BUSINESS EDUCATION ACADEMIC STAFF PROFICIENCY IN UTILIZING ARTIFICIAL INTELLIGENCE FOR RESEARCH DEVELOPMENT IN FEDERAL COLLEGE OF EDUCATION (TECHNICAL) UMUNZE, ANAMBRA STATE
Abstract
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.
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References
Bassey, A.&Ekong, M. (2020). AI proficiency in data analysis among academic staff in Nigerian colleges of education. Nigerian Journal of Educational Research and Evaluation, 8(2), 55-70.
Brown, A. (2021). Mastering skills in education: An overview. Sage Publications.
Day, N. (2021). Supporting research development in higher education. Springer.
Eze, J., Chinedu, P., &Agwu, C. (2021). The use of AI tools for data analysis in Nigerian higher education institutions. Journal of Educational Research, 11(1), 23-36.
Goodfellow, I., Bengio, Y.&Courville, A. (2018). Deep learning. MIT Press.
Jones, T.& Taylor, P. (2020). Resource management in education: Best practices for utilization. Sage Publications.
Nguyen, T. (2021). Artificial intelligence in data analysis for academic research: A guide for educators. London, UK: Academic Press.
Nwachukwu, C. (2020). Business education in the 21st century: Challenges and prospects. Oxford University Press.
Nworgu, B.G. (2015). Educational research. Basic issues and methodology. Enugu: University Trust Publishers.
Obanya, P. (2020). Education and the future of teacher training in Africa. University of Ibadan Press.
Okon, A.&Essien, A. (2019). Digital tools and AI use in higher education research: A case study in Southern Nigeria. Journal of Academic Research in Education, 7(4), 101-119.
Olawale, I.& Yusuf, A. (2021). Advances in business education: A contemporary perspective. Springer.
Osuji, U. (2021). Teacher education and professional development in Africa. Palgrave Macmillan.
Oxford Dictionary (2022). Proficiency. Oxford University Press.
Oyelade, O., Oladipupo, O.&Obagbuwa, I. (2020). Proficiency in AI-powered literature sourcing among academic staff in Nigerian universities. Journal of Education and Practice, 11(2), 78-86.
Russell, S.&Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
Salman, R.& Ahmed, I. (2020). AI’s impact on research methodologies in higher education. Advances in Educational Research and Development, 14(3), 66-79.
Salman, R. (2020). AI-enhanced literature review techniques in higher education research. Routledge, New York, NY.
Schmidt, A.& Wagner, H. (2019). The role of artificial intelligence in shaping research methodologies. Springer, Berlin, Germany.
Whetten, D.& Cameron, K. (2019). Developing management skills (10th ed.). Pearson.
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