With the rise of AI, it has become an increasingly larger issue how educators should tackle this issue. What do teachers know about current AI tools? What is considered cheating? Should educators facilitate use or forbid it?

The current research project seeks to answer some of these questions in the context of faculty members in higher education. With expertise from AI and education researchers, we aim to explore faculty's beliefs, knowledge, experiences, and practices with artificial intelligence for teaching and learning in higher education.

The purpose is to develop knowledge about how artificial intelligence impacts teaching and learning in higher education.

Our guiding research question is:

How does Artificial Intelligence (AI) affect faculty's teaching practices in higher education?

The research project is empirical and investigates how the faculty members at the Department of Informatics (IDI) and the Department of Teacher Education (ILU) approach teaching, learning, assessing and supervision through the lens of AI. We compare the two, as we believe there might be significant differences between faculty members who specialize in AI versus those who specialize in education. We use a sequential mixed methods research design involving a quantitative and a qualitative phase.

Methods:

Building on the TPACK questionnaire (Celik, 2023) , we have an online questionnaire that will be distributed to faculty members at IDI and ILU (qualitative and quantitative data). This consists of questions related to faculty members’ knowledge, beliefs, and practices of AI. The next step will be approximately 20 semi-structured focus group interviews based on the questionnaire (qualitative analysis). We will ask in-depth questions related to practices and thoughts that were unclear in the questionnaire. Lastly, we seek to observe classroom interactions to see how and if lecturers use/refer to AI in their teaching.