BranchesTags

Repository files navigation

Introduction

This is the source code for Website (https://cedanl.github.io/AI-Alignment/)
about AI alignment.

The website is part of a project to support the Dutch Education community via CEDA. Its main aim is to stimulate conversation about comparing the alignment of AI models and systems against what we consider important.

Dashboards.

  1. Information Dashboard - An information dashboard about AI Alignment. The menu option Scorecard/Visualization is a mockup of a potential community process.

Context

At the end of 2025 the Npuls LA team came to the following conclusion about the state of Generative AI in Dutch education:

The importance of LA in (Gen)AI was best summarized by the “Confused Expert” analogy. This argument posits that GenAI is a powerful but unguided medium, not a solution. The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.

Effective AI will need better data and guiding practices, not the other way around.

The solution argues for Benchmarking and training AI models on pedagogical data, and using the LA cycle to guide the development and deployment of AI in education. This approach ensures that AI systems are aligned with educational goals and can be effectively integrated into teaching and learning processes.

Before taking time efort and gold to train models based on Learning Analytics data we need to be able to measure the qualities of the models and AI systems against our values. This project is an initial review of the theme with the goal of developing a framework for benchmarking and scorecarding AI systems in education, with a focus on alignment with educational values and goals. The project will involve identifying relevant metrics, developing benchmarking methodologies, and creating scorecards to evaluate AI systems in the context of education.

The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.

About

This project explores tracking the alignment (that the models follow our values) of AI models used within Dutch education using a community-developed scorecard derived from benchmarks.

Resources

Readme
Activity
Custom properties

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

, '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" + '

Skip to content
BranchesTags
Repository files navigation
Introduction
This is the source code for Website (https://cedanl.github.io/AI-Alignment/)

about AI alignment.
The website is part of a project to support the Dutch Education community via CEDA. Its main aim is to stimulate conversation about comparing the alignment of AI models and systems against what we consider important.
Dashboards.
  1. Information Dashboard - An information dashboard about AI Alignment. The menu option Scorecard/Visualization is a mockup of a potential community process.
Context
At the end of 2025 the Npuls LA team came to the following conclusion about the state of Generative AI in Dutch education:
The importance of LA in (Gen)AI was best summarized by the “Confused Expert” analogy. This argument posits that GenAI is a powerful but unguided medium, not a solution. The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
Effective AI will need better data and guiding practices, not the other way around.
The solution argues for Benchmarking and training AI models on pedagogical data, and using the LA cycle to guide the development and deployment of AI in education. This approach ensures that AI systems are aligned with educational goals and can be effectively integrated into teaching and learning processes.
Before taking time efort and gold to train models based on Learning Analytics data we need to be able to measure the qualities of the models and AI systems against our values. This project is an initial review of the theme with the goal of developing a framework for benchmarking and scorecarding AI systems in education, with a focus on alignment with educational values and goals. The project will involve identifying relevant metrics, developing benchmarking methodologies, and creating scorecards to evaluate AI systems in the context of education.
The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
About
This project explores tracking the alignment (that the models follow our values) of AI models used within Dutch education using a community-developed scorecard derived from benchmarks. 
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Introduction
This is the source code for Website (https://cedanl.github.io/AI-Alignment/)

about AI alignment.
The website is part of a project to support the Dutch Education community via CEDA. Its main aim is to stimulate conversation about comparing the alignment of AI models and systems against what we consider important.
Dashboards.
  1. Information Dashboard - An information dashboard about AI Alignment. The menu option Scorecard/Visualization is a mockup of a potential community process.
Context
At the end of 2025 the Npuls LA team came to the following conclusion about the state of Generative AI in Dutch education:
The importance of LA in (Gen)AI was best summarized by the “Confused Expert” analogy. This argument posits that GenAI is a powerful but unguided medium, not a solution. The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
Effective AI will need better data and guiding practices, not the other way around.
The solution argues for Benchmarking and training AI models on pedagogical data, and using the LA cycle to guide the development and deployment of AI in education. This approach ensures that AI systems are aligned with educational goals and can be effectively integrated into teaching and learning processes.
Before taking time efort and gold to train models based on Learning Analytics data we need to be able to measure the qualities of the models and AI systems against our values. This project is an initial review of the theme with the goal of developing a framework for benchmarking and scorecarding AI systems in education, with a focus on alignment with educational values and goals. The project will involve identifying relevant metrics, developing benchmarking methodologies, and creating scorecards to evaluate AI systems in the context of education.
The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
About
This project explores tracking the alignment (that the models follow our values) of AI models used within Dutch education using a community-developed scorecard derived from benchmarks. 
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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
Repository files navigation
Introduction
This is the source code for Website (https://cedanl.github.io/AI-Alignment/)

