GENERATIVE TECHNOLOGY AND PEDAGOGICAL VALUE OF BUSINESS EDUCATION LECTURERS AS CORRELATE OF THEIR PRODUCTIVITY IN PUBLIC UNIVERSITIES IN SOUTH EAST, NIGERIA
Abstract
This study investigated generative technology and pedagogical values of business education lecturers as correlate of their productivity in public universities in South-East Nigeria. Two research questions and two null hypotheses guided the study. The correlational research design was adopted for the study. The population comprised 128 business education lecturers from public universities offering business education programme in the zone. The census sampling technique was adopted. Three structured questionnaires titled Generative Technology Questionnaire (GTQ), Pedagogical Values Questionnaire (PVQ), and Business Educators’ Productivity Questionnaire (BEPQ) were used for data collection. The instruments contained 10, 10, and 15 items respectively. Face and content validity of the instruments were established by three experts, while Cronbach Alpha reliability coefficients of 0.84, 0.86, and 0.88 were obtained for GTQ, PVQ, and BEPQ respectively. Of the 128 copies of the questionnaires administered, 119 copies representing 93% were retrieved and used for data analysis. Pearson Product Moment Correlation (PPMC) was used to answer the research questions and test the null hypotheses at 0.05 level of significance using SPSS version 26. Findings revealed that there was a high positive and significant relationship between generative technology and the productivity of Business Education lecturers in public universities in South-East Nigeria. The findings also revealed a high positive and significant relationship between pedagogical values and the productivity of Business Education lecturers in the study area. The study concluded that generative technology and pedagogical values have high positive and significant relationships with the productivity of Business Education lecturers in public universities in South-East Nigeria. It was recommended, among others, that Business Education departments should formally integrate generative AI technologies into teaching and research activities, while Business Education development programmes should emphasize pedagogical value formation to enhance lecturers’ productivity.
Keywords
Full Text:
PDFReferences
Ajadi, T. O. (2024). Potentials challenges of twenty-first century pedagogies in Nigeria. Journal of Education for Sustainable Innovation, 2(1), 64–73. https://doi.org/10.56916/jesi.v2i1.810
Ali, S., DiPaola, D., Lee, I., Sindat, V., & Kim, G. (2021). Children as creators, thinkers, and citizens in the age of generative AI. Computers and Education: Artificial Intelligence, 2, Article 100040. https://doi.org/10.1016/j.caeai.2021.100040
Anyaehie, G. K., Abraham, N. M., & Ojule, L. C. (2025). Examining the relationship between artificial intelligence and teacher productivity in private secondary schools in Rivers State using Zipgrade and Google Classroom. International Journal of Innovative Social & Science Education Research, 13(1), 219–230.
Asiimwe, K.T. (2025). Assessing the impact of professional development on teacher performance. Research Invention Journal of Research in Education, 5(1), 67–73.
Atah, C. A., & Alabi, B. E. (2025). Assessing the preparedness of business education graduates for success in a digitally-driven economy in the 21st century. IIARD International Journal of Economics and Business Management, 11(3), 267–277. https://www.iiardjournals.org
Bello, M., & Yusuf, A. (2021). Ethical leadership, institutional values and lecturers’ job performance in federal universities in Northern Nigeria. Journal of Education and Human Development, 10(2), 22–34. https://doi.org/10.15640/jehd.v10n2a3
Chiu, T. K. F. (2024). The impact of generative AI on practices, policies and research direction in education: A case of ChatGPT and Midjourney on the learning experiences of students in Hong Kong. Interactive Learning Environments, 32(10), 6187–6203. https://doi.org/10.1080/10494820.2023.2253861
Chukwu, P., & Nwankwo, L. (2021). Lecturers’ value orientation and research productivity in federal universities in South-East Nigeria. Nigerian Journal of Educational Research and Evaluation, 14(2), 112–128. https://doi.org/10.4314/njere.v14i2.112
Ezeabii, I. C., Ekoh, N. A. C., & Okwor, N. G. (2020). Challenges to the utilization of new technologies in business education programme of public universities in South East Nigeria. Nigerian Journal of Business Education (NIGJBED), 7(1), 388–400.
Federal Republic of Nigeria. (2013). National policy on education (6th ed.). Federal Ministry of Education/NERDC.
Gouia-Zarrad, R., & Gunn, C. (2024). Enhancing students’ learning experience in mathematics class through ChatGPT. International Electronic Journal of Mathematics Education, 19(3), Article em0781. https://doi.org/10.29333/iejme/14614
Hills, M. D. (2022). Understanding value orientation: A framework for analyzing cultural values. Journal of Cross-Cultural Psychology, 53(4), 456–470.
Ikeanyionwu, C. L., & Nzegwu, R. C. (2024). The role of business education in promoting innovation and entrepreneurship in Anambra State. International Journal of Innovative Education Research, 12(2), 177–182.
