Autonomous Cave Exploration Drone Algorithm

Posted on July 14, 2026 by Administrator Posted in Computer Science, Python - Intermediate, Python Challenges, Solved Challenges

Imagine being tasked with exploring a vast underground cave system where no human has ever been before. Narrow passages, uneven ceilings, jagged rocks and sudden drops make it far too dangerous for people to enter. Instead, scientists use autonomous drones to safely explore these hidden environments, mapping caves and collecting valuable data without putting anyone at risk.

In this activity, you’ll investigate the Python code used to control a cave exploration drone. Rather than being controlled by a pilot, the drone uses three infra-red distance sensors to detect obstacles in front of it. One sensor points diagonally upwards, one points straight ahead, and one points diagonally downwards. As the drone flies through the cave, these sensors constantly monitor the shape of the ceiling and the ground.

The Python program processes the information from the three sensors many times every second. If one of the sensors detects that the drone is getting too close to the cave walls, the program decides whether the drone should climb, descend or continue flying straight ahead. By repeatedly reading the sensors and adjusting its movement, the drone can navigate safely through the cave while avoiding collisions.

Here is the flowchart for the algorithm to control the drone:

As you work through the code, you will discover how programming, sensors and decision-making algorithms combine to create an autonomous system capable of reacting to its environment in real time. See if you can understand how the drone makes its decisions, then experiment with the code to improve its navigation or add your own ideas!

Python Code

Your Turn

As part of a space exploration project, an autonomous drone spacecraft will be sent on a journey through Jupiter’s asteroid belt. Your task is to reuse the Python code developed for the cave-exploration drone and adapt it for this new mission. Instead of detecting the cave’s ceiling and ground, the drone must use its three laser sensors to identify approaching asteroids and automatically adjust its vertical position to avoid a collision. Can you modify the existing navigation algorithm so the spacecraft can travel safely through space?

Python Code

You will need to update the code from line 48.

Solution...

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Sailing the Seven Seas (Python Challenge)

Posted on July 14, 2026 by Administrator Posted in Computer Science, Python - Advanced, Python Challenges, Solved Challenges

Long before radios and GPS, sailors relied on teamwork, experience and a good rhythm to keep a ship moving. One tradition that became famous around the world was the sea shanty. These songs were sung by crews as they hoisted sails, pulled ropes and weighed anchor, helping everyone work together in time. Many sea shanties also told stories of dangerous storms, distant lands and exciting adventures across the oceans.

Legend tells of a fearless pirate captain who sailed far beyond the known world. Wherever he travelled, his crew could be heard singing their favourite sea shanty, “Sailing the Seven Seas.” The song became so well known that sailors claimed they could recognise the pirate’s ship long before it appeared on the horizon!

According to the legend, when the pirate’s treasure was finally discovered, two mysterious pieces of parchment were found inside the treasure chest. The first parchment contained the lyrics to Sailing the Seven Seas… or so it seemed. Instead of words, it was filled with strange numbers. The second parchment contained a table matching each number to a word or short phrase.

At first, historians thought the pirate had created a secret code to stop rival pirates from stealing his famous song. However, computer scientists looking at the parchments noticed something interesting. Many words and phrases in the shanty were repeated over and over again, such as “Heave ho!”, “Raise the sail!” and “We are sailing the seven seas!”. Rather than writing these long phrases every time, the pirate had simply replaced them with short numbers and kept a lookup table on the second parchment.

Today, computers use a very similar idea when compressing data. Instead of storing the same information repeatedly, common words, patterns or sequences can be stored once and replaced with shorter references. Because the original text can be reconstructed perfectly using the lookup table, this is known as lossless compression.

In this challenge, you’ll become the pirate’s programmer! Your task is to complete the Python code provided to you by writing a function that uses a hash table (dictionary) to replace each number with its corresponding word or phrase, reconstructing the original lyrics to Sailing the Seven Seas. Can you successfully decode the pirate’s legendary sea shanty?

Python Code

Solution...

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A* Short Path Algorithm Interactive Task

Posted on July 7, 2026 by Administrator Posted in A Level Concepts, A Level Quiz, Algorithms, Computer Science, Computing Concepts, Quizzes

Finding the shortest route between two places might sound like a simple task, but when a network contains hundreds or even millions of possible paths, computers need an efficient way to decide which route to follow. This is where search algorithms come in.

You may already have explored Dijkstra’s Shortest Path Algorithm, which guarantees finding the shortest path by systematically examining the graph. While Dijkstra’s algorithm is very reliable, it can sometimes spend time investigating routes that clearly lead away from the destination.

