JOB ANALYSIS AND ORGANIZATIONAL PERFORMANCE: A STUDY OF FEDERAL UNIVERSITY WUKARI, TARABA STATE, 2021-2024
Keywords:
Job analysis, Job description, Job specification, Work environment, Organizational performance, Human ResourceAbstract
Job analysis constitutes a fundamental human resource management practice centered on the systematic study and collection of detailed information regarding the duties, responsibilities, requisite skills, outcomes, and work environment associated with a given job. The absence of a well-structured job analysis framework within organizations poses significant risks to organizational performance and the attainment of strategic objectives. This study adopted a descriptive survey research design. Data were sourced from both primary and secondary means, including questionnaires, books, journals, and online materials. There was target population of 3,289, sample size of 346 and 322 returned questionnaires for the study. Descriptive statistical tools such as percentages, frequency counts, and tables were employed to present and analyze the field data, while chi-square analysis was utilized to test the formulated hypotheses. System theory was applied to express interdependence in the practice of job analysis and functioning or outcomes from the organization. The findings revealed that job description, job specification, and work environment analysis significantly influence organizational performance at Federal University Wukari. Based on findings, the study recommends the periodically review and update of job descriptions to align with evolving roles, emerging technologies, and institutional goals. This will ensure staff recruitment and selection processes are guided by clearly defined job specifications that emphasize requisite qualifications and competencies. The measure is essential to maintaining alignment between employees and organizational objectives while ensuring clarity of responsibilities.References
Adekitan, A., & Noma-Osaghae, E. (2019). Challenges and opportunities in adopting data analytics for educational decision-making in Nigerian tertiary institutions. International Journal of Educational Technology, 6(2), 45–57.
Alamri, A., Alhaidari, F., & Alotaibi, A. (2021). Application of learning analytics in higher education: A review of predictive approaches for at-risk students. Journal of Learning Analytics, 8(1), 34–50.
CAMTECH Academic Affairs Office. (2023). ND II students’ academic performance records (2020–2023). College of Administration, Management and Technology, Potiskum, Yobe State, Nigeria.
Ifenthaler, D., & Yau, J. Y. K. (2020). Utilising learning analytics for study success: Reflections on current empirical findings. Education and Information Technologies, 25(4), 2693–2717. https://doi.org/10.1007/s10639-019-10028-5
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. https://doi.org/10.1177/001316447003000308
Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.). University of Chicago Press.
UNESCO. (2015). Education for all 2000–2015: Achievements and challenges. UNESCO Publishing.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, adaptation, and reproduction in any medium, provided that the original work is properly cited.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors are permitted to post their work online in institutional/disciplinary repositories or on their own websites. Pre-print versions posted online should include a citation and link to the final published version in Journal of Librarianship and Scholarly Communication as soon as the issue is available; post-print versions (including the final publisher's PDF) should include a citation and link to the journal's website.