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Computer science Worksheets and Python Workspaces shared by Coding Pathway teachers. Worksheets cover exam board theory as well as programming. Read any of them in full here. Teachers can copy one into their own lessons and edit it before setting it to a class.
Planning a whole course or unit? Our mapped pages put the teaching sequence in order with the Worksheets that cover it: OCR GCSE Computer Science (J277), Pearson Edexcel GCSE Computer Science (1CP2), OCR A Level Computer Science (H446), Python Turtle for Key Stage 3.
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Recursion Worksheets
3 resources match. Newest first. Opening a resource shows the whole thing, with answers and marking held back.
H446 2.3.1 · Algorithms
Includes OCR H446 2.3.1 Merge sort
Merge sort is the H446 2.3.1 divide-and-conquer example, and the difficulty is rarely the splitting; it is the merge loop, where students lose track of which values have been consumed. This worksheet makes both the recursive structure and every merge-loop state visible before asking for an implementation and a memory trade-off judgement. Students will: - model the recursive split down to base cases and the combination back up - show the complete split and merge states for a small list by hand - trace a merge loop index by index, including the condition that ends it - implement splitting and merging so no unconsumed value is lost - explain the predictable scaling of merge sort against its extra memory demand Inside: 5 explanation cells, 1 multiple-choice question, 1 fill-in-the-blanks cell, 2 written answers, 1 Python task and 1 trace table. 26 marks, about 25 to 40 minutes. Series: H446 2.3.1 · Algorithms, part 7 of 16.
WorksheetSeries · 3 partsH446 2.2.2 · Computational methods
Includes OCR H446 2.2.2 Divide and conquer
Divide and conquer appears in H446 2.2.2 as a method with three named stages, and students can usually list them without being able to trace one. Starting from summing a list, this worksheet builds the divide, solve and combine shape, then asks for a working recursive implementation and a judgement about when a loop would serve better. Students will: - identify the divide, solve and combine stages in a described method - trace recursive calls as a tree and write each returned subtotal back upwards - explain why a call waits rather than disappearing while its children run - implement a recursive method that preserves the original list, handles an empty list and always uses a smaller slice - weigh a recursive design against a loop for very large inputs on a single processor Inside: 7 explanation cells, 1 multiple-choice question, 2 fill-in-the-blanks cells, 1 written answer and 2 Python tasks. 20 marks, about 25 to 35 minutes. Series: H446 2.2.2 · Computational methods, part 3 of 14.
WorksheetSeries · 2 partsH446 2.2.1 · Programming techniques
Includes OCR H446 2.2.1 Recursive functions
Recursion is examined in H446 2.2.1 as a tracing skill and a construction skill at once. This worksheet separates the two directions of a recursive call, the descent into smaller problems and the unwinding of returned values, so students can explain why a function terminates rather than only recognise the pattern. Students will: - distinguish the base case from the recursive case in a supplied function - trace recursive calls alongside the values returned as they unwind - explain termination and the order in which results are combined - write a recursive digit sum using remainder and integer division - repair a recursion that never reaches a base case and justify the repair Inside: 6 explanation cells, 2 multiple-choice questions, 1 fill-in-the-blanks cell, 2 written answers, 1 Python task and 1 trace table. 18 marks, about 25 to 35 minutes. Series: H446 2.2.1 · Programming techniques, part 3 of 14.