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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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Algorithms Worksheets
16 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 Designing and representing algorithms
OCR H446 2.3.1 opens with algorithm design, where students must produce finite, testable steps and then move the same logic between a flowchart, pseudocode and program code. This worksheet builds that habit from the start, so students learn that changing the notation must never quietly change what the algorithm does. Students will: - separate a problem statement into inputs, validation, processing and outputs - rewrite the same logic as pseudocode and describe how its decisions appear in a flowchart - keep decision, loop-back and update order identical across representations - design an algorithm for an unfamiliar charging rule with a cap and a rejection condition - choose normal, boundary and invalid test cases with expected outputs Inside: 6 explanation cells, 1 multiple-choice question, 1 fill-in-the-blanks cell and 2 written answers. 20 marks, about 20 to 30 minutes. Series: H446 2.3.1 · Algorithms, part 1 of 16.
WorksheetSeries · 8 partsH446 2.2.2 · Computational methods
Includes OCR H446 2.2.2 Computational solvability and problem recognition
OCR H446 2.2.2 begins with a question students often skip: can this problem be solved computationally at all? Working from a rehearsal-room allocation request, the worksheet teaches them to turn a vague human aim into precise inputs, rules, stored state and testable outputs before any algorithm is chosen. Students will: - identify the inputs, rules, stored state and outputs hidden inside a described need - rewrite an ambiguous requirement so that a program could execute and test it - explain why naming sequence, selection and iteration does not answer a question about computational methods - judge whether a loosely worded request is solvable as stated, and say what information would make part of it computable - recall the central distinctions from memory in a closed-book check Inside: 7 explanation cells, 1 multiple-choice question, 2 fill-in-the-blanks cells and 2 written answers. 20 marks, about 20 to 30 minutes. Series: H446 2.2.2 · Computational methods, part 1 of 14.
WorksheetSeries · 2 partsH446 2.2.1 · Programming techniques
Includes OCR H446 2.2.1 Programming techniques consolidation
Consolidation across the whole of H446 2.2.1, built on a hack-day dashboard that mixes control flow, recursion, scope, parameter modes, debugging and object orientation. No new content is introduced, so the demand is selecting the right technique and supporting each explanation with evidence, with the planning support withdrawn as students work through it. Students will: - select an appropriate technique for a task and state a one-line plan for it - trace a recursive function and the value it returns - identify a range fault in a loop header, explain its effect and correct it - implement a class combining stored state, a calculation and a decision - justify an object-oriented design in which polymorphism produces type-specific output Inside: 4 explanation cells, 1 multiple-choice question, 3 written answers, 1 Python task and 1 trace table. 19 marks, about 25 to 40 minutes. Series: H446 2.2.1 · Programming techniques, part 13 of 14.
WorksheetOCR H446 2.1.5 Thinking concurrently
Part 1 · H446 2.1.5 · Thinking concurrently
Concurrency in OCR H446 2.1.5 is judged by dependencies and shared state rather than by speed alone. A live youth-media broadcast lets students decide what can safely overlap, what must wait for data, and what a single shared status flag can hide. Students will: - distinguish tasks that may overlap from tasks tied together by a data dependency - justify a pair of broadcast tasks that must stay in strict order - explain how two tasks writing one shared status value cause premature publishing - describe a separate-flag design that prevents that failure - evaluate concurrent processing with benefits, trade-offs and a justified conclusion Inside: 6 explanation cells, 1 multiple-choice question, 2 fill-in-the-blanks cells and 3 written answers. 25 marks, about 25 to 35 minutes. Series: H446 2.1.5 · Thinking concurrently, part 1 of 1.
WorksheetOCR H446 2.1.1 Thinking abstractly: purpose and relevant detail
Part 1 · H446 2.1.1 · Thinking abstractly
OCR H446 2.1.1 treats abstraction as a purposeful filter, not simply as making something smaller. Starting from a city cycling map and ending with an event map that must serve step-free routes, this worksheet has students decide what to keep and what to leave out from a stated purpose. Students will: - define abstraction in terms of the purpose a model has to serve - decide which details to retain and which to suppress for a named user decision - explain a benefit of abstraction when developing a real system - repair a weak model with one justified removal and one justified addition - devise a model for a new context and justify an inclusion and an exclusion Inside: 7 explanation cells, 1 multiple-choice question, 2 fill-in-the-blanks cells and 3 written answers. 22 marks, about 25 to 35 minutes. Series: H446 2.1.1 · Thinking abstractly, part 1 of 2.
