Modernizing the Practices of Science

A reflection about the journey to Modernize the Practices of Science

I like the A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas (2012) because it has some really clear and insightful practices to better reflect the work that the next generation will likely need to do.

taken from A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas (2012) page 42

The clarity is sparkling! below in blue are some arguments i would like to present

1. Asking questions (for science) and defining problems (for engineering) 
1. The order gives a good sense of the clarity and the nature way people practice science, we ask questions first right?
2. Developing and using models
1. This paragraph gives a strongly grounded reason to develop computer models/simulation as those i have co-created here http://weelookang.blogspot.sg/p/physics-applets-virtual-lab.html  to test hypothetical explanation and improve the models 
1. the construction and use of a wide variety of models and simulations (Open Source Physics for example) to help develop explanations about natural phenomena. Models make it possible to go beyond observables and imagine a world not yet seen. Models enable predictions of the form “if . . .then . . . therefore” to be made in order to test hypothetical explanations. taken from page 50
3. Planning and carrying out investigations
4. Analyzing and interpreting data
5. Using mathematics and computational thinking 
1. words such as 'appropriate' is simply to sweepingly general that it does not reflect the nature of the kinds of scientific practices for next generation, who doesn't use computer today?
2. In science, mathematics and computation 
3. are fundamental tools for representing physical 
4. variables and their relationships. They are 
5. used for a range of tasks, such as constructing 
6. simulations, statistically analyzing data, and recognizing, 
7. expressing, and applying quantitative 
8. relationships. Mathematical and computational 
9. approaches enable predictions of the behavior of 
10. physical systems, along with the testing of such 
11. predictions. Moreover, statistical techniques are 
12. invaluable for assessing the significance of patterns 
13. or correlations. 
taken from page 51
6. Constructing explanations (for science) and designing solutions (for engineering)
7. Engaging in argument from evidence
8. Obtaining, evaluating, and communicating information

here is another pictorial representation that should be included in

taken from A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas (2012) page 45