lack explicit alignment with emerging 4IR skill requirements, and none incorporate AI-enabled adaptive learning systems. Evidence from international case studies suggests that AI-powered curriculum design can dynamically align course content with learner profiles, track skill acquisition in real time, and integrate continuous industry feedback. We conclude that AI integration is essential to closing the skills gap between Nigerian polytechnic graduates and labour market needs. The study recommends a tripartite strategy involving the National Board for Technical Education (NBTE), technology providers, and industry stakeholders to co-develop adaptive learning platforms, train educators in AI tools, and institutionalize industry–academia partnerships for innovation-led workforce readiness.
Adaptive Learning, Skills Alignment, Workforce Readiness, Skills forecasting and Edtech innovation
Copyright (c) 2026 P. Chiamogu Amobi, P. Chiamogu Uchechukwu (Author)
CURRICULUM CHANGE AND ARTIFICIAL INTELLIGENCE INTEGRATION: IMPLICATIONS FOR LEARNING ENVIRONMENT AND STUDENTS’ QUALITY OF LIFE IN NIGERIA.
Curriculum change is central to educational reform in Nigeria, particularly with the growing demand to integrate Artificial Intelligence (AI) into teaching and learning. This study investigates the relationship between curriculum change involving AI, the learning environment, and students’ quality of life in Nigeria, using Metropolitan College, Onitsha, Anambra State as a case study. The study population consisted of 748 students of 2025 academic session, including 413 junior class students (55.2%) and 335 senior class students (44.8%). A descriptive survey design was employed, and structured questionnaires were distributed to a stratified sample representing 20% of the total population (n = 150). Data were analyzed using descriptive statistics and correlation analysis. Findings indicate that 72% of respondents agreed that AI-driven curriculum reforms improved access to interactive learning resources, while 65% reported enhanced classroom engagement. Similarly, 58% noted that AI-supported learning reduced academic stress and improved motivation, directly impacting students’ quality of life. Despite these benefits, 61% of students identified infrastructural limitations, such as poor internet connectivity, as a major barrier, while 54% emphasized inadequate teacher training in AI usage. The study concludes that AI integration in Nigeria’s curriculum significantly improves the learning environment and students’ well-being, but sustained policy support and resource allocation are essential for success. It recommends increased investment in digital tools, structured teacher training, and student-centered AI applications to maximize educational outcomes and quality of life.
Curriculum Change, learning environment, student quality, AI integration
Copyright (c) 2026 Francis Okereke Okorie, Chinyere Rosemary Ibe , Desire Amaka Francis-Okorie , Chikodiri Scholastica Uzondu , Lovelyn Chinwendu Ajubiga (Author)
ARTIFICIAL INTELLIGENCE (AI) AS A TOOL FOR SUSTAINABLE DEVELOPMENT IN COOPERATIVE ECONOMICS AND MANAGEMENT
This study investigates Artificial Intelligence (AI) as a tool for sustainable development in cooperative economics and management, with a focus on students in the Department of Cooperative Economics and Management, Nnamdi Azikiwe University, Awka. The population comprised 150 newly admitted students of the 2024 academic session. Using Yamane’s (1967) formula for sample size determination at a 5% margin of error, a representative sample of 109 students was selected. A descriptive survey design was adopted, and data were collected using structured questionnaires. Descriptive statistics (percentages and means) and chi-square tests were employed for data analysis. Findings showed that 72% of respondents believe AI enhances transparency and accountability in cooperative management, while 68% agreed it promotes financial inclusion by broadening access to cooperative services. Additionally, 64% reported that AI improves resource management and reduces waste, thereby contributing to environmental sustainability. However, 59% of respondents identified inadequate digital infrastructure and 55% highlighted low technical literacy as major barriers to AI adoption. The null hypothesis, which stated that AI has no significant effect on sustainable development in cooperative economics and management, was rejected at a 0.05 significance level (χ² = 21.47, p & lt; .05). The study concludes that AI can significantly promote sustainable development in cooperative management if integrated into education and practice. It recommends targeted investment in digital infrastructure, policy support, and training programs to enhance AI literacy and adoption among cooperative stakeholders.
Artificial intelligence, sustainable development, cooperative economics and management, Nnamdi Azikiwe University
Copyright (c) 2026 Francis Okereke Okorie , Rosemary Chinyere Ibe , Desire Amaka Francis-Okorie , Zipporah Kelechukwu Ogenyi , Chikodiri Scholastica Uzondu (Author)
ENERGY CONSUMPTION OPTIMIZATION IN WIRELESS SENSOR NETWORK FOR ENVIRONMENT MONITORING
Wireless sensor network (WSN) has become increasingly common in several fields of human endeavors requiring information gathering and prediction in both military and civil operation. This work has presented modified energy efficient cluster based routing in wireless sensor network for environment monitoring. The scheme uses hierarchical routing protocol technique which is based on the fact that energy used for long transmission of message is very much greater than energy required for sending message over short range. A WSN was developed using MATLAB C code and with the proposed scheme simulations were carried out to analyze and investigate the effectiveness of the system in terms of optimum range of clusters required to optimize energy of WSN which revealed that the maximum number of cluster is 54. The variation of energy per round against the number of cluster shows that energy consumed per by each sensor node in the cluster is reduced as number of cluster is increased. This indicated that with the modified algorithm there is energy consumption optimization in WSN.
