APPLICATION OF ARTIFICIAL INTELLIGENCE (AI) TOOLS FOR TEACHING ENTREPRENEURSHIP PRACTICE IN NIGERIA

Yoromar Jennifer Gbogbor (PhD)

Abstract


This paper discussed the application of Artificial Intelligence (AI) tools for teaching Entrepreneurship Practice in Nigeria. The paper defined Artificial intelligence (AI), as the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Entrepreneurship practice is gaining wide momentum among the programme of studies in tertiary institutions in Nigeria and all over the entire globe. Since entrepreneurship practice entails the acquisition of skills and competencies to meet up with today’s technological and digital demands in the industry and economic landscape, there is urgent need to deploy Artificial Intelligence (AI) tools to teach students undergoing studies in Entrepreneurship Practice for them to be fit in the present dynamic world of work. The paper identified some AI tools like ChatGPT4, Google Bard, Chatsonic Midjourney, DALL-E, SlidesAI, Alli AI, Hotspot Free AI. Content Writer, Paradox, Synthesia and other various Artificial Intelligence Tools and how they are applied to enhance the teaching and learning of Entrepreneurship Practice in Nigeria. Some benefits of using Artificial Intelligence Tools to teach Entrepreneurship Practice like the provision of specific tasks and intelligent decision support through automated data integration, improving clarity and simplicity for participants were identified in the paper. The paper established that the degree of reference of participants to AI decisions making is proportional to the complexity of the task. The paper concluded that since there is astronomical shift from manual ways of conducting businesses all over the world, emphasis must be shifted to train students with the right tools to make them fit into the demands of industries. It was recommended among others that government should deploy sufficient funds to drive Artificial Intelligence gathering in our tertiary institutions in Nigeria to curb the wave of unemployment.

Key words: Application, Artificial Intelligence, Artificial Intelligence Tools, Teaching, Entrepreneurship Practice.


Full Text:

PDF

References


Antonenko, P. and Abramowitz, B. (2023). In-service teachers’ (mis) conceptions of artificial intelligence in K-12 science education. Journal of Research on Technology in Education, 55(1), 64-78. https://doi.org/10.1080/15391523.2022.2119450.

Ashton, K. (2009). That ‘Internet of things’ thing. RFID Journal, 22(7), 97-114.

Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier, S. and MacIntyre, B. (2001). Recent advances in augmented reality. IEEE Computer Graphics and Applications, 21(6), 34-47.

Al-Zyoud, H.M.M. (2020). The role of artificial intelligence in teacher professional development.

Universal. Journal of Educational Research, 8(11B), 6263-6272. https://doi.org/10.13189/ujer.2020.082265.

Chassignol, H., Koedinger, K.R. and Junker, B. (2018). Is over practice necessary? - Improving learning efficiency with the cognitive tutor through educational data mining. In: R. Luckin, K.R. Koedinger and J.E. Greer, eds. 2007. Frontiers in Artificial Intelligence and Applications. 6(3), 511-518.

Chalmers, D., MacKenzie, N.G. and Carter, S. (2021), “AI and entrepreneurship: implications for venture creation in the fourth industrial revolution”, Entrepreneurship theory and practice, 45 (5), 1028- 1053.

Chen, L., Chen, P. and Lin, Z. (2020). Artificial intelligence in education: A Review. IEEE Access, 8(5), 75264-75278. https://doi.org/10.1109/ACCESS.2020.2988510.

Chiu, T., Xia, Q., Zhou, X., Chai, C.S. and Cheng, M., (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4(1), 553-570. https://doi.org/10.1016/j.caeai.2022.100118.

Crescenzi-Lanna, L. (2023). Literature review of the reciprocal value of artificial and human intelligence in early childhood education. Journal of Research on Technology in Education, 55(1), 21-33. https://doi.org/10.1080/15391523. 2022.2128480.

Cope, B., Kalantzis, M. and Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229- 1245. https://doi.org/10.1080/00131857. 2020.1728732.

Crompton, H., Jones, M. and Burke, D. (2022). Affordances and challenges of artificial intelligence in K- 12 education: a systematic review. Journal of Research on Technology in Education, 4(3), 992- 1005. https://doi.org/10.1080/15391523.2022.2121344.

Das, S., Dey, A., Pal, A. and Roy, N. (2015). Applications of artificial intelligence in machine learning: review and prospect. International. Journal of Computer Applications, 115(9), 31-41. https://doi.org/10.5120/20182-2402.

Dinhand, T.N. and Thai, M.T. (2018), “AI and blockchain: A disruptive integration”. Journal of Computer Languages, 51(9), 48-63.

Elhajjar, X., Karam, S. and Borna, S. (2021). Artificial intelligence in marketing education programs.

Marketing Education Review, 31(1), 2-13. https://doi.org/10.1080/10528008.2020.1835492 Elia, G., Margherita, A. and Passiante, G. (2020), “Digital entrepreneurship ecosystem: how digital

technologies and collective intelligence are reshaping the entrepreneurial process”,

Technological Forecasting and Social Change, 150(7), 149-163.

French, A.M., Shim, J.P., Risius, M. and Jain, H.K. (2021). The 4th industrial revolution powered by the integration of 5G, AI, and blockchain. Communications of the Association for Information Systems, 49(6) 55-70.

Hopcan, S., Polat, E., Ozturk, M.E. and Ozturk, L. (2022). Artificial intelligence in special education: a systematic review. Interactive Learning Environments, 12(3), 32-50

https://doi.org/10.1080/10494820.2022.2067186.

