Abstract
This systematic review analyzed the main barriers and solutions related to teacher training in artificial intelligence in higher education. Following the \textit{PRISMA} protocol, 428 records were identified in \textit{Scopus}, \textit{Web of Science}, \textit{ERIC}, and \textit{ScienceDirect}, from which 18 studies of high methodological quality were finally selected. The findings revealed technological, pedagogical, organizational, and ethical barriers, with particular emphasis on insufficient digital infrastructure, the lack of specific didactic strategies, and limited institutional governance. The most effective solutions included communities of practice, continuing professional development, teacher mentoring, and sustainable institutional policies. The review concludes that the integration of AI in higher education requires a systemic transformation of universities, rather than isolated technical training alone.
References
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[5] L. Chen, P. Chen and Z. Lin, “Artificial Intelligence in Education: A Review,” in IEEE Access IEEE Access, vol. 8, pp. 75264–75278, 2020, doi: 10.1109/ACCESS.2020.2988510.
[6] M. Koehler and P. Mishra, “What is Technological Pedagogical Content Knowledge (TPACK)?,” Contemporary Issues in Technology and Teacher Education, vol. 9, no. 1, pp. 60–70, 2009.
[7] A. Kirkwood and L. Price, “Technology-enhanced learning and teaching in higher education: what is ‘enhanced’ and how do we know? A critical literature review,” Learning, Media and Technology Learning, Media and Technology, vol. 39, no. 1, pp. 6–36, 2014.
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[10] V. Potocan, “Technology and Corporate Social Responsibility,” Sustainability Sustainability, vol. 13, no. 15, p. 8658, 2021, doi: 10.3390/su13158658.
[11] M. Ma, D. T. K. Ng, Z. Liu and G. K. Wong, “Fostering responsible AI literacy: A systematic review of K-12 AI ethics education,” Computers and Education: Artificial Intelligence Computers and Education: Artificial Intelligence, vol. 8, p. 100422, 2025, doi: 10.1016/j.caeai.2025.100422.
[12] S. Tlili, J. Shehata, B. Adarkwah, et al., “What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education,” Smart Learning Environments Smart Learning Environments, vol. 10, no. 15, 2023, doi: 10.1186/s40561-023-00237-x.
[13] O. Viberg, M. Hatakka, O. Bälter and A. Mavroudi, “The current landscape of learning analytics in higher education,” Computers in Human Behavior Computers in Human Behavior, vol. 89, pp. 98–110, 2018, doi: 10.1016/j.chb.2018.07.027.
[14] N. Selwyn, “Should robots replace teachers? AI and the future of education,” Polity Press Cambridge: Polity Press, 2019.
[15] R. Luckin and W. Holmes, “Intelligence unleashed: An argument for AI in education,” Pearson London: Pearson Education, 2016.
[16] UNESCO, “Guidance for generative AI in education and research,” UNESCO Paris: UNESCO Publishing, 2023.
[17] OECD, “Digital Education Outlook 2023: Towards an effective digital education ecosystem,” OECD Paris: OECD Publishing, 2023.
[18] J. Williamson and B. Eynon, “Historical threads, missing links, and future directions in AI in education,” Learning, Media and Technology Learning, Media and Technology, vol. 45, no. 3, pp. 223–235, 2020, doi: 10.1080/17439884.2020.1798995.
[19] M. Bond, V. I. Marín, C. Dolch, S. Bedenlier and O. Zawacki-Richter, “Digital transformation in German higher education,” International Journal of Educational Technology in Higher Education International Journal of Educational Technology in Higher Education, vol. 15, no. 48, 2018, doi: 10.1186/s41239-018-0130-1.
[20] P. Goodyear and L. Carvalho, “The analysis of complex learning environments,” Routledge London: Routledge, 2014.
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