Wireless Sensor Network, Optimization of Energy.
Copyright (c) 2026 Hope Ifeoma Ezeanya , John Nnamdi Nwoye (Author)
FACTORS INFLUENCING ACCESS TO AGRICULTURAL CREDIT AMONG FARMERS’ COOPERATIVE SOCIETY'S MEMBERS IN ANAMBRA STATE
This study examined the determinants of agricultural credits access among members of farmers’ multipurpose cooperative societies in Anambra state. The Specific Objectives of the study is to investigate the effect of educational background of cooperative farmers in accessing agricultural credit in Anambra state and to analyzed the size of farm land of cooperative farmers and its effect in accessing agricultural credit in Anambra state, In line with the above objectives, two research questions and two hypotheses were formulated. This study was particularly anchored on the social exchange theory. It was carried out in three agricultural zones in Anambra state, Nigeria. A multi stage random sampling technique was used to arrive at a sample size of twenty four cooperative societies with membership strength of 286 farmers as sample size. The instrument for data collection was a set of structured questionnaire on a 5-point likert-scale Data was analyzed using the multiple regression models. Model results indicated that Educational background of members of farmers multipurpose cooperatives significantly (3.00), t (285) = 23.98, 13.13 and 20.63; and p-values = .000have effect on agricultural credit access and Farmland size significantly (3.00), t(285) = 13.01, 4.88and 12.91; and p-values = 0.000, respectively have effect on agricultural credit access. In line with the findings of this study, it is recommended that there should be a deliberate policy aimed at providing free educative seminars to all illiterate farmers to teach them possible ways and methods of acquiring as well as proper utilization of agricultural credit. Good Policies on land redistribution should be made to make more land available to cooperative farmers, especially the experienced farmers
Agricultural credit, educational background, size of farmland, cooperative societies
Copyright (c) 2026 Ebele Theresa Ufoaroh , Ifeoma Mirian Molokwu , Paschaline Chidiebere Ozoemena , Uju Monica Ifesinachi (Author)
INCLUSION OF ETHNOGRAPHY OF SPEAKING IN L2 SPEAKING SKILL: PANACEA FOR EDUCATION POLICY, IMPLEMENTATION AND REFORM
In Second Language Teaching (SLT) of speaking skills, attention is paid more on performance while little attention is paid in the aspect of social communication performance. More scholars advocate for the inclusion of the culture of the native speakers in ESL without considering what is acceptable in the cultural environment of the ESL learners. This paper examines the cultural correctness in communication while using the Second Language during conversation L1 linguistic environment. It employed descriptive research design to explore the relevance of integrating local culture in communication skill of ESL learners and drwas inference from HYmes (1972) Communicative Theory to guide the research. Communication theory also known as Ethnography of speaking theory upholds that the meaning of words is basically determined by the society; meaning that what is communicated must be said the way the society permits language should be used in various occasions or pay attention to the language of the society. This work upholds that the social use of language is of great essence in language learning and teaching. This is because actual communication puts into consideration the societal norms as it concerns language use and occasion in order to understand distinct cultural ad contextual dimensions of communication. This paper explored the opinions of other researchers on this topic to highlight the importance and necessity for the inclusion of ethnography of communication in the learning of speaking skills in English as a Second Language.
