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Interdisciplinary Ideas

The Intentional Integration of Computational Thinking

Science Scope—May/June 2021 (Volume 44, Issue 5)

By Raja Ridgway

Since Jeanette Wing’s powerful declaration that computational thinking (CT) is for everyone (Wing 2006), we have seen an explosion in the number of organizations and people working to integrate CT into every K–12 subject. For us science teachers, we have seen CT built directly into the Next Generation Science Standards (Appendix F; NGSS Lead States 2013), explicitly as part of the science and engineering practices (i.e., Using Mathematics and Computational Thinking) and implicitly through several of the crosscutting concepts (e.g., Patterns).

The importance of integrating CT has also been highlighted—from being a way to increase students’ proficiency with larger data sets (Sneider et al. 2014) to building bridges between their real and academic lives (Ridgway 2020). Scholars have articulated the need for students to experience both unplugged and plugged versions of CT integration (Yadav and Caeli 2019), and we have started to gain more clarity about the relationships between math, science, engineering, and CT (K12 Computer Science Framework n.d.). However, integrating CT can still often feel like trying to shove yet one more thing into an already packed science curriculum—a week of trying to learn Scratch or an unrelated lesson to introduce 10 new vocabulary terms.

Over the past two years, I’ve had the opportunity to work with elementary and middle school teachers as they began to integrate CT into their classes—everything from inquiry-based STEM classes to writing and social studies. A common pitfall that teachers fall into is introducing CT without any connection to their core subject. For science teachers, this often looks like spending several lessons introducing CT practices like decomposition and algorithm development without any science content. Another approach is to spend those lessons just learning how to program in Scratch—again, without any science content to frame why Scratch can be a powerful tool to understand a science concept or how the CT practices are connected. In essence, teachers are delivering CT content and hoping that students will make the connections or be able to apply the CT practices in upcoming lessons that do focus on science concepts. I think of this approach as similar to spending a week at the start of a semester building student lab skills out of context—students learn how to graph, but don’t understand why they are graphing or how graphing impacts their understanding of specific science content. So how can you avoid this pitfall and integrate CT intentionally?

Exist/Enhance/Extend: A Framework for integrating computational thinking

In 2019, three researchers at the Education Development Center published a paper on a multilevel framework for integrating CT into existing science curriculum. Waterman, Goldsmith, and Pasquale (2020) worked with teachers from first through sixth grade to develop their students’ CT skills alongside their science content. In seeking to avoid disrupting the curriculum of the science teachers, or attempting to build skills that were out of context for the class, Waterman, Goldsmith, and Pasquale (2020) used a framework of Exist, Enhance, and Extend to intentionally integrate CT (see Table 1).


Table 1. Levels of computational thinking in middle school science.

Level of Waterman et al. (2020) framework

Middle school science example based on MS-PS2-1

Exist: The CT practices already present in an existing lesson are highlighted and discussed (Waterman et al. 2020).

As part of a lesson about car collisions, a teacher identifies and discusses how abstraction, a CT practice, is used to determine what to include and leave out when modeling the collision in one dimension.

Enhance: An activity or lesson might be adjusted to allow students to engage more with the CT practices, potentially integrating technology (Waterman et al. 2020).

Instead of only considering a handful of collisions, students use Google Sheets to make sense of data from thousands of collisions, efficiently making calculations and reviewing graphs for patterns.

Extend: An explicit focus is on the CT practices with students probably using programming to learn more about the science content (Waterman et al. 2020).

Students create or adjust the code in a simulation program to adjust variables in a series of collision simulations. The CT practices are used both for understanding collisions and for developing the code.

At all the levels of the framework, it is essential to start with the science content and then integrate CT to improve the lesson. But this can often be easier in theory than in practice. From my experience, one of the first challenges teachers have is determining which CT practices should be highlighted at the Exist level (see Table 2 for the core CT practices). Given that there is so much overlap between the CT practices and the science and engineering practices (SEPs) and crosscutting concepts (CCCs), there are often multiple CT practices that seem relevant and worth discussing with students. While teachers could attempt to highlight all the practices, I’ve found that the discussions are richer when the focus is on one or two CT practices (see Table 3 for examples of how the CT practices align with the CCCs and SEPs). The process of determining which CT practices will be most appropriate starts at the beginning of the lesson planning process.

