Managing Lecturers’ Academic Impropriety in An Era of Artificial Intelligence for University Education Goals Attainment in Rivers State

Abstract

The issue of academic impropriety is one of the menace bedeviling university administration and this is further aggravated by the emergence of artificial intelligence. This study focused on managing lecturers’ academic impropriety in an era of artificial intelligence for university education goals attainment in Rivers State. Three research questions were answered and three hypotheses tested in the study. The study adopted descriptive survey research design. The population of the study was 2,849 lecturers in the three public universities in Rivers State while 351 lecturers were sampled using stratified random sampling technique. The instrument adopted for gathering data was a 15 item questionnaire tagged “Managing Lecturers Academic Impropriety in an Era of Artificial Intelligence for University Education Goals Attainment in Rivers State Questionnaire” (MLAIEAIUEGAQ). The instrument was face and content validated by three Measurement and Evaluation experts from the Department of Educational Psychology, Guidance and Counselling in University of Port Harcourt. Reliability of the instrument was determined using Cronbach alpha statistics with a coefficient of 0.82 which showed that the instrument was reliable. Out of the 351 copies of questionnaire administered to the lecturers, 332 copies indicating a 94.6% retrieval rate was gotten from 203 male and 129 female lecturers. The research questions raised were answered using mean and standard deviation while the hypotheses were tested at 5% significance level using z-test statistics. The result of the study found that academic impropriety perpetrated by lecturers using artificial intelligence included plagiarism and manipulation of research data with mean values (x) of 2.79 and 2.78 respectively. The implications of lecturers’ academic impropriety using artificial intelligence included poor research outputs and negative institutional image. The ways of managing this menace included training of lecturers on AI professional use and rewarding professionalism. The study recommended that Universities need to make laws that will punish violation of acceptable academic standards.