THE INFLUENCE OF TEACHING STAFF UTILIZATION OF ARTIFICIAL INTELLIGENCE ON ACADEMIC RESEARCH METHODOLOGIES IN RIVERS STATE OWNED UNIVERSITIES

Abstract

The study investigated the influence of teaching staff utilization of artificial intelligence on academic research methodologies in Rivers State owned universities. Descriptive survey research design was adopted for the study. The population of the study consisted of all the three thousand six hundred and twenty (2, 538) lecturers in the two Rivers State owned universities. A sample of 424 teaching staff comprising of 308 from Rivers State University (RSU) and 116 from Ignatius Ajuru University of Education (IAUoE) was selected. The instrument for data collection was a self-structured questionnaire entitled: “Influence of Teaching Staff Utilization of Artificial Intelligence on Academic Research Methodologies Questionnaire. The instruments used for data collection was face and content validated by two other experts from the Department of Measurement and Evaluation of the Faculty of Education in Rivers State University. A reliability index of 0.80 was obtained through Cronbach Alpha method. The research questions posed were answered using mean and standard deviation while z-test was used to test the formulated hypotheses.  Findings of the study revealed that, teaching staff utilization of machine learning, natural language processing and data analytics influenced academic research methodologies in Rivers State owned universities. Based on the findings, the researcher made the following recommendations: teaching staff should incorporate machine learning concepts and techniques into research methodology courses to enhance students’ understanding and application of machine learning in research, teaching staff should be encouraged to use natural language processing tools and techniques to analyze and interpret text data in their research projects and teaching staff should incorporate data analytics concepts and techniques into research methodology courses to enhance students’ understanding and application of data analytics in research.