ETHICALCONSIDERATIONSINAIIMPLEMENTATIONFOREDUCATIONAL LEADERSHIP
This study critically examined the ethical implications and challenges associated with the integration of artificial intelligence (AI) technologies into educational leadership in Nigerian secondary schools. Specifically, it identified key ethical dilemmas faced by educational leaders when using AI tools for student data management and decision-making and explored strategies for responsible AI implementation. Three research questions guided the stud while two hypotheses were tested. A descriptive survey research design was adopted. The study was conducted in Anambra State, Nigeria. The population comprised 460 secondary school administrators, including principals, vice principals, and ICT coordinators. A sample of 230 respondents was selected through stratified random sampling. The instrument for data collection was a structured 20-item questionnaire titled “Ethical AI Implementation Inventory (EAIII),” developed by the researcher. The instrument was validated by three experts in Educational Technology and Measurement and Evaluation. The reliability coefficient of the instrument, determined using Cronbach Alpha, was 0.84. Data were collected using a self administered method. Mean and standard deviation were used to answer the research questions. The findings revealed that key ethical challenges include lack of informed consent, data privacy concerns, and algorithmic bias. Ethical awareness significantly predicted fair AI implementation. AI decision making was also found to significantly influence transparency and accountability in school leadership. These findings imply that ethical readiness is crucial in educational AI adoption. It was recommended that the Ministry of Education develop clear ethical policies, organize AI ethics workshops for school heads, and ensure the establishment of AI oversight committees in schools. A major limitation of the study was the exclusion of students and teachers from the sample. Further studies should explore perceptions of students and parents regarding AI in schools.
LEADERSHIPCHALLENGESANDSTRATEGIESFORMANAGINGCHANGEINAI INFUSEDEDUCATIONALSYSTEMSINSOUTH-EASTNIGERIA.
Abstract This study aimed to identify and evaluate effective leadership strategies required for successfully managing organizational change in educational institutions adopting AI technologies. The study was guided by three research questions and two hypotheses. A descriptive correlational survey was used to explore school leaders’ perceptions in South-East Nigeria. The population comprised 400 administrative leaders in the public and private University. The sample size for the study was 250 respondents made up of public and private university administrative leaders. The sample was drawn using a stratified random sampling. A questionnaire, titled ‘’Leadership Strategies for Managing Change in AI (LSMCAI) was developed for data collection. The content validation of the instrument was determined by five educational technology experts (CVI = 0.92).The reliability of the instrument was tested using Cronbach Alpha statistics. The overall coefficient index of (LSMCAI) was 0.84). Data were collected electronically and analyzed using descriptive statistics, Pearson correlation and linear regression at p < 0.05. Major findings revealed that major challenges include skill gaps, resistance to change, and inadequate infrastructure; transformational and collaborative leadership were most effective for fostering AI adoption; and leaders’ positive attitudes significantly predicted implementation success. Transformational leadership correlated strongly with adoption success (r = 0.68, p < .01), supporting Ha₁, while Ha₂ was also supported by a significant regression coefficient (β = 0.54, p < .001). Implications indicated that investing in AI-focused leadership training and infrastructure can facilitate smoother change. Recommendations include embedding leadership development and ethical governance into institutional AI strategies. One limitation is reliance on self- reported perceptions. Further research should examine student outcomes in AI-infused systems.
The Role of Librarians in Promoting Digital Literacy among Undergraduate Students in Universities in South-South Nigeria
This study examined the role of librarians in promoting digital literacy among final-year undergraduate students in public universities in South-South Nigeria. The population comprised 1,000 final-year students from six purposively and randomly selected universities across three states (Rivers, Delta, and Cross River). Using a multi-stage sampling technique, purposive state selection, random university selection, proportionate stratified faculty allocation, and simple random sampling a sample of 400 students was drawn. Data were collected via the Digital Literacy and Librarians’ Promotional Role Questionnaire (DL-LPRQ-FS), a 37-item Likert-scale instrument (Sections B-D: 5-point scale, Cronbach’s α = 0.872). Validity was confirmed by expert review. Descriptive statistics (means, standard deviations) assessed digital literacy levels and challenges, while inferential tests (Pearson correlation, logistic regression) examined relationships. Findings revealed a moderate overall digital literacy level (mean = 2.39), hindered by major challenges: inadequate internet access (mean = 3.90, 78% high impact), computer anxiety (mean = 3.70, 62%), insufficient training (mean = 3.60, 65%), and limited device access (mean = 3.45, 58%). Students perceived librarians' roles positively (high means in information sessions and workshops), with training significantly boosting skills (OR = 1.66, p = 0.007) and skills correlating with resource usage (r = 0.39, p < 0.001). The study concludes that systemic barriers limit digital literacy, but librarians are crucial in mitigation. Recommendations include enhanced ICT infrastructure, mandatory librarian-led workshops, device subsidies, and policy integration of digital literacy in curricula to empower students.
