Concept DOI (all versions): https://doi.org/10.5281/zenodo.17833663
A values-based, developmental framework for ethical, strategic, and creative use of artificial intelligence across education, research, public services, and the wider public good.
The authoritative, up-to-date home of the CloudPedagogy AI Capability Framework (2026 Edition) is:
https://www.cloudpedagogy.com/pages/ai-capability-framework
The CloudPedagogy website provides the full framework narrative, toolkits, practice guides, governance resources, and free courses.
This GitHub repository provides the openly licensed source files and archival releases.
The CloudPedagogy AI Capability Framework provides a structured, future-ready model for building responsible, ethical, and transparent AI capability across complex professional environments.
It defines six interdependent capability domains:
- AI Awareness & Orientation
- Human–AI Co-Agency
- Applied Practice & Innovation
- Ethics, Equity & Impact
- Decision-Making & Governance
- Reflection, Learning & Renewal
Grounded in ecological learning, systems thinking, and ethical foresight, the Framework helps individuals and organisations move beyond tool-focused AI training toward applied, reflective, and values-aligned AI capability.
The Framework defines capability expectations; it does not prescribe specific tools, platforms, or system architectures.
The CloudPedagogy AI Capability Framework is supported by open, inspectable infrastructure that enables it to be applied in real educational, research, and governance contexts — not just described in documents.
The CloudPedagogy Course Engine is an open-source, MIT-licensed system for producing transparent, reproducible, and governance-ready learning artefacts from a single, structured source of truth.
It enables educators, researchers, and institutions to:
- compile interactive static course websites and print-ready PDFs from the same source
- keep learning materials aligned across formats over time
- record design intent and AI scoping boundaries transparently
- generate inspectable evidence for QA, audit, and governance review
- track change and provenance across versions
The Course Engine treats learning design as a versioned, inspectable specification, similar to how software systems are built and reviewed.
While the Course Engine is designed around the principles of the CloudPedagogy AI Capability Framework and Capability-Driven Development (CDD), it:
- does not embed, mandate, or enforce the Framework
- does not prescribe pedagogy, quality judgements, or approval outcomes
- treats capability alignment as declared, inspectable metadata by default
Capability mapping, reporting, and validation features are informational unless explicitly configured, supporting reflection, assurance, and governance workflows rather than automated decision-making.
This separation ensures that:
- human judgement remains central
- governance is transparent rather than opaque
- institutions retain control over interpretation and policy
-
🔗 Course Engine repository
https://github.com/cloudpedagogy/cloudpedagogy-course-engine -
🌐 Live demo: interactive course site generated from source
http://cloudpedagogy-course-engine-demo.s3-website.eu-west-2.amazonaws.com/
The Course Engine provides the operational backbone that allows the AI Capability Framework to be used credibly, reproducibly, and defensibly in real institutional settings.
CloudPedagogy AI Capability Studio is an open-source, offline-first workflow environment designed to support structured, governance-ready human–AI collaboration.
It enables educators, researchers, and strategy teams to:
- Apply the AI Capability Framework in structured 6-step workflows
- Generate export-ready AI Workflow Records
- Document human judgement and AI involvement explicitly
- Maintain local, privacy-preserving workflow logs
- Produce governance-ready artefacts without relying on cloud storage or API calls
AI Capability Studio does not generate AI content and does not store user data remotely.
It structures applied capability practice and produces portable documentation.
🔗 Repository:
https://github.com/cloudpedagogy/cloudpedagogy-ai-capability-studio
The Studio complements the Framework by operationalising structured reflection, co-agency, ethical review, governance logging, and renewal practices in real institutional settings.
This repository contains the official, openly licensed source files and archival releases of the CloudPedagogy AI Capability Framework (2026 Edition) and its companion resources.
All materials are free to download, adapt, and remix for non-commercial use under the Creative Commons CC BY-NC-SA 4.0 licence.
The repository is organised into four key folders.
