Sandra Chinyeaka Nwokocha
1
,
Kennedy Oberhiri Obohwemu,
1
,
Gordon Mabengban Yakpir
1
,
Fidelis Evwiekpamare Olori
1
,
Christian Atabong Nchindia
1
,
Charles Leyman Kachitsa
1
,
Olusunmola Osinubi
1
,
Bartholomew Ituma Aleke
1
,
Aliyuda Ali
1
,
Ibrahim Olanrewaju Lawal
1
,
Iyevhobu Oshiokhayamhe Kenneth
1
,
Oluwadamilola R. Tayo
1
,
Rupali Chauhan
1
,
Shubham Sharma
1
,
Divya Motupalli
1
,
Aung Htet Sai Bo Bo
1
,
Samuel Oluwatosin Adejuyitan
1
,
Onomuighokpo Hillary Onome
1
,
4
PhD , Faculty of Business & Tourism Management, Canterbury Christ Church University, GBS Partnership, Birmingham, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , Faculty of Health, Wellbeing & Social Care, Oxford Brookes University, GBS Partnership, Birmingham, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , Faculty of Health, Wellbeing & Social Care, Oxford Brookes University, GBS Partnership, Birmingham, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , Faculty of Business Management, Oxford Brookes University, GBS Partnership, Birmingham, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , Faculty of Business Management, University of Suffolk, GBS Partnership, Manchester, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , Faculty of Business Management and Enterprise, Leeds Trinity University, GBS Partnership, Manchester, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , Faculty of Health, Wellbeing & Social Care, Oxford Brookes University, GBS Partnership, Birmingham, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , Faculty of Health, Wellbeing & Social Care, Oxford Brookes University, GBS Partnership, Leeds, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , School of Computing and Digital Technologies, Sheffield Hallam University, Sheffield, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
PhD , Faculty of Business & Tourism Management, Canterbury Christ Church University, GBS Partnership, Birmingham, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
MPH , Department of Medical Microbiology, Faculty of Medical Laboratory Science, Ambrose Alli University, Ekpoma, Edo State, Nigeria
4
MPH , Faculty of Health, Wellbeing & Social Care, Oxford Brookes University, GBS Partnership, Leeds, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
MPH , Faculty of Health, Wellbeing & Social Care, Oxford Brookes University, GBS Partnership, Manchester, United Kingdom
4
MDS , Independent Researcher, Manchester, United Kingdom
4
MPHGH , Faculty of Health, Wellbeing & Social Care, Oxford Brookes University, GBS Partnership, Manchester, United Kingdom
4
MPH , Department of Health, Wellbeing & Social Care, Oxford Brookes University, GBS Partnership, Manchester, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
MSc , Department of Project Management, School of Computing, Engineering and Physical Sciences, University of the West of Scotland, United Kingdom; and PENKUP Research Institute, Birmingham, United Kingdom
4
MBBS , Department of Orthopaedics & Trauma, Federal Medical Centre, Asaba, Delta State, Nigeria; and PENKUP Research Institute, Birmingham, United Kingdom
Abstract
Artificial Intelligence (AI) is revolutionising higher education by generating novel opportunities for inclusive learning, skill enhancement, and equal access to information. This chapter analyses the influence of AI on higher education, emphasising its contribution to fostering diversity, improving employability skills, and mitigating gender inequities. AI-driven solutions, including adaptive learning platforms, automated feedback systems, and natural language processing technologies, provide the capability to customise the learning experience, assist students with varied needs, and enhance academic English proficiency. Moreover, AI-powered career development solutions are transforming employability training through real-time feedback, workplace simulations, and focused skill enhancement interventions. Nonetheless, whereas AI presents opportunity to bridge educational disparities, it simultaneously engenders worries about algorithmic bias, ethical dilemmas, and data privacy vulnerabilities. While reviewing literature, this chapter examines AI's capacity to enhance inclusive education while critically evaluating the dangers of unequal access and algorithmic bias. It promotes a balanced approach that emphasises human-centred education, gender equality, and preparedness for employment. The findings enhance the overarching dialogue regarding AI in education, impacting policy deliberations and institutional approaches to fostering equal learning environments in the digital era.
πAoun, J. E. (2017). Robot-proof: Higher education in the age of artificial intelligence. MIT Press.
πBaker, R., & Hawn, A. (2021). Algorithmic fairness in education: Biases, mitigation, and implications. Educational Researcher, 50(5), 297-307.
