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The goal of this paper is to investigate the importance of providing visual "big pictures" in the teaching of economics. The plurality and variety of concepts, variables, diagrams, and models involved in economics can be a source of…

Economics · Quantitative Finance 2016-01-11 Seyyed Ali Zeytoon Nejad Moosavian

There is a substantial curricular overlap between calculus and physics, yet introductory physics students often struggle to connect the two. We introduce a quantity-based framing of the Fundamental Theorem of Calculus (FTC) to help unify…

Physics Education · Physics 2025-07-28 Suzanne White Brahmia , Patrick W. Thompson

Graphs are used in many disciplines to model the relationships that exist between objects in a complex discrete system. Researchers may wish to compare a network of interest to a "typical" graph from a family (or ensemble) of graphs which…

Combinatorics · Mathematics 2025-08-08 Catherine Greenhill

The centuries-long practice of the teaching turned mechanics into an academic construct detached from its underlying science, the physics of macroscopic bodies. In particular, the regularities that delineate the scope of validity of…

Classical Physics · Physics 2015-06-15 Serge A. Wagner

Although physics has become increasingly computational, with computing even being considered the third pillar of physics, it is still not well integrated into physics education. Research suggests that integrating Computational Thinking (CT)…

Physics Education · Physics 2025-11-06 Mateo Dutra , Álvaro Suárez , Arturo C. Marti

Teaching graph theory with the most adequate tools requires time and ideas. We present how an open community of teachers shares contents and ideas on an innovative platform. The objective is to get the students autonomous in their training…

Discrete Mathematics · Computer Science 2022-09-13 Nicolas Catusse , Hadrien Cambazard , Nadia Brauner , Bernard Penz , Florian Fontan

This paper re-centres the discussion of student learning in physics to focus on context. In order to do so, a theoretically-motivated understanding of context is developed. Given a well-defined notion of context, data from a novel…

Physics Education · Physics 2009-11-11 N. D. Finkelstein

We present a novel methodology to jointly perform multi-task learning and infer intrinsic relationship among tasks by an interpretable and sparse graph. Unlike existing multi-task learning methodologies, the graph structure is not assumed…

Machine Learning · Computer Science 2020-09-15 Shujian Yu , Francesco Alesiani , Ammar Shaker , Wenzhe Yin

The learning of mathematics starts early but remains far from any theoretical considerations: pupils' mathematical knowledge is first rooted in pragmatic evidence or conforms to procedures taught. However, learners develop a knowledge which…

History and Overview · Mathematics 2014-03-28 Nicolas Balacheff

We introduce an approach for imposing physically motivated inductive biases on graph networks to learn interpretable representations and improved zero-shot generalization. Our experiments show that our graph network models, which implement…

Machine Learning · Computer Science 2019-11-04 Miles D. Cranmer , Rui Xu , Peter Battaglia , Shirley Ho

At the University of Colorado Boulder, as part of our broader efforts to transform middle- and upper-division physics courses, we research students' difficulties with particular concepts, methods, and tools in classical mechanics,…

Physics Education · Physics 2015-06-05 Marcos D. Caballero , Bethany R. Wilcox , Rachel E. Pepper , Steven J. Pollock

Aspects of quantum physics are no longer confined to the upper years of a physics degree. Concepts like superposition or entanglement that were once reserved for second- or third-year undergraduate courses now deserve attention earlier in a…

Physics Education · Physics 2026-05-12 James Day , Simone Williamson

We present a framework for representing and modeling data on graphs. Based on this framework, we study three typical classes of graph signals: smooth graph signals, piecewise-constant graph signals, and piecewise-smooth graph signals. For…

Artificial Intelligence · Computer Science 2015-12-18 Siheng Chen , Rohan Varma , Aarti Singh , Jelena Kovačević

We give an overview of combinatorial methods to represent 3D data, such as graphs and meshes, from the viewpoint of their amenability to analysis using machine learning algorithms. We highlight pros and cons of various representations and…

Machine Learning · Computer Science 2024-08-19 Tomasz Prytuła

Assessments are usually thought of as ways for instructors to get information from students. In this work, we flip this perspective and explore how assessments communicate information to students. Specifically, we consider how assessments…

Physics Education · Physics 2020-07-15 Kelli Shar , Rosemary S. Russ , James T. Laverty

We consider a definition of mathematics as the art of thinking in terms of formalized systems, and the science of relations, structures and algorithms. We also touch upon the relation of mathematics to other sciences, in particular through…

History and Overview · Mathematics 2015-10-19 Snorre H. Christiansen

Usually the first course in mathematics is calculus. Its a core course in the curriculum of the Business, Engineering and the Sciences. However many students face difficulties to learn calculus. These difficulties are often caused by the…

Computers and Society · Computer Science 2012-12-27 Seifedine Kadry , Maha ElShalkamy

The ability to read, write, and speak mathematics is critical to students becoming comfortable with statistical models and skills. Faster development of those skills may act as encouragement to further engage with the discipline. Vocabulary…

Other Statistics · Statistics 2025-07-08 Tess O'Brien

Researchers in physics education have advocated both for including modeling in science classrooms as well as promoting student engagement with sensemaking. These two processes facilitate the generation of new knowledge by connecting to…

Physics Education · Physics 2023-01-31 Amogh Sirnoorkar , James T. Laverty , Paul D. O. Bergeron

Differentiable physics provides a new approach for modeling and understanding the physical systems by pairing the new technology of differentiable programming with classical numerical methods for physical simulation. We survey the rapidly…

Machine Learning · Computer Science 2021-09-17 Bharath Ramsundar , Dilip Krishnamurthy , Venkatasubramanian Viswanathan