BUSINESS EDUCATION ACADEMIC STAFF PROFICIENCY IN UTILIZING ARTIFICIAL INTELLIGENCE FOR RESEARCH DEVELOPMENT IN FEDERAL COLLEGE OF EDUCATION (TECHNICAL) UMUNZE, ANAMBRA STATE

This study examined the proficiency of Business Education academic staff in utilizing artificial intelligence (AI) for research development at the Federal College of Education (Technical), Umunze, Anambra State. Three research questions guided the study, which employed a descriptive survey research design. The population consisted of 65 Business Education lecturers at the Federal College of Education (Technical), Umunze, Anambra State. All 65 lecturers were selected as the sample using purposive sampling. A 27-item questionnaire, developed by the researcher and structured on a 4-point scale, titled 'Business Education Academic Staff Proficiency in Utilizing Artificial Intelligence (AI) for Research Development Questionnaire' (BEASPUAIRDQ), was used for data collection. The face validity of the research instrument was confirmed by two experts from the Department of Computer Science and one expert in Measurement and Evaluation from Nnamdi Azikiwe University, Awka. The reliability of the questionnaire was established through a pilot test conducted on a sample of 15 lecturers from the Nsugbe State Colleges of Education, who were not part of the main study. Scores obtained from the pilot test were analyzed using the Cronbach Alpha method, resulting in internal consistency coefficients of 0.79, 0.73, and 0.81 for the three clusters, with an overall coefficient of 0.78, indicating that the questionnaire was reliable. Data were analyzed using mean statistics, with a cut-off point of 2.50, and standard deviation statistics. The findings revealed that the Business Education lecturers were not proficient in utilizing AI for research development at the Federal College of Education (Technical), Umunze. Based on these findings, the study recommended that the leadership and management of the Federal College of Education (Technical), Umunze, should organize regular professional development workshops and other capacity-building training programs focused on enhancing the proficiency of Business Education academic staff in utilizing AI tools. These programs should also cover essential AI-driven platforms for literature sourcing (such as Google Scholar, Semantic Scholar, and others) to improve research efficiency and the quality of academic output.