STUDIES IN EDUCATION

STUDIES IN EDUCATION VOL.24 No.2, September 2026

2026-10-02T15:32:16+00:00

ISSN: 1117-2398

STUDIES IN EDUCATION

VOL.24 No.2, September 2026

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ADOPTION OF ARTIFICIAL INTELLIGENCE FOR IMPROVING ADMINISTRATIVE EFFICIENCY IN BUSINESS EDUCATION FACULTIES IN PUBLIC UNIVERSITIES IN EDO AND DELTA STATES

2026-09-26T14:06:40+00:00

This study examined the adoption of Artificial Intelligence (AI) for improving administrative efficiency in Business Education Faculties of selected public universities in Edo and Delta States, Nigeria. The study was motivated by persistent administrative inefficiencies in Nigerian universities despite global advancements in AI-driven higher education management systems. A descriptive survey research design was adopted. The population comprised academic and administrative staff from Business Education Faculties in the University of Benin (UNIBEN), Ambrose Alli University (AAU), Ekpoma, and Delta State University (DELSU), Abraka. A sample of 180 respondents was selected using stratified random sampling technique. Data were collected using a structured questionnaire titled “Artificial Intelligence and Administrative Efficiency Questionnaire (AIAEQ),” validated by experts and tested for reliability using Cronbach’s Alpha, yielding a coefficient of .82. Data were analyzed using mean and standard deviation. Findings revealed that the level of AI adoption in administrative tasks is low to moderate, with limited integration of advanced tools such as chatbots, predictive analytics, and data-driven decision systems. However, respondents strongly agreed that AI adoption enhances administrative efficiency by improving service delivery, accuracy of records, and communication systems and reducing workload. The study further identified major constraints to AI adoption, including poor ICT infrastructure, inadequate technical skills, high cost of implementation, resistance to change, and weak institutional policy frameworks. The study concluded that AI adoption in Nigerian business education faculties remains in a transitional stage, characterized by a gap between perceived usefulness and actual implementation. It recommended increased investment in ICT infrastructure, staff capacity building, institutional policy development, and strategic partnerships to enhance sustainable AI integration in university administration.

AI-DRIVEN CAREER COUNSELLING: EMERGING TRENDS, CHALLENGES AND OPPORTUNITIES IN THE DIGITAL AGE

2026-09-26T14:16:43+00:00

This paper examined the role of AI in enhancing career counselling services within the context of the digital age. Specifically, it conceptualized Artificial Intelligence, career counselling, AI-driven career counselling, and career development in the digital era. The paper argued that AI technologies, including machine learning, natural language processing, predictive analytics, recommender systems, and generative AI, enhance career counselling by analyzing learners' interests, competencies, personality traits, academic performance, and labour market trends to provide personalized career recommendations. AI also improves access to career information, facilitates lifelong career planning, and supports evidence-based counselling interventions. Despite these opportunities, AI-driven career counselling presents challenges related to algorithmic bias, data privacy, ethical concerns, digital inequality, limited human interaction, and the need for professional oversight. The paper emphasized that AI should complement rather than replace professional career counsellors because effective career counselling requires empathy, ethical judgment, contextual understanding, and interpersonal relationships that remain uniquely human. The paper concluded that effective integration of AI into career counselling therefore requires robust ethical governance, professional competence, digital inclusion, interdisciplinary collaboration, and continuous evaluation to ensure sustainable, equitable, and human-centered career counselling in the digital age.

AI-DRIVEN INNOVATION AND PEDAGOGICAL APPLICATIONS TRANSFORMING TEACHING AND LEARNING IN DIGITAL AGE: LEVERAGING AI APPLICATIONS FOR EFFICIENT EDUCATIONAL MANAGEMENT

2026-09-26T14:31:26+00:00

The fast expansion of Artificial Intelligence (AI) is changing the educational environment by introducing new solutions for education, learning, and institutional management. This paper reviewed the use of AI-enabled tools in pedagogy and educational design, with an emphasis on their ability to offer customized learning paths, enhance student engagement, and streamline administrative processes. Key concepts such as AI-enhanced pedagogy, adaptive learning systems, intelligent tutoring, predictive analytics, and automated management were examined, as well as their role in fostering lifelong learning and preparing students for a dynamic, technology-driven world. The paper also acknowledged challenges related to the implementation of AI, including data privacy concerns, equitable access, ethical considerations, and the need for training for educators. Strategies for successful adoption are discussed, emphasizing professional development, infrastructure investment, and aligning AI tools with pedagogical objectives. Suggestions were made to strengthen educational systems so that AI applications can support sustainable, inclusive, and future-ready learning environments. Institutions may utilize AI to innovate instruction and operate education effectively, rethinking traditional educational models as agile, data-driven, student-centered ecosystems that can respond to global challenges while serving local needs.

