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Computational Thinking: Solving Problems Like a Programmer
Learn the four core ideas of computational thinking, decomposition, pattern recognition, abstraction and algorithms, and how to use them on everyday problems.
Study and Digital Skills
Beginner explainers on scientific method and computing ideas.
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Learn the four core ideas of computational thinking, decomposition, pattern recognition, abstraction and algorithms, and how to use them on everyday problems.
Debugging is a method, not a talent. Learn how to reproduce a problem, isolate the cause, fix it and check the fix, in code or in any process that goes wrong.
Learn to count in base two and see how computers turn numbers, text and images into bits, with small worked examples you can check by hand.
Learn how independent, dependent and controlled variables work, why repeat trials matter, and how to plan a fair test using a simple plant-growth example.
A conceptual tour of the internet: addresses, domain names, packets, routers and servers, and what happens in the moments after you open a web page.
Learn how if statements let a program make decisions and how loops repeat actions, using plain-language explanations and short, checked Python examples.
Why repeated readings differ, how random and systematic errors work, and how to report a measurement with a margin such as 12.2 plus or minus 0.2 cm.
Meet Python's first ideas: values, variables, arithmetic, strings and printing output. Short examples with the exact output you should expect to see.
Follow the scientific method from question to conclusion using a household example of a lamp that will not light, and see how real investigations loop and revise.
Understand version control as saved snapshots of your work, how Git records history with commits, and why it helps writers and students as well as programmers.
An algorithm is a precise list of steps for solving a problem. See what makes a good one using recipes, a number-guessing game and a find-the-largest example.
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