- Rosemary Isioma Brown PhD* & AZEEZ Fatimo Moromoke PhD
- *Department of Educational Foundations, Faculty of Education Rivers State University, Nkpolu-Oroworukwo, Port Harcourt, Rivers State
- DOI: 10.5281/zenodo.22164173
The study set out to find out how staff of Rivers State-owned universities perceive the effect of ethical Artificial Intelligence (AI) practices on the way their institutions are managed. Attention was placed on two ethical dimensions, namely AI fairness and AI transparency. Two objectives, two research questions and two null hypotheses directed the enquiry. A descriptive survey design was employed. Altogether, 2,248 staff of the two state-owned universities formed the population, made up of 1,248 academic and 1,000 non-academic staff. From this number, 500 respondents were drawn through proportionate stratified random sampling, comprising 300 academic and 200 non-academic staff. A self-designed questionnaire, the Perceived Influence of Ethical Artificial Intelligence Practices on Educational Management Questionnaire (PIEAIPEMQ), built on a four-point modified Likert scale, served as the instrument for data gathering. Three experts carried out face and content validation, and Cronbach Alpha was applied to establish internal consistency, returning a coefficient of 0.86. Of the 500 copies distributed, 476 came back usable, a retrieval rate of 95.2%. The research questions were answered with mean and standard deviation, and the null hypotheses were tested with the independent samples t-test at 0.05 alpha. Results showed a high extent of influence for AI fairness, with a grand mean of 3.11, and a high extent of influence for AI transparency, with a grand mean of 3.00. On both dimensions, the ratings of academic and non-academic staff did not differ significantly. It was concluded that ethical AI practices contribute positively to effective educational management, and it was recommended, among other things, that the universities put in place institutional AI ethics policies, mount regular staff capacity-building programmes, and establish clear accountability structures for automated administrative decisions.