APPLICATION OF ARTIFICIAL INTELLIGENCE IN EDUCATIONAL ASSESSMENT AMONG POSTGRADUATE STUDENTS AT NASARAWA STATE UNIVERSITY, KEFFI, NIGERIA

2026-09-26T14:43:07+00:00

This study investigated the application of artificial intelligence in educational assessment among postgraduate students at Nasarawa State University, Keffi, Nigeria, using a descriptive survey research design. The study population consisted of 610 postgraduate students from the Faculty of Education, Nasarawa State University, Keffi. A sample of 300 students was selected through a simple random sampling technique. An unstructured questionnaire titled Applications of Artificial Intelligence in Educational Assessment (APAIEA) was used as the data-collection instrument. The instrument was subjected to experts in measurement and evaluation for validity. Using Cronbach’s alpha coefficient of reliability, a reliability coefficient of .78 was established. The study employed descriptive analysis, focusing on frequency and percentage distributions based on a Likert scale to assess awareness, usage, perceived benefits, and challenges associated with AI in educational assessment. The findings revealed that while a significant portion of respondents (68.7%) acknowledged awareness of AI tools that could aid in educational assessment, only 49.0% reported actually using them, indicating a notable gap between awareness and practical application. Also, respondents in this study reported significant perceived advantages of AI in enhancing educational assessment. Challenges such as limited training, difficulties in understanding AI tools, and concerns regarding data privacy were prevalent. This study concluded that addressing these challenges through targeted training programmes and the establishment of ethical guidelines is crucial for effective AI integration in educational assessment. It was recommended that Nasarawa State University, Keffi, should incorporate AI training into the curricula to equip postgraduate students with essential skills for using AI tools in educational assessment. This can be achieved through workshops, seminars, and dedicated courses that enhance digital literacy, thereby improving students’ assessment capabilities as well as academic outcomes, among other recommendations.

ARTIFICIAL INTELLIGENCE AND ADMINISTRATIVE EFFECTIVENESS IN HIGHER EDUCATION: REPOSITIONING INSTITUTIONAL GOVERNANCE FOR THE DIGITAL AGE

2026-09-27T04:45:00+00:00

This paper examined how artificial intelligence (AI) is reshaping administrative effectiveness in higher education, using Nigerian universities as its primary context. As a conceptual paper drawing on secondary data, it applies the Technology Acceptance Model (TAM) to argue that AI's contribution to university administration depends less on technical sophistication and more on whether administrators perceive such tools as useful and easy to use. The paper reviewed literature on AI-driven administration and identified a persistent gap where existing knowledge concentrates on students and teaching staff, leaving administrators understudied despite their central role in institutional governance. Drawing on recent empirical and conceptual studies, this paper examined global trends in AI-driven University Administration, AI as a Catalyst for Administrative effectiveness, challenges of AI adoption in Nigerian Universities, repositioning Institutional governance for the AI era, and implications for educational policy and practice. The paper concluded that repositioning Nigerian universities for the AI era requires simultaneous attention to administrators’ competence and institutional policy, rather than treating technology procurement as sufficient in itself. It closed with recommendations for policymakers and university management.

ARTIFICIAL INTELLIGENCE AWARENESS AND DIGITAL COMPETENCIES AMONG CARPENTRY AND JOINERY CRAFT TEACHERS’ IN TECHNICAL COLLEGES IN EDO STATE

2026-09-26T15:18:28+00:00

This research explored the level of artificial intelligence (AI) awareness and its association with digital competence among carpentry and joinery (C&J) craft teachers in technical colleges in Edo State, within the educational technology domain. The study focused on assessing the extent of AI awareness, evaluating the digital competence of C&J teachers, and determining the relationship between AI awareness and digital competence. A correlational survey research design was employed, with data collected from 21 C&J craft teachers using a structured questionnaire. The data were analyzed using descriptive statistics, Pearson Product-Moment Correlation, and one-way analysis of variance (ANOVA). The findings indicated that the participants demonstrated high levels of both AI awareness and digital competence. Furthermore, a strong, positive, and statistically significant correlation was found between AI awareness and digital competence (r = .560, p < .001). Demographic variables, including age, gender, and teaching experience, did not have a statistically significant effect on either AI awareness or digital competence (p > .05). The study concluded that enhancing AI awareness is important for strengthening digital competence among C&J teachers and facilitating technology-enhanced pedagogical practices. Accordingly, the study recommended continuous professional development programmes, institutional support for AI integration, and inclusive capacity-building initiatives across all trade disciplines to promote effective digital transformation within technical education institutions.

