EDUCATION

The study focused on the causes of strikes and its effect on students’ academic performance a case study of Faculty of Education University of Benin. Five research questions were raised to guide the study; 1. What are the central factors that frequently lead to strike actions within Nigerian universities? How do strike actions influence students' comprehension, retention, and engagement during their academic pursuits? What is the correlation between the specific elements triggering strikes and the subsequent underperformance of students in examinations and assessments? To what extent do institutional policies and administrative decisions contribute to either amplifying or alleviating the effects of strike actions on students' academic performance? In what ways can the educational system better manage strike actions to minimize disruptions and foster an environment conducive to sustained students’ learning? Descriptive research design was adopted for the study. The population of this study consists of all male and female students of History Education, University of Benin, Benin City. The sample of this study comprises of one hundred and fifty (150) History students of the Faculty of Education, University of Benin, Benin City, Edo State. The major findings of the study revealed that the correlation between the specific elements triggering strikes and the subsequent underperformance of students in examinations and assessments is diverse and high. The results of the analysis conducted, revealed that the extent that institutional policies and administrative decisions contribute to either amplifying or alleviating the effects of strike actions on students' academic performance is diverse and high. The results of the analysis conducted revealed that the ways that the educational system can better manage strike actions to minimize disruptions and foster an environment conducive to sustained student learning are diverse and high It was recommended that Government should address root causes of strikes, Government should enhance student support services

This study investigates the adoption, usage, and application of Generative Artificial Intelligence (GAI) in promoting sustainability and achieving the Sustainable Development Goal 4 (Quality Education) in Nigerian universities. A descriptive survey research design was employed, targeting 222 professionals, policymakers, academic staff, development officers, environmental experts, and IT personnel involved in sustainability initiatives. Data were collected through googled constructed online questionnaires, with 200 valid responses received, representing a 90% response rate. Descriptive and inferential statistical techniques, including frequency distributions, percentages, mean, standard deviation, and multiple regression analysis, were used to analyze the data. The findings revealed that GAI adoption, usage, and application have a significant positive impact on sustainability and the promotion of quality education, enhancing access to learning resources, personalizing learning experiences, improving academic performance, and reducing educational inequalities. The study also identified challenges, including limited infrastructure, high costs, lack of technical expertise, and resistance to change, which may hinder effective GAI implementation. The research concludes that strategic policy development, adequate resourcing, continuous capacity building, and ethical AI practices are critical for maximizing the benefits of GAI in Nigerian universities. The study contributes to the growing body of knowledge on AI-driven sustainability and education and provides practical recommendations for policymakers, educators, and institutional administrators.

This study is based on the role of AI in enhancing Vocational and Technical Education in Nigeria. To achieve the purpose of this study, four research questions were raised and examined. Data were collected from one hundred and forty-one (141) respondents randomly selected from 4 levels in the Department of Agricultural Education in the University of Benin, Benin city. The questionnaire was the instrument for data collection. The descriptive survey research design was adopted for the study. An analysis of the data was done using mean score and standard deviation. The findings from the study include that there is a low level of AI inclusion in the teaching, and learning process of Vocational and Technical Education in the agricultural sector. This study is focused on an analysis of how AI should be integrated in the higher institutions under competent, well equipped and experienced workforce. The study recommended that government agencies, curriculum developers, and educators collaborate to fully utilize AI-powered tools and technologies. This collaboration would enhance learning experiences, improve practical skills development, and prepare students for the future of farming by offering personalized learning, virtual simulations, and data-driven decision-making. Consequently, students would be equipped with the knowledge and abilities to drive agricultural innovation and achieve self-sustainability. Furthermore, the study suggested that the government allocate sufficient funds to equip institutions with modern computers and learning materials, thereby improving learning outcomes, increasing efficiency, and promoting sustainable agricultural practices.