The A* (pronounced “A star”) algorithm improves on this idea by introducing a heuristic — an estimate of how far each node is from the destination. Instead of only considering the distance already travelled, A* also takes into account the estimated distance remaining. At each step, it chooses the node with the lowest combined value:

Total Cost = Distance from the Start + Estimated Distance to the Goal

By using this extra information, A* can focus its search towards the target instead of exploring every possible direction. In many real-world situations, this makes it significantly faster than Dijkstra’s algorithm while still guaranteeing the shortest path, provided the heuristic never overestimates the remaining distance.

Because of its efficiency, A* is one of the world’s most widely used pathfinding algorithms. It powers route-planning software, satellite navigation systems, robotics, video games, artificial intelligence, warehouse automation, and many other applications where computers need to navigate efficiently through complex environments.

In this interactive activity, you will practise applying the A* algorithm to a series of weighted directed graphs. For each challenge, use the heuristic values shown on the graph to calculate the total cost for each node, complete the A* table step by step, and determine the shortest path and its total distance. Compare your answers with the worked solution to build confidence in using one of the most important search algorithms in computer science.
A* Short Path AlgorithmOpen this activity in a New Window

Dijkstra Short Path Algorithm Interactive Task

Posted on July 7, 2026 by Administrator Posted in A Level Concepts, A Level Quiz, Algorithms, Computer Science, Computing Concepts, Interactive Tools, Quizzes

Every time you use a sat nav, plan a journey on a map app, or search for the fastest route across a transport network, you are using ideas from graph theory. A road map can be represented as a graph: towns, junctions or stations are nodes, and the roads, railways or paths between them are edges. If each edge has a value, such as distance, time or cost, we can use an algorithm to find the shortest route.

One of the most famous algorithms for solving this problem is Dijkstra’s Shortest Path Algorithm. It was created in 1956 by Dutch computer scientist Edsger W. Dijkstra. The story goes that Dijkstra came up with the algorithm while sitting in a café in Amsterdam, trying to find an elegant way to calculate the shortest route between two cities. He later said that he designed it in about twenty minutes, without even using pencil and paper!

The algorithm works by starting at one node and gradually building up the shortest known distance to every other node in the graph. At each step, it chooses the unvisited node with the smallest temporary distance, marks it as visited, and updates the distances to its neighbouring nodes. By repeating this process, the algorithm eventually finds the shortest path from the starting node to the destination.

Dijkstra’s Algorithm is still important today. It has influenced route-planning systems, network routing, robotics, logistics, games, and many other areas of computer science. It is also a great example of how a problem can be solved by breaking it down into clear, repeatable steps.

In this interactive activity, you will practise applying Dijkstra’s Algorithm to a range of different weighted directed graphs. For each challenge, study the graph carefully, complete the table step by step, and identify the shortest path and total distance from the starting node to the target node. Use the check button to test your answers and improve your understanding of how the algorithm works.

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Vector Based Graphics Editor

Posted on July 2, 2026 by Administrator Posted in Computer Science, Computing Concepts, Interactive Tools

Not every digital image is stored as a collection of coloured pixels. While photographs and pixel art are usually saved as bitmap images, many logos, icons, maps and illustrations are created using a completely different method called vector graphics.

Instead of storing the colour of every individual pixel, a vector graphic is made up of mathematical objects such as lines, rectangles, circles, triangles and curves. Each object is stored as a set of instructions describing its position, size, colour, outline and other properties. This means the computer recreates the image by drawing these shapes whenever it is displayed.

One of the biggest advantages of vector graphics is that they can be scaled to any size without losing quality. Whether a logo is printed on a business card or stretched across a giant billboard, it remains perfectly sharp because the computer simply redraws the shapes using the stored mathematical instructions. In contrast, enlarging a bitmap image eventually reveals the individual pixels, making the picture appear blurry or blocky.

Our interactive Vector Graphics Simulator lets you explore these ideas by creating your own vector artwork from simple shapes. Add rectangles, circles, triangles and lines, then experiment with changing their size, position, colours, rotation and layering. You can drag objects around the canvas, resize them, reorder them and instantly see how the generated SVG (Scalable Vector Graphics) code changes to describe your drawing.

As you experiment, compare your experience with creating bitmap images. Rather than editing individual pixels, you’ll be editing the properties of objects and discovering how a complete image can be represented using just a small collection of mathematical instructions. You’ll also see why vector graphics often produce much smaller files for simple illustrations and why they are widely used for company logos, diagrams, technical drawings, maps, icons and user interface graphics.

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Bitmap Image Simulator

Posted on July 2, 2026 by Administrator Posted in Computer Science, Computing Concepts, GCSE Concepts, Interactive Tools

Every photo, icon, emoji and piece of pixel art you see on a computer has to be stored digitally. But have you ever wondered how a computer can save an image using nothing more than 1s and 0s?

One of the most common ways of storing images is as a bitmap. A bitmap image is made up of thousands (or even millions) of tiny coloured squares called pixels. Each pixel stores a numerical value that represents its colour, and together these pixels combine to create the picture you see on the screen.

