13 citations · 15 across the 2 of their papers we have counts for
4 papers
Combining heavy-tailed keystroke dynamics with eye tracking reveals temporal flexibility in human problem solving
Yavuz Dinc, Fabian Kieser, Peter Wulff +5
Human problem solving unfolds through complex temporal dynamics that reflect the coordination of perception, cognition, and action. The fine structure of this process is still not…
Developing an LLM-Based Feedback System Grounded in Evidence-Centered Design to Support Physics Problem Solving
Holger Maus, Fabian Kieser, Stefan Petersen +2
Generative AI offers new opportunities for individualized and adaptive learning, e.g., through large language model (LLM)-based feedback systems. While LLMs can produce factually c…
Evaluating GPT- and Reasoning-based Large Language Models on Physics Olympiad Problems: Surpassing Human Performance and Implications for Educational Assessment
Paul Tschisgale, Holger Maus, Fabian Kieser +3
Large language models (LLMs) are now widely accessible, reaching learners at all educational levels. This development has raised concerns that their use may circumvent essential le…
Educational data augmentation in physics education research using ChatGPT
Fabian Kieser, Peter Wulff, Jochen Kuhn +1
Generative AI technologies such as large language models show novel potentials to enhance educational research. For example, generative large language models were shown to be capab…