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Projects for using Flock XR to introduce A-level Computer Science concepts

Pathfinding Game

The goal of this game is to find the shortest path between two nodes of a graph. The starting node is shown in the orange, and the target node is shown in purple. You can choose your path by walking to the orange node to highlight it, and then walking to each node on your chosen path in order, until you reach the purple node.

This project is intended to be used to show students an example use of Dijkstra's shortest path algorithm. Initially, the user tries to find the shortest path themselves, but when they have finished their path, they are shown the actual shortest path, as calculated using Dijkstra's algorithm, and are shown the weights assigned to each node by the algorithm.

At the start of the lesson the students could be told to try to find the shortest path from the orange node to the purple node. They could be asked to generate their own ideas on how to work out the shortest path. After this, the program will show them the solution, which it calculates using Dijkstra's algorithm, and then the students can be taught how Dijkstra's algorithm works and found the shortest path.

The json file for the project can be found here

The project in Flock can be found here

Maze Visualisation

The purpose of this project is visualise breadth-first search and depth-first search in the scenario of solving a maze. First, a maze is created using Prim's algorithm, by randomly assigning a weight to each wall, and then picking the accessible walls with the least values that don't create cycles until it can no longer turn walls into paths. Then, it spawns a target in yellow. Next, it demonstrates a breadth-first search, placing red markers in order on each tile visited during its search for the target. Finally, it shows a depth-first search, this time placing cyan markers on the tiles.

This project is intended to be used when teaching these search algorithms to illustrate how they both work. This visualisation clearly depicts the differences in these approaches, so it should help students understand the difference between them. Additionally, at the end, the program displays the number of tiles used by each algorithm.

