Astronomy datasets can be hard to use for high school astronomy classes. Data science education pedagogy can be leveraged to create astronomy activities in which students interrogate data, create visuals, and use statistical thinking to construct astronomy knowledge. This session describes how the NASA/IPAC Infrared Science Archive (IRSA) can provide a web-based interface for students to use basic data science techniques in astronomy to build data literacy while learning astronomical concepts. The activities shared will be available for anyone but were designed to be used in astro 101 classes in high school or early college.

Quantum Engineering and You (QuERY) Program

Click here to see the slides from this presentation.

Read more about using computational thinking and data science in learning Kepler’s 3rd Law.

Modern science teaching can benefit from combining computer science and data science. Students can construct science knowledge using data science techniques through writing and programming code. This session will show some Google Colab/Jupyter Notebook Python activities using authentic datasets designed for high school science courses. Learn how to access, reduce, visualize, and interpret some scientific datasets using best practices in basic data science. Some example activities will be explored using web-based tools tested in a classroom environment with students. Ideas about finding and accessing scientific datasets will be explored. All code is available as open source, and all lessons are shared as Creative Commons material.

Be sure to check out my list of activities that incorporate computational thinking, data science, and coding.

Read more about my computational thinking research or check out my presentation and all the links here.

American Association of Physics Teachers/American Astronomical Society Winter Meeting 2024

• Google Colab Notebook Teacher version (with answers)
• Google Colab Notebook Student version (with NO answers)
• AAS 243 iPoster

Modern astronomical science is increasingly driven by data science and computational thinking. It is possible to have astronomy students construct astronomy knowledge while employing computational thinking and data science pedagogies by using partially-reduced datasets like those from the Sloan Digital Sky Survey (SDSS) in conjunction with Python and Google Colab notebooks. Here, we explore a highly scaffolded activity for students to build a Hubble-Lemaître diagram using data from the Baryon Oscillation Spectroscopic Survey (BOSS) from SDSS. Educators with access to plates from the BOSS mission can tie the activity directly to data associated with the plate. Students access the data directly from the database and use Python and Google Colab notebooks to reduce, visualize, and interpret data in a highly scaffolded format. Students are asked to interpret plots and place data in an astrophysical context. This activity is part of ongoing research into the impacts of using computational thinking pedagogies with physics and astronomy students. This activity has been used in a high school astronomy course. The activity and all associated programming code are freely available as Creative Commons content.

If you want to follow along while we explain the activity, choose one:

• Teacher version with the answers
• Student version with nothing completed

Attending CAST 2023? Come hear about how science teachers can use authentic data and Google Colab with Python to explore stellar spectroscopy. Thursday at 1 PM in room 350F in the George R. Brown convention center.

Welcome to the AAPT Summer Meeting 2023 Coding Integration and Data Science Integration in High School workshop. The workshop is happening in Ballroom A09 in the convention center.

Registered participants should direct their web browser (Chrome, Firefox, Safari, or MS Edge) to https://stemcoding.herokuapp.com/ and ask your instructor for the join key.

If you want more STEMcoding content, check out the STEMcoding YouTube channel. If you would like to 2.0 graduate credit hours in STEMcoding coursework, check out the AAPT-affiliated courses from STEMcoding.

For those in academia, use this link: http://go.osu.edu/physics_coding

Computational thinking is a natural thing to incorporate into physics and astronomy. Students can learn to create interactive models, create, collect, and visualize datasets, and ask questions that only make sense to answer with a computer. Participants will hear about current research in computational thinking using coding, where science pedagogy can leverage computer science pedagogy to allow students to construct knowledge in both domains. Some model activities using computer programming and lessons incorporating computational thinking will be shared and discussed. All code is available as open source, and all lessons are shared as Creative Commons material.

Here is a list of the coding-based labs and activities I have used in physics and astronomy. There are not really in any kind of order. All work is shared via the Creative Commons Attribution-NonCommerical-ShareAlike 4.0 license. Feel free to use the content here for non-commercial purposes, but be sure to provide attribution.

Hubble Diagram using SDSS Data	Astronomy	Modeling/Data Science
Measuring Distance with Light	Astronomy	Modeling
Relative Abundance of Europium with Spectroscopy	Astronomy	Modeling
Air Drag Modeling with p5js	Physics	Modeling
HR Diagram Introduction	Astronomy	Modeling/Data Science
Kepler’s 3rd Law	Astronomy	Modeling/Data Science
Air Drag Analysis: Video vs Modeling	Physics	Physics
RET 2021 Modeling Air Drag with Unity vs p5js	Physics	Physics
Exploring Simple Circuits	Physics	Physical computing
Micro:bit Stoplight Lab	Phyics	Physical computing
Capacitors in Series and Parallel	Physics	Physical computing
Photoplethysmography with Microcontrollers	Physics	Physical computing