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 paper describes a graduate-level course designed to help empirically-focused biology students overcome mathematical barriers and better understand theoretical biology through evidence-based teaching strategies, ultimately fostering a more productive dialogue between theory and empirical science.
This study demonstrates that while AI-supported data analysis using a custom chatbot yields cognitive learning outcomes comparable to traditional Excel methods for student teachers in physics, it significantly enhances their engagement, enjoyment, and perceived effectiveness, thereby boosting motivation and reducing stress.
Using latent profile analysis on a large multi-institutional dataset, this study reveals that physics lab critical thinking consists of two distinct multidimensional profiles with significant instructional shifts, and identifies belonging as the primary upstream predictor of both these performance profiles and students' affective development, including recognition, self-efficacy, and agency.
This study demonstrates that scalable, real-time AI-generated physics practice can be effectively validated using a streamlined set of automated structural and learner-visible checks, rather than exhaustive scoring, to ensure both technical soundness and student engagement.
This study demonstrates that an inquiry-based tutorial on the method of images effectively improves physics students' learning gains and problem-solving skills, while also revealing that instructor framing significantly influences student engagement and performance.
This paper outlines the transformative potential of multimodal astronomy by reflecting on the "Unseen Astronomy" session at the 2025 UK National Astronomy Meeting, which highlighted novel projects using non-visual methods for education, communication, and research while emphasizing community building and broader impact.
This study identifies and categorizes the specific experimental skills required for bachelor's-level positions in the quantum information science industry through interviews with professionals, offering educators concrete learning goals to better align undergraduate curricula with career needs.
This paper presents AI4CHEM, an accessible, web-based introductory course designed to equip synthetic chemistry students with no prior programming experience with essential data science and AI skills through chemistry-specific examples and hands-on projects.
This paper challenges the assumption of time invariance in large language model performance by demonstrating through a longitudinal study of GPT-4o that its output quality exhibits significant daily and weekly periodic variability, accounting for approximately 20% of total variance.
This paper presents training materials and resources developed by the HEP Software Foundation to equip physicists with Apptainer containerization skills, thereby enhancing the reproducibility, portability, and collaboration of High Energy and Nuclear Physics analyses.