The json file for the project can be found here

The project in Flock can be found here

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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a-level-resources
Projects for using Flock XR to introduce A-level Computer Science concepts
Pathfinding Game
The goal of this game is to find the shortest path between two nodes of a graph. The starting node is shown in the orange, and the target node is shown in purple. You can choose your path by walking to the orange node to highlight it, and then walking to each node on your chosen path in order, until you reach the purple node.
This project is intended to be used to show students an example use of Dijkstra's shortest path algorithm. Initially, the user tries to find the shortest path themselves, but when they have finished their path, they are shown the actual shortest path, as calculated using Dijkstra's algorithm, and are shown the weights assigned to each node by the algorithm.
At the start of the lesson the students could be told to try to find the shortest path from the orange node to the purple node. They could be asked to generate their own ideas on how to work out the shortest path. After this, the program will show them the solution, which it calculates using Dijkstra's algorithm, and then the students can be taught how Dijkstra's algorithm works and found the shortest path.
The json file for the project can be found here
The project in Flock can be found here
Maze Visualisation
The purpose of this project is visualise breadth-first search and depth-first search in the scenario of solving a maze. First, a maze is created using Prim's algorithm, by randomly assigning a weight to each wall, and then picking the accessible walls with the least values that don't create cycles until it can no longer turn walls into paths. Then, it spawns a target in yellow. Next, it demonstrates a breadth-first search, placing red markers in order on each tile visited during its search for the target. Finally, it shows a depth-first search, this time placing cyan markers on the tiles.
This project is intended to be used when teaching these search algorithms to illustrate how they both work. This visualisation clearly depicts the differences in these approaches, so it should help students understand the difference between them. Additionally, at the end, the program displays the number of tiles used by each algorithm.
The json file for the project can be found here
The project in Flock can be found here
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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a-level-resources
Projects for using Flock XR to introduce A-level Computer Science concepts
Pathfinding Game
The goal of this game is to find the shortest path between two nodes of a graph. The starting node is shown in the orange, and the target node is shown in purple. You can choose your path by walking to the orange node to highlight it, and then walking to each node on your chosen path in order, until you reach the purple node.
This project is intended to be used to show students an example use of Dijkstra's shortest path algorithm. Initially, the user tries to find the shortest path themselves, but when they have finished their path, they are shown the actual shortest path, as calculated using Dijkstra's algorithm, and are shown the weights assigned to each node by the algorithm.
At the start of the lesson the students could be told to try to find the shortest path from the orange node to the purple node. They could be asked to generate their own ideas on how to work out the shortest path. After this, the program will show them the solution, which it calculates using Dijkstra's algorithm, and then the students can be taught how Dijkstra's algorithm works and found the shortest path.
The json file for the project can be found here
The project in Flock can be found here
Maze Visualisation
The purpose of this project is visualise breadth-first search and depth-first search in the scenario of solving a maze. First, a maze is created using Prim's algorithm, by randomly assigning a weight to each wall, and then picking the accessible walls with the least values that don't create cycles until it can no longer turn walls into paths. Then, it spawns a target in yellow. Next, it demonstrates a breadth-first search, placing red markers in order on each tile visited during its search for the target. Finally, it shows a depth-first search, this time placing cyan markers on the tiles.
This project is intended to be used when teaching these search algorithms to illustrate how they both work. This visualisation clearly depicts the differences in these approaches, so it should help students understand the difference between them. Additionally, at the end, the program displays the number of tiles used by each algorithm.
The json file for the project can be found here
The project in Flock can be found here
About
Projects for using Flock XR to introduce A-level Computer Science concepts
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Readme
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1 fork
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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a-level-resources
Projects for using Flock XR to introduce A-level Computer Science concepts
Pathfinding Game
The goal of this game is to find the shortest path between two nodes of a graph. The starting node is shown in the orange, and the target node is shown in purple. You can choose your path by walking to the orange node to highlight it, and then walking to each node on your chosen path in order, until you reach the purple node.
This project is intended to be used to show students an example use of Dijkstra's shortest path algorithm. Initially, the user tries to find the shortest path themselves, but when they have finished their path, they are shown the actual shortest path, as calculated using Dijkstra's algorithm, and are shown the weights assigned to each node by the algorithm.
At the start of the lesson the students could be told to try to find the shortest path from the orange node to the purple node. They could be asked to generate their own ideas on how to work out the shortest path. After this, the program will show them the solution, which it calculates using Dijkstra's algorithm, and then the students can be taught how Dijkstra's algorithm works and found the shortest path.
The json file for the project can be found here
The project in Flock can be found here
Maze Visualisation
The purpose of this project is visualise breadth-first search and depth-first search in the scenario of solving a maze. First, a maze is created using Prim's algorithm, by randomly assigning a weight to each wall, and then picking the accessible walls with the least values that don't create cycles until it can no longer turn walls into paths. Then, it spawns a target in yellow. Next, it demonstrates a breadth-first search, placing red markers in order on each tile visited during its search for the target. Finally, it shows a depth-first search, this time placing cyan markers on the tiles.
This project is intended to be used when teaching these search algorithms to illustrate how they both work. This visualisation clearly depicts the differences in these approaches, so it should help students understand the difference between them. Additionally, at the end, the program displays the number of tiles used by each algorithm.
The json file for the project can be found here
The project in Flock can be found here
About
Projects for using Flock XR to introduce A-level Computer Science concepts
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
a-level-resources
Projects for using Flock XR to introduce A-level Computer Science concepts
Pathfinding Game
The goal of this game is to find the shortest path between two nodes of a graph. The starting node is shown in the orange, and the target node is shown in purple. You can choose your path by walking to the orange node to highlight it, and then walking to each node on your chosen path in order, until you reach the purple node.
This project is intended to be used to show students an example use of Dijkstra's shortest path algorithm. Initially, the user tries to find the shortest path themselves, but when they have finished their path, they are shown the actual shortest path, as calculated using Dijkstra's algorithm, and are shown the weights assigned to each node by the algorithm.
At the start of the lesson the students could be told to try to find the shortest path from the orange node to the purple node. They could be asked to generate their own ideas on how to work out the shortest path. After this, the program will show them the solution, which it calculates using Dijkstra's algorithm, and then the students can be taught how Dijkstra's algorithm works and found the shortest path.
The json file for the project can be found here
The project in Flock can be found here