Ethnography of speaking, Culture, Second language learning,
Copyright (c) 2026 Chinenye Onyinyechukwu Helen Abana, Temple Chiadikaobi Ezeh, Peace Adaobi Ike, Amaka Evelyn Chidebe (Author)
WASTE MANAGEMENT PRACTICES AND ORGANIZATIONAL PERFORMANCE IN BEVERAGE MANUFACTURING FIRMS IN SOUTH-EAST NIGERIA
Waste Management Practices and Organizational Performance in Beverage Manufacturing Firms in South East Nigeria. With the growing concerns over environmental sustainability and corporate efficiency, waste management has become a critical focus in the manufacturing sector. This study investigates the effect of waste management practices on organizational performance in beverage manufacturing firms in South East Nigeria. The study seeks to find out specifically the effect of, waste recycling on organizational profitability and waste reduction on operational efficiency in beverage manufacturing firms in the region. Relevant conceptual, theoretical and empirical literature were reviewed, taking cognizance of the problem and hypothesis of the study. The study was anchored on Resource -Based View (RBV) theory developed by Wernerfelt (1996), which holds a reasonable explanation for the relationship that might exist between waste management and corporate sustainability. And also the theories of environmental sustainability by Robert Goodland (1995). Primary data was collected through survey method and interviews with managers and employees in selected beverage manufacturing firms. The population of the study comprised 2090 employees in selected Beverage Manufacturing firms in South-East Nigeria. A sample size of 408 was determined by using statistical formula devised by Borg and Gall (1973). The result showed that waste recycling had a significant positive effect on organizational profitability and this implies that firms with effective waste management strategies experience improved production process. Secondly, that Waste reduction had a significant positive effect on operational efficiency in beverage manufacturing firms in south- east Nigeria. The study concluded that waste management had a significant positive effect on organizational performance. This shows that the integration of efficient waste management systems not only contributes to environmental sustainability but also plays a pivotal role in enhancing the competitiveness and long term success of beverage manufacturing firms in south east Nigeria. Based on the findings, the study therefore recommended that Beverage manufacturing firms should formalize recycling initiatives as core components of their operational strategy as well as establish dedicated recycling units within the production plants to ensure systematic sorting, collection, and processing of recyclable materials, and that Beverage manufacturing firms should fully integrate Lean Manufacturing tools-such as 5S, kaizen, and Just-In-Time (JIT)- to systematically eliminate waste at every stage of production. This shows that waste management should be part of the organizations strategic goals by linking waste reduction targets with performance.
Interdisciplinary Research, Science and Technology, Peer-reviewed Journal, Scientific Innovation, Scholarly Discovery
Copyright (c) 2026 Anthony Chukwuma Okoye, Ogochukwu Joy Okoye (Author)
SCALABILITY OF AMBIENT ENERGY HARVESTING (AEH) TECHNOLOGY
The Energy Harvesting Chain from ambient source to electrical load of a complete energy harvesting system is an integrated chain of components, each playing a critical role in converting ambient energy into a stable power supply for an electronic load. The main forms of ambient phenomena include solar, thermal, kinetic and electromagnetic energies. A review of the scalability methods of these phenomena for industrialization and secured futuristic balance include use of perovskite, smart management tools, low cost polymer and respectively.
Solar, Thermal, Kinetic, Electromagnetic
Copyright (c) 2026 Ngozi Ernest-okoye, Ugochukwu Chinedu Odogwu (Author)
STRENGTHENING SMALLHOLDER FARMERS’ OUTPUT THROUGH COOPERATIVE-BASED AGRICULTURAL INNOVATIONS
The study titled “Strengthening Smallholder Farmers’ Output through Cooperative-Based Agricultural Innovations” examines the potential of agricultural cooperatives as strategic mechanisms for enhancing smallholder productivity in Nigeria, with specific reference to Anambra State Polytechnic, Mgbakwu. The study investigates how cooperative-based innovations—such as shared access to agricultural technology, credit facilities, input distribution, and collective marketing—contribute to improved yields, income stability, and social empowerment among smallholder farmers. Using a descriptive survey design, a population of 200 respondents (comprising lecturers, agricultural extension officers, and agricultural science students) was purposively selected. A structured questionnaire was administered, and data were analyzed using descriptive and inferential statistics, including mean, standard deviation, and regression analysis. Findings revealed that cooperative societies play a significant role in disseminating innovations and mitigating individual risks associated with small-scale farming. Results also indicated that access to modern farming technologies, cooperative-led extension services, and collective marketing improved farmers’ productivity by an estimated 36%. The study concludes that cooperative-based agricultural innovations are vital to sustainable rural development and recommends enhanced governmental support, capacity building, and the integration of digital technologies into cooperative frameworks to strengthen the agricultural sector.
smallholder farmers, agricultural cooperatives, innovation, productivity, Anambra State Polytechnic, rural development.
Copyright (c) 2026 Chikodiri Scholastica Uzondu, Francis Okereke Okorie , Chinyere Attah, Ekene Ezinwa Nwankwo , Njideka Rita Chikezie (Author)
INDIGENOUS PEOPLE AND INDIGENIZED ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE DEVELOPMENT IN AFRICA
One of the global challenges that confront humanity today is the great divide that dichotomize peoples and countries with socioeconomic labels of developed and developing, rich and poor, Global North and Global South categories. These nomenclatures capture the social injustice that have characterized international relations in the past and which has continued to the present in a more sophisticated way as technocolonialism. Unfortunately it is the indigenous people who are, most of the times, victims of this global injustice. This study, indigenous people and indigenized artificial intelligence for sustainable development in Africa, is an attempt to explore the basis of indigenization of AI for effective development of indigenous people, and the overall realization of Sustainable Development Goals (SDGs). The study adopted the method of content analysis to collect data from World Bank Annual Reports from 2020 to 2025, and the data was analysed using simple percentage calculations. The theories of demystifying emerging media and participatory development provided the framework for the study. The findings of the study revealed that education and empowerment of indigenous people are key to the process of indigenization of AI, which drives the people to assume responsibility for their self-definition and development. The study recommended compulsory study of the history of indigenous people for all indigenous students, that tertiary institutions within the regions of the indigenous communities prioritize and encourage research on indigenous knowledge system and indigenization of AI, and that scholars develop local theories and paradigms for the study and development of indigenous knowledge system. The researcher concluded that indigenization is an effective means of involving indigenous people in AI and community development projects.
