ARTIFICIAL INTELLIGENCE RESOURCES, RESEARCH SKILLS AND RESEARCH PRODUCTIVITY IN NIGERIAN PUBLIC UNIVERSITIES

Abstract

This study examined how Artificial Intelligence (AI) adoption and research competencies impact the scholarly output of lecturers at Nigerian public universities. It adopted a descriptive survey design, using stratified random sampling to select 341 academic staff from a population of 3,412 across five institutions. Data gathered via a structured questionnaire were analyzed using descriptive statistics, Pearson correlation, and multiple regression. Results showed moderate to high access to AI tools, with utilization closely tracking availability. Plagiarism detection led in availability (82.1%) and usage (79.2%), followed by reference management (73.3% available; 70.4% used) and literature search tools (64.5% available; 61.6% used). Text generation and data analysis tools had lower adoption. Regression analysis revealed AI resources significantly impacted productivity, explaining 44% of the variance (R² = 0.44, F(5, 335) = 57.80, p < .001). Academic staff demonstrated moderate to high research competencies, scoring highest in citation (M = 3.82) and information literacy (M = 3.76), but lower in digital literacy (M = 3.29) and data analysis (M = 3.15). Correlation analysis showed a strong positive relationship between research skills and productivity (r = 0.58, p < .001). Combined, AI resources and research skills explained 57% of productivity variance (R² = 0.57, F(3, 337) = 147.83, p < .001), with research skills serving as the primary predictor (beta = 0.34). The study recommends integrating AI technologies and research skills by expanding AI infrastructure, launching focused capacity building programs, and implementing institutional policies for ethical and effective academic research.