Adoption of Artificial Intelligence (AI) Components to Improve Entrepreneurship Study in Oyo State Tertiary Institutions, Oyo State, Nigeria

Authors

  • Salihu Abdulwaheed Adelabu Ibrahim Badamasi Babagida University, Lapia, Niger State
  • Agbaje Fausiat Olajumoke Lead City University, Ibadan
  • Oluwole Eyitayo Adewale Lead City University, Ibadan
  • Ibrahim Ojo Rasheed University of Ibadan

DOI:

https://doi.org/10.55927/ijsmr.v3i7.434

Keywords:

Entrepreneurship, AI Components, Undergraduate Students

Abstract

Studying entrepreneurship imparts a significant role for self-development, self-reliance, self-employment among others for every individual including people with special needs. Extant studies largely focused on factors influencing entrepreneurship study, with little consideration for adaptation of AI components to improve entrepreneurship study. The purpose of this study was to adopt AI components to improve entrepreneurship study. The study used descriptive of survey type as research design. The target population was undergraduate study in Oyo State Tertiary Institutions, Oyo State, Nigeria. A purposive sampling technique was used to select 1250 undergraduate students used in the study. The instruments used were standardized scales named Entrepreneurship Studies Questionnaire (r=.86), AI Checklist instrument, and Questionnaire of AI use Motives (r =.81). Four research questions were raised and answered. Data were analyzed using frequency count, simple percentage and t-test tested at 0.05 level of significant. Findings showed significant high influence of teaching and learning of entrepreneurship study with average mean (3.88) and standard deviation (0.75) while some items had no significant high mean scores. The result revealed that planning and scheduling 898(71.8%) is the most component of AI use in teaching and learning entrepreneurship study followed by knowledge representation 741 (59.3%)

References

Ahmed, S., Khalil, M. I., Chowdhury, B., Haque, R., bin S Senathirajah, A. R., and bin Omar Din,

Center and an Elaboration of the Logistics Field Within the Scope of the Department. Euroasia Journal of Social Sciences & Humanities, Vol. 10 No. 31, pp. 20-31.

Dinçel, S. 2019. Business Management and Logistics. Istanbul: Togan Publishing House

Dinçel, S. 2023. An Analysis, of the Thesis, in the Field of Logistics that Found at the YÖK Thesis

F. M. 2022. Motivators and barriers of artificial intelligent (AI) based teaching. Eurasian Journal of Educational Research, Vol. 100, pp. 74-89.

Gansser, O. A., and Reich, C. S. 2021. A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology in Society, Vol. 65, pp. 101-535.

Giray, L. 2024. Ten myths about artificial intelligence in education. Higher Learning Research Communications, Vol. 14 No. 2, pp. 1–12.

Gish, J. J., Guedes, M. J., Silva, B., and Patel, P. 2022. Latent profiles of personality, temperament, and eudaimonic well-being: Comparing life satisfaction and health outcomes among entrepreneurs and employees. Journal of Business Venturing Insights, Vol. 17, e00293.

Hmoud, M., Swaity, H., Hamad, N., Karram, O., and Daher, W. 2024. Higher Education

Implications for Entrepreneurship Research and Practice.” The Academy of Management Review Vol. 32 No. 3, pp. 747-760.

Jennings, J., and Brush, M. 2014. “Work-Family Interface Experiences and Coping Strategies:

Naqvi, A. 2020. Artificial intelligence for audit, forensic accounting, and valuation: A strategic perspective. Wiley.

Nwangwu, I. O. 2006. Fundamentals of entrepreneurship in educational management. Enugu: Cheston Agency Ltd.

Odjegba, E. 2005. “Building Nigeria’s entrepreneurship: What stakeholders say about essential ingredients”. Sunday Vanguard. July 3.

Onah, J. 2004. Empowering small and medium scale enterprises in Nigeria Enugu ECCIMA/MANAMARK Association Ltd.

Streb, C., and Gupta, V. K. 2021. Methodology of entrepreneurship research in a radical subjectivist paradigm. In Entrepreneurship, growth and economic development: Frontiers in European entrepreneurship research (pp. 262–288). Edward Elgar.

Students’ Task Motivation in the Generative Artificial Intelligence Context: The Case of ChatGPT. Information, Vol. 15 No. 1, 1-18.

Suleiman, A.S. 2006. The business entrepreneur: Entrepreneurial development, Small and medium enterprises. 2nd edition Kaduna: Entrepreneurship Academy publishing.

Torres, P., and Godinho, P. 2022. Levels of necessity of entrepreneurial ecosystems elements. Small Business Economics, Vol. 59, pp. 29–45

Wiklund, J., Davidsson, P., Audretsch, D. B., and Karlsson, C. 2011. The Future of Entrepreneurship Research. Entrepreneurship Theory and Practice, Vol. 35 No. 1, 1–9.

Wurth, B., Stam, E., & Spigel, B. 2022. Toward an entrepreneurial ecosystem research program. Entrepreneurship Theory and Practice, Vol. 46(3), pp. 729–778.

Yu J, Tang YM, Chau KY, Nazar R, Ali S, and Iqbal, W. 2021. Role of solar-based renewable energy in mitigating CO2 emissions: evidence from quantile-on-quantile estimation. Renew Energy Vol. 182, pp. 216-226.

Yurt, E. & Kasarci, I. (2024). A Questionnaire of Artificial Intelligence Use Motives: A contribution to investigating the connection between AI and motivation. International Journal of Technology in Education (IJTE), 7(2), 308-325. https://doi.org/10.46328/ijte.725

Downloads

Published

2025-07-30

Issue

Section

Articles