United States

Numerical modeling is used extensively in astrophysics and -- when used in a classroom -- allows students to explore how models are built in physics in general and how model building is facilitated by computational methods in particular. It also exposes them to ubiquitous tools such as Python and Runge-Kutta. Using a relatively simple N-body simulation students are able to go beyond the usual Kepler&#39;s Third law introductory descriptions of orbital dynamics and examine 3-body and chaos effects. I will show some cases where students encounter questions which are central to the current state-of-the-art in planetary dynamics research.

AAPT SM 20

Python N-body simulation of solar system dynamics

solar system

n-body

numerical

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. 

Numerical modeling is used extensively in astrophysics and -- when used in a classroom -- allows students to explore how models are built in physics in general and how model building is facilitated by computational methods in particular. It also exposes them to ubiquitous tools such as Python and Runge-Kutta. Using a relatively simple N-body simulation students are able to go beyond the usual Kepler's Third law introductory descriptions of orbital dynamics and examine 3-body and chaos effects. I will show some cases where students encounter questions which are central to the current state-of-the-art in planetary dynamics research.

technical paper

We have implemented a framework for personalized remote learning in an introductory algebra-based physics course at the University of Alabama at Birmingham. This framework, developed to address issues related to equity and inclusion, is based on a combination of strategies from physics education research and best practices in online learning. Our approach centers around the Gameful Learning pedagogy. Within this framework, we have incorporated several interventions including (1) the adaptive learning platform ALEKS for mathematical remediation (2) activities in metacognition and (3) a physics teaching-assistant managed “virtual help desk”. The implementation of this framework, materials developed, and experiences delivering the curriculum to a diverse student population during COVID-19 will be discussed.

Applying “Gameful Learning” in a Remote Introductory Physics Course

The Newton´s laboratory is an app created under Unity development platform (C and C ++ language) implemented to COLAF (Colombian Air Force) Cadets, whom allow them to go further in the researching field, improve their skills on the basic fundamentals of physics (Newton´s Laws) for applications in aerospace projects. Military personnel are undergraduate students who are subjected to a rhythm of life of constant physical demand, discipline, stress and mental development that are simultaneously complemented by academic training. The impact of the interaction of the cadets with this implemented tool, the contribution to their professional development and the future influence on the use of new technological applications in the training of the Colombian aerospace leaders are evaluated and the results are presented. This app was implemented as a way of supporting the education system due to the ongoin global pandemic.

Newton´s Laws app in Military School

We present our pedagogical experiences and practitioner recommendations for introductory physics undergraduate laboratories using the Scale-Up methodology, in the context of the sudden adaptation to the online teaching environment due to the COVID-19 pandemic. Specifically, we focus on the challenges of implementing focused critical-thinking labs with a diverse student population and graduate teaching staff ill-prepared for such a quick and forced transition. Given the task of achieving pre-COVID-19 learning objectives without providing physical access to laboratory materials, we examine the demonstrated benefits and disadvantages of several tools, such as technology, university resources, communication methods, and leadership skills.

Remote Delivery of Introductory Physics Labs During the COVID-19 Transition Period

Canadian Universities suspended regular in-person classes around mid-March due to the growing concerns about the pandemics. At my Department, the switch to the emergency remote teaching proceeded relatively smoothly, with remote classes up and running within one week. The synchronous lectures and office hours were conducted via zoom. It helped that the asynchronous online homework already existed as a part of a regular course. Not surprisingly, the real challenge turned out to be a remote testing part. The talk will discuss the challenges of running a traditional exam remotely, and the pressing need for the meaningful alternative ways of evaluating the students while teaching remotely.

Lessons From Remote Testing

The physics education and computer science researchers at Ithaca College collaborated to develop a mobile application to provide students with a dynamic experience studying electric fields, a notoriously difficult topic. This study is the first in a longitudinal study comparing the impacts of the mobile application and paired worksheet activity to other learning tools including a laptop simulation and a worksheet-only activity. Participants include health science majors enrolled in an algebra-based physics class. The normalized gain in performance on a diagnostic administered prior to and after interacting with one of the three activities was used to measure the impact of each activity on student understanding. Student attitude was measured using a questionnaire in the post-activity diagnostic. The results show students prefer laptop activities as physics learning aids and students in the two sections, mobile application and laptop simulation, produced higher average gains in learning than those in the worksheet-only section.

Developing and Testing a New Educational App about Electric Fields

We present our experience of conducting first semester calculus-based introductory physics laboratories remotely in the Spring 2020 semester. Six laboratories were redesigned to give students maximally hands-on experience under the restrains of coronavirus stay-at-home conditions. The video analysis by using Tracker software was used to collect and process the experimental data for most of these labs. The lessons learned allowed us to confidently teach the full semester of the labs remotely the following Summer 2020 semester.

Teaching the Introductory Laboratories Remotely: Lessons Learned

Understanding the student experience with emergency remote teaching

Our Junior Lab requires four experiments per semester. In spring 2020 the final two experiments were done by students at home. They were asked to design their own experiments using available resources. Extra credit was given for an inventory of these resources, which varied quite widely amongst students. Details and computer code for one possible experiment was given to students: the use of mobile phone image sensors for cosmic ray detection. An alternative to the final experiment was to submit instead a white paper describing plans to develop an application of physics to the Covid19 pandemic; students were sent a primer on possible topics. Students were individually counseled on their projects by email and through Zoom meetings. The capacity of students to independently conceive of and execute experiments varied widely and revealed the need to better equip students with knowledge and skills to pose problems, deal with ambiguity, and work resourcefully with physical devices, materials, and supporting literature.

Student Design of Advanced Lab Experiments at Home using Available Resources

Many instructors have recently been thrust into the online delivery of physics courses. When Athabasca University pioneered distance education physics in the 1990s with standard freshman mechanics and E&M content, labs could not be done remotely. Then, calculators able to control detectors, such as sonic rangers, became available. A “home lab” approach was developed, which later extended to other subjects, allowing students to perform quality physics experiments with real data, using a lab kit borrowed from the library and sent by mail. Through time our highly successful home lab approach has changed to use what are now common household items like smartphones. We discuss how to implement physics home labs now and urge retaining them when “normal” status returns. In the overall adjustment to a post-COVID world, we argue that successes with our home labs show that this approach should become part of the “new normal”.

Hands-On Laboratories in Online Physics: For Now and Post-COVID

Graphs form an integral part during STEM education and the understanding of graphs is essential for the interpretation of data, critical thinking and reasoning in physics. Different previous works have shown that students struggle with specific difficulties, such as a confusion of slope and height, interpreting changes in height and changes in slope and the area underneath a curve. In this work we use eye tracking to study the question how the students' conceptual understanding of the slope and area concept is linked to the visual attention to different areas of a graph. Using machine learning and different gaze-based metrics, the eye-tracking data reveals characteristic visual strategies during solving of quantitative slope and area problems. The results allow the optimization of classifying correct and incorrect answers and the identification of underlying students’ difficulties.

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Python N-body simulation of solar system dynamics

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