Background

CloudPedagogy develops digital-learning infrastructure that helps educators and institutions move from fragmented content, platform data and manual processes to structured, maintainable and inspectable learning systems.

The portfolio brings together:

  • learning publishing and content transformation;
  • Moodle course analysis;
  • curriculum and assessment systems;
  • educational visualisation;
  • integration and supporting infrastructure.

These systems are designed to strengthen professional practice—not replace educational judgement.


From Educational Content to Connected Learning Systems

Digital education often depends on disconnected documents, platforms, data exports and specialist technical processes.

This can make courses difficult to:

  • understand;
  • maintain;
  • update;
  • reuse;
  • evaluate;
  • migrate between systems;
  • improve systematically.

CloudPedagogy develops open systems that make these processes more structured and transparent.

The digital-learning lifecycle is:

Analyse → Design → Publish → Deliver → Evaluate → Improve

Each system can be used independently or as part of a connected workflow.


Explore Digital Learning Systems

1. Learning Publishing and Content Transformation

Systems for transforming structured educational source material into accessible, reusable and reproducible learning resources.

Learning Publisher

A Word-first publishing system for transforming structured educational content into interactive digital learning resources.

Learning Publisher allows authors to work in a familiar Microsoft Word environment while producing modern outputs through Quarto.

It supports the creation of:

  • interactive course websites;
  • structured eLearning materials;
  • printable lesson PDFs;
  • combined course handbooks;
  • presentations;
  • browser-based activities;
  • reusable learning resources.

Structured Word content can include headings, callouts, tabs, quizzes, self-check activities, reveals, mathematical notation, code examples, videos, downloadable files and embedded interactive visualisations.

The underlying source remains editable and maintainable, reducing dependence on manually constructed webpages.

Technology: Python · Quarto · Pandoc · Markdown · DOCX

→ Learning Publisher Demo
→ View Learning Publisher source

Course Engine

A command-line publishing engine for producing traceable and defensible course outputs from structured specifications.

Course Engine uses reproducible source files and explicit configuration to support consistent course generation, quality assurance and publication through Quarto.

Technology: Python · Quarto · YAML · Reproducible publishing

→ View Course Engine source

Moodle Book Converter

A structured conversion system for transforming Word documents into Moodle Book import packages.

It supports heading-based chapter generation, HTML conversion, image handling and automated quality and accessibility checks.

Technology: Python · DOCX · Moodle Book · HTML · ZIP · Accessibility QA

→ View Moodle Book Converter source

Video Learning Mapper

A local-first tool for mapping video transcripts to structured learning segments, themes and learning objectives.

It can help educators examine how recorded material relates to intended learning, identify key sections and create more structured educational uses of video.

Technology: TypeScript · WebVTT · Transcript analysis · Local-first processing

→ Explore Video Learning Mapper
→ View Video Learning Mapper source


2. Moodle Course Analysis Platform

A developing collection of interoperable tools for inspecting, recovering, evaluating and restructuring Moodle courses.

Moodle courses can become difficult to understand after years of development, revision and reuse. The Moodle Course Analysis Platform makes their underlying structure, content and dependencies more visible.

Together, its components support:

  • course-backup auditing;
  • section, activity and resource inventories;
  • Moodle Book analysis;
  • hidden-content identification;
  • file and storage analysis;
  • external-link and dependency review;
  • activity-age analysis;
  • file extraction and recovery;
  • integrity verification;
  • accessibility and quality assurance;
  • migration and archival review;
  • redesign and reconstruction planning;
  • pilot integration of access and engagement data.

Moodle Course Auditor

Analyses Moodle backup files to generate structured inventories, metadata reports, quality insights and course-level visualisations.

The auditor can identify sections, activities, resources, Moodle Books, hidden content, files, external domains and the age of course components.

Technology: Python · Moodle MBZ · XML · CSV · Plotly

→ View Moodle Course Auditor source

Moodle File Extractor

Extracts files from Moodle backup files, restores their original filenames and paths, verifies file integrity and generates a structured CSV manifest.

