United States

Introductory calculus-based physics is taught at Bridgewater College with both laboratory and computational components. Simple programming in Glowscript (a vpython environment) is introduced to students in recitation section. In two of the lab experiments (cart sliding with constant velocity, collision between two carts), students use the experimental data to determine the parameters for a numerical simulation of the system. The computational activities are designed to provide practice with momentum conservation and with updating the position of an object based on its previous position and velocity. Integrating them with lab activities is intended to promote understanding of the physical parameters. If coded correctly, the numerical output will resemble the experimental data, providing plausibility checks on the code. A more advanced laboratory activity done in Physics I, the ballistic pendulum, has also been simulated numerically by a student as an Honors Upgrade. The simulation applies the principle of momentum conservation to reproduce the motion of a pendulum after a collision with a projectile.

AAPT SM 20

Computational Simulations of Introductory Lab Experiments in Physics I

picup

computation

The 2020 AAPT Virtual Summer Meeting brought together physics educators from around the globe to learn about the latest in physics theory, research methodology and education from leaders in their field. The program featured plenary speakers, sessions, workshops and many special activities.

For more information please visit the 2020 AAPT Virtual Summer Meeting page at: https://www.aapt.org/Conferences/SM2020/index.cfm.


The 2020 AAPT Virtual Summer Meeting brought together physics educators from around the globe to learn about the latest in physics theory, research methodology and education from leaders in their field. 

poster

Modern Techniques to Engage Students using Microcontroller Hardware and Python

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Computation has much to offer in terms of teaching quantum mechanics. In this presentation we give specific examples of use of computation in quantum mechanical problems. We also discuss standard toolkits either well-known, used in research or found in software libraries, and not-so-standard tools one can implement themselves. Examples utilizing numerical and visualization techniques for solving time-dependent and time-independent quantum systems will be discussed (see also http://www.faculty.umassd.edu/j.wang/) including superposition, scattering flux, eigenstates in periodic structures, evolution of uncertainties, and quantum dots.

Computational toolkits in quantum mechanics

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In the Chinese high school physics curriculum, the Ampere's rule, the left-hand rule, and the right-hand rule are used to determine the direction of the magnetic field, the ampere and Lorentz force, and the direction of the electric current. However, without a deep understanding of the basis of these rules, which arises from the concept of cross-product, it is easy for students to confuse these rules. This leads to inefficiency and difficulty in problem-solving, which is also the difficulty faced by most teachers. The central idea of these three rules is the cross product; therefore, by guiding students to establish the concept of cross product can cultivate deep learning of electromagnetism knowledge. In this presentation, a conceptual framework of the hand rules will be instructed along with an assessment tool that evaluates students’ understanding of the mastery of the three rules at different phases of their learning.

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