United States

AAPT SM 20

Vernier Video Analysis on Chromebooks, Computers, and Tablets

AAPT® is a strong professional physics science society dedicated to the pursuit of excellence in physical science education.

Winter and Summer National Meetings:
These National Meetings, held each winter and summer, are opportunities for members, colleagues, and future physicists from around the world to:

- participate in physics workshops
- meet and greet other physics educators
- form networks nationally and locally
- engage exhibitors and learn about the latest physics resources
- discuss innovations in teaching methods
- share the results of research about teaching and learning.

If you're not able to log in, you're most likely using **incorrect login credentials**. Double-check that you are using the same email and password that you used to register for the conference, submit your abstract or access your AAPT membership. There may also be **an issue with your AAPT meeting registration**. Please email aapt2021@underline.io and programs@aapt.org and we will work quickly to resolve this issue.

AAPT WM 21

technical paper

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.


Computation is a critical part of professional physics practice and has been shown again and again to be useful for helping student build physics understanding. But, what are the essential elements that allow physics students to productively use computation? I argue that we can use the theory of computational literacy to answer this question. According to diSessa (2000) and Berland (2016), computational literacy consists of three main elements, or pillars: 1) The material pillar, which involves writing and understanding computer code; 2) The cognitive pillar, which involves breaking down problems into a form that can be addressed with computation (also known as computational thinking); 3) The social pillar, which involves communicating with and about computation. Using the physics department of the University of Oslo, Norway, as a case study, I describe what each of these elements can look like and how we can help our students achieve computational literacy in physics

Computational Literacy and Computational Essays at the University of Oslo

Understanding and supporting graduate education policies and practices is critical to the success of future physicists and astronomers and to supplying well-trained science, technology, engineering and mathematics (STEM) professionals to the US workforce. As such, it is essential that graduate programs study and promote practices that support equity and inclusion. During the 2018-19 academic year, admissions into the Physics and Astronomy graduate program at the University of Utah was halted while a complete overhaul of all aspects of the program was initiated by the Department. The program reform included the recruitment and admissions process, orientation and teaching assistant training, advising practices and other student support, the curriculum, and the exam structure. This presentation will outline our process of change and highlight results from the first year of new policy implementations.

Graduate Program Reform at the University of Utah

We have previously established a ranking of incorrect responses to FMCE questions using Item Response Theory. In Bock’s Nominal Response Model (NRM), each student has an associated latent trait (i.e., understanding of mechanics), and each response is represented by two parameters. One of the parameters is reported as showing the strength of correlation between that response choice and the latent trait. Bock does not interpret the meanings of these parameters; however, the mathematical form of the NRM is identical to the probability of a system being in a discrete degenerate energy state in the canonical ensemble. Through analogy we may interpret the latent trait as relating to the system temperature, and explain why one parameter (“energy”) is related to the latent trait but the other parameter (“degeneracy”) is not. We may also gain additional information by extending this analogy to consider macroscopic quantities such as average energy and entropy.

Modeling Students as Thermodynamic Systems using the Canonical Ensemble

The life sciences present a rich trove of physics problems to ponder and solve. However, a challenge I faced in teaching the physics of biological topics is that, as a physicist, I don’t know very much biology. To address this challenge, I developed and co-teach two life-science oriented physics courses in collaboration with biologists. In collaboration with a molecular biologist, I teach a research-based course for first-year students focusing on modalities of microscopy including fluorescence and atomic force microscopy. In collaboration with a human biology and kinesiology professor, I developed and co-teach a 100-level science requirement course focusing on human athletic performance. In this talk I discuss several of the activities and labs developed from these collaborations. I also discuss the rewards and the challenges of teaching with life science colleagues.

Vernier Video Analysis on Chromebooks, Computers, and Tablets

Downloads

Next from AAPT SM 20

Computational Literacy and Computational Essays at the University of Oslo

Similar lecture

Direct Air Capture and Achieving Net Zero Emissions

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES