APPLICATION OF ARTIFICIAL INTELLIGENCE IN BUSINESS EDUCATION RESEARCH IN UNIVERSITIES IN SOUTH-SOUTH NIGERIA

This study examined the application of artificial intelligence in business education research within universities in the South-South region of Nigeria. The study was guided by two research questions and four hypotheses. A descriptive survey research design was employed. The study population consisted of 232 business education lecturers, made up of 138 lecturers from state universities and 94 from federal universities. Given the manageable size, the entire population was used as the sample. Data were collected using a 37-item questionnaire developed by the researchers. The instrument was designed on a four-point rating scale: Very High Extent (4), High Extent (3), Low Extent (2), and Very Low Extent (1). Both face and content validity of the questionnaire were established through expert review by two computer science specialists, three experts in measurement and evaluation, and two business education experts from Delta State University, Abraka. To determine the reliability of the instrument, 18 copies of the questionnaire were pilot-tested on 18 business education lecturers at Nnamdi Azikiwe University, Awka, located in South-East Nigeria and outside the study area. The responses were analyzed using Cronbach’s Alpha, yielding reliability coefficients of 0.86 and 0.89 for the two research questions, indicating high internal consistency. A total of 243 questionnaires were distributed to business education lecturers, of which 232 were correctly completed and returned within two weeks, representing a response rate of 95.47%. The collected data were analyzed using mean scores and standard deviations, while independent samples t-test was employed to test the hypotheses at the 0.05 level of significance. Decisions on the hypotheses were based on comparing the calculated t-values with the critical t-values. Findings related to the first research question indicated that strategies for enhancing the use of artificial intelligence in business education research include improved funding for AI-related research infrastructure and the availability of data to support AI-driven research activities. Results from the second research question revealed several challenges, such as the absence of comprehensive public policies on AI application in education and research, as well as limited understanding of adaptive learning algorithms necessary for effective AI-based research. The hypotheses testing showed, among other outcomes, that there was no significant difference between the mean ratings of male and female lecturers regarding strategies for promoting the application of artificial intelligence in business education research in South-South Nigerian universities. Based on these findings, the study recommended that university authorities should provide adequate funding for workshops and conferences aimed at equipping lecturers with relevant skills and strategies for applying artificial intelligence in business education research.