ARTIFICIAL INTELLIGENCE LITERACY AND DIGITAL RESILIENCE AS PREDICTORS OF BUSINESS EDUCATION STUDENTS’ CYBERPRENEURIAL INTENTION IN EDO STATE

2026-09-26T15:35:15+00:00

The rising rate of graduate unemployment in Nigeria has heightened the need to equip business education students with digital competencies capable of driving job creation. The study evaluated the extent to which artificial intelligence literacy and digital resilience predict business education students’ cyberpreneurial intention in Edo State, adopting a correlational survey research design. Three research questions were addressed, while three hypotheses were tested at the .05 level of significance. The population comprised 481 business education students from Ambrose Alli University, Ekpoma, and the University of Benin. Data were collected using the Artificial Intelligence Literacy, Digital Resilience, and Cyberpreneurial Intention Questionnaire (AILDRASIQ), which was validated by two experts. The reliability coefficients obtained using Cronbach’s alpha were .88 for artificial intelligence literacy, .82 for digital resilience, and .85 for cyberpreneurial intention following administration to 30 business education students at Delta State University, Abraka. Simple linear regression and multiple regression were used to analyze the data. The results demonstrated that artificial intelligence literacy and digital resilience individually and jointly predicted business education students’ cyberpreneurial intention in Edo State. The findings imply that deliberate efforts should be made to review the curriculum to incorporate AI literacy, digital business tools, and resilience-building digital learning experiences to enhance students’ readiness for cyberpreneurship. The study addressed a research gap by examining the relatively underexplored relationship among AI literacy, digital resilience, and cyberpreneurial intention. Based on the findings, it was recommended that students be introduced to emerging AI tools that can facilitate digital business operations.

ARTIFICIAL INTELLIGENCE TOOLS AND THEIR INFLUENCE ON STUDENTS’ ACADEMIC PERFORMANCE IN TERTIARY INSTITUTION

2026-09-26T15:47:07+00:00

Artificial Intelligence (AI) has significantly transformed teaching and learning, research, and assessment in higher education. The rapid adoption of AI-powered tools such as ChatGPT, Google Gemini, Microsoft Copilot, Grammarly, QuillBot, and adaptive learning platforms has significantly influenced teaching and learning processes in tertiary institutions worldwide. This paper examined artificial intelligence tools and their influence on students’ academic performance in tertiary institutions. The purpose was to discuss the concept of artificial intelligence, commonly used AI tools among students, the positive and negative influences of AI on academic performance, challenges associated with AI adoption in higher education, and strategies for promoting the ethical and effective use of AI technologies. The paper adopted a descriptive review approach by synthesizing findings from recent empirical studies conducted in Nigeria. Evidence from the reviewed literature indicates that AI tools improve students’ academic performance by enhancing personalized learning, increasing learning motivation, supporting academic writing, improving research efficiency, and providing immediate feedback. However, excessive dependence on AI may weaken critical thinking, reduce creativity, encourage academic dishonesty, and compromise the development of independent learning skills. The paper concluded that AI should complement rather than replace students’ cognitive efforts. It suggested, among other measures, that tertiary institutions formulate AI usage policies, train lecturers and students on responsible AI practices, redesign assessment methods, and integrate AI literacy into the curriculum to maximize its educational benefits.

DATA-DRIVEN SPORTS: THE CHALLENGES OF ARTIFICIAL INTELLIGENCE IN GLOBAL SPORTS MANAGEMENT

2026-09-26T15:55:27+00:00

The rapid integration of Artificial Intelligence (AI) into the sports industry has transformed how athletes train, teams compete, and organizations make strategic decisions. This paper examined the role of AI in enabling data-driven sports by exploring its applications in performance analysis, injury prevention, talent identification, tactical decision-making, fan engagement, and sports management. The paper argues that AI-driven technologies, including machine learning, computer vision, wearable sensors, and predictive analytics, have significantly improved the collection, processing, and interpretation of sports data, thereby enhancing athletic performance and organizational efficiency. However, the widespread adoption of AI also presents challenges related to data privacy, algorithmic bias, ethical governance, financial accessibility, and the evolving role of human expertise in decision-making. The paper maintains that while AI should be embraced as a transformative tool in modern sports, its implementation must be guided by ethical standards, transparency, and human oversight to ensure fairness and inclusivity. It concluded that the future of sports lies in a balanced partnership between artificial intelligence and human judgment, where technological innovation complements rather than replaces the expertise of coaches, athletes, officials, and sports administrators. The paper provided recommendations for policymakers, sports organizations, and researchers to promote responsible AI adoption that supports sustainable development and competitive excellence in the global sports industry.

EXPLORING ACADEMIC STAFF PERCEPTIONS AND ACCEPTABILITY OF AI IN INSTRUCTIONAL DELIVERY IN TVET PROGRAMMES IN FEDERAL UNIVERSITIES IN SOUTH-SOUTH NIGERIA

2026-09-26T16:26:47+00:00

This study examined the perception and acceptability of artificial intelligence (AI) in instructional delivery among Technical and Vocational Education and Training (TVET) academic staff in federal universities in South-South Nigeria. A descriptive survey research design was adopted. A structured questionnaire, validated by three lecturers, was administered to a sample of 158 TVET academic staff randomly selected from federal universities in South-South Nigeria. The instrument yielded a Cronbach’s alpha reliability coefficient of α = .79. Data were analyzed quantitatively using the mean and standard deviation to assess participants’ responses and their degree of dispersion around the mean. The findings revealed that TVET academic staff perceived AI as a valuable tool for enhancing teaching, improving research, facilitating learning practices, and supporting effective classroom management. Furthermore, the results indicated that TVET academic staff accepted the use of AI in instructional delivery because it provides adequate content knowledge, offers effective tools for teaching practical lessons, and enables students to learn more effectively, among other benefits. Based on the findings, the study recommended that major stakeholders in TVET programmes collaborate to promote the integration of AI into instructional delivery and strengthen its effective utilization in TVET programmes.