πBender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610-623
πBennett, D., Butler, P., & Green, J. (2022). AI-driven medical simulators: Improving clinical reasoning and reducing errors in medical trainees. Journal of Medical Education and Training, 45(3), 123-134. https://doi.org/10.1007/jmet.2022.6789
πBessen, J. (2019). AI and jobs: The role of demand. NBER Working Paper Series, 24235. https://doi.org/10.3386/w24235
πBinns, R. (2018). Fairness in machine learning: Lessons from political philosophy. Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency, 149-159.
πBrynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W. W. Norton & Company.
πBuchanan, T. (2021). The limitations of AI in student assessment: Balancing automation with human oversight. Journal of Educational Technology & Society, 24(4), pp.115-129. Available at: https://doi.org/10.2307/41505691 [Accessed 5 March 2025].
πBuolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Conference on Fairness, Accountability, and Transparency, 77-91.
πBurrus, J., Jackson, T., Xi, N., & Steinberg, J. (2013). Identifying the most important 21st-century workforce competencies: An analysis of the Occupational Information Network (O*NET). ETS Research Report Series, 2013(2), 1-55.
πCrawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press.
πDede, C., Richards, J., & Saxena, A. (2021). The 60-year curriculum: New models for lifelong learning in the digital economy. Routledge.
πHuang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
πHolmes, L., McElwee, G., & Palmer, M. (2021). Developing employability skills through AI: Enhancing career preparedness in a digital world. Journal of Higher Education and Employment, 34(1), 67-80. https://doi.org/10.1093/jhee.2021.0567
πHolmes, W., Bialik, M. and Fadel, C., 2022. Artificial intelligence in education: The importance of human oversight. AI and Education Journal, 33(1), pp.9-25. Available at: https://doi.org/10.1007/s10826-022-01697-2 [Accessed 5 March 2025].
πJordan, K., 2020. The role of artificial intelligence in student assessment and feedback. International Journal of Educational Technology, 9(2), pp.112-127. Available at: https://doi.org/10.1080/20424775.2020.1760781 [Accessed 5 March 2025].
πJohnson, W. L., and Valente, A. (2021). AI-driven virtual humans for soft skills training. Educational Technology Research and Development, 69(4), 927-948.
πKnox, J. (2020). Artificial intelligence and education: A critical view through the lens of human learning. Learning, Media and Technology, 45(3), 257-270.
πLazarus, A., Stern, S., and Tilly, J. (2020). Soft skills and the future of work. Brookings Institution.
πLuckin, R., Motiwalla, L., & Bradshaw, J. (2021). AI-based feedback systems in higher education: Transforming student learning and employability. Educational Technology Review, 42(5), 234-249. https://doi.org/10.1016/j.etr.2021.0234
πMakridakis, S. (2017). The forthcoming AI revolution: Its impact on society and firms. Futures, 90, 46-60.
πMolnar, A., and Wiliam, D. (2023). AI-driven simulations for developing employability skills: A transformative approach to learning. Educational Technology & Society, 26(4), 124-137. https://doi.org/10.1111/ets.2023.0479
πPopenici, S. A., and Kerr, S. (2017). Exploring the impact of AI on higher education. Research and Practice in Technology Enhanced Learning, 12(1), 1-13.
πSelwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
πShermis, M.D. and Burstein, J., 2018. Automated essay scoring: A cross-disciplinary perspective. Springer. Available at: https://doi.org/10.1007/978-3-319-98635-4 [Accessed 5 March 2025].
πWilliamson, B., & Eynon, R. (2020). Datafication and education: A critical sociological perspective on emerging trends and impacts. Learning, Media and Technology, 45(2), 117-131.
πUNESCO. (2020). Artificial intelligence and gender equality: Key findings and recommendations. Retrieved from https://unesdoc.unesco.org
πVerma, S. (2022). AI-driven career guidance and gender stereotypes: A critical review. International Journal of Educational Technology in Higher Education, 19(1), 45-63.
πWest, D., Johnson, K., & Smith, L. (2019). AI-driven career advising systems: Navigating the future of work through technology. Career Development Quarterly, 60(2), 79-92. https://doi.org/10.1002/cdq.2020.1078
πZhai, C., Xu, Q. and Liu, L., 2022. AI-powered feedback in programming education: Advancements and challenges. Computers in Education, 153, pp.76-93. Available at: https://doi.org/10.1016/j.compedu.2020.103920 [Accessed 5 March 2025].
πZhang, H., & Lu, C. (2021). AI-driven mentorship programs and female participation in STEM: A systematic review. Journal of Educational Research & Practice, 11(3), 78-95.