Computational Thinking: Difference between revisions

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[[file:computation.png|right|frame|Computational thinking, problem-solving and programming<ref>http://www.flaticon.com/</ref>]]
[[file:computation.png|right|frame|Computational thinking, problem-solving and programming<ref>http://www.flaticon.com/</ref>]]


== Understandings ==  
== What you need to know ==  
Computational thinking (abbreviated to CT) is an analytical process that can be broken down into four elements: Abstraction; Decomposition; Algorithms; and Pattern recognition.


Computational thinking (abbreviated to CT) is an analytical process.
Students must be able to explain (in the context of Computational thinking to analyse a given problem):  
Students must be able to explain (in the context of Computational thinking to analyse a given problem):  
# [[Abstraction]]
# [[Abstraction]]
# [[Decomposition]]
# [[Decomposition]]
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Computational thinking is essential for the development of computational solutions which may or may not be computer-based.
Computational thinking is essential for the development of computational solutions which may or may not be computer-based.
Students must be able to demonstrate:
Students must be able to demonstrate:


# an approach to any given problem from a computational thinking point of view.
# an approach to any given problem from a [[computational thinking point of view]].




Computational thinking is a problem-solving process used across multiple disciplines, and not just in computer science.
Computational thinking is a problem-solving process used across multiple disciplines, and not just in computer science.
Students must be able to apply:
Students must be able to apply:


# computational thinking to non-computer-based activities.
# [[computational thinking]] to non-computer-based activities.






Computational thinking includes algorithmic thinking. Algorithmic thinking is the basis of solving problems through developing algorithms.
Computational thinking includes algorithmic thinking. Algorithmic thinking is the basis of solving problems through developing algorithms.
Students must be able to construct:


Students must be able to construct:
# [[algorithms]] that address a given problem and evaluate whether a given algorithm would solve a given problem.
 
== Standards ==
# explain Abstraction
# explain Decomposition
# explain pattern recognition
# explain algorithms
# demonstrate an approach to any given problem from a computational thinking point of view
# apply computational thinking to non-computer-based activities
# construct algorithms that address a given problem
# evaluate whether a given algorithm would solve a given problem
 
== References ==
<references />


[[algorithms]] that address a given problem and evaluate whether a given algorithm would solve a given problem.
[[Category:2024 IB DP]]

Latest revision as of 09:40, 4 December 2022

Computational thinking, problem-solving and programming[1]

What you need to know[edit]

Computational thinking (abbreviated to CT) is an analytical process. Students must be able to explain (in the context of Computational thinking to analyse a given problem):

  1. Abstraction
  2. Decomposition
  3. Algorithms
  4. Pattern recognition


Computational thinking is essential for the development of computational solutions which may or may not be computer-based. Students must be able to demonstrate:

  1. an approach to any given problem from a computational thinking point of view.


Computational thinking is a problem-solving process used across multiple disciplines, and not just in computer science. Students must be able to apply:

  1. computational thinking to non-computer-based activities.


Computational thinking includes algorithmic thinking. Algorithmic thinking is the basis of solving problems through developing algorithms. Students must be able to construct:

  1. algorithms that address a given problem and evaluate whether a given algorithm would solve a given problem.

Standards[edit]

  1. explain Abstraction
  2. explain Decomposition
  3. explain pattern recognition
  4. explain algorithms
  5. demonstrate an approach to any given problem from a computational thinking point of view
  6. apply computational thinking to non-computer-based activities
  7. construct algorithms that address a given problem
  8. evaluate whether a given algorithm would solve a given problem

References[edit]