Artificial intelligence, cultural identity, development, global divide, indigenization, indigenous data, indigenous people, participation, sustainability, traditional knowledge.
Copyright (c) 2026 K. Inaku Egere, William Nwachukwu Ozuluonye (Author)
THE IMPACT OF AI-ENHANCED ENTREPRENEURSHIP EDUCATION ON ENTREPRENEURIAL INTENTIONS AMONG STUDENTS OF ANAMBRA STATE POLYTECHNIC, MGBAKWU
This study investigates the impact of Artificial Intelligence (AI)-enhanced entrepreneurship education on entrepreneurial intentions among students at Anambra State Polytechnic, Mgbakwu. Grounded in the Theory of Planned Behaviour (TPB), the research examines how AI-driven tools, such as virtual learning platforms, predictive analytics, and AI-supported mentorship, influence students’ attitudes toward entrepreneurship, subjective norms, and perceived behavioural control. A mixed-methods design was employed, combining a structured questionnaire administered to 90 current and former students, selected through stratified random sampling, with semi-structured interviews conducted with 15 purposively selected participants. Regression analysis revealed a significant positive relationship between AI-enhanced entrepreneurship education and entrepreneurial intentions, while thematic analysis of interviews highlighted how AI tools foster practical skills and confidence. Validity and reliability were ensured through pre-tested instruments and triangulation. The findings indicate that AI-driven interventions cultivate positive entrepreneurial attitudes, strengthen subjective norms, and enhance perceived behavioural control, thereby encouraging entrepreneurial ventures. The study recommends that Anambra State Polytechnic, integrate AI-powered tools into entrepreneurship curricula, develop AI-based simulation practical training, and establish AI-supported mentorship and funding platforms to promote sustainable entrepreneurial growth, contributing to transformative education and sustainable development.
Artificial Intelligence, Entrepreneurship Education, Entrepreneurial Intentions, , Theory of Planned Behaviour, Sustainable Development.
Copyright (c) 2026 Chukwuka Ameke Benson , Eugenia Ginika Mmaduakonam Nwadiogo, Chinyere Cordelia Ezenyimulu (Author)
THE IMPACT OF FINANCIAL INCLUSION ON POVERTY REDUCTION AND ECONOMIC GROWTH IN MGBAKWU AND ISUANIOCHA COMMUNITIES
Financial Inclusion is crucial for alleviating poverty and fostering economic growth in rural Nigeria, particularly in underserved communities such as Mgbakwu and Isuaniocha in Awka North Local Government Area (LGA), Anambra State. This study examines the impact of financial inclusion, emphasising fintech innovations, on poverty reduction and economic growth in these communities, with an estimated adult population of 20,000. Employing a mixed-methods approach, primary data were collected via questionnaires (n=200) and interviews (n=15-20, supplemented by secondary data from the Enhancing Financial Innovation and Access (EFInA) 2023 survey and Central Bank of Nigeria (CBN) reports. Participants were selected through stratified random sampling for questionnaires and purposive sampling for interviews. Statistical tests rejected all three null hypotheses, confirming that financial inclusion significantly reduces poverty levels (β = -0.32, p = 0.02), correlates positively with short-term economic growth (r = 0.45, p = 0.01), and is enhanced by fintech (t =2.89, p = 0.004). Fintech adoption, especially mobile money among the 18-34 age group (40% usage), drives entrepreneurship, but barriers such as inadequate digital infrastructure (80% of respondents) and low financial literacy (60% unaware of benefits) persist. Recommendations include investing in rural digital infrastructure, implementing financial literacy programmes, and strengthening regulatory frameworks to promote inclusive fintech. This study fills the knowledge gap in community-specific data and offers policy insights for inclusive rural development.
Financial inclusion, poverty reduction, economic growth, fintech, Mgbakwu, Isuaniocha, Awka North LGA, Anambra State, Nigeria, digital infrastructure, financial literacy.