WorksheetSeries · 2 partsH446 2.1 · Elements of computational thinking
Includes OCR H446 2.1 Integrated computational-thinking exam transition
The assessment for the whole of OCR H446 2.1: one city arts-trail app, and all five computational-thinking modes examined inside it, from inputs and abstraction through caching, reuse, decomposition, ordering, decisions and concurrency. Students work closed-book, with correctness held until teacher review. Students will: - select and apply the right computational-thinking mode without being told which it is - specify inputs, outputs and missing preconditions for an unfamiliar service - devise an abstraction and state the limitation its omissions create - evaluate a cache policy and a component-reuse decision in the same system - decompose the system, order its sub-procedures and judge which work may overlap Inside: 2 explanation cells, 1 multiple-choice question, 11 written answers and 1 trace table. 54 marks, about 70 to 85 minutes. Series: H446 2.1 · Elements of computational thinking, part 1 of 2.
WorksheetOCR H446 1.3.2 Indexing and referential integrity
Part 7 · H446 1.3.2 · Databases
Indexing and referential integrity are easily blurred together, so this H446 1.3.2 worksheet keeps them apart: one is about finding data quickly, the other about keeping the links between tables meaningful. Students trace lookups and parent-child operations, then weigh what an index costs to maintain. Students will: - explain how an index supports retrieval in a large table - decide whether an operation leaves every foreign key pointing at a record that exists - explain why a particular insertion, deletion or update would be rejected - weigh search speed against storage and update cost for a proposed index - design a safe procedure for deleting a record that other records still refer to Inside: 7 explanation cells, 2 multiple-choice questions, 2 fill-in-the-blanks cells and 3 written answers. 29 marks, about 25 to 40 minutes. Series: H446 1.3.2 · Databases, part 7 of 13.
WorksheetSeries · 6 partsH446 1.2.3 · Software development
Includes OCR H446 1.2.3 Waterfall lifecycle and spiral model
H446 1.2.3 asks not what waterfall and spiral are called but what their movement changes for a project. This worksheet traces a linear route and a risk-driven cycle against contrasting briefs, so iteration, risk and change are argued as consequences rather than as labels. Students will: - follow the stages of a waterfall lifecycle and the repeating structure of a spiral cycle - explain a benefit and a drawback of waterfall for a project with fixed, signed-off rules - design a first spiral cycle with an objective, a major risk and a risk-reduction activity - explain how evidence from one cycle changes the plan for the next - compare both routes for a project carrying safety and integration risk, then recommend one Inside: 6 explanation cells, 1 multiple-choice question, 2 fill-in-the-blanks cells and 4 written answers. 36 marks, about 45 to 55 minutes. Series: H446 1.2.3 · Software development, part 1 of 6.
WorksheetSeries · 5 parts1CP2-CT-8 · Tracing, debugging, sorting and searching
Includes 1CP2-CT-8.1 Formal trace tables and variable state
A trace table records how an algorithm's state changes while it runs. Examiners use traces to check that you can follow sequence, selection and iteration systematically. A trace is evidence, not a guess at the final output. Students will: - record changing state, conditions and output in execution order - complete a formal trace without treating blanks as zero - distinguish a stored value from printed output - explain evidence from a trace precisely Inside: 6 explanation cells, 1 fill-in-the-blanks cell, 3 multiple-choice questions, 3 written answers and 1 trace table. 12 marks, about 45 minutes. Series: 1CP2-CT-8 · Tracing, debugging, sorting and searching, part 1 of 5.
WorksheetSeries · 4 parts1CP2-CT-1 · Programming foundations
Includes 1CP2-CT-1.1 Problems, algorithms, sequence and IPO
The opening Computational thinking worksheet, establishing what an algorithm is before any Python is written. Students will: - tell an algorithm apart from a restatement of the problem - say what makes a set of steps followable by someone else - put steps into a sequence that can actually be carried out - label the input, processing and output stages of a task - write and then improve a short informal algorithm Inside: 9 explanation cells, 2 multiple-choice questions, 4 fill-in-the-blanks cells and 2 written answers. 20 marks, about 45 minutes. Series: 1CP2-CT-1 · Programming foundations, part 1 of 7.