PRINCIPALS’ CHANGE MANAGEMENT PRACTICES AND TEACHERS’ ADOPTIONOF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN PUBLIC SECONDARY SCHOOLS IN ANAMBRA STATE.
The purpose of the study was to ascertain the relationship between principals’ change management practices and teachers’ adoption of Artificial Intelligence technologies in public secondary schools in Anambra State. Correlation research design was adopted for the study. The population of the study comprised 267 public secondary school principals in Anambra State. Census technique was used. Principals’ Change Management Practices Questionnaire (PCMPQ) and ‘‘Teachers’ Adoption of AI Technologies Questionnaire (TAAITQ)’’ were used for data collection. The reliability of face validated PCMPQ and TAAITQ was ascertained using Cronbach alpha method to obtain reliability coefficient values of 0.77 and 0.71 respectively. Data were analyzed using Pearson Product Moment Correlation coefficient. The findings of the study revealed that a very high positive and significant relationship existed between principals’ resistance management and teachers’ adoption of AI technologies in public secondary schools in Anambra State. Based on the findings of the study, it was recommended among others that principals should be more strategic in their resistance management process so as to sustain teachers’ adoption of AI technologies in public secondary schools in Anambra State.
Perceived Impact of Artificial Intelligence (AI) Usage on Library Services in Secondary Schools in Calabar, Cross River State, Nigeria
The main purpose of the study was to investigate perceived impact of Artificial Intelligence (AI) usage on library services in secondary schools in Calabar, Cross River State, Nigeria. Two null hypotheses were formulated to achieve the purpose of this study. Descriptive survey design was adopted for the study. A sample of 250 librarians and students from 25 secondary schools in Calabar, Cross River State, Nigeria was drawn for the study. A duly vetted structured questionnaire instrument was used for data collection. Data generated were subjected to statistical analysis using independent t test at 0.05 level of significance. The result obtained from the analysis revealed that there is a significant impact of user experience and library management efficiency on artificial intelligence (AI) in library services in the study area. Based on the findings of this study, conclusion was drawn. It was recommended that: school management should prioritize AI tools that enhance user experience, such as personalized recommendation systems, voice assistants, or automated reference services to boost student engagement and satisfaction; the management should implement AI-powered management platforms to automate cataloguing, track usage patterns, and optimize resource allocation. This will not only improve efficiency but also create a data-driven environment for future innovations.
GROWTH MINDSET, PERCEIVED CURRICULUM RELEVANCE, AND ADMINISTRATIVE SUPPORT AS CORRELATES OF TEACHERS’ ADOPTION OF AI-BASED INSTRUCTIONAL PRACTICES
The integration of artificial intelligence (AI) into higher education has the potential to transform teaching and learning, yet lecturers’ adoption of AI-based instructional practices remains uneven across Nigerian universities. This study examined the relationship among growth mindset, perceived curriculum relevance, administrative support and lecturers’ adoption of AI-based instructional practices at Chukwuemeka Odumegwu Ojukwu University. Guided by a correlational survey design, the study involved 210 lecturers selected through stratified random sampling. A validated questionnaire was employed for data collection, with reliability coefficients of .82, .84, and .86 for growth mindset, curriculum relevance, and administrative support respectively, and .87 for the overall instrument. Data were analyzed using Pearson’s correlation and multiple regression analyses. Results indicated that growth mindset, perceived curriculum relevance, and administrative support were each significantly associated with lecturers’ adoption of AI-based instructional practices. Collectively, the predictors accounted for 37% of the variance in AI adoption. Administrative support emerged as the strongest predictor, followed by growth mindset, while curriculum relevance also contributed significantly though to a lesser extent. The findings underscore the importance of fostering supportive institutional frameworks, cultivating lecturers’ adaptive mindsets, and aligning curricula with emerging digital realities to enhance AI adoption in teaching. The study concluded that a holistic approach involving psychological, curricular, and institutional factors is crucial for advancing effective AI integration in higher education.
TEACHING IN THE DIGITAL AGE: STRATEGIES FOR INTEGRATING EMERGING TRENDS AND TECHNOLOGIES IN CURRICULUM PLANNING AND CLASSROOM MANAGEMENT
The rapid emergence of digital technologies has transformed education, reshaping curriculum planning and classroom management practices. While digital integration has become a global trend, disparities remain in how teachers adopt and implement these tools, particularly across different school contexts. This study employed a descriptive survey design to examine strategies for integrating emerging digital trends into teaching practices. Data were collected from secondary school teachers across public and private institutions. Descriptive statistics, independent t-tests, and analysis of variance (ANOVA) were used to analyze the data, focusing on curriculum planning, classroom management, and the influence of teaching experience and school type. Findings revealed that learning management systems, virtual platforms, and cloud-based collaboration tools were widely adopted for curriculum planning. For classroom management, digital attendance systems, gamification, and AI-enabled monitoring tools were reported as key strategies. Significant differences were observed between public and private schools, with private schools demonstrating higher levels of digital adoption. However, no significant differences were found across teaching experience levels, suggesting that institutional support and access to infrastructure outweighed years of professional practice. Digital technologies hold transformative potential for enhancing teaching effectiveness and student engagement. However, persistent inequalities between public and private schools highlight the need for equitable access and resource provision. The study recommends continuous digital literacy training, infrastructure development, and supportive policies to foster inclusive technology integration in education.
