Ai-Powered Applicant Screening Systems, Ai-Based Credential Verification, Ai Automated Assessment Tools and Selection Outcome in Federal Universities, South-South, Nigeria

Abstract

This study examined the relationship between artificial intelligence and selection outcome in federal universities, South-South, Nigeria, focusing specifically on AI-powered applicant screening systems and Assessment Test Result; AI-based credential verification and Educational qualification of candidates; and AI automated assessment tools and Candidate Satisfaction. The study was motivated by the persistence of manual, time-consuming and bias-prone selection practices in federal universities, alongside growing concern over credential fraud and inconsistent applicant evaluation, which continue to undermine the fairness, integrity and quality of academic and non-academic staff selection in the region. The study was anchored on the Attraction-Selection-Attrition (ASA) theory. A survey research design was adopted. The study was carried out in the South-South geopolitical zone of Nigeria, covering the University of Port-Harcourt, University of Uyo, University of Benin, and University of Calabar. The population of the study comprised 28,125 senior academic and senior non-academic staff of the four universities, from which a sample size of 394 was determined using Taro Yamane's formula, with Bowley's proportional allocation method employed to distribute the questionnaire across the institutions. Data were analysed using descriptive statistics, while hypotheses were tested using the Pearson Product Moment Correlation Coefficient at a 0.05 level of significance. Findings revealed a strong positive and significant relationship between AI-powered applicant screening systems and Assessment Test Result, AI-based credential verification and Educational Qualification of candidates, AI automated assessment tools and Candidate Satisfaction in federal universities, South-South, Nigeria. The study concluded that artificial intelligence significantly enhances the objectivity, integrity and satisfaction associated with selection outcomes in federal universities in South-South Nigeria. It was recommended among others, that university management should prioritise the deployment of AI-powered screening software devoid of human bias; that the National Universities Commission (NUC) should mandate the adoption of AI-based credential verification systems across federal institutions to curb certificate forgery.