Han, J.W., Park, J. and Lee, H. (2022). Analysis of the effect of an artificial intelligence chatbot educational program on non-face-to-face classes: a quasi-experimental study. BMC Medical Education, 22(8), 1-10. https://doi.org/10.1186/s12909-022-03898-3.

Iansiti, M. and Lakhani, K. (2020), Competing in the age of AI: Strategy and leadership when Algorithms and Networks Run the World, Harvard Business Review Press.

Khosravi, H., Shum, S.B., Chen, G., Conati, C., Tsai, Y.S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S. and Gasevic, D. (2022). Explainable artificial intelligence in education. Computers and Education: Artificial Intelligence, 3(4), 1-22. https://doi.org/10.1016/j.caeai.2022.100074.

Krause, T. Scholz, D., Stiegeier, D. and Bauman, M. (2020). The more you know: Trust dynamics and calibration in highly automated driving and the effects of take-overs, system malfunction, and system transparency. Human factors, 62(5),718-736, 10.1177/0018720819853686.

Ley, T., Tammets, K., Pishtari, G., Chejara, P., Kasepalu, R., Khalil, M., Saar, M., Tuvi, I., Väljataga, T. and Wasson, B., (2023). Towards a partnership of teachers and intelligent learning technology: A systematic literature review of model‐based learning analytics. Journal of Computer Assisted Learning, 3(9), 1397-1417. https://doi.org/ 10.1111/jcal.12844.

Lasi, H., Fettke, P., Kemper, H.G., Feld, T. and Hoffmann. (2014). Industry 4.0. Business and Information

Systems Engineering, 6(4), 239-242.

Liz, P (2016). Artificial intelligence in Music Education. International Journal of Human-Computer Interaction, 4(3), 122-135) https://doi.org/10.1080/10447318.2023. 2209984.

Maki, N. (2021). Implementation of adaptive learning at higher education institutions by means of Moodle LMS. Journal of Physics: Conference Series, 4(5), 1-13. https://doi.org/10.1088/1742- 6596/1840/1/012062.

Martin, O and David, B. A. (2020). “Artificial intelligence and big data in entrepreneurship: a new era has begun “Small Business Economics, Spinger, 55(3),529-539.

Murray, T. (2019). Authoring intelligent tutoring systems: an analysis of the state of the art. International Journal of Artificial Intelligence in Education, 3(10), 98-129.

McGrath, C., Pargman, T.C., Juth, N. and Palmgren, P. (2023). University teachers’ perceptions of responsibility and artificial intelligence in higher education – An experimental philosophical study. Computers and Education: Artificial Intelligence, 2(4), 1-9.

https://doi.org/10.1016/j.caeai.2023.100139.

Meziane, F., Vadera, S., Kobbacy, K. and Proudlove, N. (2014). Intelligent systems in manufacturing: current developments and future prospects. Integrated Manufacturing Systems, 11(4), 218-238. Matzavela, V. and Alepis, E. (2021). Decision tree learning through a Predictive Model for Student Academic Performance in Intelligent M-Learning Environments. Computers and Education:

Artificial Intelligence, 4(2), 1-12. https://doi.org/10.1016/j.caeai.2021.100035.

Nuseir, M., Basheer, M.F. and Aljumah, A. (2020). Antecedents of entrepreneurial intentions in smart city of Neom Saudi Arabia: Does the entrepreneurial education on artificial intelligence matter?. Cogent Business and Management, 7(1), 1-16.

https://doi.org/10.1080/23311975.2020.1825041.

Oztemel, E. and Gursev, S. (2018). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(1), 127-182.

Obschonka, M., Lee, N., Rodr_ıguez-Pose, A., Eichstaedt, J.C. and Ebert, T. (2020). Big data methods, social media, and the psychology of entrepreneurial regions: capturing cross-county personality traits and their impact on entrepreneurship in the USA. Small Business Economics, 55(3), 567- 588.

Ouyang, F. and Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 3(2), 1-6. https://doi.org/10.1016/j.caeai.2021.100020.

Ouyang, F., Zheng, L. and Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(4), 7893-7925. https://doi.org/10.1007/s10639-022-10925-9.

Sahu, C.K., Young, C. and Rai, R. (2020). Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review. International Journal of Production Research. 59(16), 4903-4959.

Southwart, A, Christodoulou, P, Doitsidis, L. and Chatzichristofis, S.A. (2023). Computer vision meets educational robotics. Electronics, 10(6), 1-24. https://doi.org/10.3390/electronics10060730.

Treiblmaier, H. (2018). The impact of the blockchain on the supply chain: a theory-based research framework and a call for action. Supply Chain Management, 23(6), 545-559.

Tinio, E., (2019). Adaptive learning: An innovative method for online teaching and learning. The Journal of Extension, 56(5), 1-8. https://doi.org/10.34068/joe.56.05.17.

Tan, V. O (2020). Applied logistic regression. 3rd ed.: Wiley. AE

Yang, M., Khoroshavin, A., Klimova, A. and Bilyatdinova, A. (2022). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 7(3), 16-24.

https://doi.org/10.1016/j.procs.2018.08.233.

Zhang, D. L & Aslan, T. M. (2021). An educational robot system of visual question answering for preschoolers. In: s.n. The 2017 2nd International Conference on Robotics and Automation Engineering, (ICRAE). 3(2), 29-41.


Refbacks

  • There are currently no refbacks.