Ari Krakowski, Eric Greenwald, Natalie Roman, Christina Morales, Suzanna Loper

Original article: Krakowski, A., Greenwald, E., Roman, N., Morales, C., & Loper, S. (2024). Computational Thinking for Science: Positioning coding as a tool for doing science. Journal of Research in Science Teaching, 61(7), 1574-1608. https://doi.org/10.1002/tea.21907

How can we teach coding in a way that feels natural in science class—and truly meaningful for students? 

This study introduces the Computational Thinking for Science (CT+S) model, a powerful teaching approach designed to help students develop coding and computational thinking (CT) skills through science learning. Rather than treating coding as an “add-on,” this model integrates it directly into authentic science tasks—making it both relevant and engaging for middle school students.

The research team partnered with classroom teachers to design and test the CT+S model in real science classrooms. Their work revealed three key strategies for meaningful integration:

1. Multimodal learning experiences – Blending hands-on, “unplugged” activities, coding tasks, and group discussions to build deep conceptual understanding.
2. Real-world problem-solving – Framing science lessons around relevant challenges, such as coral reef restoration or air quality analysis, to show the value of CT in everyday life.
3. Disciplinary authenticity – Ensuring that CT supports core science practices, like modeling and data interpretation, without adding to teachers’ workload.  

This STEM teaching model helps students not only develop computational skills, but also see themselves as capable, creative problem-solvers. Teachers in the study noted how students became more confident and motivated when they saw how coding could be used to explore scientific questions that matter to them and their communities. For example, one teacher reported that for the sequence focusing on coral reef ecosystems, her students “learned that there were solutions that they could be a part of. [They] learned about coral reefs in such a way that they were eager to know more and felt an urgent sense of care for coral reefs.” A sentiment echoed by the students as well, “The fact that we're saving the coral reef makes it interesting. Getting to be able to code this feels like I'm right there working on something real, having this really cool experience saving the reef.

What this means for teachers and educators:

• Use coding to enhance science instruction, not replace it.
• Choose authentic science contexts—like environmental data or health topics—to make computational thinking relevant.
• Incorporate student voices and experiences to boost engagement and inclusivity.
• Use unplugged activities to lower barriers to entry and build conceptual foundations.

By positioning computational thinking as a tool for doing real science, the CT+S model supports both teacher goals and student learning. It offers a scalable, equity-driven approach to STEM education that connects classroom learning to future opportunities in science, technology, engineering, and math. 

“With CT integrated in this way, and with support for them to learn alongside their students, teachers found the approach not only deepened student learning, but also offered the kind of window into 21st-century STEM careers they highly value as educators." 

As one teacher nicely summarized, “Seeing the long list of numbers [in the dataset] was really impressive for them, and for me … just like oh, it keeps scrolling and it keeps growing! But we can organize it… this is what coders do, they take all these crazy numbers and they try to structure them. Being able to see that connection is really important, because that's what science is, all this data."