AI LEARNING AND EDUCATIONALLY DISADVANTAGED STUDENTS IN RURAL SECONDARY SCHOOLS IN OWERRI EDUCATION ZONE11, IMO STATE, NIGERIA
This study investigated Artificial Intelligence and Educationally Disadvantaged students in Rural Secondary Schools in Owerri Education Zone II. The researchers posed three research questions and formulated three hypotheses. The study was anchored on Expectancy-Contingency theory. The design of the study was correlational survey. The population of the study was 1125 secondary school students whereas the sample was 385 SS2 students were selected through multistage random sampling technique. Two instruments were used in data collected namely: Students vulnerability questionnaire (SVQ) and educationally at risk questionnaire (ERQ). They were adopted with reliability coefficient determined to be 0.72, 0.76 and 0.79. Data collected were analyzed using Pearson Product Moment Correlational Statistics. The findings of the study indicated that there is significant relationship between AI learning and motivation of students, there is significant relationship between AI learning and adjustment of students, and there is no significant relationship between AI learning and tasks engagement of students. The researchers recommended that secondary schools should be equipped with Artificial Intelligence facilities for familiarity and frequent use.
APPLICATION OF ARTIFICIAL INTELLIGENCE POWERED TOOLS FOR PRINCIPALS’ MANAGEMENT OF SECONDARY SCHOOLS IN ANAMBRA STATE
The study examined principals’ application of AI powered tools for secondary schools management in Anambra State. Two research questions guided the study and two hypotheses were tested at 0.05 level of significance. The descriptive survey design was adopted for the study. The population of the study comprised 267 principals of public secondary schools in Anambra State. The entire population was used for the study because it was manageable. The instrument for data collection was a self-structured questionnaire which was validated by three experts. Test of reliability was done using Cronbach Alpha which reported reliability coefficients of 0.86 and 0.88 for Clusters, 1 and 2 respectively with an overall reliability coefficient of 0.87. Mean and Standard deviation and t-test were used to analyse data for the study. Finding of the study revealed that principals applied QuickBooks AI tool in the financial management of secondary schools in Anambra State to a low extent. Finding also showed principals applied BambooHR AI tool for the management of human resources in secondary schools in Anambra State to a low extent. Finding also showed that principals with prior experience in using AI tools reported significantly higher levels of application than those without such experience. Based on these findings, the researchers conclude that principals apply AI-powered tools in secondary school management to a low extent. It was therefore recommended that the Post Primary Schools Service Commission should organise regular training and capacity-building workshops for school principals on the effective use of AI-powered tools like QuickBooks and BambooHR.
Teachers’ Readiness and Perception of AI Integration in Science Teaching: Implications for Innovation and Curriculum Reform in Anambra State
The study investigated secondary school teachers’ readiness and perception of AI integration in teaching of science subjects in Anambra State. Three research questions and two hypotheses guided the study. A descriptive survey research design was employed to collect data from a sample of 80 secondary school science teachers. The instrument for data collection was adopted by the researchers, from the standard methods of “Technological Pedagogical Content Knowledge Framework”; developed by Mishra and Koehler (2006); “Teachers’ Acceptance of AI Instrument”; developed by Guo, Shi and Zhai (2024); and “Unified Theory of Acceptance and Use of Technology Model” by Venkatesh, Thong and Xu (2012). The instruments have strong validation and reliability rating; making them credible instrument to use for this study. Data collected were analyzed using descriptive statistics (mean and standard deviation) to answer the research question, and inferential statistics (paired t test) for the research hypotheses. The study's findings provided insights into teachers' attitudes, knowledge, and skills in integrating AI in Science education, highlighting areas of strength and weakness. The results informed policymakers, educators, and stakeholders on how to support teachers in embracing AI-driven innovations and reforming the curriculum to meet the demands of a rapidly changing technological landscape. The study recommended among others that educational authorities should organize training programs to enhance teachers' knowledge and skills in integrating AI in Science. It was also recommended that the science curriculum should be restructured to give room for the incorporation of AI-driven innovations, ensuring that it aligns with the demands of a rapidly changing technological landscape and prepares students for future challenges.
