ARTIFICIAL INTELLIGENCE APPLICATION AS PREDICTOR OF EFFECTIVE SECONDARY EDUCATION MANAGEMENT IN RIVERS STATE, NIGERIA

Abstract

This study examined artificial intelligence application as predictor of effective secondary education management in Rivers State, Nigeria. The study was guided by three objectives, six research questions and six null hypotheses. The study adopted a correlation survey research design, with a population of 6,153 academic staff from 320 public senior secondary schools in Rivers State. The sample size of the study was 376 drawn from the population Taro Yamane. Stratified sampling technique was the study sampling technique. Questionnaire of two set was the instrument for the study and it was titled: Artificial Intelligence Application Assessment Scale (AIAAS) and Effective Secondary Education Management Assessment Scale (ESEMAS). The instruments were validated and their reliability were tested using Cronbach alpha method and reliability coefficients of 0.81 and 0.86 for both respectively were derived. For method of data analysis, the research questions were answered using simple regression, while the hypotheses were tested with t-test associated with simple regression at 0.05 level of significance. The findings of the study revealed that artificial intelligence application in decision making, resources optimization and enhancement of security significantly predict effective secondary education management in Rivers State to a high extent. Based on this finding, it was recommended among others that school administrators should continue to ensure that school personnel do not see artificial intelligence application in school management as a silver bullet in order to minimize the bias behaviour they have towards AI and issues that has to do with poor decision-making. Also, government through the Ministry of Education management should regularly carrying out training and retraining programme for staff to ensure effective usage of Al facilities in resource optimization for effective secondary education management.