This supports course recovery, content migration, archival review and the reconstruction of course-resource collections.

Technology: Python · Moodle MBZ · XML · SHA-1 verification · CSV

→ View Moodle File Extractor source

Moodle Book QA

A governance-oriented toolkit for offline inspection, accessibility review, quality assurance and recovery of exported Moodle Books.

It helps make Moodle Book content available for systematic checking outside the live course environment.

Technology: Python · Moodle · IMS Content Package · HTML · Pandoc · Accessibility QA

→ View Moodle Book QA source

Moodle Book Converter

Transforms structured Word documents into Moodle Book import packages with automated quality and accessibility checks.

The converter provides a route from maintainable source documents to Moodle-native learning resources.

Technology: Python · DOCX · Moodle Book · HTML · ZIP

→ View Moodle Book Converter source

From Structural Audit to Learning Analytics

Structural audit information can be combined with selected Moodle activity reports to begin exploring relationships between course design and learner engagement.

Current pilot work includes bringing access data alongside Moodle Book information to show:

  • the number of pages within each Book;
  • the number of learners who accessed it;
  • the number who did not access it;
  • the percentage of learners reached.

This work remains exploratory. Engagement figures require appropriate interpretation, verification and attention to institutional data-protection requirements.

The platform is intended to help digital education teams, programme teams and course owners understand both what a Moodle course contains and how it may be improved.


3. Curriculum and Assessment Systems

Structured tools for designing, analysing and improving programmes, curricula, learning pathways and assessments.

These systems make relationships between modules, learning outcomes, assessments, capabilities, workload and programme requirements more visible.

Applications include:

  • curriculum alignment mapping;
  • programme structure analysis;
  • curriculum simulation;
  • assessment design;
  • AI-use and academic-integrity planning;
  • learner-pathway exploration;
  • shared-module management;
  • curriculum change management;
  • programme governance and evidence generation.

Programme Governance Dashboard

Analyses programme structure, curriculum alignment and governance readiness.

It helps surface structural relationships, gaps and areas requiring further review across modules, outcomes and assessments.

Technology: TypeScript · Browser-based visualisation · Local-first data

→ Explore Programme Governance Dashboard
→ View Programme Governance Dashboard source

Curriculum Alignment Mapping Engine

Visualises relationships between modules, learning outcomes, assessments and skills.

It supports the identification of gaps, duplication, weak alignment and areas of curriculum concentration.

Technology: TypeScript · Curriculum mapping · Interactive visualisation

→ Explore Curriculum Alignment Mapping Engine
→ View Curriculum Alignment Mapping Engine source

Curriculum Simulation Tool

Simulates curriculum pathways, learner progression and workload distribution.

It allows programme teams to test sequencing, structural changes and programme resilience before implementation.

Technology: TypeScript · Simulation · Education analytics

→ Explore Curriculum Simulation Tool
→ View Curriculum Simulation Tool source

Pathway Personalisation Engine

Supports exploration of curriculum sequences aligned with capability frameworks, learner progression and alternative pathways.

Technology: TypeScript · Pathway modelling · Curriculum design

→ Explore Pathway Personalisation Engine
→ View Pathway Personalisation Engine source


Shared Module Repository System

A structured registry for maintaining reusable curriculum modules across programmes.

It supports version tracking, dependency mapping and governance-ready inspection of shared educational components.

Technology: TypeScript · Module registry · Version tracking · Dependency mapping

→ Explore Shared Module Repository System
→ View Shared Module Repository System source

Assessment Design Engine

Supports the design of structured, AI-aware assessments aligned with learning outcomes.

It enables educators to define assessment tasks, connect them with outcomes, manage weighting and consider the implications of generative AI.

