most citedEvaluating GPT- and Reasoning-based Large Language Models on Physics Olympiad Problems: Surpassing Human Performance and Implications for Educational Assessment

13 citations · 13 across the 1 of their papers we have counts for

collaborators

2 papers

physics.ed-ph2025

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…

physics.ed-ph2025★ 13 cited

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…