The quality of a bitmap image depends on two important factors. Resolution is the number of pixels used to create the image. A higher resolution contains more pixels, allowing the picture to show finer detail, but it also increases the amount of data that must be stored. Colour depth determines how many bits are used to store the colour of each pixel. A greater colour depth allows many more colours to be represented, producing smoother and more realistic images, but again increases the file size.

Bitmap images also contain metadata. This is information about the image rather than the picture itself. Metadata can include the image width and height, the colour depth, the file format and, depending on the file type, additional information such as the date the image was created, the device used to capture it or even the author’s details.

Our interactive Bitmap Image Storage Simulator lets you explore these ideas for yourself. Choose from a selection of classic pixel-art sprites or create your own image by colouring individual pixels. Experiment with different resolutions and colour depths, watch the binary data that is generated for every pixel, investigate how the file size changes, and discover the metadata that must be stored alongside the image.

Bitmap Image SimulatorOpen Simulator in a New Window

Sound Sampling Simulator

Posted on June 30, 2026 by Administrator Posted in Computer Science, Computing Concepts, GCSE Concepts

Have you ever wondered how your computer or smartphone stores music, podcasts or voice recordings? Although sound travels through the air as a continuous (analogue) wave, computers can only store digital data made up of 1s and 0s. So how does a smooth sound wave become a digital audio file?

The answer lies in a process called sound sampling. During sampling, the computer measures the height (amplitude) of the sound wave at regular intervals. These measurements are then rounded to the nearest value that can be stored using a fixed number of bits. The two most important factors that affect the quality of the recording are the sample rate (how often the sound is measured) and the bit depth (how many different amplitude values can be stored). Higher sample rates and greater bit depths produce more accurate recordings, but they also create much larger files.

Our interactive Sound Sampling Simulator lets you explore this process step by step. Watch a smooth analogue sound wave being sampled, see how the measurements are converted into digital values, examine the binary data that is generated, and discover how changing the sample rate or bit depth affects both the quality of the recording and the final file size.

Experiment with different settings, compare low-quality and high-quality recordings, and see for yourself the trade-off between sound quality and storage space. By the end of the activity, you’ll have a much better understanding of how digital audio is created and why these concepts are so important in Computer Science.

Sound Sampling SimulatorOpen Simulator in a New Window

Interactive Trace Table Challenge

Posted on June 29, 2026 by Administrator Posted in Algorithms, Algorithms (GCSE), Coding Quiz, Computer Science, Computing Concepts, GCSE Concepts, GCSE Quiz, Quizzes

Put your programming skills to the test with this interactive Trace Table Challenge! Whether you’re learning to code or preparing for your GCSE Computer Science exams, trace tables are one of the most useful techniques for understanding exactly how an algorithm works.

A trace table lets you follow a program one line at a time, recording how the values of variables change as each instruction is executed. By tracing an algorithm step by step, you can predict the program’s output, spot logical errors before writing any code, and develop a much deeper understanding of sequencing, selection (IF statements) and iteration (FOR and WHILE loops).

This interactive activity contains a series of progressively more challenging algorithms. Your task is to complete the trace table by recording the values of variables, the results of conditions and any output produced by the program. If you get stuck, you can watch the built-in animation to see the algorithm execute line by line before having another go yourself.

Trace Table ChallengesOpen Quiz in a New Window

CSS Code Builder

Posted on June 26, 2026 by Administrator Posted in A Level Concepts, A Level Quiz, Coding Quiz, Computer Science, Quizzes

Put your knowledge of the main CSS selectors and properties to the test with this interactive CSS Selector & Property Builder! Complete a series of drag-and-drop challenges to demonstrate your skills in styling HTML web pages using CSS. Choose the most appropriate selectors to target elements on the page and match them with the correct CSS properties to achieve the required formatting. With instant feedback, a live preview and the HTML code displayed alongside each challenge, this activity is a fun and engaging way to practise the essential CSS skills needed to create attractive and well-designed websites.

CSS Code BuilderOpen Quiz in a New Window

HTML Tag Builder

Posted on June 26, 2026 by Administrator Posted in A Level Concepts, A Level Quiz, Coding Quiz, Computer Science, HTML, CSS & JavaScript, Quizzes

Put your knowledge of the main HTML tags to the test with this interactive HTML Tag Builder! Complete a series of drag-and-drop challenges to demonstrate your skills in building the HTML code needed to create basic web pages. Practise using headings, paragraphs, hyperlinks, images, lists, tables and form controls such as text boxes, checkboxes, radio buttons and drop-down lists. With instant feedback and a live preview of the web page you’re creating, this activity is a fun and engaging way to learn and revise the fundamental building blocks of HTML.

HTML Tag BuilderOpen Quiz in a New Window

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