Technology: TypeScript · Assessment alignment · Curriculum design · Local-first processing

→ Explore Assessment Design Engine
→ View Assessment Design Engine source


Curriculum Change Manager

Records, compares and explains curriculum and assessment changes over time.

It supports transparent change management, review histories and the creation of clearer curriculum-development audit trails.

Technology: TypeScript · Versioning · Change management · Audit trails

→ Explore Curriculum Change Manager
→ View Curriculum Change Manager source



4. Educational Visualisation Systems

Word-driven tools for producing interactive educational visualisations without requiring authors to write JavaScript.

Authors define data, content and relationships using structured tables in Microsoft Word. Each renderer validates the source and generates a standalone interactive webpage that can be hosted independently or embedded within a learning environment.

The current portfolio includes hierarchy, flow-diagram, chart-dashboard, Sankey, timeline and network renderers.

Word Hierarchy Renderer

Creates interactive trees and hierarchical visualisations from structured Word tables.

It can represent programme structures, organisational relationships, taxonomies, topic hierarchies and branching learning pathways.

Technology: Python · D3.js · DOCX · HTML

→ Launch Word Hierarchy demonstration
→ View Word Hierarchy Renderer source

Word Flow Diagram Renderer

Creates interactive process, decision, workflow and pathway diagrams from structured Word documents.

It can be used for procedures, decision pathways, research workflows, learner journeys and institutional processes.

Technology: Python · JavaScript · DOCX · HTML

→ Launch Word Flow Diagram demonstration
→ View Word Flow Diagram Renderer source

Word Chart Dashboard Renderer

Generates interactive dashboards containing bar, line, area, scatter, bubble, pie and donut charts.

It provides a structured route from Word-based data tables to browser-based visual analysis.

Technology: Python · Plotly.js · DOCX · HTML

→ Launch Word Chart Dashboard demonstration
→ View Word Chart Dashboard Renderer source

Word Sankey Renderer

Creates interactive Sankey diagrams for showing pathways, resource allocation and quantitative flows between categories.

Potential educational uses include learner progression, curriculum pathways, funding flows and transitions between programme stages.

Technology: Python · Plotly.js · DOCX · HTML

→ Launch Word Sankey demonstration
→ View Word Sankey Renderer source

Word Timeline Renderer

Produces filterable and grouped interactive timelines from structured Word tables.

It can represent historical sequences, programme milestones, project histories, research developments and staged learning processes.

Technology: Python · JavaScript · DOCX · JSON · HTML

→ Launch Word Timeline demonstration
→ View Word Timeline Renderer source

Cytoscape Network Renderer

Generates interactive network and relationship visualisations from structured Word documents.

It can represent stakeholder networks, concept relationships, course-development teams, dependencies and connections between educational components.

Technology: Python · Cytoscape.js · DOCX · Network visualisation

→ Launch Cytoscape Network demonstration
→ View Cytoscape Network Renderer source

Educational Applications

These visualisation systems can be used to represent:

  • stakeholder relationships;
  • programme and module structures;
  • learning pathways;
  • processes and decision flows;
  • historical sequences;
  • movement between categories;
  • conceptual relationships;
  • research findings;
  • organisational structures.



A Word-Driven Approach to Digital Learning

A recurring principle across the portfolio is the use of structured, accessible authoring formats.

Microsoft Word remains widely used by educators, subject specialists and professional teams. Rather than requiring every author to learn a web-development system, CloudPedagogy explores how structured Word documents can become sources for:

  • online courses;
  • Moodle learning resources;
  • interactive visualisations;
  • networks and diagrams;
  • browser-based activities;
  • handbooks and printable publications.

This separates content from presentation.

Authors can concentrate on the meaning, educational structure and accuracy of their material, while reproducible rendering systems handle the technical output.

Word is not the only supported source format. Other systems use structured YAML, JSON, CSV, transcripts and Moodle backup data where these formats are more appropriate to the task.


How the Systems Connect

The portfolio supports different stages of digital-learning development.

Analyse

Understand an existing course, programme or collection of learning materials.