FROM CHALKBOARD TO ALGORITHM: HISTORICAL SHIFTS IN TEACHER AUTHORITY IN THE DIGITAL AGE

2026-09-26T16:36:42+00:00

The accelerated development of digital technologies and artificial intelligence has drastically changed the historical foundations of teachers’ authority in modern educational systems. This paper examined historical changes in teacher authority, from traditionally chalkboard-based pedagogy to algorithmically driven learning in the digital era. The theoretical basis for the analysis was drawn from Weber’s theories of authority, Foucault’s theories of power and discipline, and Freire’s critical pedagogy. The paper explored how technological innovation, algorithmic governance, and AI-driven instructional systems have reshaped educational power dynamics, class dynamics, and pedagogy. It contended that, while teachers traditionally relied on their monopoly over knowledge dissemination, institutional authority, and the ability to control and discipline students, modern technological developments have gradually transformed educational power dynamics. The paper examined key issues surrounding algorithmic surveillance, automated evaluation, dependence on digital platforms, and the growing tension between human teacher–student relationships and machine-based learning processes. Although technology can democratize education, improve efficiency, and facilitate personalized learning, the paper maintained that it cannot substitute for essential human elements of teaching, including moral reasoning, emotional intelligence, mentoring, and interpersonal communication. The paper concluded that teacher authority is not disappearing but undergoing historical reformation within digital educational realities, with teachers increasingly serving as facilitators, moral guides, and human navigators in algorithmic learning environments. It advocated a balanced use of technology, preservation of human-centered pedagogy, and ethical regulation of artificial intelligence in education.

IMPACT OF AI-DRIVEN SIMULATIONS ON TEACHING CHEMISTRY AND SCIENTIFIC CONCEPTS IN PUBLIC SECONDARY SCHOOLS IN EKPOMA, EDO STATE, NIGERIA

2026-09-26T16:53:52+00:00

This study examined the perceived impact of AI-driven simulations on Chemistry teaching and students’ understanding of scientific concepts in public secondary schools in Ekpoma, Edo State, Nigeria. The study adopted a descriptive survey design involving 210 respondents, comprising 180 Senior Secondary II Chemistry students and 30 Chemistry teachers selected through simple random sampling. Data were collected using a researcher-developed instrument titled AI-Driven Simulations and Chemistry Teaching Questionnaire (AIDSCTQ), which recorded a Cronbach’s alpha reliability coefficient of .86. Mean and standard deviation were used to analyze the data, with a criterion mean of 2.50. The findings showed that respondents perceived AI-driven simulations as positively influencing Chemistry teaching and students’ understanding of scientific concepts (grand mean = 2.95). The strongest perceived benefit was the simplification of difficult Chemistry concepts (mean = 3.26), followed by improved understanding of scientific concepts (mean = 3.14). However, perceived effects on knowledge retention and teachers’ classroom effectiveness were comparatively moderate. Major implementation barriers included inadequate ICT facilities (mean = 3.31), poor electricity supply (mean = 3.20), inadequate internet connectivity (mean = 3.09), insufficient government support, limited teacher training, and the cost of digital facilities (grand mean = 3.01). The study concludes that AI-supported simulations can strengthen Chemistry instruction when implemented as a complement to teacher-led and laboratory-based learning. It recommends sustained investment in digital infrastructure, teacher professional development, curriculum alignment, and the responsible, human-centred use of AI-enabled learning technologies.

INFLUENCE OF ARTIFICIAL INTELLIGENCE COMPUTERIZED MULTIPLE CHOICE ADAPTIVE ACHIEVEMENT TEST (AI-CAT) ON ACADEMIC PERFORMANCE OF UNDERGRADUATES IN LAGOS STATE UNIVERSITY OF EDUCATION, LAGOS STATE, NIGERIA

2026-09-26T17:03:10+00:00

This study examined how the use of Artificial Intelligence Computerized Multiple Choice Adaptive Achievement Test (AI-CMCAAT) influenced undergraduates’ performance at Lagos State University of Education, Lagos State, Nigeria. Two hypotheses were formulated for the study. A quasi-experimental research design, specifically a pretest-posttest control group design, was adopted. The population comprised 2,345 third-year undergraduate students at Lagos State University of Education. One-tenth of the population was used, resulting in a sample of 285 undergraduates selected through a multi-stage sampling procedure. Data were collected using the AI-CMCAAT, which covered seven selected topics in Educational Measurement and Evaluation. The instrument contained 35 items using a four-option response format. The validity of the test was established by three experts in Measurement and Evaluation. Cronbach’s alpha was used to determine the internal consistency of the items, yielding a reliability coefficient of r = .779. An independent-samples t-test was used to analyze the data, with the hypotheses tested at the .05 level of significance. The findings revealed that students’ performance was generally not as significant as expected when compared with findings from previous studies. The study also found that although AI-generated adaptive assessment provides personalized assessment, immediate feedback, and improved test precision, the conventional test (Teacher-Made Test) was perceived as more learner-friendly, more closely related to learners’ learning conditions and time, and more considerate of students’ ability levels during test development. The authors concluded that while AI adaptive tests remain an effective assessment innovation capable of improving students’ academic performance, teachers need to be trained in globally accepted structured formats for formulating test items, particularly in the era of digital learning. The study recommended that educational stakeholders should complement the use of AI adaptive tests in classrooms to enhance learning outcomes.

