Artificial Intelligence in Education: Psychological Effects and Learning Outcomes of Public Secondary School Students in Abia State (Published)
This study investigated Artificial Intelligence in Education: Psychological Effects and Learning Outcomes of Public Secondary School Students in Abia State. Two research questions guided the study, and two hypotheses were formulated and tested at a 0.05 level of significance. The study employed a descriptive research design. The population of the study comprised 3220 SS II students in the public secondary schools in Umuahia North, Abia State. Five public secondary schools out of seventeen were selected in the Umuahia North Local Government Area for the study using a purposive sampling technique. The sample comprised 109 SS II students from the 5 schools sampled and used for the study. The instrument for data collection was a researcher-designed questionnaire titled “Psychological Effects and Learning Outcomes of Artificial Intelligence Questionnaire (PELOAIQ)”, it was validated by three experts and subjected to reliability using split-half reliability, which was done twice in 2-week intervals, and it yielded a coefficient of 0.80 and 0.83 for the first and second tests. These coefficients indicated that the instrument was reliable for the study. Mean and standard deviation were used to answer the research questions posed to guide the study. The findings from the study showed that students had a moderate agreement that AI has psychological impacts (both positive and negative). AI tends to increase motivation, engagement, and confidence but also raises concerns about distraction, dependency, and anxiety when unavailable; students generally perceive AI as having a positive influence on their academic performance, though concerns about over-dependence and limited task efficiency remain. The study concluded that artificial intelligence (AI) has a generally positive influence on students’ learning outcomes in public secondary schools. The study also recommends that teachers and school administrators should integrate AI tools into classroom teaching in a structured and balanced manner. Since students reported improvements in understanding difficult topics, creativity, and overall academic performance through AI use, educators should deliberately adopt AI-powered learning platforms to supplement teaching and provide timely feedback that enhances students’ progress.
Keywords: Artificial Intelligence, Information and Communication Technology, Learning Outcomes
Integrating Partial Least Squares Structural Equation Modelling and Artificial Intelligence in Educational Research: A Simulation-Based Methodological Framework for Resource-Constrained Contexts (Published)
The rise in the need to make decisions in the educational system based on data has led to the application of sophisticated data analysis methods like Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Intelligence (AI). Nevertheless, their joint use is not yet widespread, especially in resource-limited scenarios. This paper suggests and illustrates a unified methodological framework of applying PLS-SEM and AI via a simulation-based method. The explanatory modelling and machine learning (Random Forest) of synthetic data to represent key educational constructs were performed using PLS-SEM and machine learning, respectively. The results of the PLS-SEM showed that there were strong correlations between constructs (satisfaction, student engagement, and institutional support) that described 54% of the variance in academic performance. The AI model had a better predictive accuracy (R2 = 0.71), as compared to the PLS-SEM model. The integration had complementary and consistent results. The research shows that the combination of PLS-SEM and AI increases the explanatory and predictive power. The framework is specifically applicable to resource-limited settings and provides viable advice to education researchers.
Keywords: Artificial Intelligence, PLS-SEM, Simulation, education research, predictive analytics, resource-constrained contexts
Artificial Intelligence in Education for Sustainable Development: A Review of Digital Equity, Inclusive Learning, and Ethical Governance (Published)
This review examines artificial intelligence in education for sustainable development, focusing on digital equity, inclusive learning, and ethical governance. It analyzes how intelligent tutoring systems, adaptive platforms, and assistive technologies advance Sustainable Development Goal 4 (quality education) while connecting with goals on poverty, health, gender equality, decent work, innovation, reduced inequality, sustainable cities, and international partnerships. Research demonstrates AI’s potential for personalizing learning, supporting students with disabilities, and expanding access in resource-constrained contexts. However, these benefits materialize only when technologies complement human-centered pedagogical approaches rather than replace educators. Significant challenges persist, including algorithmic bias, data privacy concerns, infrastructure disparities, and digital divides that threaten to exacerbate inequalities if unaddressed. Critical research gaps remain regarding longitudinal impacts on learning outcomes, cost-effectiveness in developing countries, and participatory approaches incorporating teacher perspectives. Realizing AI’s educational benefits requires robust ethical governance, substantial infrastructure investment, comprehensive professional development emphasizing human-AI collaboration, and multi-stakeholder partnerships aligned with SDG 17. This review contributes to ethical AI discourse by providing evidence-based recommendations ensuring technological innovation serves human development rather than market imperatives alone.
Keywords: Artificial Intelligence, Inclusive Education, Sustainable Development Goals, algorithmic bias, digital equity, ethical governance
Emerging Technological Trends and Their Contributions to Inclusive and Accessible Education (Published)
The rapid advancement of technology is reshaping global education systems, creating opportunities for inclusivity and accessibility in ways that were previously unattainable. Emerging technological trends, such as artificial intelligence, virtual and augmented reality, adaptive learning platforms, mobile applications, and assistive technologies, are transforming how learners access, engage with, and benefit from educational content. Using data from both secondary and interdisciplinary sources, and adopting the use of the Connectivism Theory, this study revealed that these innovations not only personalize learning experiences but also break down barriers related to geography, disability, language, and socioeconomic status. For instance, AI-driven tools facilitate individualized instruction, while digital learning platforms expand opportunities for remote and underserved communities. More so, the study revealed that assistive technologies empower students with visual, auditory, or cognitive impairments to participate fully in learning environments. It showed that despite these advancements, challenges such as the digital divide, infrastructural gaps, and concerns about data privacy persist. The study established that when strategically integrated with supportive policies and equitable access, these technologies can significantly advance the global agenda for inclusive, equitable, and quality education as envisioned in the United Nations Sustainable Development Goal 4 (SDG 4). The paper recommends the integration of digital learning tools, investment in assistive technologies, capacity building for educators, and affordable infrastructure and policy support etc. It concludes that emerging technological trends have become transformative forces in advancing inclusive and accessible education across the globe.
Keywords: Artificial Intelligence, ai-driven tools, assistive technology, cognitive impairment, digital learning
Advancement of Smart Academic Libraries in Northern Nigeria: Issues and Way Forward (Published)
The 21st century is known as the beginning of the knowledge age; a millennium characterized by leveraging on information to stay ahead using technology. The library occupies a critical place in the quality of information accessed and leveraged on by researchers and students. Academic libraries in Nigeria are not disconnected from this technology-based-information revolution. This study looked at advancement of smart academic libraries in Northern Nigeria: issues and way forward. Its objectives was to determine smart services available, investigate the extent of deployment, examine the underlying issues that hinder effective smart service delivery and proffer strategies for way forward in Northern university public academic libraries in Nigeria. The study adopted a review of documents and literature on smart academic libraries in Nigeria. Five public universities were purposively observed and sampled on their smart library perspective and capacity. Google-Forms-structured questionnaire was used through different online platforms. Simple percentage and frequencies were used in analyzing data collected. Findings showed that there are existing smart library services in the academic libraries of Northern Nigerian public universities but the extent of deployment of smart library services in their academic libraries is low. The research also revealed the numerous issues faced in providing smart services. The study recommended that the institution and library managements of academic libraries in Northern Nigerian public universities step up on ICT policy framework, practical deployment of smart library technologies and training of library staff for improved smart services
Keywords: Academic Libraries, Artificial Intelligence, Nigeria, Northern Nigeria, Smart Library, Technology