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Computational thinking: decomposition, abstraction and algorithms

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レッスンノート

Computational thinking

  • Computational thinking is a way of solving problems so that a computer can help. Its main parts are decomposition, abstraction, pattern recognition and algorithmic thinking.
  • Decomposition: breaking a big problem into smaller, more manageable parts. Planning a school timetable can be split into rooms, teachers, classes and times.
  • Abstraction: removing unnecessary detail to focus on what matters. A map of the Tube shows stations and lines, not every street.
  • Pattern recognition: spotting similarities, so a solution can be reused.

Decomposition

Decomposition

Algorithms

  • An algorithm is a finite, ordered set of unambiguous steps for a task. It terminates for each valid input in the model used here, but different inputs may take different numbers of steps. Algorithms may process stored input and need not request new user input.
  • Algorithms can be shown in plain English, flowcharts or pseudocode.
  • Structure: sequence (steps in order), selection (decisions: IF), iteration (repeating: loops).

What is an algorithm?

What is an algorithm?

Example

  • Algorithm to find the larger of two numbers: input A, input B; if A is greater than B then output A, otherwise output B.

Why it matters

  • Computational thinking helps design programs that are efficient and easy to test and change.

Control structures

  • Sequence follows instructions in order; selection chooses a branch; iteration repeats a body.
  • Example: input a mark, use IF to choose pass/fail, and repeat for each student.
  • Choose relevant details: omit button styling when designing scoring logic, but retain it when designing the interface.

Sequence in algorithms

Sequence in algorithms

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練習問題

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  1. 1.What is an algorithm?

    Easy
    • Aa set of step-by-step instructions to solve a problem
    • Ba type of computer
    • Ca programming language
    • Da hardware part

  2. 2.What is decomposition?

    Easy
    • Abreaking a problem into smaller parts
    • Bhiding details
    • Crepeating steps
    • Dfixing errors

  3. 3.What is abstraction?

    Easy
    • Afocusing on important details and ignoring the rest
    • Bbreaking into parts
    • Crepeating
    • Dtesting

  4. 4.What is pattern recognition?

    Easy
    • Aspotting similarities or trends
    • Bremoving detail
    • Clooping
    • Ddeleting

  5. 5.Which structure repeats instructions?

    Easy
    • Aiteration
    • Bselection
    • Csequence
    • Dinput

  6. 6.Which structure makes a decision?

    Easy
    • Aselection
    • Biteration
    • Csequence
    • Doutput

  7. 7.Which is an example of abstraction?

    Easy
    • Aa Tube map showing stations but not streets
    • Ba list of all streets
    • Ca photograph
    • Da full city plan

  8. 8.Which is an example of decomposition?

    Easy
    • Asplitting a game into graphics, sound, scoring and controls
    • Bwriting one long program
    • Cignoring parts
    • Ddeleting code

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