Worksheet1CP2-CT-7.4 Structured programming problem solving
Part 4 · 1CP2-CT-7 · Subprograms, scope and libraries
The structured problem-solving worksheet, working from a stated requirement to a tested program built from cohesive functions. Students will: - state the inputs, processes and outputs a requirement implies - trace a function call to check it returns what the caller needs - explain a boundary result produced by selection inside a function - choose a boundary test and say what it checks - identify and correct a runtime failure on an empty list Inside: 7 explanation cells, 2 multiple-choice questions, 1 Python task, 1 trace table and 4 written answers. 17 marks, about 45 minutes. Series: 1CP2-CT-7 · Subprograms, scope and libraries, part 4 of 5.
WorksheetSeries · 3 partsJ277 2.1.2 · Tracing and refining algorithms
Includes J277 2.1.2 Completing, correcting and refining algorithms
The OCR question types that hand students an algorithm to complete, correct or refine. Students will: - work from the stated purpose and test data rather than guessing - complete missing statements in an algorithm - find and correct a logic error in an accumulator - validate an inclusive range correctly - refine an algorithm to meet a new requirement Inside: 7 explanation cells, 3 runnable Python tasks, 2 multiple-choice questions, 1 fill-in-the-blanks cell and 2 written answers. 23 marks, about 60 minutes. Series: J277 2.1.2 · Tracing and refining algorithms, part 1 of 3.
WorksheetSeries · 4 partsJ277 2.1.3 · Searching and sorting
Includes J277 2.1.3 Linear and binary searching
The two search algorithms in OCR J277, understood and applied rather than memorised as code. Students will: - describe the steps of a linear search - describe the steps of a binary search - state the prerequisite binary search depends on - apply both algorithms to given data - recognise each algorithm from code Inside: 5 explanation cells, 2 runnable Python tasks, 3 multiple-choice questions and 3 written answers. 16 marks, about 45 minutes. Series: J277 2.1.3 · Searching and sorting, part 1 of 4.
WorksheetSeries · 5 partsJ277 Paper 2 · Exam transition
Includes J277 2 Paper 2 exam language and response precision
How OCR Paper 2 is structured, and what each question's wording asks you to produce. Students will: - describe what Section A and Section B each assess - decide the response form a question requires - turn a vague answer into one that earns the marks - write a programming response with the precision a marker needs - use a repeatable checking routine before moving on Inside: 6 explanation cells, 1 runnable Python task, 1 multiple-choice question, 1 fill-in-the-blanks cell and 3 written answers. 18 marks, about 45 minutes. Series: J277 Paper 2 · Exam transition, part 1 of 5.
WorksheetSeries · 2 partsJ277 2.1.1-2.1.2 · Computational thinking and algorithms
Includes J277 2.1.2 Inputs, processes, outputs and decomposition
Defining a problem before writing any code, using the input-process-output model and decomposition. Students will: - define a problem using the input-process-output model - decompose a large problem into smaller testable parts - read and complete a structure diagram - identify inputs, processes and outputs in running code - explain why decomposition makes testing easier Inside: 5 explanation cells, 1 runnable Python task, 2 multiple-choice questions, 1 fill-in-the-blanks cell and 4 written answers. 20 marks, about 45 minutes. Series: J277 2.1.1-2.1.2 · Computational thinking and algorithms, part 2 of 3.
WorksheetSeries · 2 partsJ277 2.2.3 · Applied programming
Includes J277 2.2.3 Random number generation
Random number generation in an algorithm, and turning a requirement into the correct inclusive bounds. Students will: - use random.randint() with inclusive bounds - turn a stated requirement into the correct bounds - map random integers onto outcomes - generate several values in one program - explain why the program behaves differently each run Inside: 5 explanation cells, 3 runnable Python tasks, 2 multiple-choice questions and 2 written answers. 14 marks, about 45 minutes. Series: J277 2.2.3 · Applied programming, part 4 of 5.