Topic pathway
Algorithms
Computational thinking, searching, sorting, flowcharts, pseudocode, and trace tables.
Exam-board information
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Specification section
Computational thinking
Decomposition, abstraction and algorithmic thinking. Pattern recognition can support a general solution.
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Lesson 01
Decomposition: Breaking Problems Down
Identify sensible sub-problems in a larger task.
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Lesson 02
Abstraction: Keeping What Matters
Identify relevant details in a scenario.
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Lesson 03
Pattern Recognition and Algorithmic Thinking
Identify the inputs, processes and outputs of a problem.
Specification section
Designing, creating and refining algorithms
Pseudocode, flowcharts, trace tables, dry runs, and improving algorithm logic.
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Lesson 01
Writing Clear Pseudocode
Identify sequence, selection and iteration in a written requirement.
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Lesson 02
Flowcharts and Algorithm Paths
Identify and use the standard flowchart symbols, including sub programs.
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Lesson 03
Trace Tables for Variables
Follow an algorithm line by line and record meaningful state changes.
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Lesson 04
Refining an Algorithm
Locate logic errors, ambiguity and unsafe boundary behaviour.
Specification section
Searching and sorting algorithms
Linear search, binary search, bubble sort, merge sort, and insertion sort concepts.
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Lesson 01
Linear Search
Explain how linear search checks an unsorted list and terminates.
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Lesson 02
Binary Search
Explain why binary search requires sorted data.
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Lesson 03
Bubble Sort
Explain adjacent comparisons, swaps, passes and the shrinking upper bound.
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Lesson 04
Insertion Sort
Explain the current item and the growing sorted region.
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Lesson 05
Merge Sort
Explain splitting, base cases and merging in divide-and-conquer order.