# Science Practices: Using Mathematics and Computational Thinking

#### Example Questions:

- How do the qualitative and quantitative data support one another?
- What is the rate of change of this variable?
- Characterize the dataset by finding the mean, median, and mode. How do these vary? What opportunities for deeper understanding of these data do we miss if we only report on the mean, median, or mode?

#### MY NASA DATA Lesson Plans:

- Basic Line Plots (Grade 3-5)
- Sailing Trip (Grade 3-5)
- Cold, Clouds, and Snowflakes (Grade 4-7)
- Comparing Graphs of Temperature and Radiation (Grade 6-8)
- Correlation of Variables by Graphing (Grade 6-10)
- Earths Energy Budget-Seasonal Cycles (Grade 9-12)
- Using Radiosonde Data From a Weather Balloon Launch (Grade 7-12)
- Validation of Stratospheric Ozone (Grade 9-12)

*Although there are differences in how mathematics and computational thinking are applied in science and in engineering, mathematics often brings these two fields together by enabling engineers to apply the mathematical form of scientific theories and by enabling scientists to use powerful information technologies designed by engineers. Both kinds of professionals can thereby accomplish investigations and analyses and build complex models, which might otherwise be out of the question.*(NRC Framework, 2012, p 65)

K-2: Mathematical and computational thinking in K-2 builds on prior experiences and progresses to recognizing that mathematics can be used to describe the natural and designed world(s).

- Use counting and numbers to identify and describe patterns in the natural and designed world(s).
- Describe, measure, an/or compare quantitative attributes of different objects and display the data using simple graphs.

3-5: Mathematical and computational thinking in 3-5 builds on K-2 experiences and progresses to extending quantitative measurements to a variety of physical properties and using computation and mathematics to analyze data and compare alternative design solutions.

- Organize simple data sets to reveal patterns that suggest relationships.

6-8: Mathematical and computational thinking in 6-8 builds on K-5 experiences and progresses to identifying 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 or computational representations of phenomena to describe explanations. (HS-ESS1- 4)(HS-ESS3- 6)
- Create a computational model or simulation of a phenomena, designed device, process, or system. (HS-ESS3- 3)

9-12: Mathematical and computational thinking in 9-12 builds on K-8 experiences and progresses to using algebraic thinking and analysis, a range of linear and nonlinear functions including trigonometric functions, exponentials and logarithms, and computational tools for statistical analysis to analyze, represent, and model data. Simple computational simulations are created and used based on mathematical models of basic assumptions.