Table 2. Computational thinking practices.

Decomposition: Breaking down into components (K12 Computer Science Framework n.d.)

Pattern matching: Finding similarities between components (Krauss and Prottsman 2017)

Abstraction: The process of reducing complexity by focusing on the main idea. By hiding details irrelevant to the question at hand and bringing together related and useful details, abstraction reduces complexity and allows one to focus on the problem (K12 Computer Science Framework n.d.)

Algorithms: A step-by-step process to complete a task (K12 Computer Science Framework n.d.)

Table 3. Example alignment of computational thinking with the crosscutting concepts and science and engineering practices.

Computational thinking practice

Crosscutting concept

Science and engineering practices


Structure and function

Asking questions and defining problems

Pattern Matching


Analyzing and interpreting data

Using mathematics and computational thinking


Systems and systems models

Developing and using models


Cause and effect

Planning and carrying out investigations

Understanding by Design—Backwards planning

Most educators have heard of the concept of backwards planning—and potentially in the context of unit planning while reading Understanding by Design by Grant Wiggins and Jay McTighe (see Online Resources). The same principles of backwards planning at the unit level can be applied to great effect when considering how to intentionally integrate CT.

To begin, start by laying out the NGSS performance expectations (PEs) and your daily objective. Next, break the objective down into a comprehensive list of knowledge, skills, and mindsets (in addition to using the disciplinary core ideas [DCIs] for knowledge and the SEPs for skills, I’ve found the NGSS Evidence Statements are helpful in making sure I stay within the scope of the PEs; see Online Resources). Once you have a clear picture of what students need to know and what they need to be able to do, begin to look for overlap between the science content/skills and the CT practices. Do students need to create a physical, mental, or mathematical model? Chances are high that they will need to use abstraction to determine which details to keep and which to remove. Are you asking students to plan an investigation? This might require developing an algorithm, or if they have recently planned a similar investigation (such as in the 5E Model with the Explore and Elaborate phases), they might be using pattern recognition to determine which steps need to be repeated in the new investigation.

With the overlapping CT practices identified, now build out the exemplar responses you want to see from students. At the Exist level, this is likely not an end-of-class assessment. Instead, what do you want to hear students saying about abstraction and the model they are building during the lesson? What should they be doing when they collaboratively write a procedure for an experiment that builds from a previous lab? Consider asking students if they can describe their own examples of the CT practices, or utilize the new vocabulary as part of their discussions. The more students are making connections to other content or experiences, the more fluent they will become with the CT practices.


The importance of integrating CT across all content areas has never been clearer. But integrating CT intentionally requires more than just getting students to write a program in Scratch or analyze data in Google Sheets. It requires us as educators to think critically about which CT practices will best enhance or extend our students’ understanding of their science content. That thinking starts when we begin to plan our lessons—from the very first time we consider our standards and objectives!

How else are you integrating CS into your middle school science classroom? Do you have a great resource or experience to share? Let me know via email! 

Raja Ridgway ( is the director of computer science education at Relay Graduate School of Education in Denver, Colorado.


K12 Computer Science Framework. n.d. Computational thinking.

Krauss, J., and K. Prottsman. 2017. Computational thinking and coding for every student: The teacher’s getting-started guide. Thousand Oaks, CA: SAGE Publications.

NGSS Lead States. 2013. Next Generation Science Standards: For states, by states. Washington, DC: National Academies Press.

Ridgway, R. 2020. Building bridges with computational thinking. Science Scope 48 (8): 12–15.

Sneider C., C. Stephenson, B. Schafer, and L. Flick. 2014. Exploring the science framework and NGSS: Computational thinking in the science classroom. Science Scope 38 (3): 10–15.

Waterman, K.P., L. Goldsmith, and M. Pasquale. 2020. Integrating computational thinking into elementary science curriculum: An examination of activities that support students’ computational thinking in the service of disciplinary learning. Journal of Science Education and Technology 29: 53–64.

Wing, J. 2006. Computational thinking. Communications of the ACM 49 (3): 33–35.

Yadav, A., and N.E. Caeli. 2019, July. Unplugged approaches to computational thinking: A historical perspective. Tech Trends 1–8.

Computer Science Crosscutting Concepts Interdisciplinary Middle School

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