119 papers
Physics explores the fundamental rules governing our universe, from the tiniest subatomic particles to the vastness of distant galaxies. This category focuses on educational physics, bridging the gap between complex theoretical concepts and clear, understandable explanations for students and enthusiasts alike. It covers how we teach, learn, and visualize the laws of nature in everyday contexts.
Gist.Science monitors arXiv daily to process every new preprint in this specific field. We transform these raw scientific manuscripts into accessible plain-language overviews alongside detailed technical summaries, ensuring that cutting-edge educational research reaches a wider audience without losing its rigor. Below are the latest papers in physics education research and related studies that have recently appeared on arXiv.
This study utilizes Computational Grounded Theory to analyze over 10 million tokens of chatbot interactions from a university Modern Physics course, successfully identifying persistent student misconceptions and reasoning patterns to demonstrate the method's potential for scaling insights in AI-driven educational research.
This paper presents Stan, a locally deployed, privacy-preserving AI system for an undergraduate thermodynamics course that utilizes open-weight models to simultaneously provide grounded, reference-backed tutoring for students and generate actionable teaching insights for instructors from a shared corpus of lecture transcripts and textbook data.
This paper presents a web-based, installation-free smartphone application that compensates for device rotation to provide global-coordinate acceleration data, enabling undergraduate students to accurately reconstruct motion trajectories and deepen their understanding of mechanics through hands-on experiments.
This bibliometric analysis of 138 Web of Science publications from 2021 to 2025 reveals that physics education is undergoing an AI-driven transformation characterized by exponential growth since 2023, a shift from traditional data analysis to generative AI and interdisciplinary applications, and a future trajectory focused on adaptive learning ecosystems and ethical AI integration.
A simple agent built on the Gemini 3.1 Pro Preview model achieved a perfect score on the IPhO 2025 theory problems, though this result may be compromised by potential data contamination due to the model's release occurring after the competition.
This paper compares three pendulum lab designs to demonstrate how differing institutional expectations, ancillary goals, and interpretations of shared theoretical commitments can lead to divergent curriculum choices, thereby highlighting the complex relationship between theory, goals, and design while advocating for transparent reasoning and responsive adaptation.
This paper presents the open-source design, construction, and operation of a high-performance, multi-link pendulum on a cart system as a flexible, reproducible benchmark for studying chaos, learning, and control in dynamical systems.
This paper argues that Newtonian mechanics can be derived directly from energy conservation without defining work, demonstrating that both special relativity and quantum theory are intrinsically Hamiltonian and suggesting that the historical progression of mechanical formulations should be reversed to prioritize the Hamiltonian approach over Newtonian and Lagrangian methods.
This paper illustrates how supporting a quantum mechanics instructor through an online community enabled him to persist with evidence-based active engagement strategies by adapting his approach to include productive struggle via graded corrections, ultimately improving student learning outcomes when the initial clicker-based method failed.
This paper presents a web-based interactive platform developed at St. Xavier's College, Kolkata, which successfully replicates physical physics laboratory setups to enhance undergraduate students' conceptual understanding and experimental confidence, as evidenced by overwhelmingly positive feedback from users.