INFLUENCE OF TEACHERS' PROFESSIONAL DEVELOPMENT ON INSTRUCTIONAL DELIVERY AND PERCEIVED ACADEMIC PERFORMANCE OF PUPILS IN PRIMARY SCHOOLS IN ESAN CENTRAL LOCAL GOVERNMENT AREA, EDO STATE

2026-09-26T17:14:13+00:00

Teachers' professional development (TPD) refers to the continuous process through which teachers upgrade their knowledge, skills, and teaching practices in response to changing curricula, technologies, and pedagogical trends. This study examined the influence of TPD on instructional delivery and teachers' perceived academic performance of pupils in public primary schools in Esan Central Local Government Area, Edo State, Nigeria. A descriptive survey design was adopted. The population comprised 272 public primary school teachers, from which a sample of 40 teachers (approximately 15%) was drawn using simple random sampling. Data were collected using a structured questionnaire titled the Teachers' Professional Development, Instructional Delivery and Academic Performance Questionnaire (TPDIDAPQ), validated by subject experts and found reliable (Cronbach's alpha = .84), and analyzed using frequency counts, percentages, mean, and standard deviation. Findings showed that teachers who participated regularly in workshops, seminars, and in-service training reported improved lesson planning, classroom management, and instructional delivery, which they perceived to be associated with better pupil engagement and academic outcomes. The study concludes that TPD is associated with improvements in teachers' self-reported instructional practice, though the descriptive, self-report design used here does not permit causal claims about pupils' actual academic performance. It is recommended that government, school administrators, and other stakeholders provide regular, sustained training opportunities for teachers, and that future studies incorporate objective measures of pupils' academic performance, such as school-based test or examination scores.

LEVERAGING BLOCKCHAIN AND BIG DATA FOR TRANSPARENT AND EFFICIENT FINANCIAL REPORTING: EVIDENCE FROM NIGERIAN LISTED FIRMS

2026-09-26T17:20:50+00:00

This study empirically examined the effects of blockchain adoption readiness and big data analytics capability on the transparency and efficiency of financial reporting among firms listed on the Nigerian Exchange (NGX). The study is anchored on the Technology Acceptance Model and Diffusion of Innovation theory to explain the reporting-quality implications of these technologies. An ex post facto research design was adopted, covering 68 non-financial listed firms from 2019 to 2024, resulting in 408 firm-year observations. Primary data were collected through structured questionnaires administered to 312 preparers, auditors, and users of financial statements, while secondary data were obtained from audited annual reports and NGX filings. Financial reporting transparency was measured using a disclosure quality index and analyst forecast dispersion, while efficiency was assessed through audit report lag and financial reporting preparation cost. Data were analyzed using descriptive statistics, Pearson correlation, ordinal logistic regression, and generalized least squares panel estimation. The findings reveal that blockchain adoption readiness and big data analytics capability significantly improve both financial reporting transparency and efficiency. Big data analytics, however, has a stronger and more mature presence among Nigerian listed firms, while blockchain adoption remains at an early stage. Regulatory and infrastructural readiness significantly strengthens the relationship between technology adoption and financial reporting outcomes. The study contributes firm-level evidence from an emerging economy and integrates technology readiness with measurable reporting outcomes. It recommends clearer blockchain regulation, improved digital and power infrastructure, phased technology investment, and stronger professional capacity development. The study concludes that technological capability and a supportive institutional environment are essential for effective adoption.

OPTIMIZING SCHOOL FACILITIES AND INFRASTRUCTURE THROUGH ARTIFICIAL INTELLIGENCE IN PUBLIC SECONDARY SCHOOLS IN EDO SOUTH SENATORIAL DISTRICT

2026-09-26T17:26:48+00:00

This study was conducted to ascertain the extent to which AI applications are utilized in managing school facilities and infrastructure in public secondary schools in Edo South Senatorial District, using a descriptive survey research design. Six research questions were raised to guide the study. The population comprised 148 public secondary school principals in the seven local government areas that make up Edo South Senatorial District. A stratified random sampling technique was used to select 74 principals who formed the sample of the study. Data were collected using a structured questionnaire titled Optimizing School Facilities and Infrastructure Through Artificial Intelligence (OSFITAI). The instrument had a reliability coefficient of .974. Data were analyzed using descriptive statistics, including mean score and standard deviation, while Pearson’s r was used to analyze the hypotheses at the .05 alpha level of significance. The mean score was used to determine the extent to which AI applications are utilized in managing school facilities and infrastructure. The Pearson r value of .48 was greater than the alpha level of .05, indicating a moderate positive relationship between AI utilization and efficient utilization of school facilities. Findings revealed that AI applications are not yet widely utilized in the management of school facilities and infrastructure in public secondary schools in Edo South Senatorial District. The study recommended that the government and stakeholders in education should increase budgetary allocations to enable the provision of AI tools to public secondary schools.

