A lightweight, browser-based tool for mapping modules, learning activities, and assessments against the six domains of AI capability, supporting reflective discussion, curriculum design, and quality assurance in education and research contexts.
This tool is part of the CloudPedagogy AI Capability Tools suite.
👉 http://cloudpedagogy-ai-capability-programme-mapping.s3-website.eu-west-2.amazonaws.com/
The screenshot below shows the AI Capability Programme Mapping Tool in use, with modules and activities tagged against different AI capability domains. It illustrates how domain coverage, observations, and reflection prompts are generated dynamically as part of the mapping process.
git clone [repository-url]
cd [repository-folder]npm installnpm run devOnce running, your terminal will display a local URL (often http://localhost:5173). Open this in your browser to use the application.
npm run buildThe production build will be generated in the dist/ directory and can be deployed to any static hosting service.
- Fully local: All data remains in the user's browser
- No backend: No external API calls or database storage
- Privacy-preserving: No tracking or data exfiltration
- Suitable for use in sensitive organisational and governance contexts
The AI Capability Programme Mapping Tool helps educators, curriculum designers, and programme teams:
- make AI capability visible across a programme
- reflect on balance, emphasis, and gaps
- support design conversations and QA discussions
- export a clear, reusable mapping artefact
The tool is framework-led, non-prescriptive, and designed to support professional judgement, not replace it.
This tool is not:
- a scoring or benchmarking system
- a compliance checklist
- an automated evaluator of quality
- a replacement for institutional governance processes
All outputs are interpretive prompts, not decisions.
Items are mapped against six interdependent domains:
-
Awareness & Orientation
Shared understanding, assumptions, AI literacy, and expectations -
Human–AI Co-Agency
How people partner with AI systems, maintain agency, and clarify roles -
Applied Practice & Innovation
Authentic use of AI in practice, experimentation, and improvement -
Ethics, Equity & Impact
Bias, accessibility, risk, and downstream impacts -
Decision-Making & Governance
Ownership, safeguards, approval processes, and institutional alignment -
Reflection, Learning & Renewal
Review, feedback, iteration, and long-term learning
These domains act as lenses, not checkboxes.
- Add Modules, Activities, and/or Assessments
- Name each item and optionally add notes
- Tag each item against one or more AI capability domains
- Review the automatically generated:
- coverage snapshot
- observations
- reflection prompts
- Optionally add programme details (title, award, institution, version)
- Export the mapping for reuse or discussion
Creates a QA-ready Markdown report that includes:
- programme details
- purpose and framing
- domain coverage table
- key observations
- domain lenses
- items grouped by type (modules / activities / assessments)
- reflection prompts
- use and limitations
This output can be pasted directly into:
- programme documentation
- QA or review notes
- curriculum design workshop materials
Creates a portable data file containing:
- programme metadata
- all mapping items and domain tags
This can be used to:
- back up your work
- move a mapping between devices or browsers
- re-import a mapping into the tool
Restores a previously exported mapping file, replacing the current browser state.
- The tool runs entirely client-side
- Data is stored locally in your browser using
localStorage - No data is transmitted, uploaded, or tracked
- Clearing browser storage will remove saved mappings (export first if needed)
This design makes the tool suitable for static hosting (e.g. AWS S3).
- Programme design workshops
- Curriculum review and refresh cycles
- QA and validation discussions
- Identifying implicit vs explicit AI capability coverage
- Supporting cross-team dialogue about AI use
The tool is especially effective when used collaboratively, not individually.
This repository contains exploratory, framework-aligned tools developed for reflection, learning, and discussion.
These tools are provided as-is and are not production systems, audits, or compliance instruments. Outputs are indicative only and should be interpreted in context using professional judgement.
All applications are designed to run locally in the browser. No user data is collected, stored, or transmitted.
This repository contains open-source software released under the MIT License.
CloudPedagogy frameworks and related materials are licensed separately and are not embedded or enforced within this software.
CloudPedagogy develops open, governance-credible resources for building confident, responsible AI capability across education, research, and public service.