ARTIFICIAL INTELLIGENCE AND SELECTION OUTCOME IN FEDERAL UNIVERSITIES, SOUTH EAST, NIGERIA

Abstract

The study examined the relationship that exists between Artificial Intelligence and Selection Outcome in Federal Universities, South East, Nigeria. The study adopted descriptive survey research design. The population of the study comprised of 28,326 senior teaching and senior non-teaching staff of Federal Universities in the South East Region of Nigeria. The sample size for the study comprised of 394 senior teaching and senior non-teaching staff of Federal Universities in the study area which was determined using Taro Yamane formula. Cluster probability sampling technique was used to determine the number of questionnaire distributed. The study was guided by two research questions and two research hypotheses. The instrument for data collection was a questionnaire. The instrument was validated by two experts, one from Faculty of Education (Education Foundation Department) and the other from Faculty of Management Sciences, both in Nnamdi Azikiwe University, Awka. The reliability of the instrument was determined using Cronbach’s Alpha method with an overall reliability of 0.91. The data was analyzed using descriptive statistics and hypotheses were tested with the aid of Pearson Product Moment Correlation Coefficient on Statistical Packages for Social Science (SPSS version 27) at 5% level of significance. The findings of the study showed that there is a strong positive significant correlation (r = 0.724) that exist between the Applicant Tracking System (ATS) and Assessment Test Result, with p-value of 0.000 (p<0.05the study concludes that Artificial Intelligence (AI) has the potential to revolutionize selection outcomes in Federal Universities in South East Nigeria by enhancing efficiency, objectivity, and candidate experience. By implementing AI-driven tools like Applicant Tracking Systems and Chatbots, universities can streamline the recruitment process, reducing biases that often influence hiring decisions. The study recommended that the Management of Federal universities in South East Nigeria should enhance the implementation and effectiveness of Applicant Tracking Systems (ATS) to improve assessment test results.