GROWTH MINDSET AND ACADEMIC RESILIENCE AS PREDICTORS OF STUDENTS’ ADAPTATION TO AI-ASSISTED LEARNING AMONG UNDERGRADUATES IN TERTIARY INSTITUTIONS IN ANAMBRA STATE
The integration of artificial intelligence (AI) in higher education is accelerating, yet student adaptation remains a challenge, particularly in developing contexts like Nigeria. This study investigated growth mindset and academic resilience as predictors of undergraduates' adaptation to AI-assisted learning in Anambra State. The sample of the study comprised 350 undergradutes selected using Stratified Random Sampling. The study employed a quantitative correlational design. Data were collected using standardised scales; Dweck's Growth Mindset Scale and Connor-Davidson Resilience Scale, as well as a 12-item AI Adaptation Scale, adapted from the Technology Acceptance Model. Data collected were analyzed using Pearson correlations and multiple regression. Results revealed strong positive correlations: growth mindset with adaptation (r = .62, p < .001), academic resilience with adaptation (r = .58, p < .001), and growth mindset with resilience (r = .65, p < .001). Regression analysis indicated that growth mindset (β = .35, p < .001) and academic resilience (β = .28, p < .001) collectively explained 45% of the variance in adaptation (R² = .45, F(2, 347) = 140.23, p < .001). These findings underscore the psychological mechanisms facilitating AI adoption in resource-limited settings. Implications for educational policy, practice, and future research in African higher education are discussed, emphasizing interventions to cultivate these traits.
RELEVANCE OF ULESSON PLATFORM IN THE ERA OF ARTIFICIAL INTELLIGENCE IN EDUCATION SYSTEM
The integration of Artificial Intelligence (AI) into education through developed and utilization of an educative platform called ulesson is heralding a new era of teaching and learning with profound application of using indigenous learning resources. It remains highly relevant because it utilizes personalized learning, localized learning experiences that address specific student gaps in African education. It functions as a complementary tool to human teachers not a replacement but enhance engagement, academic outcomes through adoptive / adaptive learning materials that drives learning home in a rapidly changing global educational landscape. This paper provides an in-depth knowledge on the benefits of integrating AI into education through utilization of personalized developed educative platform.
REVOLUTIONIZING TEACHER EDUCATION THROUGH ARTIFICIAL INTELLIGENCE
This study investigated Artificial Intelligence (AI) in revolutionizing teacher education with a focus on its applications in content delivery, and professional development. The study was guided by three research questions. A descriptive survey design was adopted. The population consisted of 3200 teacher educators in faculties of education across four institutions in Anambra State, Nigeria. Using stratified random sampling, 320 respondents were selected. A structured questionnaire validated by experts and with a Cronbach alpha reliability coefficient of 0.89 was used for data collection. Data were analysed using mean scores, standard deviation, and t-test statistics. Findings revealed that AI tools are not formally adopted for instruction and professional development, remain in skeletal, informal use. Recommendations include curriculum redesign, AI literacy training, and institutional reform. One major limitation was limited institutional access to AI tools.
ARTIFICIAL INTELLIGENCE IN CURRICULUM DEVELOPMENT AND PLANNING: FOSTERING 21ST CENTURY SKILLS
The study explored the transformative role of Artificial Intelligence (AI) in redesigning curricula to equip Nigerian secondary school students with essential 21st-century skills, particularly critical thinking and creative problem-solving. Two research questions guided the study. Descriptive research design was adopted to give direction to the study. The population comprised senior secondary school students in a metropolitan area in Nigeria. The sample consisted of 120 students drawn through purposive and stratified random sampling techniques. A 20-item researcher-developed instrument titled “AI-Curriculum and 21st Century Skills Questionnaire” (AI-C21SQ) was used to collect data. The instrument's validity was established through expert review, and reliability was determined using Cronbach’s alpha, yielding a coefficient of 0.86. Data were analyzed using mean and standard deviation. Findings revealed that AI tools enable students in the design and revision of secondary school curricula to promote critical thinking. The findings of the study further showed that AI integration in curriculum planning positively influenced students’ development of creative problem solving skills as perceived by the students. It is recommended that government should improve Infrastructure to support AI deployment in public schools. That way, students’ critical thinning and problem-solving skills will be fostered.
APPLICATION OF ARTIFICIAL INTELLIGENCE IN ASSESSMENT OF ACADEMIC ACHIEVEMENT OF UNDERGRADUATE STUDENTS IN SOUTH EAST ZONE OF NIGERIA
Artificial Intelligence (AI) is increasingly transforming assessment practices in higher education and other learning contexts. This study examined the application of artificial intelligence in assessing academic achievement of undergraduate students. Descriptive survey research design was adopted for the study and six research questions were answered. The population of the study comprised 6,972 Faculty of Education third year (Year 3) undergraduate students of federal universities who were registered for the 2024/2025 academic session in the South-East, Nigeria. However, a sample of 378 undergraduate students for this research was determined by using the Taro Yamane formula for sample estimation. The instrument for data collection was a questionnaire titled Application of Artificial Intelligence in Assessment of Academic Achievement of Undergraduate Students (AAIAAAUS). The instrument was validated by experts in Educational Measurement and Evaluation, Faculty of Education; and Computer Science from NnamdiAzikiwe University Awka. Reliability indices of the sub-sections of the instrument was determined using Crombach Alpha method and the indices are 0.87, 0.91, 0.68, 0.77, and 0.74 respectively. Mean and standard deviation were used to answer the research questions. Findings among others revealed that AI is relevant and beneficial in test construction, grading, feedback provision, plagiarism detection, and continuous assessment, though concerns remain about its fairness and accuracy. Based on the findings, it was recommended among others that universities should organize extensive training sessions and workshops for both students and lecturers to build their capacity and improve their effective use of AI tools in teaching and assessment.
