PERCEIVED IMPACT OF AI- DRIVEN TECHNOLOGIES ON RESOURCES ALLOCATION, WORK LOAD AND TIME MANAGEMENT IN TARABA STATE UNIVERSITY, JALINGO, TARABA STATE, NIGERIA

Abstract

The study investigated perceived impact of AI driven technologies on resource allocation, workload and time management in Taraba State University, Jalingo, Taraba State, Nigeria. Three research questions and hypotheses were formulated in line with the purpose of the study. Descriptive survey design was adopted for this study. The population was 59, comprising 11 Deans of faculties and 48 Heads of Departments in Taraba State University. All the Deans and Heads of Departments were used because of their manageable size. The instrument for data collection was a researcher-designed questionnaire titled “AI-Driven Technology Questionnaire (AIDTQ). The instrument was designed on a four –point rating scale of Very High Extent (VHE), High Extent (HE), Low Extent, (LE), and Very Low Extent (VLE). They were scored 4, 3, 2 and 1 respectively.  The instrument was validated by two experts, one from Educational Administration and Planning and one from Measurement and Evaluation, all in Department of Educational Foundations, Faculty of Education, Taraba State University, Jalingo. The internal consistency of the instrument was determined using split- half method of estimating reliability. 5 Deans of faculties, 10 heads of Departments and 25 lecturers, totalling 40 respondents from Benue State University Makurdi were randomly selected for the trial test using the balloting method. Data generated were analyzed using Cronbach Alpha method. Cronbach Alpha was used because the items were not dichotomously scored. The researchers, with the help of 3 trained research assistants administered and collected the completed questionnaire for analysis. Data generated from the study were analyzed using both descriptive and inferential statistics. Descriptive statistics of mean and standard deviation were used to answer the research questions. Inferential statistics of chi-square goodness of fit was used to test all the null hypotheses at 0.05 level of significance. The study found that AI-driven technologies have significant impact on resource allocation, workload management, and time management in Taraba State University.  Based on the findings, recommendations were made that AI-driven technologies should be deployed by the management of Taraba State University Jalingo in resource allocation across all sections of the University. Deans and Heads of Departments should constantly adopt AI in creating schedule of activities for staff and also for determining workload distribution, among others.