Copyright (c) 2026 Ekene Ezinwa Nwankwo, Benson Chukwuka Ameke, Chikodiri Scholastica Uzondu, Chiekezie Rita Njideka (Author)
HARNESSING ARTIFICIAL INTELLIGENCE FOR DDOS THREAT DETECTION AND MITIGATION TO STRENGTHEN RESILIENCE IN FINANCIAL AND EDUCATIONAL SYSTEMS
This review explores the application of Artificial Intelligence (AI) techniques for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks in financial and educational systems to enhance operational resilience. A DDoS attack overwhelms a target server, application, or network with excessive or maliciously crafted traffic originating from multiple distributed sources, thereby disrupting normal access for legitimate users. The escalating frequency and sophistication of DDoS attacks present a critical challenge to the stability of digital ecosystems, particularly within financial and educational systems that depend on uninterrupted online services. The risk is compounded by the growing availability of automated attack tools and the rising cyber curiosity among younger users, exposing these sectors to persistent threats. DDoS incidents can cripple essential services, causing financial losses, eroding digital trust, and disrupting learning and research outcomes that undermine sustainable development goals in finance and education. Traditional static defense systems such as firewalls and access control lists (ACLs) have proven inadequate in countering these dynamic and large-scale threats. This review consolidates existing literature on AI-driven DDoS detection and mitigation approaches, including machine learning, deep learning, and hybrid models, highlighting their architectures, performance, and limitations. The study emphasizes the need for adaptive, intelligent, and context-aware defense mechanisms that leverage real-time analytics to protect financial and educational infrastructures. The paper concludes with a proposed conceptual AI-driven resilience framework and outlines future research directions to strengthen digital trust and operational continuity in critical sectors.
Distributed Denial-of-Service (DDoS), Artificial Intelligence (AI), Machine Learning, Cybersecurity, Financial Systems, Educational Systems, Resilience, Mitigation, Digital Trust, Sustainable Development.
Copyright (c) 2026 Stephen Ochiabuto Nwaoha , Blessing C. Mmaduekwe (Author)
MACHINE LEARNING-BASED TECHNIQUE FOR SPECTRUM ALLOCATION IN 5G NETWORKS
The exploitative increase in mobile data traffic and the spread of connected devices has increased the pressure on effective spectrum allocation in Fifth-Generation (5G) networks. Conventional, fixed spectrum management strategies are becoming less effective in response to the very dynamic and heterogenous nature of 5G conditions, which commonly results in under-utilization of spectrum, enhanced levels of interference, and diminished quality of service. This study proposes a machine learning-based spectrum allocation technique using a Deep Q-Network (DQN) reinforcement learning model to address these challenges. A publicly available dataset of 5G spectrum usage on the Kaggle platform consisting of 50, 000 records was used and includes such key parameters as Signal-to-Noise Ratio (SNR), Channel State Information (CSI), User Equipment (UE) density, bandwidth usage, traffic demand, and level of interference. The DQN agent was trained to make real-time, context aware spectrum allocation decisions, depending on the current network states, where spectral efficiency, throughput, latency, interference as well as fairness index were used as a metric to assess performance. The experimental findings showed that the proposed model attained spectral efficiency of 4.85bits/s/Hz, 980 Mbps throughput on average, 11ms latency, 8.2dB interference, and a fairness index of 0.93, which was superior in all metrics compared to the traditional methods of statical allocation. These results indicate that reinforcement learning can be effectively used in dynamic spectrum management in 5G networks, which provides a scalable and adaptable solution to the improvement of network functionality and the utilization of resources in next-generation wireless networks.
5G Networks; Spectrum Allocation; Machine Learning; Deep Q-Network (DQN); Reinforcement Learning; Spectral Efficiency.
Copyright (c) 2026 Onyeka Stanislaus Ezeobi, Nwadiogo E.G Mmaduakonam, (Author)
CONSTRUCTION OF TRANSMUTED PROBABILITY MASS FUNCTION OF DISCRETE UNIFORM DISTRIBUTION ON A DEFINED INTERVAL [A,B]
This study introduces the construction and analysis of a transmuted probability mass function (TPMF) derived from the discrete uniform distribution on a defined interval. The discrete uniform distribution, while widely applied in scenarios where all outcomes are equally likely, is limited by its inability to capture variations in probabilities that arise in practical settings. To address this limitation, the transmutation technique proposed by Shaw and Buckley (2007) is extended to the discrete case, resulting in a more flexible distributional framework. The TPMF is defined by embedding a transmutation parameter, which adjusts the probability structure of outcomes and enhances modeling versatility. The study provides a rigorous construction of the TPMF, beginning with the determination of the normalization constant and establishing its validity through proofs of non-negativity and normalization. Closed-form expressions for key distributional properties such as the mean, variance, and moment generating function (MGF) are derived. Theoretical results are supported with worked examples, demonstrating explicit computation of the PMF, mean, and variance for defined intervals under specified parameter values. These examples verify consistency with probabilistic principles and highlight the adaptability of the TPMF relative to the standard discrete uniform distribution. Findings indicate that the TPMF introduces controlled variability into outcome probabilities without sacrificing analytical tractability. The parameter shifts both expectation and dispersion, making the distribution suitable for contexts where uniformity is unrealistic. Potential applications are discussed in areas such as risk management, decision theory, and fuzzy systems, where probabilistic models must accommodate uncertainty and non-uniform influences. This work thus contributes to probability theory by extending the scope of transmutation methods to discrete distributions, offering a novel tool for statistical modeling and real-life problem solving.
