ETHICAL CONSIDERATION FOR INTEGRATION OF ARTIFICIAL INTELLIGENCE IN BUSINESS EDUCATION CURRICULUM DEVELOPMENT IN TERTIARY INSTITUTIONS IN BAUCHI STATE
Abstract
This study determined ethical consideration for integration of Artificial Intelligence in business education curriculum development in tertiary institutions in Bauchi state of Nigeria. The study employed a cross-sectional research design, the population of the study comprised 104 business educators, total population sample was used. Structured questionnaire was used as the instrument for data collection which was validated by experts. The reliability of the instrument obtained was 0.82. Data was analyzed using simple linear regression. The findings revealed that there is no significant relationship between AI bias and fairness, data privacy and policy and ethical students‟ data usage ethical consideration and business education curriculum development in tertiary institutions in Bauchi state. The study concluded that AI can improve educational outcomes in Business education programme when it is integrated, developed and implemented with transparency and ethical considerations in the curriculum. It was recommended that the tertiary institutions should establish and enforce comprehensive ethical guidelines with respect to how AI is used within educational settings, more so regarding the ethical use of AI bias and fairness, data privacy and policy, and ethical students‟ data usage in business education curriculum development for and integrity in business education programme.
Keywords: Ethics, Artificial Intelligence, Business Education, Curriculum Development.
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Ahmad, K., Iqbal, W., El-Hassan, A., Qadir, J., Benhaddou, D., Ayyash, M., & Al-Fuqaha, A. (2023). Data-driven artificial intelligence in education: A comprehensive review. IEEE Transactions on Learning Technologies.
Al-Zahrani, A. M. (2024). Unveiling the shadows: Beyond the hype of AI in education. Heliyon, 10(9).
Ayeni, O. O., Al Hamad, N. M., Chisom, O. N., Osawaru, B., & Adewusi, O. E. (2024). AI in education: A review of personalized learning and educational technology. GSC Advanced Research and Reviews, 18(2), 261-271.
Borenstein, J., & Howard, A. (2021). Emerging challenges in AI and the need for AI ethics education. AI and Ethics, 1, 61-65.
Bulathwela, S., Pérez-Ortiz, M., Holloway, C., Cukurova, M., & Shawe-Taylor, J. (2024). Artificial intelligence alone will not democratise education: On educational inequality, techno- solutionism and inclusive tools. Sustainability, 16(2), 781.
Cantú-Ortiz, F. J., Galeano Sánchez, N., Garrido, L., Terashima-Marin, H., & Brena, R. F. (2020). An artificial intelligence educational strategy for the digital transformation. International Journal on Interactive Design and Manufacturing (IJIDeM), 14, 1195-1209.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. Ieee Access, 8, 75264-75278.
Cheong, B. C. (2024). Transparency and accountability in AI systems: safeguarding wellbeing in the age of algorithmic decision-making. Frontiers in Human Dynamics, 6, 1421273.
Chinta, S. V., Wang, Z., Yin, Z., Hoang, N., Gonzalez, M., Quy, T. L., & Zhang, W. (2024). FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applications. arXiv preprint arXiv:2407.18745.
Deci, E. L., & Ryan, R. M. (1985). Self-determination theory. Handbook of theories of social psychology, 1(20), 416-436.
Díaz-Rodríguez, N., Del Ser, J., Coeckelbergh, M., de Prado, M. L., Herrera-Viedma, E., & Herrera, F. (2023). Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation. Information Fusion, 99, 101896.
Grimmelikhuijsen, S. (2023). Explaining why the computer says no: Algorithmic transparency affects the perceived trustworthiness of automated decision‐making. Public Administration Review, 83(2), 241-262.
Igbokwe, I. C. (2023). Application of artificial intelligence (AI) in educational management. International Journal of Scientific and Research Publications, 13(3), 300- 307.
Kayyali, M. (2024). Future possibilities and challenges of AI in education. In Transforming education with generative AI: Prompt engineering and synthetic content creation (pp. 118-137). IGI Global.
Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y. S., Kay, J., ... &Gašević, D. (2022). Explainable artificial intelligence in education. Computers and Education: Artificial Intelligence, 3, 100074.
Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., ... & Tsai, C. C. (2020). Challenges and future directions of big data and artificial intelligence in education. Frontiers in psychology, 11, 580820.
Mouawad, G. P. (2020). Students‟ Privacy in a Digital Age (Doctoral dissertation, University of La Verne).
Mupaikwa, E. (2023). The Use of Artificial Intelligence in Education: Applications, Challenges, and the Way Forward. In Emerging Technology-Based Services and Systems in Libraries, Educational Institutions, and Non-Profit Organizations (pp. 26-50). IGI Global.
Mutiga, A. N. (2024, July). AI in Education: Mapping NIST AI Biases to Understand and Mitigate them in Teaching and Learning Applications. In EdMedia+ Innovate Learning (pp. 248- 257). Association for the Advancement of Computing in Education (AACE).
Olateju, O., Okon, S. U., Olaniyi, O. O., Samuel-Okon, A. D., &Asonze, C. U. (2024). Exploring the concept of explainable AI and developing information governance standards for enhancing trust and transparency in handling customer data. Available at SSRN.
Oluyemisi, O. M. (2023). Impact of Artificial intelligence in Curriculum Development in Nigerian Tertiary Education. International Journal of Educational Research, 12(2), 192-211.
Omrani, N., Rivieccio, G., Fiore, U., Schiavone, F., & Agreda, S. G. (2022). To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts. Technological Forecasting and Social Change, 181, 121763.
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development.
Porayska-Pomsta, K., & Rajendran, G. (2019). Accountability in human and artificial intelligence decision-making as the basis for diversity and educational inclusion. Artificial intelligence and inclusive education: Speculative futures and emerging practices, 39-59.
Reidenberg, J. R., & Schaub, F. (2018). Achieving big data privacy in education. Theory and Research in Education, 16(3), 263-279.
Saaida, M. B. (2023). AI-Driven transformations in higher education: Opportunities and challenges. International Journal of Educational Research and Studies, 5(1), 29-36.
Selvyn, N. (2019). Education and Artificial intelligence; an introduction. City press
Schwartz, R., Schwartz, R., Vassilev, A., Greene, K., Perine, L., Burt, A., & Hall, P. (2022). Towards a standard for identifying and managing bias in artificial intelligence (Vol. 3, p. 00). US Department of Commerce, National Institute of Standards and Technology.
Shiohira, K. (2021). Understanding the Impact of Artificial Intelligence on Skills Development. Education 2030. UNESCO-UNEVOC International Centre for Technical and Vocational Education and Training.
Stine, J., Trumbore, A., Woll, T., & Sambucetti, H. (2019). Implications of artificial intelligence on business schools and lifelong learning. Final Report at Academic Leadership Group.
Vinichenko, M. V., Melnichuk, A. V., & Karácsony, P. (2020). Technologies of improving the university efficiency by using artificial intelligence: Motivational aspect. Entrepreneurship and sustainability issues, 7(4), 2696.
UNESCO. (2020).The feature of education; how can enhance teaching and learning. Journal of education data and mining. 10 (2).
Vistorte, A. O. R., Deroncele-Acosta, A., Ayala, J. L. M., Barrasa, A., López-Granero, C., & Martí- González, M. (2024). Integrating artificial intelligence to assess emotions in learning environments: a systematic literature review. Frontiers in Psychology, 15, 1387089.
Wischmeyer, T. (2020). Artificial intelligence and transparency: opening the black box. Regulating artificial intelligence, 75-101.
World Economic Forum (2019). Impact of AI on education. Report
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