about AI alignment.
The website is part of a project to support the Dutch Education community via CEDA. Its main aim is to stimulate conversation about comparing the alignment of AI models and systems against what we consider important.
Dashboards.
  1. Information Dashboard - An information dashboard about AI Alignment. The menu option Scorecard/Visualization is a mockup of a potential community process.
Context
At the end of 2025 the Npuls LA team came to the following conclusion about the state of Generative AI in Dutch education:
The importance of LA in (Gen)AI was best summarized by the “Confused Expert” analogy. This argument posits that GenAI is a powerful but unguided medium, not a solution. The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
Effective AI will need better data and guiding practices, not the other way around.
The solution argues for Benchmarking and training AI models on pedagogical data, and using the LA cycle to guide the development and deployment of AI in education. This approach ensures that AI systems are aligned with educational goals and can be effectively integrated into teaching and learning processes.
Before taking time efort and gold to train models based on Learning Analytics data we need to be able to measure the qualities of the models and AI systems against our values. This project is an initial review of the theme with the goal of developing a framework for benchmarking and scorecarding AI systems in education, with a focus on alignment with educational values and goals. The project will involve identifying relevant metrics, developing benchmarking methodologies, and creating scorecards to evaluate AI systems in the context of education.
The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
About
This project explores tracking the alignment (that the models follow our values) of AI models used within Dutch education using a community-developed scorecard derived from benchmarks. 
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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
Introduction
This is the source code for Website (https://cedanl.github.io/AI-Alignment/)

about AI alignment.
The website is part of a project to support the Dutch Education community via CEDA. Its main aim is to stimulate conversation about comparing the alignment of AI models and systems against what we consider important.
Dashboards.
  1. Information Dashboard - An information dashboard about AI Alignment. The menu option Scorecard/Visualization is a mockup of a potential community process.
Context
At the end of 2025 the Npuls LA team came to the following conclusion about the state of Generative AI in Dutch education:
The importance of LA in (Gen)AI was best summarized by the “Confused Expert” analogy. This argument posits that GenAI is a powerful but unguided medium, not a solution. The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
Effective AI will need better data and guiding practices, not the other way around.
The solution argues for Benchmarking and training AI models on pedagogical data, and using the LA cycle to guide the development and deployment of AI in education. This approach ensures that AI systems are aligned with educational goals and can be effectively integrated into teaching and learning processes.
Before taking time efort and gold to train models based on Learning Analytics data we need to be able to measure the qualities of the models and AI systems against our values. This project is an initial review of the theme with the goal of developing a framework for benchmarking and scorecarding AI systems in education, with a focus on alignment with educational values and goals. The project will involve identifying relevant metrics, developing benchmarking methodologies, and creating scorecards to evaluate AI systems in the context of education.
The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
About
This project explores tracking the alignment (that the models follow our values) of AI models used within Dutch education using a community-developed scorecard derived from benchmarks. 
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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
Repository files navigation
Introduction
This is the source code for Website (https://cedanl.github.io/AI-Alignment/)