Health Promotion Enhancement Using Artificial Intelligence (AI) Among Science Lecturers At Federal College of Education (Technical), Umunze.
In the recent years, there has been a growing recognition of the need to integrate technology into health promotion strategies. Artificial Intelligence (AI), which refers to computer systems capable of performing tasks typically require human intelligence is transforming health care delivery and preventive health systems world wide. The study adopted a descriptive survey design in investigating Health Promotion Enhancement Using Artificial Intelligence Among Science Lecturers at Federal College of Education (Tech), Umunze. Four research questions which are in line with four purposes guided the study. The population of the study is one hundred and twenty-five (125) which science lecturers in the seven (7) departments in the school of sciences at F.C.E(T) Umunze. A purposive sampling technique was adopted to select sixty (60) science lecturers in all the departments who have basic awareness or access of AI technologies. Structured Questionnaire titled “AI-Enhanced Health Promotion (AI.EHP)” developed by the researchers was used for data collection. The instrument yielded a reliability co-efficient of 0.82 indicating high reliability. Data was analyzed using mean and standard deviation. The mean of 2.50 and above indicated agreement while below 2.50 indicated disagreement. The findings reveals among others moderate level of awareness of AI tools among science lecturers, relatively low level of utilization of AI tools. Based on the findings, the study recommended that institutions should organize workshops and training programs for science lecturers to enhance their digital literacy and practical skills in using AI tools for health promotion, institutional policies should be developed to support the integration of AI tools into staff wellness programs among others.
Preservice Science Teachers’ Perceived Influence of Artificial Intelligence Application on their Academic Motivation in Anambra State.
The study aimed at investigating the perceived influence of preservice science teachers’ artificial intelligence application on their academic motivation in learning science in Nnamdi Azikiwe University (NAU), Awka, Anambra State Nigeria. The study guided by five research questions adopted a descriptive survey research design. Simple random sampling technique was used to draw a sample of 500 Science Education Department students, in NAU, used in the study. The instrument used for data collection was an adapted questionnaire titled “AI Application Questionnaire on Students’ Academic Motivation” (AIAQSAM). AIAQSAM was validated by three experts, yielded a reliability coefficient of 0.86, established using Cronbach Alpha. In analyzing the items in the research questions, Mean and standard deviation were used while grand mean, compared against a number line, was used in answering the research questions. The results obtained showed that the respondents agreed that application of AI in the classroom to a very high extent positively influenced their students’ academic motivation and its dimensions; attainment, utility and intrinsic values. Furthermore, the study revealed that students are willing to invest more time and finance into AI application skills, and thus recommended among others that as the world gets more digitalized, institutions should organize orientation programmes to encourage students to equip themselves with AI application skills and tools in other to fit in the ever evolving world.
Perceived Effects of Use of Artificial Intelligence for Knowledge Management at Danbaba Danfulani Suntai Library, Taraba State University, Jalingo, Nigeria.
The study explores the perceived effects of artificial intelligence (AI) on knowledge management at the Danbaba Danfulani Suntai (DDS) Library, Taraba State University, Jalingo. Despite concerns about job replacement among library staff, the research highlights the significant benefits of AI in knowledge management in academic libraries. Five research objectives and corresponding questions guided the study. Using a descriptive survey with 36 library staff, data were collected through a structured questionnaire and analyzed using frequency counts, percentages, and mean scores. Findings revealed that among 17 investigated AI tools, the DDS Library staff only used Team-GPT, and its application was limited. Nonetheless, AI tools were perceived to enhance automation of knowledge processes, facilitate conversion of tacit to explicit knowledge, and support handling large volumes of unstructured data. Yet, use remains low due to challenges such as fears of job loss leading to resistance, inadequacies in ICT infrastructure, and insufficient funding. The study concludes that while AI holds promise for improving knowledge management in academic libraries, usage at DDS Library is minimal and hindered by structural and attitudinal obstacles. Recommendations include the need for comprehensive training for library staff on AI tools to improve their utilization and advocating for increased financial investment to address longstanding resource shortages in Nigerian academic libraries. These steps are crucial to unlocking the full potential of AI in transforming library services and knowledge management.
