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One area of physics education research has focused on the nature of ontologies (mental categorizations of concepts, substances and processes), and how they might be used to gain insight into student thinking when learning classical physics.…

Physics Education · Physics 2014-10-01 Charles Baily , Noah D. Finkelstein

We introduce resource graphs, a representation of linked ideas used when reasoning about specific contexts in physics. Our model is consistent with previous descriptions of resources and coordination classes. It can represent mesoscopic…

Physics Education · Physics 2009-11-11 Michael C. Wittmann

Uncertainty quantification is at the core of the reliability and robustness of machine learning. In this paper, we provide a theoretical framework to dissect the uncertainty, especially the \textit{epistemic} component, in deep learning…

Machine Learning · Computer Science 2023-06-21 Ziyi Huang , Henry Lam , Haofeng Zhang

Physics education research has used quantitative modeling techniques to explore learning, affect, and other aspects of physics education. However, these studies have rarely examined the predictive output of the models, instead focusing on…

Physics Education · Physics 2019-05-22 John M. Aiken , Rachel Henderson , Marcos D. Caballero

Recent investigations have been carried out on critical analyses of beginning physics teachers confronted with questionable explanations. These studies raise the question of the choices made by teachers for their teaching once they have…

Physics Education · Physics 2021-04-29 Laurence Viennot

A standard assumption for causal inference from observational data is that one has measured a sufficiently rich set of covariates to ensure that within covariate strata, subjects are exchangeable across observed treatment values. Skepticism…

Methodology · Statistics 2020-09-24 Eric J Tchetgen Tchetgen , Andrew Ying , Yifan Cui , Xu Shi , Wang Miao

A common approach to solving physical reasoning tasks is to train a value learner on example tasks. A limitation of such an approach is that it requires learning about object dynamics solely from reward values assigned to the final state of…

Artificial Intelligence · Computer Science 2021-09-03 Eltayeb Ahmed , Anton Bakhtin , Laurens van der Maaten , Rohit Girdhar

Physics, like many scientific disciplines, has long struggled with attracting and retaining a diverse population and fostering inclusivity. While there have been improvements in addressing equity issues within physics, significant…

Physics Education · Physics 2024-09-13 Alia Hamdan , Ash Bista , Dina Newman , Scott Franklin

Causal decomposition analyses can help build the evidence base for interventions that address health disparities (inequities). They ask how disparities in outcomes may change under hypothetical intervention. Through study design and…

Methodology · Statistics 2020-09-17 John W. Jackson

It is becoming common to hear teaching advice about spending more time on the "physics of the problem" so that students will get more physical insight and develop a stronger intuition that can be very helpful when thinking about physics…

Physics Education · Physics 2007-08-02 S. Rojas

Conceptual reasoning, the ability to reason in abstract and high-level perspectives, is key to generalization in human cognition. However, limited study has been done on large language models' capability to perform conceptual reasoning. In…

Computation and Language · Computer Science 2024-04-02 Ben Zhou , Hongming Zhang , Sihao Chen , Dian Yu , Hongwei Wang , Baolin Peng , Dan Roth , Dong Yu

The capabilities and limitations of Large Language Models have been sketched out in great detail in recent years, providing an intriguing yet conflicting picture. On the one hand, LLMs demonstrate a general ability to solve problems. On the…

Causal approaches to post-hoc explainability for black-box prediction models (e.g., deep neural networks trained on image pixel data) have become increasingly popular. However, existing approaches have two important shortcomings: (i) the…

Machine Learning · Computer Science 2025-08-12 Numair Sani , Daniel Malinsky , Ilya Shpitser

It is often said that a deep learning model is "invariant" to some specific type of transformation. However, what is meant by this statement strongly depends on the context in which it is made. In this paper we explore the nature of…

Machine Learning · Computer Science 2022-10-11 Henry Kvinge , Tegan H. Emerson , Grayson Jorgenson , Scott Vasquez , Timothy Doster , Jesse D. Lew

Extreme values modeling has attracting the attention of researchers in diverse areas such as the environment, engineering, or finance. Multivariate extreme value distributions are particularly suitable to model the tails of multidimensional…

Statistics Theory · Mathematics 2017-01-16 Helena Ferreira , Marta Ferreira

In randomized clinical trials, adjustments for baseline covariates at both design and analysis stages are highly encouraged by regulatory agencies. A recent trend is to use a model-assisted approach for covariate adjustment to gain…

Methodology · Statistics 2021-07-14 Ting Ye , Jun Shao , Yanyao Yi , Qingyuan Zhao

In recent years there has been a lot of interest in discussing frame dependences/independences of the cosmological perturbations under the conformal transformations. This problem has previously been investigated in terms of the covariant…

General Relativity and Quantum Cosmology · Physics 2018-03-14 Yunlong Zheng , Yicen Mou , Haomin Rao , Mingzhe Li

Modified theories of gravity have been invoked recently as an alternative to dark energy, in an attempt to explain the apparent accelerated expansion of the universe at the present time. In order to describe inhomogeneities in cosmological…

General Relativity and Quantum Cosmology · Physics 2016-04-15 Adam J. Christopherson

In this paper, I discuss my personal journey through one research tradition, that of the resources framework, and how it has evolved over time. In my present work, understanding learners' reasoning in physics in terms of the construction of…

Physics Education · Physics 2018-01-30 Michael C. Wittmann

Students' difficulties in quantum mechanics may be the result of unproductive framing and not a fundamental inability to solve the problems or misconceptions about physics content. We observed groups of students solving quantum mechanics…

Physics Education · Physics 2017-08-23 Bahar Modir , John D. Thompson , Eleanor C Sayre
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