PATH-ANALYTIC STUDY OF STUDENTS’ ACADEMIC CAPABILITY AND COMPLETION RATE OF PH.D. PROGRAMMES IN SOUTHWESTERN NIGERIA PUBLIC UNIVERSITIES

2026-09-26T20:15:22+00:00

Abstract

This study examined the influence of students’ academic capability on the completion rate of Ph.D. programmes using a path analytic framework. It conceptualizes academic capability as a multidimensional construct comprising research ability, analytical ability, research productivity, and self-efficacy. The study adopted a descriptive survey research design approach to obtain information using both physical and online approaches from 200 study participants, comprising postgraduates who are through with their programmes of study and those who are on research, using a four-point scale questionnaire developed from the list of academic capability dimensions influencing completion rate as identified by the researcher through inductive and deductive studies. The findings of the study revealed that research ability, analytical ability, and self-efficacy directly and indirectly influenced one another as well as completion rate, except for research productivity, which exhibited a single path of direct relationship with completion rate. Self-efficacy demonstrated positive direct influences on research ability, research productivity, and completion rate (β = .049), (β = .666), and (β = .152), respectively. Furthermore, research productivity exhibited indirect positive effects on analytical ability and research productivity but a negative indirect influence on completion rate at (β = .37), (β = .456), and (β = -.060), respectively. It was also revealed that self-efficacy and research productivity demonstrated negative total effects on completion rate (β = -.152) and (β = -.467), indicating that individual students’ overconfidence in their ability to successfully plan and execute their research-related tasks might make them end up graduating late.

PRINCIPALS' EFFICIENCY TOWARDS UTILIZATION OF AI-DRIVEN APPLICATIONS FOR SUSTAINABLE SCHOOL MANAGEMENT IN THE DIGITAL AGE IN DELTA STATE

2026-09-26T20:38:37+00:00

This study examined principals’ efficiency towards the utilization of AI-driven applications for sustainable school management in the digital age in Delta State. Four research questions guided the study. The study adopted a descriptive survey research design. The population of the study comprised all 474 principals of public secondary schools in Delta State. A total of 237 principals from 237 public secondary schools was used as the sample size, selected at 50% using a proportionate stratified random sampling technique. A 20-item self-structured questionnaire designed by the researcher and titled “Principals’ Efficiency in Utilization of AI-Driven Applications for Sustainable School Management Questionnaire (PEAIASSMQ)” was used for data collection. Both the validity and reliability of the questionnaire were established. Data collected and collated were analyzed using mean statistics, with a criterion mean of 2.50, and standard deviation statistics. Findings of the study generally revealed, among others, that principals were inefficient in utilizing AI-driven applications for sustainable curriculum and instructional management, personnel management, decision-making management, and teaching-learning resource management in the digital age in secondary schools.Among the recommendations proffered from the findings was that the Delta State Government, in conjunction with the Post Primary Education Board (PPEB) and other educational authorities, should organize consistent compulsory capacity-building programmes and continuous professional development (CPD) training for principals on AI-driven applications and digital leadership, particularly in the areas of curriculum and instructional management, in order to improve principals’ efficiency in using AI tools for the sustainability of instructional, administrative, and decision-making processes in public secondary schools in the digital age.

ROLE OF ARTIFICIAL INTELLIGENCE IN ENGLISH LANGUAGE ACQUISITION AND PEDAGOGY AMONG SECONDARY SCHOOL STUDENTS AND TEACHERS IN EDO STATE

2026-09-27T03:39:54+00:00

The present study empirically investigated the role of Artificial Intelligence (AI) in English language acquisition and pedagogy in Nigeria. Employing a descriptive survey design, the research gathered data from 320 participants, comprising English language teachers and students, who were identified through stratified random sampling across the five local government areas of Edo Central Senatorial District, Edo State. The main data-collection instrument was a validated structured questionnaire, which was further complemented by focus group discussion. Data analysis drew on both descriptive measures (mean scores, standard deviations, and frequency distributions). Results indicate that AI-powered platforms, notably ChatGPT and Duolingo, yielded meaningful gains across speaking, writing, and reading domains (mean = 3.74, SD = .61). The study further established that most aspects of English language pedagogy, including Phonetics, Grammar, and Reading Comprehension, were perceived to be taught more effectively with AI platforms. Despite these gains, significant ethical concerns around data privacy, over-dependence on AI tools, and algorithmic bias were identified. The authors recommended, among others, that Nigerian educational policymakers should endeavor to develop a national AI integration framework for secondary English language education that specifies content standards, data privacy protocols, and usage guidelines for AI tools.

