Computer Science Resources

Computer Science Resources

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Coding and computational thinking are among the skills that will serve students well in the future. Coding goes beyond websites and software – it’s an essential component in finding solutions to everyday problems. Computational thinking has many applications beyond the computer lab or math class – it teaches reasoning, creativity and expression, and is an innovative way to demonstrate content knowledge and see mathematical processes in action.

Why teach computer science in your content area?
Every child should have a chance to learn about algorithms, how to make an app, or how the internet works just like they learn about photosynthesis, the digestive system, or electricity. Every student needs a solid understanding of how the digital world communicates as much as they need to have a grasp on the English language to be productive and prepared citizens in our world economy.

The book, “No Fear Coding” by Heidi Williams states that based on research, there are five reasons why computer sciences are critical for students:
  • Making their thinking visible
  • Sustaining creativity
  • Encouraging computational thinking
  • Fostering future ready skills
  • Empowering students to take action
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“Individualizing education and starting with empathy for those we serve is where innovative teaching and learning begins.” ― George Couros, The Innovator's Mindset: Empower Learning, Unleash Talent, and Lead a Culture of Creativity

Designing Lessons with Computational Thinking?

Computational thinking in the K–12 Computer Science Framework extends beyond the general use of computers or technology in education to include specific skills such as designing algorithms, decomposing problems, and modeling phenomena. If computational thinking can take place without a computer, conversely, using a computer in class does not necessarily constitute computational thinking. For example, a student is not necessarily using computational thinking when he or she enters data into a spreadsheet and creates a chart. However, this action can include computational thinking if the student creates algorithms to automate the transformation of the data or to power an interactive data visualization.
Computational thinking requires understanding the capabilities of computers, formulating problems to be addressed by a computer, and designing algorithms that a computer can execute. The most effective context and approach for developing computational thinking is learning computer science; they are intrinsically connected. Computational thinking is at the heart of the computer science practices and is delineated by the practices below.

1. Decomposition
2. Pattern Recognition
3. Abstraction (Pattern Generalization)
4. Algorithm Design