Use Moodle auditing, file extraction, curriculum mapping and structural analysis tools.

Design

Define learning structures, pathways, assessments, relationships and educational workflows.

Use curriculum, assessment, simulation and visualisation systems.

Publish

Transform structured source material into accessible and reusable learning resources.

Use Learning Publisher, Course Engine, the Moodle Book Converter and Word-driven rendering systems.

Deliver

Deploy resources through websites, Moodle, or other digital-learning platforms.

Evaluate

Combine structural information with quality indicators and, where appropriate, selected learning-activity data.

Improve

Update the structured source, document changes and reproduce the required outputs.


Shared Design Principles

CloudPedagogy Digital Learning Systems are guided by a common set of principles.

Structured

Content, relationships, data and decisions should be represented in forms that can be understood, reviewed and reused.

Inspectable

Users should be able to examine the source, assumptions and transformations behind an output.

Maintainable

Educational resources should be updateable without repeatedly rebuilding them through opaque manual processes.

Portable

Where practical, content should not be permanently locked into a single delivery platform.

Reproducible

The same structured source should be capable of generating consistent outputs over time.

Local-first where appropriate

Several applications process information within the user’s browser or local environment, reducing unnecessary transfer of educational data.

Human-controlled

Technology supports the work, but responsibility for educational quality, interpretation and implementation remains human.

Open

Selected tools, demonstrations and source code are published openly to support exploration, adaptation and further development.


Connection to Human–AI Capability

Digital Learning Systems form a distinct but connected part of CloudPedagogy.

The AI Capability portfolio focuses on how people and organisations design, govern and operate AI-supported systems responsibly.

The Digital Learning portfolio applies related principles to educational infrastructure:

  • clear structures;
  • visible processes;
  • inspectable transformations;
  • accountable decision-making;
  • maintainable sources;
  • responsible automation;
  • continuous improvement.

Some systems use AI to support analysis, transformation or workflow design. Others are deterministic publishing, analysis or visualisation tools and do not depend on AI.

Where AI is used, its outputs should remain explainable, reviewable and subject to professional judgement. This reflects the principles of the CloudPedagogy AI Capability Framework and Capability-Driven Development.



Who These Systems Are For

CloudPedagogy Digital Learning Systems are designed for:

  • educators and academic authors;
  • learning designers;
  • digital education teams;
  • programme and module leaders;
  • curriculum developers;
  • educational technologists;
  • quality-assurance teams;
  • researchers;
  • institutions undertaking course redesign or migration;
  • developers exploring open educational infrastructure.

They are particularly relevant where educational content and systems must be understandable, maintainable and transferable across teams or platforms.



Open Projects and Demonstrations

Selected Digital Learning Systems are available as open-source repositories and working demonstrations.

The projects are published as practical implementations and proofs of concept. They can be inspected, tested and adapted in accordance with their respective licences.

Different projects are at different stages of maturity. Demonstrations should be evaluated within their intended educational and technical context before institutional adoption.

The portfolio will continue to evolve as individual systems are tested across additional content types, courses and educational settings.

→ Browse CloudPedagogy on GitHub


Digital Learning with Structure

CloudPedagogy approaches digital education as more than the production of online content.

It is the design of connected systems through which content can be created, understood, published, evaluated and improved.

Analyse with evidence.
Design with clarity.
Publish with structure.
Improve with confidence.


Disclaimer

Unless otherwise stated, CloudPedagogy applications, source code, documentation and associated materials are independently maintained and published through CloudPedagogy.

They are not affiliated with, endorsed by or representative of any employer, university, institution or organisation.

The systems are provided for educational, experimental and illustrative purposes. They do not replace institutional review, accessibility testing, data-protection assessment, security review, quality-assurance processes or professional judgement.

Users are responsible for checking outputs and determining whether a system is appropriate for their technical, educational and institutional context.

Open-source repositories remain subject to their respective licences and terms of use.