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As students pursue a bachelor's degree in physics, they may ponder over which area to specialize in, such as theory, computation, or experiment. Often students develop preferences and dislikes, but it's unclear when this preference…

Physics Education · Physics 2023-06-28 Dina Zohrabi Alaee , Keegan Shea Tonry , Benjamin M. Zwickl

Expert problem solvers are characterized by continuous evaluation of their progress towards a solution. One characteristic of expertise is self-diagnosis directed towards elaboration of the solvers' conceptual understanding, knowledge…

Physics Education · Physics 2016-03-11 Andrew Mason , Elisheva Cohen , Edit Yerushalmi , Chandralekha Singh

Humans have long relied on visual aids like sketches and diagrams to support reasoning and problem-solving. Visual tools, like auxiliary lines in geometry or graphs in calculus, are essential for understanding complex ideas. However, many…

Human-Computer Interaction · Computer Science 2025-04-03 Steven-Shine Chen , Jimin Lee , Paul Pu Liang

Many real-world networks exhibit correlations between the node degrees. For instance, in social networks nodes tend to connect to nodes of similar degree. Conversely, in biological and technological networks, high-degree nodes tend to be…

Discrete Mathematics · Computer Science 2015-09-30 Kevin E. Bassler , Charo I. Del Genio , Péter L. Erdős , István Miklós , Zoltán Toroczkai

Many recent prompting strategies for large language models (LLMs) query the model multiple times sequentially -- first to produce intermediate results and then the final answer. However, using these methods, both decoder and model are…

Computation and Language · Computer Science 2023-11-10 Luca Beurer-Kellner , Mark Niklas Müller , Marc Fischer , Martin Vechev

Diagrammatic reasoning (DR) is pervasive in human problem solving as a powerful adjunct to symbolic reasoning based on language-like representations. The research reported in this paper is a contribution to building a general purpose DR…

Artificial Intelligence · Computer Science 2014-01-17 Bonny Banerjee , B. Chandrasekaran

Framing affects how students interpret, approach, and accomplish tasks. Little is known, however, about how students frame tasks in physics labs. During the first lab of a sequence designed to teach students about modeling and critical…

Physics Education · Physics 2019-06-28 Emily M. Smith , Martin M. Stein , N. G. Holmes

In recent years, graph prompting has emerged as a promising research direction, enabling the learning of additional tokens or subgraphs appended to the original graphs without requiring retraining of pre-trained graph models across various…

Machine Learning · Computer Science 2025-05-28 Qunzhong Wang , Xiangguo Sun , Hong Cheng

I present a scheme of drawing causal diagrams based on physically motivated mathematical models expressed in terms of temporal differential equations. They provide a means of better understanding the processes and causal relationships…

Classical Physics · Physics 2015-09-07 Paul Kinsler

[Taken from the "README" in the book] My goal with this book is to provide some kind of bridge for mathematics between the high-school-level and college-level for physics students. From my perspective, our job as physicists is to observe…

Physics Education · Physics 2018-05-31 William J. Meese

Integrating computation into physics teaching is a curricular move that, at present, has been predominately studied for its cognitive impacts. However, if this modality of instruction shifts how students engage with physics, we argue there…

Physics Education · Physics 2026-01-16 Sarah McHale , Tor Ole B. Odden , Ken Heller

Recent advances in video generation models have sparked interest in world models capable of simulating realistic environments. While navigation has been well-explored, physically meaningful interactions that mimic real-world forces remain…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Nate Gillman , Charles Herrmann , Michael Freeman , Daksh Aggarwal , Evan Luo , Deqing Sun , Chen Sun

We all are fascinated by the phenomena of intelligent behavior, as generated both by our own brains and by the brains of other animals. As physicists we would like to understand if there are some general principles that govern the structure…

Biological Physics · Physics 2007-05-23 William Bialek

Two algorithms are presented for "compiling" influence diagrams into a set of simple decision rules. These decision rules define simple-to-execute, complete, consistent, and near-optimal decision procedures. These compilation algorithms can…

Artificial Intelligence · Computer Science 2013-03-08 Paul E. Lehner , Azar Sadigh

Single particle models are sufficient for many topics in introductory physics courses, but become misleading when applied to situations involving changes in internal energy. This paper merges two parallel attempts to reform the teaching of…

Physics Education · Physics 2007-06-29 Matthew L. Greenwolfe

Recently, physics informed neural networks have successfully been applied to a broad variety of problems in applied mathematics and engineering. The principle idea is to use a neural network as a global ansatz function to partial…

Machine Learning · Computer Science 2022-03-28 Alexander Henkes , Henning Wessels , Rolf Mahnken

The bulk macroscopic response of a system of particles or inclusions with field-induced forces is studied. The susceptibilities and transport coefficients in such a system are expressed as averages of a multiple scattering expansion. A…

Statistical Mechanics · Physics 2009-11-13 P. Szymczak , B. Cichocki

In a recent report, the American Association of Physics Teachers has developed an updated set of recommendations for curriculum of undergraduate physics labs.1 This document focuses on six major themes: constructing knowledge, modeling,…

Physics Education · Physics 2015-09-02 N. G. Holmes , D. A. Bonn

The problem of learning the structure of a high dimensional graphical model from data has received considerable attention in recent years. In many applications such as sensor networks and proteomics it is often expensive to obtain samples…

Machine Learning · Statistics 2016-04-08 Gautam Dasarathy , Aarti Singh , Maria-Florina Balcan , Jong Hyuk Park

One of the most influential recent results in network analysis is that many natural networks exhibit a power-law or log-normal degree distribution. This has inspired numerous generative models that match this property. However, more recent…

Data Structures and Algorithms · Computer Science 2011-09-01 Isabelle Stanton , Ali Pinar
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