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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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Graphs and networks
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 Post-order DFS and breadth-first traversal
H446 2.3.1 names post-order depth-first and breadth-first traversal specifically, and each is controlled by a different structure: recursion or an explicit stack for one, a queue for the other. This worksheet produces both orders by hand with the queue state written out, then transfers the same algorithms to a graph where repeats become possible. Students will: - produce post-order depth-first and breadth-first orders for a rooted tree - name the controlling structure behind each traversal and say why it fits - show queue states as a breadth-first traversal proceeds, including an added child - implement both traversals, marking discovered nodes when running on a graph - compare the memory demands and typical uses of the two traversals Inside: 5 explanation cells, 1 multiple-choice question, 1 fill-in-the-blanks cell, 2 written answers and 1 Python task. 29 marks, about 25 to 40 minutes. Series: H446 2.3.1 · Algorithms, part 12 of 16.
WorksheetOCR H446 2.2.2 Visualisation for understanding and planning
Part 12 · H446 2.2.2 · Computational methods
Visualisation earns marks in H446 2.2.2 only when the mapping is explained, so a diagram of labelled boxes will not do. Dependency graphs for a workflow give students something concrete to read, extend and judge, and the worksheet also draws the line between visualisation and abstraction. Students will: - state what each symbol and arrow in a visual representation stands for - read a dependency graph for ordering constraints and for work that could run concurrently - extend a diagram with a new task and explain what the added arrow means - explain how visualisation depends on abstraction without being the same idea - design a visualisation for a software release and evaluate how useful it would be 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 12 of 14.
WorksheetSeries · 2 partsH446 1.4.2 · Data structures
Includes OCR H446 1.4.2 Graphs: concepts and representations
Graph questions in H446 1.4.2 reward precise vocabulary, so this worksheet separates direction from weight and node from edge before any representation is chosen. A collaboration network of people, venues and routes gives students a graph to read accurately, then store as an adjacency list or an adjacency matrix. Students will: - distinguish directed from undirected and weighted from unweighted graphs - use node, edge, path, cycle and connectedness precisely rather than loosely - read the outgoing neighbours and weights of a node from a drawn graph - compare adjacency lists with adjacency matrices for a network with few connections per node - design a one-way weighted route system and justify direction, weight meaning and representation Inside: 7 explanation cells, 2 multiple-choice questions, 1 fill-in-the-blanks cell and 3 written answers. 21 marks, about 45 to 55 minutes. Series: H446 1.4.2 · Data structures, part 7 of 14.