STRATEGIC INTEGRATION OF ARTIFICIAL INTELLIGENCE IN UNIVERSITY MANAGEMENT FOR ENHANCED GLOBAL COMPETITIVENESS AND EDUCATIONAL INNOVATION
This mixed-methods study investigates the strategic integration of Artificial Intelligence (AI) in university management across four Nigerian institutions—two public (University of Nigeria Nsukka, Nnamdi Azikiwe University) and two private (Coal City University, Peaceland University). Drawing on surveys from 40 administrators and qualitative interviews, the study explores four dimensions: administrative efficiency, student outcomes, research innovation, and staff readiness. Quantitative data were analyzed using descriptive statistics and paired-sample t-tests; thematic analysis was used for interview data. Findings indicate significant improvements in efficiency, student satisfaction, and research innovation following AI implementation, but financial and training constraints remain significant barriers. The paper concludes with actionable recommendations for enhancing AI integration in higher education.
AI and Automation in South East Nigeria: Empirical Study on Their Impact on Economy, Governance, and Human Capital Development
This study investigated the influence of Artificial Intelligence (AI) and automation in South East Nigeria, with particular emphasis on economic growth, governance efficiency and transparency, and human capital development. A descriptive survey design was adopted, guided by three research questions and one null hypothesis. Using multi-stage sampling techniques, 205 respondents were selected from Ebonyi, Anambra, and Abia States. Purposive sampling was further employed to select participants comprising ICT professionals, policymakers, lecturers, and entrepreneurs. Data were collected using the AI and Automation for Nation Building Questionnaire (AA-NBQ) developed by the researcher. The instrument was validated by experts, and its reliability was established using Cronbach’s alpha, yielding a coefficient of 0.89. Data were analyzed using mean, standard deviation, and multiple regression analysis. Findings revealed that AI and automation play a crucial role in improving governance in South East Nigeria by reducing inefficiencies, enhancing transparency, and supporting data-driven reforms. Respondents also acknowledged that AI and automation contribute positively to human capital development, although their influence was found to be moderate. Regression analysis further indicated that AI and automation have a significant relationship with governance efficiency and transparency, but no significant relationship with economic growth or human capital development. Based on these findings, the study recommended the development of a coherent national AI policy framework, increased investment in digital literacy, and stronger collaboration between industry and academia to promote innovation, workforce preparedness, and sustainable national development in an increasingly AI-driven economy.
ARTIFICIAL INTELLIGENCE (AI) IN LIBRARY MANAGEMENT: EMPOWERING ACCESSOR REWRITING THE RULES
This paper explores the evolving role of artificial intelligence (AI) in library management, evaluating its benefits, challenges, and ethical implications. The discussion emphasizes how AI can enhance cataloging, reference services, administrative efficiency, and user engagement while underscoring the continued importance of human oversight. By reviewing current literature and case studies, the paper argues that AI should serve as a complementary tool rather than a replacement for librarians, ensuring libraries remain centers of equitable knowledge access.
Perceived Influence of Artificial Intelligence Usage on Students’ Academic Performance in Nnamdi Azikiwe University Awka, Anambra State
The advancement of digital technologies has significantly transformed the landscape of higher education worldwide. Artificial Intelligence (AI) has emerged as one of the most powerful innovations in this regard, offering tools that can enhance learning, teaching, assessment, and student support. In Nigeria, particularly in Anambra State, the integration and utilization of AI technology in tertiary institutions remain relatively underexplored, despite its potential to improve students’ academic performance. This study examined the perceived influence of artificial intelligence technology on students’ academic performance in Nnamdi Azikiwe University Awka, Anambra State. Three research questions guided the study. The study adopted a descriptive survey design. The population of the study consisted of 30,919 which includes all the 400 level students at Nnamdi Azikiwe University Awka, Anambra state. The sample comprised 400 students obtained through multi-stage sampling procedure using simple random sampling technique. An instrument titled “Artificial Intelligence Usage and Academic Performance Questionnaire (AIUAPQ)” was used to generate data. The instrument was validated and trial tested to determine the reliability coefficient which gave 0.86 as the index. Data were analyzed using mean. Results revealed that AI usage among students is moderate but uneven, with significant potential to enhance academic achievement if institutional and infrastructural barriers are addressed. The findings underscored the need for targeted institutional policies, capacity building, and digital infrastructure to support AI-driven education. It was recommended among others that regular training workshops should be organized to enhance students’ technical skills in AI usage and awareness programme should be carried out to sensitize students on the academic benefits of AI technologies.
Assessing Awareness and Engagement with Artificial Intelligence Tools: Enhancing Academic Performance among Secondary School Students in the Awka Educational Zone.
