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CloudPedagogy AI Capability Framework (2026 Edition)

DOI

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.


🌐 Canonical Framework Page

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.


📘 About the Framework

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.


⚙️ Framework Infrastructure: CloudPedagogy Course Engine

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.

CloudPedagogy Course Engine (Open Source)

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.

Relationship to the AI Capability Framework

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

Learn more

The Course Engine provides the operational backbone that allows the AI Capability Framework to be used credibly, reproducibly, and defensibly in real institutional settings.


📁 Repository Structure & Contents

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.


/core — Canonical Framework Documents

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

/application — Application Handbook & Executive Summary

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

/toolkit — Tools, Templates & Worksheets

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

/practice-guides — Role- & Context-Specific Practice Guides

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)

/documentation — Framework Documentation & Orientation

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:


🔗 Related CloudPedagogy Repositories

This repository is the canonical source for the CloudPedagogy AI Capability Framework (2026 Edition), including the framework model, domains, and core reference resources.

The following repositories provide applied companion resources and software tools derived from, and explicitly grounded in, the Framework.


📘 Applied Guidance & Practice Resources

AI Capability Briefs
Short, role- and context-specific briefs supporting professional judgement and decision-making using the AI Capability Framework.
https://github.com/cloudpedagogy/ai-capability-briefs

AI Capability Framework — Scenario Library
Facilitation-ready scenarios for applying the Framework in real professional settings, including teaching, research, governance, leadership, and public-impact contexts.
https://github.com/cloudpedagogy/ai-capability-framework-scenarios


🧩 AI Capability Tools Suite (Index + Launchpad)

CloudPedagogy AI Capability Tools
An index and launchpad for the CloudPedagogy AI Capability Tools suite — including recommended flow, shared design principles, and direct links to live tools and their source repositories.
https://github.com/cloudpedagogy/cloudpedagogy-ai-capability-tools


⚙️ CloudPedagogy Course Engine

The CloudPedagogy Course Engine is an open-source, MIT-licensed software tool designed to support transparent, reproducible course production and review.

It enables educators and institutions to compile course artefacts from a single source of truth, inspect build metadata, and optionally declare and review capability alignment using structured, auditable outputs.

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 this Framework.

Capability mapping, reporting, and validation features are informational by default and are intended to support reflection, assurance, and governance workflows rather than determine quality, compliance, or approval outcomes. https://github.com/cloudpedagogy/cloudpedagogy-course-engine


⚙️ Operational Workflows

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.
https://github.com/cloudpedagogy/cloudpedagogy-n8n-workflows


🛠 Capability-Driven Development (CDD)

A capability-first system design method for translating AI Capability Framework principles into software, workflows, and AI-enabled systems. https://github.com/cloudpedagogy/capability-driven-development


Companion repositories extend the Framework into applied guidance, diagnostics, and operational practice.
This repository remains the authoritative reference for the CloudPedagogy AI Capability Framework model, domains, and core resources.


📜 Licence

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/


👤 Authorship and Development

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.


🧭 Citation

Preferred citation (Concept DOI)

Wong, J. (2025). CloudPedagogy AI Capability Framework (2026 Edition). Zenodo.
https://doi.org/10.5281/zenodo.17833663

Version-specific citation (v1.2)

Wong, J. (2025). CloudPedagogy AI Capability Framework (2026 Edition) (v1.2). Zenodo.
https://doi.org/10.5281/zenodo.17873465


🔄 Versioning & Archiving

  • 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

🌱 CloudPedagogy

More frameworks, free courses, and applied resources:
https://www.cloudpedagogy.com

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