Transmuted distribution, Discrete uniform distribution, Probability mass function, Expectation, Variance, Moment generating function.
Copyright (c) 2026 Obuikem A. Okoli, Chukwuemeka O. Agwu, Daniel Francis (Author)
SYNTHESIS, CHARACTERIZATION AND ANTIMICROBIAL ACTIVITIES OF PYRROLIDIN-2-YLIDENE-2,(4-CHLOROPHENYL)SEMICARBAZONE AND ITS PD(II) COMPLEX
A novel Schiff base ligand has been prepared by condensation between 4-chlorophenylsemi- carbazide and 2-pyrrolidone in the presence of glacial acetic acid with aim to elucidating their structures and determining their antimicrobial activities. The ligand and its Palladium (II) complex were characterized using GC-MS, UV-Vis., IR, XRD, conductivity, melting point measurements and magnetic studies. The ligand and its Palladium (II) complex are pure crystals with space group symmetries of p3121 and p63/mmc and respective cell volumes of 130.907 and 349.022Å3. The complex is diamagnetic with square pyramidal geometry. GC-MS results revealed respective m/z values of 256.2 and 498.2 for the ligand and the complex. Ѵ(M-N) absorption band was observed at 621cm-1 only in the palladium (II) complex of the ligand. The ligand and its palladium (II) were tested in vitro antibacterial activities against S. aureus, E. coli, K. pneumonia, B. subtilis and for antifungal activities againt A. flavus and C. albicans. Among organisms tested, palladium (II) complex of the ligand proved to be a more potent antimicrobial agent against E. coli, B. subtilis and C albicans. Palladium (II) complex exhibited better antimicrobial activity than the free ligand.
Semicarbazones, chelates, pyrrolidone moiety, Anti-bacterial activities, Anti-fungal activities.
Copyright (c) 2026 C.C. Achonye, E.N. Ojiako, O.E. Ogbuagu (Author)
DIGITAL TAXATION AND REVENUE MOBILIZATION IN NIGERIA: 2012 – 2024.
This study examined the effect of digital taxation on revenue mobilization in Nigeria from 2012 to 2024, focusing on the impact of digital stamp duty and electronic value-added tax (e-VAT) platforms. Using secondary time series data, the study employs multiple regression modeling to investigate how digital tax platforms influence tax revenue performance, with GDP and inflation included as control variables. The results of the Ordinary Least Square Regression reveal that both digital stamp duty and e-VAT have a statistically significant positive effect on revenue mobilization, suggesting that tax digitalisation has enhanced the efficiency, transparency, and compliance levels in Nigeria’s tax system. The findings align with earlier empirical studies that emphasize the benefits of digital tax reforms but also highlight the need for macroeconomic stability. The study concludes that expanding and strengthening digital tax platforms is essential for boosting non-oil revenue performance and recommends targeted policy support, technological investment, and economic stabilisation efforts to sustain these gains.
Tax digitalisation, digital stamp, e-VAT, VAT revenue, and Stamp duty revenue
Copyright (c) 2026 Goodluck Happiness Chibuzor (Author)
FRAGMENTED IDENTITIES AND ANONYMITY IN LITERATURE AND AI
This paper examines Chika Unigwe’s On Black Sisters’ Street (2009) using the theoretical framework, postcolonial feminism and digital surveillance ethics. It explores how Unigwe’s narrative of four Nigerian ladies who disguise and remodel their individualities links to modern day concerns of online identity, visibility, and anonymity. The paper reasons that the author’s treatment of masking reflects the act of artificial intelligence (AI) assembling and utilizing of personal data to generate “avatars” or digital versions of people. Though anonymity can shield individuals, it can also intensify manipulation and invisibility. Through the connection of literature and technological ethics, this work portrays how Unigwe’s literary work aids the comprehension of the ethical challenges of visibility and invisibility in a monitored digital world. In achieving this, the researcher utilizes qualitative interpretative research method which is ideal for examining complex social constructs such as identity, anonymity, agency and surveillance. The paper concludes that fragmented identities and anonymity function jointly, supporting forces within On Black Sisters’ Street, determining the characters’ experiences and revealing wider effects for understanding identity in the age of AI and digital surveillance.
AI surveillance, anonymity, postcolonial feminism, digital identity, veiling.