This study investigated the awareness and engagement of secondary school students in the Awka Educational Zone with artificial intelligence (AI) tools. Prompted by increasing calls for the integration of AI into educational settings, the study specifically aimed to assess how aware and engaged students are with AI tools that can potentially improve their academic outcomes. The study was guided by three research questions and one null hypothesis was tested. Study population was 5,010 Senior Secondary Two (SS2) students from 54 government-owned schools, from which 350 were selected using a multistage sampling procedure. Data were collected through a 25-item, researchers-developed questionnaire titled “Awareness and Engagement with Artificial Intelligence Tools for Enhancing Academic Performance Questionnaire (AEAITEAPQ)” validated by three experts from the Faculty of Education, Nnamdi Azikiwe University Awka, and found to be reliable with coefficient value of 0.80 using Cronbach alpha statistics. Means and standard deviation were used to answer research questions, while inferential statistics of two-sample z- test was used to test the null hypothesis at 0.05 level of significance. Findings reveals moderate level of awareness of AI tools, with commonly used tools including AI chatbots. On the other hand, students engagement with AI tools for academic purposes shows great extent engagement. In addition, factors such as parents, teachers, instant response, friends, access to devices among others influenced their engagement with AI tools. Result of the hypothesis shows that there is no significant difference between males and females among secondary school students in Awka Educational zone(p=0.866 >a=0.05) ) therefore, the null hypothesis is not rejected. Based on the findings, it was therefore recommended among others that: educational authorities should initiate more sensitization campaigns or interactive learning program that show students how AI tools can be directly applied to schoolwork
Social Interaction, Problem-Solving, Critical Thinking, and Creative Ability as Predictors’ of Students’ Digital Learning Readiness in Public Secondary School E-learning.
This study brings attention to the predictors of students’ digital learning readiness which focuses on the interplay among their social interaction, critical thinking, creative ability, and problem-solving as fostering factors for digital education.The study employed a predictive correlational research design. The sample size was made up of 897secondary school students in Anambra State. Instrument for data collection were as follows; Problem Solving Inventory (PSI), Interpersonal and Communication Skills Questionnaire (ICSQ), California Critical Thinking Disposition Inventory (CCTDI), “How Creative Are You? Scale and Learners Readiness for Online Learning Scale (LROLS). The data were analyzed using standard multiple regression analyses. Our findings showed thatin the unique contribution, social interaction positively contributed to the predicting model, while critical thinking, creative ability, and problem-solving negatively contributed to the predicting model. Also, the analysis of variance shows that the regression equation was significant (4, 892) = 17.292, p <. 05. This implies that at least one of the independent variables significantly predicted students’ digital learning readiness scores. Based on these findings, it was recommended that students should be motivated to participate actively in the digital learning instructional process and technological driven workshops to update their knowledge on digital education.
Enhancing Assessment through AI: A Comparative Study of Lecturers’ Views on Human and AI-Based Feedback in Nigerian University Settings
This study comparatively examined lecturers' perceptions of AI-based versus human feedback in Nigerian university settings, focusing on attitudes, perceived effectiveness, and integration preferences at Nnamdi Azikiwe University, Awka. The study was guided by three research questions and two corresponding hypotheses were tested. The population comprised all 3,200 academic staff of Nnamdi Azikiwe University, Awka, from which a sample size of 357 lecturers was selected using Taro Yamane's formula at 95% confidence level. Adopting a descriptive survey design, data were collected using the instrument titled "Lecturers' Perception of AI-Based Feedback Questionnaire (LPAIFQ)" with a reliability coefficient of 0.864, and validated by three experts, two in Educational Measurement, Evaluation and Research and one in Educational Technology. Quantitative data were analyzed using descriptive statistics of frequencies, percentages, means and standard deviation and inferential statistics including independent t-test and ANOVA using SPSS version 26.0. Findings reveal nuanced perceptions: while 68% of lecturers appreciate the speed and consistency of AI generated feedback, concerns persist regarding its contextual accuracy, emotional sensitivity, and adaptability to individual student needs, with significant differences in perception based on years of teaching experience (F=12.34, p<0.05) and disciplinary affiliation (t=4.67, p<0.05). The study concluded that disciplinary differences and prior experience with AI tools emerged as significant factors influencing attitudes toward AI in assessment, while 72% preferred hybrid models combining human judgment with AI efficiency. It is recommended that institutions should develop balanced integration approaches with culturally-sensitive AI feedback systems and adequate training programs to enhance feedback practices in AI-enhanced learning environments.
Tourists' Mental Health Support and AI-Powered Interventions in Calabar, Cross River State, Nigeria
The main purpose of this study was to investigate tourists' mental health support and AI-powered interventions in Calabar, Cross River State, Nigeria. To achieve the purpose of this study, two null hypotheses were tested at 0.05 level of significance. Review of relevant literature was carried out according to the variables in the study. Survey research design was employed for the study. Stratified sampling technique was adopted to sort the tourists while purposive sampling technique was employed to select the two hundred and forty-three (243) respondents used for the study. A structured questionnaire was the instrument used for data collection. The instrument was vetted by relevant authorities. Pearson product moment correlation statistical tool was used to test the hypotheses formulated for the study for data analysis. The result of the analysis of data and hypotheses testing revealed that there was a significant relationship between stress management and tourists’ wellbeing using AI-powered interventions. Based on these findings, conclusion was drawn and it was recommended that tourism stakeholders in Calabar should consider implementing AI-powered stress management tools to support tourists' mental health; AI-powered interventions can be integrated into existing tourism services, such as hotel amenities or tourist information centers.
