Since the introduction of ChatGPT in November 2022, higher education institutions and educators have been exploring the role of Generative AI (GenAI) in education. With its ability to produce human-like content, such as text and images, and imitate human abilities and skills, GenAI is viewed as both a disruptor of the status quo in education but also a catalyst for rethinking teaching and learning (Jensen, Buhl, Sharma, & Bearman, 2024). While researchers acknowledge GenAI's potential to enhance education, they also recognize its capacity to negatively affect student learning (Kasneci et al., 2023). Unlike previous educational technologies, which were often slow to be adopted (Liu et al., 2020), GenAI stands out due to its accessibility, adaptability, and widespread societal impact. As a result, GenAI is already reshaping the educational landscape and will continue to do so in the future.
In a series of studies, we focus on two key areas: (1) educators’ and students’ AI literacy, perceptions, and experiences, and (2) the impact of GenAI tools within learning environments. These studies aim to shed light on the competencies and skills that both educators and students need to develop, as well as how didactics must be rethought in times of GenAI.
In research field 1, we focus on:
In research field 2, we focus on:
The studies apply a wide range of methodological approaches to explore how teaching and learning must be rethought in times of GenAI, including cross-sectional survey designs, experimental or quasi-experimental designs. In addition to traditional qualitative and quantitative methods, the studies incorporate innovative methodologies, such as Natural Language Processing and GenAI-supported qualitative analyses, to further investigate their potential applicability in educational research.
The studies will contribute to the responsible adoption of generative AI in education by providing educators with research-based insights into how GenAI tools can be meaningfully integrated into teaching and learning practices. They will offer guidance on the competencies and skills required by both educators and students in the era of GenAI, supporting the rethinking of established pedagogical approaches. In addition, the studies will explore the potential of AI-based methods to advance educational research itself. Overall, this research aims to support informed and responsible decision-making about the future of education in an increasingly AI-driven world.
Prilop, C. N., Mah, D.-K., Jacobsen, L. J., Hansen, R. R., Weber, K. E., & Hoya, F. (2025). Generative AI in teacher education: Educators’ perceptions of transformative potentials and the triadic nature of AI literacy explored through AI-enhanced methods. Computers and Education: Artificial Intelligence, 6, 100471. https://doi.org/10.1016/j.caeai.2025.100471
Prilop, C. N., Rotsaert, T., & Vanderlinde, R. (2025). Fostering pre-service teachers’ classroom management knowledge, self-efficacy, and professional vision: The effect of different expert feedback and pre-service teachers' feedback perceptions during online video analysis. Teaching and Teacher Education, 157, 104949. https://doi.org/10.1016/j.tate.2025.104949
Hansen, R. R., Hougaard, R. F., Lindberg, A. B., Møller, K. L., Nielsen, T. A., & Prilop, C. N. (2025). The effects of an AI feedback coach on peer feedback composition, quality, and experience. Læring og Medier, 17(31). https://doi.org/10.7146/lom.v17i31.148831
Dalsgaard, C., & Prilop, C. N. (2025). Partnerskaber mellem elever og AI: Nye arbejdsmetoder med generativ AI. Læring og Medier, 17(31), 1-30. https://doi.org/10.7146/lom.v17i31.150410 (English version: https://doi.org/10.31219/osf.io/zcm6p_v1)
Jacobsen, L. J., Weber, K. E., Prilop, C. N., Huang, Y., Geske, A., & Richter, E. (2025). Enabling peer feedback in teacher education: the use of virtual reality-based microteaching. Journal of Educational Computing Research, 0(0). https://doi.org/10.1177/07356331251390698
