The increasing integration of generative Artificial Intelligence (AI) tools in higher education raises essential questions about how students engage with content, regulate their learning, and develop critical thinking skills in AI-augmented environments. This paper presents results from the second phase of a longitudinal, quasi-experimental study conducted in a dual study program in Germany. The first phase (N = 93) quantitatively examined the impact of AI-supported learning on knowledge gain, motivation, cognitive load, critical thinking, and reflective use across three measurement points (T1, T2, T3) conducted throughout the semester. These findings provided the empirical foundation for the second phase. In phase two, a particular focus was placed on prompting behaviour as a potential behavioural indicator of underlying learning processes. At mid-semester (T2), one intervention group (N = 32) was systematically observed with regard to prompt behaviour, frequency, preferred AI use-cases, and whether outputs were revised or adopted directly. These variables were descriptively analysed and explored in relation to the findings from phase one. Preliminary patterns suggest that prompting behaviour may be meaningfully associated with deeper learning dynamics, including motivation, critical engagement, and over-reliance on AI tools. Students who revised AI outputs more frequently also tended to score higher in critical thinking and reflective use. These findings highlight prompting behaviour as a meaningful indicator of student critical engagement with AI and self-regulated learning.

Authors:
Chrysanthi Melanou, Freiburg University of Education, Germany

About the Presenter(s)
Chrysanthi Melanou is a research associate at DHBW and a PhD student at Freiburg University of Education, specializing in AI in Higher Education. She leads research projects and studies on AI chatbots and their didactic integration in academia.

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