SYSTEMATIC EVALUATION OF TECHNOLOGY-ENHANCED LEARNING ENVIRONMENTS: A COMPREHENSIVE REVIEW OF FRAMEWORKS, METRICS, AND ETHICAL CONSIDERATIONS
From school systems to job trainings, the proliferation of technology is overwhelming. The big question is ‘how do we distinguish the signal from noise? This paper provides a comprehensive, scholarly review of the systematic evaluation of Technology-Enhanced Learning (TEL) environments. It establishes a foundational understanding of both TEL and systematic evaluation as a structured, data-driven, and repeatable process. The research synthesizes and critically analyzes prominent theoretical frameworks, including the foundational Kirkpatrick Model and the more holistic Cook and Ellaway framework. It delineates key metrics and criteria for assessment, spanning pedagogical, technical, and financial dimensions, and highlights the shift from lagging to leading indicators. Through an examination of case studies and lessons from both successful and unsuccessful implementations, the paper explores major challenges, such as the silver bullet fallacy and the pitfalls exposed by the COVID-19 pandemic. A critical discussion of ethical and security imperatives, particularly in the context of AI-powered tools, reveals a fundamental tension between innovation and principles of privacy, equity, and human oversight. The review concludes by identifying significant research gaps, chief among them the absence of a standardized, comprehensive evaluation methodology, and proposes a pathway toward a more integrated, agile, and holistic approach for future TEL assessment.
TYONYION,Richard Sughnen (Ph. D in view)
PHYSICAL ACTIVITY AND PERCEIVED HEALTH OF PREGNANT WOMEN IN ODUKPANI LOCAL GOVERNMENT AREA OF CROSS RIVER STATE
The main purpose of this study was to investigate physical activity and perceived health of pregnant women in hard- to-reached areas communities in Odukpani Local Government Area of Cross River State, Nigeria. To achieve this purpose, two null hypotheses were formulated to guide the study. A detailed review of related literature was carried out based on the variables of the study. Survey research design was employed for the study. A sample of 342 was used for the study. Simple random sampling technique was adopted in selecting the twenty-two communities while systematic random sampling technique was adopted in selecting the three hundred and forty (342) respondents used for the study. Twenty items four-point scale questionnaire was the instrument used for data collection. The instrument was validated by relevant authority one expert in department of Health Education and Promotion and two others in Measurement and Evaluation. To test the hypotheses formulated for the study, Pearson product moment correlation statistical tool was used for data analysis. The findings obtained from analysis of data and testing of hypotheses in the study revealed that there was a significant relationship between swimming, walking, and perceived health of pregnant women in the study area. Based on these findings it was recommended that relevant authorities should ensure that more women are sensitized on the need to participate actively in walking activities in order to improve their health during pregnancy.
EXPLORING THE ADOPTION AND INTEGRATION OF AI-POWERED TOOLS IN SCHOOL ADMINISTRATION IN ENUGU STATE NIGERIA: CHALLENGES, BENEFITS AND BEST PRACTICES
This paper explores the adoption and integration of AI-powered tools in school management and administrative tasks in secondary schools. The paper further examined AI-powered tools application on school management, benefits and best practices for successful integration of AI tools on school management and administrative tasks. Based on the findings from both print and online publication, the paper concluded that AI-powered tools can lead to effective and efficient data collection, data analysis, problem solving, decision making, streamlined parents, teachers and students communicate; students enrollment and registration, resource planning and optimization, enhancing security and safety. Based on the problems, the researcher recommended among other things effective adoption and implementation of AI-Powered tools in school should ensure that it serves as tools for enhancing education rather than replacing human interaction.
TEACHERS’ KNOWLEDGE AND USE OF ARTIFICIAL INTELLIGENCE IN DEAF EDUCATION IN AKWA IBOM STATE, NIGERIA
Artificial Intelligence (AI) is reshaping educational practice in ways that are especially consequential for deaf learners. Its ability to achieve desired results, however, depends on teachers’ knowledge, attitudes, and material conditions. This qualitative descriptive study examined how teachers in Akwa Ibom State, Nigeria, understand and use AI in deaf education. Semi structured interviews were conducted with fifteen teachers working in special and inclusive schools. The results were analyzed using reflexive thematic analysis. Findings indicate a spectrum of awareness and emerging practice, broad belief in AI’s value for communication access, participation, and learner independence, and interlocking infrastructural and pedagogical barriers, including unreliable electricity and internet, scarce devices and funding, limited training, and poor localization to Nigerian sign and classroom contexts. The paper proposes a practical roadmap for responsible AI integration that emphasizes state supported professional development, infrastructural investment, clear school-level implementation routines, and codesign processes that localize tools for deaf learners. The study provides practice based evidence to inform policy and guide responsible AI adoption in African deaf education.