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Because electric fields cannot be touched or seen, simulations are often utilized to build students&#39; understanding of them by providing them with a visual experience of electric fields and the motion of test charges through them. The objective of the simulation is to improve students’ qualitative understanding of how electric fields are impacted by the charges around them by creating a dynamic representation of the electric field lines, field vectors, equipotential lines, and the voltage created by the charges on screen. After creating a charge configuration, students can observe the motion of test charges through the electric field. The simulation was built in JavaScript so it will run on most browsers on a computer or mobile device. The simulation is intended to be used by college students taking introductory physics courses. A study of the impact on students&#39; understanding and attitude will be analyzed in future work.

AAPT SM 20

Dynamic Simulation to Help With the Understanding of Electric Fields

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Join AAPT and Physics Educators worldwide in developing and strengthening your professional connections by attending the 2021 AAPT Virtual Summer Meeting. AAPT meetings are a great way to reflect on your teaching, recommit to best practices and re-energize your career with new research, products, and techniques.

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AAPT SM 21

Because electric fields cannot be touched or seen, simulations are often utilized to build students' understanding of them by providing them with a visual experience of electric fields and the motion of test charges through them. The objective of the simulation is to improve students’ qualitative understanding of how electric fields are impacted by the charges around them by creating a dynamic representation of the electric field lines, field vectors, equipotential lines, and the voltage created by the charges on screen. After creating a charge configuration, students can observe the motion of test charges through the electric field. The simulation was built in JavaScript so it will run on most browsers on a computer or mobile device. The simulation is intended to be used by college students taking introductory physics courses. A study of the impact on students' understanding and attitude will be analyzed in future work.

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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. 

Interpreting and understanding the way students use and understand the mathematics used in physics is a central theme in Physics Education Research. Physical phenomena described by partial differential equations (PDEs) provide a promising context to study how students combine physics and mathematics. An example is the description of heat flow and temperature distribution in a one-dimensional rod, which can be described by the (1D) heat equation, together with an initial condition (IC), and boundary conditions (BCs). In this contribution, we present data from an interview study where we gave students the mathematical description of a system (PDE, IC and BCs) together with the analytical solution. We asked to describe the time evolution of the system, both in mathematical and physical terms. Our analysis shows that students’ reasoning is mainly mathematical with little reference to the underlying physics and that most students do not connect their mathematical statements to physical processes.

Relating solutions to the heat equation to the underlying physics

First, a fully comprehensive lab-manual for physics-I (kinematics) online-class was developed by using video-analysis and simulations. Only open educational resources (OER) were used to develop the lab manual. New lab manuals for ten experiments were written to investigate important basic concepts of kinematics class. Online lab classes are done synchronous format (at regular meeting time) online-live. During online meetings, the instructor work on at least two shared windows simultaneously one for writing and explanation (use the tablet mode of a dual-mode laptop) and one to access the lab manual. The instructor works with the students to collect the data by using virtual tools and demonstrate further data analysis, graphing, curve-fitting, calculations, and error analysis with the MS-Excel software package. Finally, students were required to compile a full lab report at a scientific standard and submitted to the learning-management-system (LMS) via plagiarism-checker. The learning outcome was analyzed by quizzes and exams.

Development of Physics-I (Kinematics) Lab-class for Virtual (fully online) Delivery

We are finishing development of around twenty video-based activities for topics in mechanics at the introductory undergraduate level (also useful for high school physics and AP physics I). Videos were taken of real moving objects - like a basketball, a girl on a playground slide, a billiard ball collision, a girl on a swing and even a diving board undergoing damped oscillatory motion to name a few. Videos were analyzed using Logger Pro. Each activity has the actual video, tracked motion images, graphs of relevant quantities and physics concept questions that rely primarily on getting information from the graphs. These will be integrated into the Expert TA system before the start of the fall semester. They can be used for homework where students will gain skills in estimating and interpreting graphs. They can also be used to replace some lab experiences students might miss because of online teaching.

VIDEO BASED GRAPHICAL ANALYSIS PROBLEMS - A supplement or replacement for lab experience in mechanics

How data guided pedagogical changes can help traditionally under-served populations

Doing Flight Physics with Smartphones and Real-time Data Analysis

QuarkNet High School students and teachers have collected data on cosmic ray muons. Their data is available to all on the i2u2.org site. QuarkNet has made available several experimental analysis tools to use with the existing 100K data files. In a remote learning environment, students can design their own experiment to measure fundamental properties like the speed or lifetime of muons, changes in the cosmic ray rate over time or with angle of orientation, or investigate the size of cosmic ray air showers.

QuarkNet Supports Remote Analyses of Cosmic Rays for High Schools

Despite limiting access to applicants from underrepresented racial and ethnic groups, the practice of using hard or soft GRE cutoff scores in physics graduate program admissions is still a popular method for reducing the pool of applicants. The present study considers whether the undergraduate institutions of applicants have any influence on the admissions process by modelling a physics GRE cutoff score with application data from admissions offices of five Midwestern universities. Two distinct approaches based on inferential and predictive modelling are conducted. While there is some disagreement regarding the relative importance between features, the two approaches largely agree that to include institutional information significantly aids the analysis. Both models identify cases where the institutional effects are comparable to factors of known importance such as gender and undergraduate GPA. As the results are stable across many cutoff scores, we advocate against the practice of employing physics GRE cutoff scores in admissions.

How do undergraduate institutions matter for physics GRE cutoff scores?

During the Spring 2020 quarter, the COVID-19 pandemic precluded access to our acoustics laboratory. In response, I redeveloped the experiments of our acoustics lab course in several ways. For some introductory activities, I employed videos to show basic concepts and methods in place of lab demonstrations and used applets to maintain some student interactivity. However, for most of the specialized experiments, I was able to draw upon past student work archived in electronic laboratory notebooks to extract photos, setup details, and experimental data sets. I then used that information to write activities that described the experimental methods, but required the current students to visualize, analyze, and interpret the data. To facilitate the course remotely, I used electronic laboratory notebooks to deliver and receive content. Preliminary indications are that the students are obtaining a similar understanding of the experimental methods and possibly better understanding of the data analysis than previous students.

Teaching an Advanced Acoustics Laboratory Course without a Laboratory

Lawrence’s Advanced Laboratory course trains students in experimental physics. Using research equipment, students engage deeply with real physics while learning scientific communication. Students worked on three self-selected projects using analog and digital electronics, ranging from single photon detectors to chaotic dynamics. Each student created an extension to one project, consisting of design and prototyping as well as collection and analysis of data. One student built an analog electronics neuron, firing upon exposure to a trumpet played at 392 Hz. Students shared project results with their scientific community via a scientific symposium (after students attended the APS Virtual April Meeting), an issue of Advanced Laboratory Letters at Lawrence (after PRL-based journal club discussions), and video demonstrations. Join us for a discussion of our approaches to evaluation and feedback, inclusive strategies, and course (and Zoom-related) fatigue. We will present what worked, what fell flat, and what surprised us along the way.

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Dynamic Simulation to Help With the Understanding of Electric Fields

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Relating solutions to the heat equation to the underlying physics

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