STAKEHOLDERS’ AWARENESS, PERCEPTIONS, UTILIZATION AND OBSERVED CHALLENGES OF ARTIFICIAL INTELLIGENCE INTEGRATION IN BUILDING CONSTRUCTION EDUCATION IN TECHNICAL COLLEGES IN EDO STATE

2026-09-27T03:51:16+00:00

Abstract

This study investigated stakeholders’ awareness, perceptions, utilization, and observed challenges of Artificial Intelligence (AI) integration in Building Construction Education in Technical Colleges in Edo State, Nigeria, using a descriptive survey research design. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), the population comprised 344 stakeholders, including students, teachers, administrators, parents, and employers involved in building construction education in government-owned Technical Colleges in Edo State. Given the manageable size of the population, a census approach was employed for students, teachers, and administrators, while convenience sampling was used to reach parents and employers who were available and willing to participate during data collection. A total of 333 valid responses were retrieved and analyzed. Data were collected using a structured questionnaire titled Stakeholders’ AI Integration in Building Construction Education Questionnaire (SAIBCEQ), with a Cronbach’s alpha reliability coefficient of .82. Mean and standard deviation were used to answer the research questions, while one-way Analysis of Variance (ANOVA) was used to test the hypotheses at the .05 level of significance. Where significant differences existed, Tukey HSD post hoc tests were conducted to identify the specific stakeholder groups responsible for the observed differences. Findings revealed moderate awareness (M = 2.59), favourable perceptions (M = 3.46), very low utilization (M = 1.49), and high perceived challenges (M = 3.60) regarding AI integration among stakeholders. Significant differences existed among stakeholder groups in awareness, perceptions, and utilization, while no significant difference was found in observed challenges. The study recommended improved digital infrastructure, teacher training, and curriculum integration to enhance AI adoption in Technical Colleges in Edo State.

TECHNOLOGICAL UTILIZATION AND SECONDARY SCHOOL RECORDS MANAGEMENT PERFORMANCE

2026-09-27T04:00:56+00:00

Abstract

This study examined the impact of technological utilization on secondary school records management performance in Esan West Local Government Area of Edo State, Nigeria. Specifically, it investigated the relationship between technology adoption and two performance indicators: data processing and retrieval speed, and accuracy of records. The study employed a survey research design, using a structured questionnaire administered to all 85 teachers from eight public secondary schools through census sampling. Data were analyzed using percentages for descriptive statistics and Pearson correlation for hypothesis testing. Findings revealed a strong positive relationship (r = .84) between technological utilization and records management performance, indicating that schools using tools such as Microsoft Excel, OpenSIS, and Google Workspace achieved faster data retrieval and greater accuracy. However, challenges such as inadequate ICT infrastructure, limited training, and unstable electricity supply hindered optimal results. The study recommends improved ICT facilities, regular staff training, and policy support to enhance sustainable records management.

THE ROLE OF ARTIFICIAL INTELLIGENCE IN BUSINESS EDUCATION ASSESSMENT AND EVALUATION

2026-09-27T04:08:35+00:00

Abstract

Artificial Intelligence (AI) is increasingly reshaping how teaching, learning, assessment, and evaluation are conceived and practised in business education. This opinion paper critically examined the opportunities, limitations, and pedagogical implications of AI-enabled assessment and evaluation, with particular attention to contexts in which technological, infrastructural, ethical, and human-capacity constraints can affect implementation. The paper adopted an analytical opinion-paper design rather than an empirical research design. Its arguments are developed through a critical and thematic synthesis of selected scholarly literature, policy-oriented publications, and conceptual works published principally between 2021 and 2026, supplemented where necessary by foundational theoretical sources. The discussion focused on automated grading, adaptive and personalised assessment, real-time feedback, academic-integrity monitoring, learning analytics, predictive assessment, and the implications of these applications for teaching practice and institutional effectiveness. The paper argued that AI should not be understood merely as a mechanism for automating assessment; rather, its greatest educational value lies in augmenting professional judgement, enabling timely feedback, supporting competency-based evaluation, and generating evidence for instructional decision-making. At the same time, concerns relating to algorithmic bias, privacy, transparency, academic integrity, digital inequality, infrastructure, staff preparedness, and overdependence on automated systems cannot be treated as secondary issues. The paper therefore advanced the position that responsible AI integration requires human oversight, curriculum redesign, educator capacity development, institutional investment, and clear ethical and governance arrangements. AI can strengthen business education assessment and evaluation, but only when technology serves sound pedagogical purposes rather than replacing professional educational judgement.

