Ismail Isa, Ibrahim and Md Nor, Nor Saadah and Sarif Abdullah, Sharifah Nur Amirah and Shah, Asadullah and Shehu, Habib (2025) Exploring user engagement with DRS in the federal university libraries in Northwest Nigeria: applying TPB & RUSA standards. In: 7th International Conference on Libraries (ICOL2025), 2025, Pulau Pinang, Malaysia.
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Abstract
This study explores user engagement with digital reference services in federal university libraries across Northwest Nigeria, applying the theory of planned behavior and aligning with reference and user services association, standards. Despite the growing adoption of DRS globally, libraries in the region face challenges such as poor ICT infrastructure, inadequate librarian competencies, and limited user awareness. The main research question investigates how factors like librarian skills, technological competence, complex tasks, and user attitudes influence satisfaction with DRS. A quantitative research design was employed, surveying 376 undergraduate and postgraduate students across eight federal universities using structured questionnaires. Data analyses via SPSS revealed that librarian communication, clarity in instruction, and digital tool navigation significantly affect user satisfaction. While users showed high confidence in using DRS and appreciated its accessibility, response delays and interface complexity remained barriers. The study extended TPB by integrating four new constructs: LibrarianSkills, Technological Competence, Complex Tasks, and User Attitude, providing a more nuanced understanding of digital engagement behaviors. Key findings highlight the importance of enhancing infrastructure, streamlining user interfaces, and integrating real-time support tools. Recommendations include continuous training for librarians, promotional campaigns for DRS, and implementation of feedback loops to drive iterative service improvement. Practical applications lie in using the extended TPB framework to guide DRS policy and design in academic libraries. Future research could focus on AI-powered DRS systems, cultural influences on user behavior, and longitudinal assessments of satisfaction trends.
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