ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: PEDAGOGICAL INNOVATION FROM A HUMANISTIC APPROACH
Keywords:
artificial intelligence, higher education, pedagogical innovationAbstract
DOI: https://doi.org/10.46296/yc.v10i18.0896
Abstract
Artificial intelligence (AI) has become increasingly prominent in higher education, fostering pedagogical innovation aimed at personalizing learning and improving access to educational resources. However, its integration also raises important challenges related to the preservation of the human dimension of the educational process. This study aims to analyze the adoption of artificial intelligence in higher education settings, examining its implications for pedagogical innovation from a humanistic perspective. A mixed-methods approach was employed, based on a case study design, involving surveys administered to 100 students and 100 faculty members, as well as semi-structured interviews with 30 participants from each group. The findings reveal a generally positive perception of AI, particularly regarding its capacity to support personalized learning. However, a notable gap emerges between the frequent use of AI tools by students and their limited integration into formal teaching practices, suggesting an uneven adoption across educational actors. Additionally, key challenges are identified, including insufficient teacher training, concerns about technological dependency, and ethical considerations related to AI implementation. The study concludes that AI can serve as a valuable resource for pedagogical innovation, provided that its integration is critically and contextually grounded. Rather than replacing human interaction, AI should be incorporated in ways that support the development of critical thinking and maintain the central role of human engagement in higher education.
Keywords: artificial intelligence, higher education, pedagogical innovation.
Downloads
References
Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33(7), 14–26.
https://doi.org/10.3102/0013189X033007014
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Knox, J., Wang, Y., & Gallagher, M. (2020). Artificial intelligence and inclusive education.
International Journal of Educational Technology in Higher Education, 17(1), 19.
https://doi.org/10.1186/s41239-020-00196-0
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., Nerdinger, F., 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, 102274.
https://doi.org/10.1016/j.lindif.2023.102274
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research. Education and Information Technologies, 27, 7893–7925. https://doi.org/10.1007/s10639-022-10925-9
Selwyn, N. (2022). Should robots replace teachers? AI and the future of education.
Polity Press.
Williamson, B. (2021). Education technology: Critical perspectives. Routledge.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education: Where are the educators? International Journal of Educational Technology in Higher Education, 16(39).
https://doi.org/10.1186/s41239-019-0171-0
Zhao, Y., Llorente, A. M. P., & Gómez, M. C. S. (2021). Digital competence in higher education: Teachers’ adoption of AI technologies. Educational Technology Research and Development, 69, 189–215. https://doi.org/10.1007/s11423-020-09830-1
Published
How to Cite
License
Copyright (c) 2026 REVISTA CIENTÍFICA MULTIDISCIPLINARIA ARBITRADA YACHASUN - ISSN: 2697-3456

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.


























