Community

Community resources

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.

  • 438 resources
  • 3 teachers sharing
  • Creative Commons licensed

Artificial intelligence

2 resources match. Newest first. Opening a resource shows the whole thing, with answers and marking held back.

Worksheet

OCR H446 2.3.1 A star and heuristics

Part 14 · H446 2.3.1 · Algorithms

A star is not Dijkstra with relabelled numbers, and H446 2.3.1 expects students to calculate g, h and f and to say what the heuristic is doing to the search. This worksheet works the selection rule through frontier scores, then tests three different heuristics on the same nodes so students can see informativeness and overestimation as separate issues. Students will: - calculate g, h and f for frontier nodes and select the next node from them - recalculate a selection after a cheaper route lowers a node's known cost - compare A star with Dijkstra on goal information, nodes explored and stopping - judge whether given heuristic values would still allow an optimal result - explain what a zero heuristic does to the search and the risk in an overestimate Inside: 6 explanation cells, 1 multiple-choice question, 1 fill-in-the-blanks cell and 3 written answers. 28 marks, about 30 to 45 minutes. Series: H446 2.3.1 · Algorithms, part 14 of 16.

By Coding Pathway · 11 cells · 30 min · CC BY-SA 4.0 · Shared 31 Aug 2026

A LevelOCRAlgorithmsGraphs and networks
Worksheet

1CP2-P-10.1 Artificial intelligence machine learning and robotics

Part 1 · 1CP2-P-10 · AI, personal data and ethical/legal issues

Artificial intelligence (AI) describes systems carrying out tasks associated with intelligent behaviour. Machine learning (ML) is an AI approach that learns patterns from data instead of receiving every decision rule explicitly. Robotics concerns programmable physical machines that sense or act. The categories can overlap without being identical. Students will: - distinguish artificial intelligence, machine learning and robotics - connect sensor input, processing and physical action - classify systems without treating the terms as interchangeable - explain a mechanism in a stated application Inside: 6 explanation cells, 1 fill-in-the-blanks cell, 2 multiple-choice questions and 3 written answers. 13 marks, about 45 minutes. Series: 1CP2-P-10 · AI, personal data and ethical/legal issues, part 1 of 5.

By Coding Pathway · 12 cells · 45 min · CC BY-SA 4.0 · Shared 17 Aug 2026

GCSEEdexcelArtificial intelligencePractice