Copyright (c) 2026 Peace Adaobi Ike, Anthony Ogugua. Obiesili, Helen Chinenye Abana (Author)
DEVELOPMENT OF AN AI-ENHANCED SMART ROLE ASSIGNMENT AND AUDIT TRAIL MODEL FOR SECURE ENTERPRISE INFORMATION SYSTEMS
Enterprise information systems face increasing challenges in managing user access and ensuring cybersecurity compliance. Traditional Role-Based Access Control (RBAC) models are often static, requiring manual intervention and lacking intelligent monitoring capabilities. This study proposes an AI-enhanced Smart Role Assignment and Audit Trail Model, integrating machine learning algorithms with RBAC and comprehensive audit logs. The system dynamically recommends user roles, records all user actions, and proactively detects anomalies, enhancing security and operational efficiency. The methodology adopted involved system design and development using ASP.NET (C#) and MS SQL Server, combined with experimental evaluation using simulated enterprise data. The simulated dataset included 1,000 users across 10 modules with historical access logs. Performance metrics such as role assignment accuracy, audit coverage, administrative efficiency, and anomaly detection were measured to assess the system’s effectiveness. Results demonstrated improved role assignment accuracy (93.5%), audit coverage (98%), and a 77% reduction in administrative effort compared to traditional RBAC systems. The findings indicate that AI-enhanced RBAC with intelligent audit trails can significantly improve security, traceability, and operational efficiency in enterprise environments.
AI, Role-Based Access Control, Audit Trail, Enterprise Information Systems, Anomaly Detection, Cybersecurity
Copyright (c) 2026 Blessing C. Mmaduekwe, Benedine Chinelo Nweke , Stephen Ochiabuto Nwaoha (Author)
EXPLORING THE IMPACT OF DIGITAL TRANSFORMATION ON SMALL ANDMEDIUM-SIZED ENTERPRISES (SMES) IN SELECTED FIRMS IN ANAMBRA STATE
This study investigates the impact of digital transformation on Small and Medium-sized Enterprises (SMEs) in developing economies, focusing on the challenges, opportunities, and policy implications for SME growth and development. A mixed-methods approach is employed, combining surveys of 300 SMEs with in-depth interviews of 10 business owners in elected SME organisations in Anambra State. The findings reveal significant relationships between digital transformation, innovation, and SMEs’ competitiveness, which improve customer engagement and increase access to new markets. However, infrastructure constraints, skills gaps, and regulatory barriers hinder the adoption of digital solutions. This study identifies key drivers of digital transformation for SMEs, including cloud computing, big data analytics, and social media. It also emphasizes the significance of government support, infrastructure development, workforce development, and training in facilitating digital transformation. Policy recommendations are provided to address the challenges and leverage digital transformation for inclusive economic growth. These include investing in digital infrastructure, promoting digital literacy, and implementing policies that foster innovation and entrepreneurship. This research contributes tothe understanding of digital transformation’s impact on SMEs in developing economies, informing policymakers, practitioner,s and scholars.
Digital transformation, SMEs, developing economies, innovation, policy implications
Copyright (c) 2025 Benson Chukwuka Ameke (Author)
ACHIEVING SUSTAINABLE DEVELOPMENT OF BOTTLED WATER BUSINESSESIN NIGERIA THROUGH INNOVATIVE DIGITAL MARKETING PLATFORMS
This paper investigated the effect of innovative digital marketing platforms on the sustainable development of bottled water businesses in Nigeria, with a special reference to Anambra State. The paper aimed to investigate how specific innovative social media marketing platforms, affiliate marketing platforms, search engine platforms, email marketing platforms, and mobile marketing platforms contribute to the sustainable development of selected bottled water manufacturing firms in Anambra State, Nigeria. Relevant literature concerning the study variables was reviewed. A descriptive research design was employed, utilizing a survey method. The methodology was used to address the research. Objectives. The hypotheses formulated to guide the study were tested using the partial least squares structural equation modeling statistical technique at a 0.05 level of significance. The findings revealed that an innovative social media marketing platform has a significant and positive impact on the sustainable development of bottled water manufacturing firms. The findings showed that an innovative affiliate marketing platform has a substantial and positive effect on the sustainable development of bottled water manufacturing firms. The study found that an innovative search engine marketing platform has a significantly positive impact on the sustainable development of bottled water manufacturing firms. The findings revealed that the EMA marketing platform has a significant and positive effect on the sustainable development of bottled water manufacturing firms. The study found that an innovative mobile marketing platform has significantly and positively contributed to the sustainable development of bottled water manufacturing firms. Based on the significant and positive effects of innovative digital marketing platforms on the sustainable development of bottled water firms in Anambra State, Nigeria, the paper recommends that innovativeness in digital marketing strategies should be sustained.