Ismail, F., Tan, E., Rudolph, J., Crawford, J., & Tan, T. (2023). Artificial intelligence in higher education: A critical review of assessment and pedagogical practices. Journal of Applied Learning and Teaching, 6(2), 56–63. https://doi.org/10.37074/jalt.2023.6.2.34
Karakose, T., Demirko, M., Aslan, N., Köse, H., & Yilmaz, H. (2023). A conversation with ChatGPT about the impact of the COVID-19 pandemic on education: Comparative review based on human–AI collaboration. Educational Process: International Journal, 12(3), 7–25. https://doi.org/10.1016/j.ijedudev.2023.100050
Kluckhohn, F. R., & Strodtbeck, F. L. (2020). Variations in value orientations. Row Peterson.
Korkmaz Guler, N., Dertli, Z. G., Boran, E., & Yildiz, B. (2024). An artificial intelligence application in mathematics education: Evaluating ChatGPT’s academic achievement in a mathematics exam. Pedagogical Research, 9(2), Article em0188. https://doi.org/10.29333/pr/14145
McKinsey & Company. (2021). It’s time for businesses to chart a course for reinforcement learning. https://www.mckinsey.com/capabilities/quantumblack/our-insights/its-time-for-businesses-to-chart-a-course-for-reinforcement-learning
Njoku, C. U. (2022). Business education and value orientation for national economic empowerment and development. Business Education Journal. https://www.researchgate.net
Ogunode, N. J., Jegede, D., & Abubakar, M. (2022). Problems facing academic staff of Nigerian universities and the way forward. International Journal on Integrated Education, 4(1), 230–241.
Ogwu, E. N., Emelogu, N. U., Azor, R. O., et al. (2023). Educational technology adoption in instructional delivery in the new global reality. Education and Information Technologies, 28, 1065–1080. https://doi.org/10.1007/s10639-022-11203-4
Onwuka, J., & Onwuachu, P. (2022). Lecturers’ ethical behaviour and administrative effectiveness in Nigerian public universities. Journal of Educational Review, 14(2), 55–67. https://doi.org/10.5897/JER2022.0452
Palahicky, S., Smith, J., Brown, K., & Davis, L. (2017). Exploring pedagogical values in contemporary education. Journal of Educational Philosophy, 45(3), 210–225.
Rokeach, M. (2019). The nature of human values. Free Press.
Roppertz, J. (2020). Artificial intelligence: Defining intelligence and exploring its implications for autonomous systems. Journal of AI Research, 68, 113–129.
Samara, V., & Kotsis, K. T. (2024). Use of artificial intelligence in teaching the concept of magnetism in preschool education. Journal of Digital Educational Technology, 4(2), Article ep2419. https://doi.org/10.30935/jdet/14864
Schwartz, S. H. (2021). The Schwartz theory of basic human values: Overview and applications. Springer. https://doi.org/10.1007/978-3-030-58868-2
Slagg, A. (2023). AI for teachers: Defeating burnout and boosting productivity. EdTech Magazine. https://edtechmagazine.com/k12/article/2023/11/ai-for-teachers-defeating-burnout-boosting-productivity-perfcon.com
Su, K. D. (2024). Problem-based life situational issues exploration: Taking the learning effectiveness of artificial intelligence in natural sciences. Interdisciplinary Journal of Environmental and Science Education, 20(2), Article e2406. https://doi.org/10.29333/ijese/14420
Sulaiman, T. T. (2022). Examining the influence of pedagogical beliefs on technology adoption among university lecturers. Computers & Education, 179, 104419. https://doi.org/10.1016/j.compedu.2022.104419
Tunde-Olaitan, I., & Adekunle, S. (2023). Moral values instruction and staff performance in public universities in Southwestern Nigeria: A quasi-experimental study. Journal of Educational Intervention, 5(4), 76–90. https://doi.org/10.30918/JEI.54.23.015
Ukeh, B. O., & Anih, A. A. (2024). Utilization of artificial intelligence based tools for teaching and research among lecturers in Federal University Otuoke, Bayelsa State, Nigeria. Sapientia Foundation Journal of Education, Sciences and Gender Studies (SFJESGS), 6(1), 153–159.
Umo, O.B., & Okon, E.E. (2023). Components of business education curriculum and the development of entrepreneurial skills among undergraduates in Nigerian universities. Journal of Entrepreneurship Education, 26(S5), 1-25.
Yahya, R. I. (2025). Influence of workload distribution on teaching effectiveness in business education department of federal college of education, Yola. Journal of Educational Research and Practice, 7(8), 31–42. https://doi.org/10.70382/bejerp.v7i8.008
Yakubu, C. U., Hamza, S., & Aliyu, M. M. (2022). Motivation as a determinant of business education lecturers’ productivity in colleges of education in North-Central Nigeria. Galaxy International Interdisciplinary Research Journal, 10(3), 384–396.
Refbacks
- There are currently no refbacks.
Copyright (c) 2026 Ngozika Teccla Onwu
ISSN PRINT: 2630 - 7081

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.