University Library http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/172 2026-10-29T23:00:02Z 2026-10-29T23:00:02Z Baji, M. I., Musa, HUSSAINI http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32041 2026-10-28T11:07:20Z 2026-10-12T00:00:00Z

Title: Artificial Intelligence, Psychological Well-being and Workforce Productivity in Higher Education: An Educational Psychology Perspective on Sustainable Human Capital Development. Authors: Baji, M. I.,; Musa, HUSSAINI Abstract: Artificial Intelligence (AI) is reshaping teaching, research and administration in universities, yet its psychological consequences for academic staff are under-examined. This paper proposes and specifies a mixed-methods study of how AI competence and perceived organizational support relate to work engagement, psychological well-being and workforce productivity among lecturers and academic support staff in selected African universities. Grounded in the Job Demands–Resources (JD-R) model and Self-Determination Theory (SDT), the study treats AI as both a job resource (automation, feedback, time savings) and a job demand (learning load, technostress, fear of displacement). An explanatory sequential design is proposed: a cross-sectional survey of about 400 staff using validated scales, analysed with descriptive statistics and structural equation modelling (SEM), followed by 20–24 semi-structured interviews analysed thematically. Because data collection is still to be completed, the Results section reports the pre-specified hypotheses, fit criteria and the pattern of findings anticipated from theory and prior evidence, not observed estimates. The expected pattern is that AI adoption raises productivity indirectly, through AI competence, organizational support and work engagement, and that its benefits weaken where technostress is high and psychological safety is low. The paper recommends integrating AI-competency training with well-being provision, organizational counselling services and evidence-based institutional policy. These actions support SDGs 3, 4, 8 and 9 Description: Conference Paper pdf

2026-10-12T00:00:00Z Baji, M. I., Musa, H. http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32040 2026-10-28T10:30:48Z 2026-10-12T00:00:00Z

Title: Artificial intelligence and digital learning for workforce productivity and efficiency: Transforming continuing education and e-learning in African universities Authors: Baji, M. I.,; Musa, H. Abstract: The Fourth Industrial Revolution has reshaped continuing education, compelling higher education institutions to adopt digital solutions that strengthen workforce productivity and efficiency, lifelong learning and institutional competitiveness. Artificial Intelligence (AI) has emerged as a transformative technology capable of personalising learning experiences, automating administrative processes, supporting data-driven decision-making and enhancing learner engagement. Despite this potential, many continuing education and e-learning centres in Africa continue to grapple with inadequate digital infrastructure, limited staff AI competencies, policy gaps and resistance to technological change. This paper examines how AI and digital learning technologies can improve workforce efficiency and productivity within continuing education programmes in African universities. Guided by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study adopts a mixed-methods design involving administrators, lecturers, instructional designers and adult learners from selected universities. Data will be collected through structured questionnaires, interviews and institutional document analysis to assess AI readiness, digital competence, employee productivity, learner satisfaction and organisational performance. The study anticipates that effective AI integration will significantly enhance administrative efficiency, teaching quality, learner retention, staff productivity and institutional responsiveness to labour-market demands. It further argues that sustainable implementation depends on strategic leadership, investment in digital infrastructure, continuous staff capacity development, robust governance frameworks and clear ethical guidelines for AI deployment. The paper concludes that continuing education centres must reposition themselves as innovation hubs that leverage AI to advance flexible, inclusive and high-quality lifelong learning, offering practical recommendations for university administrators, policymakers and educational leaders seeking to strengthen workforce productivity and efficiency and accelerate digital transformation across African higher education. The study contributes directly to Sustainable Development Goals (SDGs) 4 (Quality Education), 8 (Decent Work and Economic Growth), 9 (Industry, Innovation and Infrastructure) and 17 (Partnerships for the Goals). Description: Conference Paper pdf

2026-10-12T00:00:00Z MUSA, H. http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32033 2026-10-22T22:24:39Z 2026-10-22T00:00:00Z

Title: OPENING ADDRESS BY THE UNIVERSITY LIBRARIAN Authors: MUSA, H. Abstract: This address, delivered by Dr. Musa Hussaini on behalf of the University Librarian of the Federal University of Technology, Minna (FUTMINNA), during International Open Access Week 2026, examines the theme “The Cost of Knowledge.” It highlights the financial, institutional, technological, and social barriers that constrain equitable access to scholarly information and the dissemination of research findings, particularly in resource-constrained institutions. The address emphasises the strategic role of university libraries in advancing open access through institutional repositories, open educational resources, research data management, digital literacy, and scholarly communication support. It further highlights the launch of the FUTMINNA/LIBSENSE Open Science Community of Practice as a platform for collaboration, capacity development, and the adoption of open science principles. In addition, it discusses the importance of Diamond Open Access as a publishing model that eliminates subscription charges for readers and article processing charges for authors, while recognising the need for sustainable institutional support, digital infrastructure, and effective editorial management. The address calls for collective action by university management, researchers, librarians, publishers, funding agencies, students, and policymakers to promote responsible open access, strengthen research visibility, uphold research integrity, and reduce barriers to scholarly communication. It concludes that knowledge achieves its greatest value when it is accessible, discoverable, shareable, and usable for education, innovation, and societal development. Description: Speech docx

2026-10-22T00:00:00Z MUSA, H. http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32032 2026-10-22T21:59:33Z 2026-08-06T00:00:00Z

Title: Reimagining technical services in university libraries: Leveraging AI for efficient resource management Authors: MUSA, H. Abstract: REIMAGINING TECHNICAL SERVICES IN UNIVERSITY LIBRARIES: LEVERAGING AI FOR EFFICIENT RESOURCE MANAGEMENT Hussaini Musa 1. Introduction The Technical Services Department is responsible for acquisitions, cataloguing, classification, metadata creation, and processing and has traditionally been the “backbone” of university library operations. However, in the AI era, automation, machine learning, and intelligent metadata systems are transforming workflows, reducing manual repetition, and introducing predictive and adaptive tools. This chapter will explore how technical services units can evolve from purely operational units to innovation hubs that power seamless access and discovery in academic libraries. The Technical Services Department of a university library traditionally responsible for acquisitions, cataloguing, classification, metadata creation, and the processing of information resources forms the operational backbone of library functions. While public services departments engage directly with patrons through reference, circulation, and instructional services, technical services work largely behind the scenes to ensure that resources are accurately described, systematically organized, and efficiently processed for seamless discovery and access (Intner & Weihs, 2019; Taylor & Joudrey, 2018). Without effective technical services, even the most extensive library collection risks being invisible to its intended users. In the artificial intelligence (AI) era, these long-standing responsibilities are undergoing unprecedented transformation. Advances in machine learning (ML), natural language processing (NLP), computer vision, and knowledge graph technologies have begun to reshape how libraries manage their back-end operations (Yu & Qin, 2023). Routine, repetitive tasks such as descriptive cataloguing, subject indexing, and metadata cross-walking that once required hours of meticulous human effort Description: Book Chapter pdf

2026-08-06T00:00:00Z