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B 1.1.2 Computational Thinking
Computational thinking is a problem-solving approach that involves breaking down complex problems into smaller, more manageable parts (decomposition), identifying patterns within data (pattern recognition),...
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B 1.1.3 Applying computational thinking
Dive into the world of Computational Thinking (CT), where problem-solving meets computer science! Discover how CT's core concepts – decomposition, pattern recognition, abstraction, and algorithmic design...
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1.2 Human interaction with the system
This section discusses human interaction with systems, focusing on usability and accessibility. It identifies common usability problems with digital devices and systems and suggests methods to improve...
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1.2 Components of a computer system
This section covers the definitions of key terms such as hardware, software, peripheral, network, and human resources. It also describes the various roles a computer can play in a networked world, including...
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1.2 System design and analysis
This section covers planning a new IT system. It emphasises identifying stakeholders, obtaining requirements, and gathering necessary information. The importance of illustrating system requirements, using...
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Why fixing bugs is better than writing code Free
We have all been there. You introduce a new programming concept like while loops, and give your students a blank screen and a prompt: "Write a program that counts to ten." Five minutes later, half the...
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B 2.5 File Processing
This section covers saving data permanently in programs using file processing. Key operations include opening (read, write, append modes), reading from, writing to, and closing text files. Mentions relevant...
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B 2.4 Programming algorithms
This section covers algorithmic thinking in programming: efficiency (Big O notation), linear/binary search (construction, tracing, efficiency), bubble/selection sort (construction, tracing, time/space...
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B 2.3 Programming constructs
This section focuses on programming constructs for controlling program flow: sequence (order of execution), selection (if/else), and iteration (loops). Also covers modularisation using functions for reusable,...
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B 2.2 Data structures
This section covers data structures: static (arrays) vs dynamic (lists). Explores 1D/2D arrays & lists, plus abstract data types: stacks (LIFO: push, pop, peek, isEmpty) and queues (FIFO: enqueue, dequeue,...