Innovative Digital Marketing Platforms, Sustainable Development, Bottled Water Businesses
Copyright (c) 2025 John Chidume Anetoh, Vivian Chioma Anetoh , Nkoli Augustina Chendo, Helen Ijeoma Oranye (Author)
ACHIEVING SUSTAINABLE DEVELOPMENT OF LISTED DEPOSIT MONEY BANKS INNIGERIA THROUGH CREDIT RISK MANAGEMENT
Sustainable development has become a topical issue in the 21st century due to climate change and environmental degradation, which has spurred the implementation of sustainable development by deposit money banks in Nigeria. Sustainable development has become a rising awareness of the ecological, social, and financial aspects. This study examined the effect of credit risk management on the sustainable development of listed deposit money banks in Nigeria, employing a post-facto research design. Secondary data extracted from the financial statements were analyzed using both descriptive and inferential analyses. The study found that credit risk management, as proxied by Nonperforming Loan (NPL) and Loan Deposit Ratio (LDR has a significant and positive effect on the sustainable development of listed Deposit Money Banks (DMBs) in Nigeria. This study recommends, among other things, that bank management of deposit money banks should devise a risk management mechanism to reduce the level of non-performing loans, thereby promoting the sustainable development of deposit money banks in Nigeria.
Credit risk management, Non-performing loan, Loan deposit ratio, Sustainable development, Deposit money banks, Nigeria
Copyright (c) 2025 Vivian Chioma Ajakpo , John Chidume Anetoh , Clara Nkem Okafor , Anthony Onyeka Anyadufu , Chimaobi Johnson Chiekezie (Author)
MANAGING THE CHALLENGES OF ENGLISH AS A SECOND LANGUAGE (ESL) INNIGERIA IN A DIGITAL ERA
English language teaching and learning face numerous challenges. This paper examines the challenges of English as a Second Language (ESL) in Nigeria and proposes strategies for managing these problems. There is no gainsaying the fact that the English language has become a Nigerian language. However, despite being the official language, English poses significant difficulties for Nigerians, impacting education, communication, and economic development, as it is not the native language of Nigerians. Therefore, the Republicans are not the new speakers of the English language. Learning a language involves a complete set of interlocking features, most of which have implications for several problems of learning the English language. The study reviews existing literature on SL Neria, identifying key issues such as linguistic interference, inadequate teacher training, cultural differences, and inadequate instructional materials, among others. To solve these and many other problems, the paper opines that English learners must be extensive readers; teachers must reward efforts of learners to motivate their struggle to acquire the language skills; government as a matter of priority should make available necessary facilities that will empower teaching and learning of English nd also, school management hould e the interest f English rners by providing relevant equipment and facilities for effective English teaching and learning.
English Language, Second language, Bilingualism, Communication, Challenges
Copyright (c) 2025 Anthony Ogugua Obiesili (Author)
STRATEGIES FOR DATA PROTECTION AND PRIVACY IN ADMINISTRATIVEINFORMATION SYSTEMS
Administrative information systems handle sensitive personal data, making data protection and privacy a critical concern. This paper discusses strategies for ensuring patient protection and confidentiality in these systems, highlighting the importance of a multifaceted approach. A comprehensive literature review and a conceptual framework integrating technical, organizational, and legal measures are presented. Technical strategies include encryption, access control, anonymization, and audit trails. Organizational strategies involve data governance, employee training, incident response planning, and compliance with privacy regulations. Legal strategies focus on compliance with data protection regulations and laws, such as GDPR, NDPR, NDPC, and HIPAA. A mixed-methods approach was adopted, combining a survey of administrative information systems professionals (n = 100) with semi-structured interviews (n = 20). The survey and interviews gathered data on the current state of data protection and privacy practices, highlighting the need for improvement. Recommendations are provided for organizations seeking to improve their data protection and privacy practices, including the implementation of technical, organizational, and legal measures. By applying these strategies, organizations can reduce the risks associated with data breaches, unauthorized access, and non-compliance with legal standards, ensuring the integrity, confidentiality, and availability of sensitive data.
Access control, administrative information systems, compliance, Data Governance, data protection, privacy, encryption, audit trails
Copyright (c) 2025 Ifeyinwa Nkemdilim Obiokafor, Uchenna Paulinus Onwuka, Ogochukwu Maryern Okoye, Benson Chukwuka Ameke (Author)
EXPERIMENTAL STUDY ON ADOPTING RENEWABLE ENERGY FORSUSTAINABILITY IN RURAL PARTS OF ANAMBRA STATE: ISSUES ANDPROSPECTS
Nigeria has been experiencing an energy crisis, which has had a profound impact on the economy. The evolution of the energy sector worldwide has triggered intense research on finding alternative renewable energy sources for environmental sustainability. A country’s secure energy supply is needed to support development in all sectors. This opinion paper reviews the state of the power industry in the country. The renewable energy resources potential of Anambra State, and aexploresavenues of improving the efficiency of various alternative energy systems, while minimizing their potentia environmentally disruptive ide effects Considering the pattern of electricity generation and consumption over the last couple of decades, the paper via descriptive literature rreview Proposes how the renewable sources like solar, biomass, wind should be integrated to electricity generation and used to improve power generation in the rural parts of the state.
Sustainability, renewable energy, solar, biomass, wind
Copyright (c) 2025 Francis Chukwudi Ibeneme (Author)