Authoritative, foundational framework texts, maintained in Markdown as the canonical source, with PDF and Word versions provided as stable reference artefacts and editable copies:
- AI-Capability-Framework-2026.md
- AI-Capability-Framework-Overview-2026.md
- AI-Capability-Framework-2026.pdf
- AI-Capability-Framework-Overview-2026.pdf
- AI-Capability-Framework-2026.docx
- AI-Capability-Framework-Overview-2026.docx
Applied guidance for institutional and organisational use, maintained in Markdown, with PDF and Word versions provided for distribution and reuse:
- AI CAPABILITY FRAMEWORK APPLICATION HANDBOOK.md
- AI Capability Framework Application Handbook — Executive Summary.md
- AI CAPABILITY FRAMEWORK APPLICATION HANDBOOK.pdf
- AI CAPABILITY FRAMEWORK APPLICATION HANDBOOK.docx
- AI Capability Framework Application Handbook — Executive Summary.pdf
- AI Capability Framework Application Handbook — Executive Summary.docx
Modular practical resources supporting applied use, maintained in Markdown, with Word (.docx) versions provided for flexible reuse:
- Self-Assessment Matrix (Worksheet)
- Scenario-Based Workshop Guides
- Reflection Toolkit
- Governance & Ethics Templates
- Applied Examples Case Pack
- AI Interaction & Design Toolkit
- Resource Index & Glossary
Short, applied guides demonstrating how to use the Framework in real-world contexts.
Guides are maintained in Markdown as the canonical source format, with PDF (stable) and Word (editable) versions provided in subfolders.
Included guides:
- Teaching
- Research
- Governance & Decision-Making
- Leadership & Strategy
- Individual Practice
- Business & Entrepreneurship
- High-Risk or Public-Impact Contexts
Also included:
- Quick Reference Guide for Course Designers (Markdown + export formats)
Guidance explaining how the AI Capability Framework ecosystem fits together in practice, including how scenarios, briefs, quizzes, slides, and facilitation materials are intended to be used.
Included documentation:
This repository provides the canonical reference for the CloudPedagogy AI Capability Framework.
The following companion repositories extend the Framework into applied guidance, software tools, workflows, and supporting infrastructure.
AI Capability Briefs
Short, role- and context-specific briefs supporting professional judgement and decision-making using the AI Capability Framework.
AI Capability Framework — Scenario Library
Facilitation-ready scenarios for applying the Framework in real professional settings.
CloudPedagogy Books Repository
A curated collection of open, versioned texts supporting responsible AI capability across education, research, and public services.
CloudPedagogy AI Capability Studio
A structured workflow environment for documenting human–AI collaboration and generating governance-ready AI Workflow Records.
CloudPedagogy AI Capability Tools
Index and launchpad for CloudPedagogy capability tools and live demos.
CloudPedagogy Course Engine
An open-source system for producing transparent, reproducible course artefacts from a single structured source.
CloudPedagogy Research Object Template
A governance-ready template for building transparent, reproducible research artefacts and AI-aware research outputs.
It enables researchers to package data, analysis, documentation, and governance information into inspectable research objects suitable for sharing, review, and long-term preservation.
CloudPedagogy n8n Workflows (under development)
Human-in-the-loop automation workflows translating the Framework into operational processes and decision-support systems using everyday institutional tools.
Capability-Driven Development (CDD)
A capability-first design methodology for translating AI Capability Framework principles into software systems, workflows, and AI-enabled infrastructure.
This repository is licensed under the Creative Commons Attribution–NonCommercial–ShareAlike 4.0 International (CC BY-NC-SA 4.0) licence.
You may:
- Use, share, and adapt this work for educational, research, and public-interest purposes
- Do so with appropriate attribution
- Share adaptations under the same licence
You may not:
- Use this work for commercial purposes
- Resell, sublicense, or incorporate it into paid products, services, or platforms without explicit permission
Full licence text: https://creativecommons.org/licenses/by-nc-sa/4.0/
This framework, associated software, and their underlying design were developed by Jonathan Wong as part of the CloudPedagogy initiative.
All architecture, code, documentation, and conceptual resources are produced in-house and aligned with the CloudPedagogy AI Capability Framework.
CloudStartupTech is used as a technical development identity for tooling, workflows, and software components.
Wong, J. (2025). CloudPedagogy AI Capability Framework (2026 Edition). Zenodo.
https://doi.org/10.5281/zenodo.17833663
Wong, J. (2025). CloudPedagogy AI Capability Framework (2026 Edition) (v1.2). Zenodo.
https://doi.org/10.5281/zenodo.17873465
- Stable releases are published via GitHub Releases
- Each release is automatically archived and assigned a DOI via Zenodo
- The Concept DOI remains constant across versions
- All historical versions remain permanently accessible
More frameworks, free courses, and applied resources:
https://www.cloudpedagogy.com