HUMAN INTELLIGENCE FACTORS PREDICTING EFFECTIVE AI USE IN NIGERIAN UNIVERSITIES' EDUCATION

Abstract

The study investigated the relationship between human intelligence factors and their ability to predict effective AI usage in educational settings in Nigeria with the intent of determining the level of effective AI use in education among educators and undergraduate students; examining the extent to which human intelligence factors (cognitive, emotional, social, and metacognitive intelligence) predict effective AI use in education; and the combined predictive effect of cognitive, emotional, social, and metacognitive intelligence on effective AI use in education. The study employed a quantitative survey research design and the population included university educators and undergraduate students from Nigerian institutions that have implemented Artificial Intelligence (AI) tools for educational purposes. The research selected ten universities with multiple ownership types i.e. federal, state and private. Multistage, Stratified and proportionate random sampling was used for sample selection; The study collected survey data from 1500 undergraduate students and 150 educators who worked at the ten different universities using descriptive statistics, Pearson correlation and multiple regression for analysis. The study shows that among undergraduates, the predominant level of effective AI use was medium, whereas a larger share of educators demonstrated high effectiveness in AI usage; the study also found that metacognitive intelligence was the strongest predictor for the research results, while cognitive and emotional intelligence followed behind. The results demonstrate that human abilities serve as the main factor that enables people to use AI technology in ways that respect ethical standards and support educational needs.