about AI alignment.
The website is part of a project to support the Dutch Education community via CEDA. Its main aim is to stimulate conversation about comparing the alignment of AI models and systems against what we consider important.
Dashboards.
  1. Information Dashboard - An information dashboard about AI Alignment. The menu option Scorecard/Visualization is a mockup of a potential community process.
Context
At the end of 2025 the Npuls LA team came to the following conclusion about the state of Generative AI in Dutch education:
The importance of LA in (Gen)AI was best summarized by the “Confused Expert” analogy. This argument posits that GenAI is a powerful but unguided medium, not a solution. The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
Effective AI will need better data and guiding practices, not the other way around.
The solution argues for Benchmarking and training AI models on pedagogical data, and using the LA cycle to guide the development and deployment of AI in education. This approach ensures that AI systems are aligned with educational goals and can be effectively integrated into teaching and learning processes.
Before taking time efort and gold to train models based on Learning Analytics data we need to be able to measure the qualities of the models and AI systems against our values. This project is an initial review of the theme with the goal of developing a framework for benchmarking and scorecarding AI systems in education, with a focus on alignment with educational values and goals. The project will involve identifying relevant metrics, developing benchmarking methodologies, and creating scorecards to evaluate AI systems in the context of education.
The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
About
This project explores tracking the alignment (that the models follow our values) of AI models used within Dutch education using a community-developed scorecard derived from benchmarks. 
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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
Introduction
This is the source code for Website (https://cedanl.github.io/AI-Alignment/)

about AI alignment.
The website is part of a project to support the Dutch Education community via CEDA. Its main aim is to stimulate conversation about comparing the alignment of AI models and systems against what we consider important.
Dashboards.
  1. Information Dashboard - An information dashboard about AI Alignment. The menu option Scorecard/Visualization is a mockup of a potential community process.
Context
At the end of 2025 the Npuls LA team came to the following conclusion about the state of Generative AI in Dutch education:
The importance of LA in (Gen)AI was best summarized by the “Confused Expert” analogy. This argument posits that GenAI is a powerful but unguided medium, not a solution. The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
Effective AI will need better data and guiding practices, not the other way around.
The solution argues for Benchmarking and training AI models on pedagogical data, and using the LA cycle to guide the development and deployment of AI in education. This approach ensures that AI systems are aligned with educational goals and can be effectively integrated into teaching and learning processes.
Before taking time efort and gold to train models based on Learning Analytics data we need to be able to measure the qualities of the models and AI systems against our values. This project is an initial review of the theme with the goal of developing a framework for benchmarking and scorecarding AI systems in education, with a focus on alignment with educational values and goals. The project will involve identifying relevant metrics, developing benchmarking methodologies, and creating scorecards to evaluate AI systems in the context of education.
The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
About
This project explores tracking the alignment (that the models follow our values) of AI models used within Dutch education using a community-developed scorecard derived from benchmarks. 
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, '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
Repository files navigation
Introduction
This is the source code for Website (https://cedanl.github.io/AI-Alignment/)

about AI alignment.
The website is part of a project to support the Dutch Education community via CEDA. Its main aim is to stimulate conversation about comparing the alignment of AI models and systems against what we consider important.
Dashboards.
  1. Information Dashboard - An information dashboard about AI Alignment. The menu option Scorecard/Visualization is a mockup of a potential community process.
Context
At the end of 2025 the Npuls LA team came to the following conclusion about the state of Generative AI in Dutch education:
The importance of LA in (Gen)AI was best summarized by the “Confused Expert” analogy. This argument posits that GenAI is a powerful but unguided medium, not a solution. The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
Effective AI will need better data and guiding practices, not the other way around.
The solution argues for Benchmarking and training AI models on pedagogical data, and using the LA cycle to guide the development and deployment of AI in education. This approach ensures that AI systems are aligned with educational goals and can be effectively integrated into teaching and learning processes.
Before taking time efort and gold to train models based on Learning Analytics data we need to be able to measure the qualities of the models and AI systems against our values. This project is an initial review of the theme with the goal of developing a framework for benchmarking and scorecarding AI systems in education, with a focus on alignment with educational values and goals. The project will involve identifying relevant metrics, developing benchmarking methodologies, and creating scorecards to evaluate AI systems in the context of education.
The LA cycle, grounded in pedagogical data, clear metrics, and a feedback loop, is an essential framework for guiding AI responsibly and effectively in an educational context.
About
This project explores tracking the alignment (that the models follow our values) of AI models used within Dutch education using a community-developed scorecard derived from benchmarks. 
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages