# Exploring the Science Framework and NGSS: Computational Thinking in the Science Classroom

## Article excerpt

"Computational thinking is a fundamental skill for everyone, not just for computer scientists. To reading, writing, and arithmetic, we should add computational thinking to every child's analytical ability" (Wing 2006, p. 33).

A Fram ework for K-12 Science Education identi-fies eight practices as "essential elements of the K-12 science and engineering curriculum" (NRC 2012, p. 49). These practices are embedded in the Next Generation Science Standards (NGSS) (NGSS Lead States 2013), where they are wedded closely to core ideas in the science disciplines.

Most of the practices, such as Developing and Using Models, Planning and Carrying Out Investigations, and Analyzing and Interpreting Data, are well known among science educators. In contrast, Using Mathematics and Computational Thinking, specifically "computational thinking," may be less familiar. The vision of computational thinking as a powerful intellectual tool is described in the Framework as follows:

```   Since the mid-20th century, computational theories, information
and computer technologies, and algorithms have revolutionized
virtually all scientific and engineering fields. These tools and
strategies allow scientists and engineers to collect and analyze
large data sets, search for distinctive patterns, and identify
relationships and significant features in ways that were previously
impossible. They also provide powerful new techniques for employing
mathematics to model complex phenomena--for example, the circulation
of carbon dioxide in the atmosphere and ocean (NRC 2012, p. 64).
```

[ILLUSTRATION OMITTED]

When considering the different forms of computational thinking suggested in this description, we should also reflect on how computational thinking differs from mathematical thinking. Students develop mathematical thinking when they approach a new situation with mathematical skills at their disposal. Similarly, they develop computational thinking when they approach a new situation with an awareness of the many ways that computers can help them visualize systems and solve problems. Many students have already begun their journey into computational thinking through informal use of computers. Teachers aware of the features of computational thinking can leverage students' informal understanding and take students to the next level of knowledge and skill.

One way to understand computational thinking is to look at capabilities that can be considered mathematical thinking, those that can be considered computational thinking, and those capabilities that are both. The Venn diagram (itself a mathematical tool) in Figure 1 shows how we (the authors) see the relationship between mathematical and computational thinking.

[FIGURE 1 OMITTED]

As illustrated in Figure 1, analyzing and interpreting data is just one of several capabilities common to both mathematical and computational thinking. Others are problem solving, modeling, and statistics and probability.

The NGSS describes the practice of mathematics and computational thinking for middle school as follows:

```   "Mathematical and computational thinking in [grades] 6-8 builds on
K-5 experiences and progresses to identify patterns in large data
sets and using mathematical concepts to support explanations and
arguments.
* Use digital tools (e.g., computers) to analyze very large data
sets for patterns and trends.
* Use mathematical representations to describe and/or support
scientific conclusions and design solutions.
* Create algorithms (a series of ordered steps) to solve a problem.
* Apply mathematical concepts and/or processes (e.g., ratio, rate,
percent, basic operations, simple algebra) to scientific and
engineering questions and problems.
* Use digital tools and/or mathematical concepts and arguments to
test and compare proposed solutions to an engineering design
problem. … ```
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