Maze Visualisation
The purpose of this project is visualise breadth-first search and depth-first search in the scenario of solving a maze. First, a maze is created using Prim's algorithm, by randomly assigning a weight to each wall, and then picking the accessible walls with the least values that don't create cycles until it can no longer turn walls into paths. Then, it spawns a target in yellow. Next, it demonstrates a breadth-first search, placing red markers in order on each tile visited during its search for the target. Finally, it shows a depth-first search, this time placing cyan markers on the tiles.
This project is intended to be used when teaching these search algorithms to illustrate how they both work. This visualisation clearly depicts the differences in these approaches, so it should help students understand the difference between them. Additionally, at the end, the program displays the number of tiles used by each algorithm.
The json file for the project can be found here
The project in Flock can be found here
About
Projects for using Flock XR to introduce A-level Computer Science concepts
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1 fork
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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a-level-resources
Projects for using Flock XR to introduce A-level Computer Science concepts
Pathfinding Game
The goal of this game is to find the shortest path between two nodes of a graph. The starting node is shown in the orange, and the target node is shown in purple. You can choose your path by walking to the orange node to highlight it, and then walking to each node on your chosen path in order, until you reach the purple node.
This project is intended to be used to show students an example use of Dijkstra's shortest path algorithm. Initially, the user tries to find the shortest path themselves, but when they have finished their path, they are shown the actual shortest path, as calculated using Dijkstra's algorithm, and are shown the weights assigned to each node by the algorithm.
At the start of the lesson the students could be told to try to find the shortest path from the orange node to the purple node. They could be asked to generate their own ideas on how to work out the shortest path. After this, the program will show them the solution, which it calculates using Dijkstra's algorithm, and then the students can be taught how Dijkstra's algorithm works and found the shortest path.
The json file for the project can be found here
The project in Flock can be found here
Maze Visualisation
The purpose of this project is visualise breadth-first search and depth-first search in the scenario of solving a maze. First, a maze is created using Prim's algorithm, by randomly assigning a weight to each wall, and then picking the accessible walls with the least values that don't create cycles until it can no longer turn walls into paths. Then, it spawns a target in yellow. Next, it demonstrates a breadth-first search, placing red markers in order on each tile visited during its search for the target. Finally, it shows a depth-first search, this time placing cyan markers on the tiles.
This project is intended to be used when teaching these search algorithms to illustrate how they both work. This visualisation clearly depicts the differences in these approaches, so it should help students understand the difference between them. Additionally, at the end, the program displays the number of tiles used by each algorithm.
The json file for the project can be found here
The project in Flock can be found here
About
Projects for using Flock XR to introduce A-level Computer Science concepts
Resources
Readme
Activity
Custom properties
Stars
0 stars
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0 watching
Forks
1 fork
Report repository
Releases
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
a-level-resources
Projects for using Flock XR to introduce A-level Computer Science concepts
Pathfinding Game
The goal of this game is to find the shortest path between two nodes of a graph. The starting node is shown in the orange, and the target node is shown in purple. You can choose your path by walking to the orange node to highlight it, and then walking to each node on your chosen path in order, until you reach the purple node.
This project is intended to be used to show students an example use of Dijkstra's shortest path algorithm. Initially, the user tries to find the shortest path themselves, but when they have finished their path, they are shown the actual shortest path, as calculated using Dijkstra's algorithm, and are shown the weights assigned to each node by the algorithm.
At the start of the lesson the students could be told to try to find the shortest path from the orange node to the purple node. They could be asked to generate their own ideas on how to work out the shortest path. After this, the program will show them the solution, which it calculates using Dijkstra's algorithm, and then the students can be taught how Dijkstra's algorithm works and found the shortest path.
The json file for the project can be found here
The project in Flock can be found here
Maze Visualisation
The purpose of this project is visualise breadth-first search and depth-first search in the scenario of solving a maze. First, a maze is created using Prim's algorithm, by randomly assigning a weight to each wall, and then picking the accessible walls with the least values that don't create cycles until it can no longer turn walls into paths. Then, it spawns a target in yellow. Next, it demonstrates a breadth-first search, placing red markers in order on each tile visited during its search for the target. Finally, it shows a depth-first search, this time placing cyan markers on the tiles.
This project is intended to be used when teaching these search algorithms to illustrate how they both work. This visualisation clearly depicts the differences in these approaches, so it should help students understand the difference between them. Additionally, at the end, the program displays the number of tiles used by each algorithm.
The json file for the project can be found here
The project in Flock can be found here
About
Projects for using Flock XR to introduce A-level Computer Science concepts
Resources
Readme
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Custom properties
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
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a-level-resources
Projects for using Flock XR to introduce A-level Computer Science concepts
Pathfinding Game
The goal of this game is to find the shortest path between two nodes of a graph. The starting node is shown in the orange, and the target node is shown in purple. You can choose your path by walking to the orange node to highlight it, and then walking to each node on your chosen path in order, until you reach the purple node.
This project is intended to be used to show students an example use of Dijkstra's shortest path algorithm. Initially, the user tries to find the shortest path themselves, but when they have finished their path, they are shown the actual shortest path, as calculated using Dijkstra's algorithm, and are shown the weights assigned to each node by the algorithm.
At the start of the lesson the students could be told to try to find the shortest path from the orange node to the purple node. They could be asked to generate their own ideas on how to work out the shortest path. After this, the program will show them the solution, which it calculates using Dijkstra's algorithm, and then the students can be taught how Dijkstra's algorithm works and found the shortest path.
The json file for the project can be found here
The project in Flock can be found here
Maze Visualisation
The purpose of this project is visualise breadth-first search and depth-first search in the scenario of solving a maze. First, a maze is created using Prim's algorithm, by randomly assigning a weight to each wall, and then picking the accessible walls with the least values that don't create cycles until it can no longer turn walls into paths. Then, it spawns a target in yellow. Next, it demonstrates a breadth-first search, placing red markers in order on each tile visited during its search for the target. Finally, it shows a depth-first search, this time placing cyan markers on the tiles.
This project is intended to be used when teaching these search algorithms to illustrate how they both work. This visualisation clearly depicts the differences in these approaches, so it should help students understand the difference between them. Additionally, at the end, the program displays the number of tiles used by each algorithm.
The json file for the project can be found here
The project in Flock can be found here
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Projects for using Flock XR to introduce A-level Computer Science concepts
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