The Erosion of Core Skills in the Face of the Adoption of Artificial Intelligence in Higher Education: A Critical Reflection

Authors

DOI:

https://doi.org/10.34630/tth.v6i1.7277

Keywords:

Artificial Intelligence, Higher Education, Cognitive Development, Cognitive Substitution, Academic Integrity, Critical Thinking

Abstract

This article examines the dual nature of the impact of Artificial Intelligence on higher education, seeking to understand whether it enhances or undermines student development. On the one hand, AI offers added value by streamlining tasks and promoting critical thinking through personalised support. However, according to Carr (2010), there is a real risk of ‘cognitive substitution’ and dependency if intellectual effort is neglected, undermining academic integrity and autonomy, a risk exacerbated by the ‘hallucinations’ (Ji et al, 2023). It can be concluded that the impact of AI is not solely about the technology itself, but rather how students use it. The key to the effective use of these tools lies in changing assessment methods, focusing on critical and ethical reflection, to ensure that the student’s education and development are not compromised as a future professional.

 

References

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp.610–623). Association for Computing Machinery. https://doi.org/10.1145/3442188.3445922

Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education, 32(3), 347–364. https://doi.org/10.1007/BF00138871

Borji, A. (2023). A categorical archive of ChatGPT failures [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2302.03494

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.

Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. In S.A. Friedler & C. Wilson (Eds.), Proceedings of Machine Learning Research, 81, 1–15. https://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf

Carr, N. (2010). The shallows: What the Internet is doing to our brains. W. W. Norton & Company.

Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148

Currie, G. M. (2023). Academic integrity and artificial intelligence: Is ChatGPT hype, hero or heresy? Seminars in Nuclear Medicine, 53(5), 719–730. https://doi.org/10.1053/j.semnuclmed.2023.04.008

Dawson, P. (2020). Defending assessment security in a digital world: Preventing e-cheating and supporting academic integrity in higher education. Routledge. https://doi.org/10.4324/9780429324178

Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01

Dibek, M. I., Kursad, M. S., & Erdogan, T. (2025). Influence of artificial intelligence tools on higher order thinking skills: A meta-analysis. Interactive Learning Environments, 33(3), 2216–2238. https://doi.org/10.1080/10494820.2024.2402028

Floridi, L. (2019). The logic of information: A theory of philosophy as conceptual design. Oxford University Press. https://doi.org/10.1093/oso/9780198833635.001.0001

Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., & Fung, P. (2023). Survey of hallucination in natural language generation. ACM Computing Surveys, 55(12), Article 248. https://doi.org/10.1145/3571730

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., ... Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual. Differences, 103, Article 102274. . https://doi.org/10.1016/j.lindif.2023.102274

Kohlberg, L. (1981). The philosophy of moral development. Harper & Row.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

Matar, S. (2024). The development of educational technology and artificial intelligence and their impact on the future of education: Opportunities and risks. Journal of Posthumanism, 4(2), 417–438. https://doi.org/10.63332/joph.v4i2.2915

Mollick, E. R., & Mollick, L. (2023). Using AI to implement effective teaching strategies in classrooms: Five strategies, including prompts SSRN. http://dx.doi.org/10.2139/ssrn.4391243

Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187–192.10.1126/science.adh2586

Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors, 39(2), 230–253. https://doi.org/10.1518/001872097778543886

Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press. https://doi.org/10.47328/rpv.v12i3.16088

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4

Vygotsky, L.S. (1978). Mind in society: Development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4

Wang, H., Dang, A., Wu, Z., & Mac, S. (2024). Generative AI in Higher Education: Seeing ChatGPT Through Universities’ Policies, Resources, and Guidelines. (arXiv:2312.05235). (arXiv)https://doi.org/10.48550/arXiv.2312.05235

Williams, R. T. (2024). The ethical implications of using generative chatbots in higher education. Frontiers in Education, 8. 1331607. https://doi.org/10.3389/feduc.2023.1331607

Yeo, M. A. (2023). Academic integrity in the age of Artificial Intelligence (AI) authoring apps. TESOL Journal, 14(3), e716.

Zou, X., Su, P., Li, L., & Fu, P. (2024). AI-generated content tools and students’ critical thinking: Insights from a Chinese university. IFLA Journal, 50(2), 228-241. https://doi.org/10.1002/tesj.716

Zuboff, S. (2019). The age of surveillance capitalism: the fight for a human future at the new frontier of power. PublicAffairs.

Published

2026-07:-27

How to Cite

Santos , F. (2026). The Erosion of Core Skills in the Face of the Adoption of Artificial Intelligence in Higher Education: A Critical Reflection. The Trends Hub, Revista De Tendências Em Comunicação E Ciências Empresariais, 6(1). https://doi.org/10.34630/tth.v6i1.7277