CAST 2025
Jimmy Newland and Justin Hickey
If you are interested in the role of data science pedagogy in teaching science, check out this page.
STEM Educator and Researcher.
CAST 2025
Jimmy Newland and Justin Hickey
If you are interested in the role of data science pedagogy in teaching science, check out this page.
When doing domain-specific programming in science, some CS pedagogy can be used to
scaffold concepts like conditionals, function writing, and looping. Using worked examples,
minimally working programs, sub-task labeling, and live coding can help a student bring
coding to bear on learning concepts in science. Room B107 1:15 – 2:15 pm CDT
Chanel Belvin, Elaine Anita De Melo Gomes Soares, Toni Dunlap, James Newland
Expanding Pathways in Computing,
Texas Advanced Computing Center,
University of Texas at Austin




Visit the project page for lots more information, including code and references.
In this session, participants will learn how integrating computer science (CS) pedagogy into science and math classes can positively impact students’ attitudes about computer science. When students experience lessons in science and math classes that incorporate computer science (CS), they feel more confident about CS. They 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 students’ attitudes about the use of computer science (CS) in non-CS STEM courses.
Participants will use STEMcoding during the session and can access STEMcoding for free for one year.
If you are interested in more academic details about the STEMcoding study, click here.
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.
If you are attending the Data Science Education K12 Conference in San Antonio, talk to me about data science education in astronomy classes during the individual showcases. Be sure to visit the website for my poster!


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.
https://tinyurl.com/CASTPivotData

Eric Friberg and Jimmy Newland share how data science can help drive science learning through analyzing real-world phenomena.