UNDERGRADUATE STUDENTS’ AWARENESS, UTILIZATION, AND PERCEIVED EFFECTIVENESS OF AI-CHATBOTS FOR COUNSELLING SERVICES DELIVERY IN A NIGERIAN UNIVERSITY

2026-09-27T04:13:49+00:00

Abstract

This study investigated undergraduate students' awareness and utilization of AI chatbots and examined the perceived effectiveness of ChatGPT, Google Gemini, and Meta AI in enhancing counselling service delivery at Ambrose Alli University, Ekpoma, Nigeria, using a descriptive survey research design involving 400 participants selected through a multi-stage sampling technique. Data were collected using the validated Students' Perspectives on AI Chatbots in Counselling Service Delivery Questionnaire (SPAICSDQ). The data collected were analyzed using descriptive and inferential statistics at the .05 level of significance. The findings revealed that students demonstrated high levels of awareness and utilization of AI chatbots for counselling-related purposes. Participants perceived AI chatbots as effective tools for improving the accessibility, responsiveness, and efficiency of counselling services. No significant differences were found in students' perceptions based on gender and level of study, whereas a significant difference was observed across faculties, with students from the Faculty of Education reporting more favourable perceptions. The study concluded that AI chatbots can effectively complement conventional counselling services but should not replace professional counsellors. Therefore, the paper recommends the integration of AI chatbots into university counselling services through appropriate institutional policies, ethical guidelines, digital literacy initiatives, and continuous professional oversight.

USE OF ARTIFICIAL INTELLIGENCE IN ENHANCING COUNSELLING SERVICE DELIVERY IN EDUCATIONAL INSTITUTIONS: EVIDENCE FROM PRIVATE UNIVERSITIES IN EDO STATE, NIGERIA

2026-09-27T04:20:48+00:00

Abstract

Artificial intelligence (AI) is increasingly transforming counselling practice by improving the accessibility, efficiency, and responsiveness of student support services in higher education. Despite its growing adoption globally, empirical evidence on its application in university counselling services in Nigeria remains limited. This study investigated the role of artificial intelligence in enhancing counselling service delivery in selected private universities in Edo State, Nigeria, using a descriptive survey research design. The study involved 240 respondents, comprising 25 professional counsellors, 15 student affairs personnel, and 200 undergraduate students, selected through proportionate stratified and simple random sampling techniques. Data were collected using a researcher-developed instrument titled Artificial Intelligence and Counselling Service Delivery Questionnaire (AICSDQ). The instrument was validated by experts in Guidance and Counselling, Educational Technology, and Measurement and Evaluation, while a pilot study yielded a Cronbach's alpha reliability coefficient of .88. Data were analyzed using mean and standard deviation, with a criterion mean of 2.50. The findings revealed that artificial intelligence had a moderately positive influence on counselling service delivery (Grand Mean = 3.01). Respondents agreed that AI improved students' access to counselling services, facilitated quicker responses to enquiries, and strengthened career guidance and academic advising. The study further revealed that inadequate AI training for counsellors, ethical and confidentiality concerns, weak institutional policies, and limited funding were the major barriers to effective AI integration (Grand Mean = 3.08). The study concluded that AI can significantly strengthen counselling service delivery when supported by adequate institutional policies, professional competence, and ethical safeguards. It was recommended that private universities should invest in AI infrastructure, continuous capacity building, and responsible AI governance to enhance counselling services.

USING ARTIFICIAL INTELLIGENCE TOOLS TO STRENGTHEN THE QUALITY, EFFICIENCY AND INTEGRITY OF EDUCATIONAL RESEARCH IN HIGHER EDUCATION

2026-09-27T04:27:12+00:00

Abstract

Artificial intelligence (AI) is increasingly becoming part of the everyday work of researchers in higher education. Its value, however, depends less on the novelty of the technology than on how carefully researchers use it. This paper examined how AI tools can support three closely related goals in educational research: improving quality, reducing avoidable time and effort, and protecting research integrity. A PRISMA-informed conceptual review was undertaken using literature and substantive sources published between 2021 and 2026. Attention was given to AI-supported literature discovery, synthesis, data analysis, academic writing, peer review, and research-integrity activities. Tools discussed include Elicit, Consensus, Scite, ResearchRabbit, Semantic Scholar, Grammarly, Paperpal, Trinka AI, and Turnitin's AI-related features. The review suggests that AI can make some research tasks faster and can widen access to scholarly information, particularly for researchers working in resource-constrained settings. At the same time, AI outputs may contain inaccurate claims, incomplete coverage, biased summaries, or fabricated references. These risks become more serious when researchers treat AI output as a substitute for reading, judgement, and methodological verification. In response, the paper proposes the QUERI framework—Quality, Use, Ethics, Rigour, and Integrity—as a practical guide for responsible AI-assisted educational research. The paper argues that Nigerian higher education institutions should move beyond either unrestricted enthusiasm or blanket rejection of AI. Instead, they should build research cultures in which AI is used transparently as an assistant, while responsibility for evidence, interpretation, and scholarly judgement remains with the researchers.

STUDIES IN EDUCATION VOL.24 No.2, September 2026

2026-10-02T15:50:09+00:00

ISSN: 1117-2398

STUDIES IN EDUCATION

VOL.24 No.2, September 2026