WeTeach_CS Summit 2025

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Impacting Student Attitudes About CS Through Coding Integration into Science

In this session, participants will learn how integrating CS pedagogy into science and math classes can positively impact student attitudes about CS. When students experience lessons in science and math classes that use CS, they feel more confident about CS and are more likely to pursue academic pathways that include CS. Participants will see examples of specific lessons that can be used in science and math courses to improve student attitudes about the use of CS in non-CS STEM courses.

Participants will use STEMcoding during the session and can access STEMcoding for free for one year.

TSAAPT/TSAPS Spring 2025: Modeling with STEMcoding in AP Physics 1

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Improving Student Computational Thinking Outcome Expectancy through Integrating Model-building in a Secondary Physics Course

The role of computation in physics is increasing in both a professional and educational context. High school physics pedagogy should incorporate computational thinking, data science, and computer science skills to bolster learning across these domains. The study described here shows that when students build physically meaningful models using computer programming in a physics course, their outcome expectancy is positively impacted. Outcome expectancy can predict students’ future academic and professional choices. The STEMcoding platform asks students to construct models using Euler-Cromer step-wise modeling of physical phenomena, such as those described by the laws of motion. The study presented had students use STEMcoding during the kinematics portion of Advanced Placement Physics 1 classes at a large, urban high school in southeast Texas. A moderate positive impact on outcome expectancy was found across various groups in the study population. Results show how computational essays can provide scaffolded learning while allowing students to use code to create interactive models, allowing knowledge construction in a domain-specific manner.

Bridging Research and the Classroom: Leveraging Multi-Wavelength Data for SED Plots of Young Stellar Objects Using Google Colab (AAS 245 WM)

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Modern astronomy research requires computation and data science tools, which are not traditionally part of the Astronomy 101 course. This computational essay describes what a spectral energy distribution (SED) is and uses code to construct one. Although existing computational thinking tools like spreadsheets can be leveraged to allow computational thinking to construct science knowledge, the needs of a student or teacher astronomical researcher will likely go beyond introductory tools. The goal of the SED computational essay presented is not only to inform about SEDs and their use but also to be a part of a toolset meant to allow students and teachers to interrogate other stellar photometric datasets at scale. This notebook was designed by alumni of the NASA/IPAC Teacher Archive Research Project (NITARP). The code can be found on GitHub. This presentation is in the iPoster format, as seen at this link.

Using Data Science in High School Astronomy @ ASP 2024

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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.