An integrated system for
professional VET education
CyberTAFE delivers industry-aligned vocational education through a purpose-built ecosystem — connecting course development, AI-assisted resource generation, automated grading, and online delivery in one coherent platform.
From unit standard to student outcome
Every piece of the CyberTAFE system fits into a structured development and delivery pipeline aligned to ASQA’s Standards for RTOs.
The tools that power CyberTAFE
Each component is purpose-built for the Australian VET sector, working together as a unified system.
The delivery layer — students enrol, access course content, submit assessments, and track their progress through a branded CyberTAFE interface.
- Custom CyberTAFE VCCMS theme (Moodle 5.x)
- Course sections mapped to unit elements
- Completion tracking per activity
- Gradebook aligned to competency outcomes
- Forum, quiz, assignment and SCORM support
A custom PHP/MySQL platform for managing VET content — the single source of truth for all units of competency, resources, and mapping records.
- Unit of Competency catalogue with PC mapping
- Training package taxonomy (AQF 1–8)
- Twelve resource types across four categories
- ASQA compliance checklist per unit
- Dual-track version control system
Integrated with the Anthropic Claude API, the engine auto-generates learning resources directly from performance criteria — dramatically reducing development time.
- Generates all 5 resource types from PC text
- Outputs are mapped to specific criteria codes
- Knowledge evidence automatically addressed
- Scenario activities use industry-specific context
- Human review and edit before publishing
An AI-powered short-answer grading tool (v3) for knowledge-based assessments. Teachers upload a marking guide; students receive instant, consistent AI feedback.
- Accepts student answer uploads in bulk
- Grades against teacher answer key via Claude API
- Produces Teacher Report and Student Report
- Student report: question number + feedback only
- PDF export and printable session history
Evidence-based competency assessment grader for practical projects. Evaluates submitted evidence against marking rubrics, producing competency determinations.
- Rubric-driven competency / not-yet-competent outcomes
- Evidence review with AI-generated feedback
- Separate
dg_database tables - Shares MySQL database with Answer Grader
- Designed for portfolio and project submissions
A supplementary student resource portal with 99+ module files covering networking labs, reference guides, Packet Tracer exercises, and interactive tools.
- Lab guides and cheat sheets per unit
- Interactive subnet calculator
- Packet Tracer lab exercises (DHCP, email, TFTP)
- Network command reference with explanations
- PHP authentication system with admin tooling
12 resource formats, four categories
Every unit of competency can draw on twelve resource types organised into four categories — Content, Interactive, Contextual and Media. Each is mapped to specific performance criteria and knowledge evidence.
Structured written content — theory explanations, reading material, and foundational knowledge for each unit.
Knowledge EvidenceRich interactive HTML content — styled study guides, embedded diagrams, and formatted reference pages.
Study GuideCurated external resources — vendor documentation, Training.gov.au references, and industry standards.
ReferenceMultiple choice and short-answer questions testing knowledge evidence — graded via the AI Answer Grader.
Knowledge EvidenceHands-on practical tasks — Packet Tracer labs, VirtualBox environments, command-line drills and configuration exercises.
Practical SkillsStructured observation checklists for assessors and self-assessment — verifying skill demonstration against performance criteria.
Assessment EvidenceWorkplace simulation scenarios requiring applied decision-making — AI-generated with industry-specific context mapped to performance criteria.
Performance CriteriaGuided reflective prompts asking students to connect learning to their own workplace experience and prior knowledge.
Foundation SkillsReal-world or simulated organisational case studies for analysis — supporting higher-order application of knowledge across a unit.
Applied KnowledgeDiagrams, network topology maps, screenshots and visual aids embedded within units to support understanding.
Visual SupportInstructional video content — walkthroughs, demonstrations, and recorded lab sessions linked or embedded per unit.
Instructional MediaDownloadable assets — lab files, Packet Tracer activities, templates, configuration scripts and reference documents.
Downloadable AssetAvailable training modules
Units are developed in training package clusters. Each unit is fully resourced with AI-generated materials, lab exercises, and grading rubrics before release.
From enrolment to competency
Students access CyberTAFE’s Moodle instance at moodle.cybertafe.com and enrol into a qualification or skill set. Each course is structured around units of competency.
Each unit contains study guides, knowledge checks, and scenario activities — all generated by the VCCMS pipeline and mapped to specific performance criteria.
Hands-on practicals are completed in virtual labs (VirtualBox environments with Kali, Metasploitable, pfSense) or via Cisco Packet Tracer simulations.
Short-answer assessment tasks are graded through the Answer Grader — students receive a personalised feedback report per question within minutes.
Practical projects and evidence portfolios are assessed via the Project Grader, which evaluates performance against unit rubrics and issues a competency determination.
Once all units are assessed as Competent, students receive their qualification or statement of attainment — aligned to the Australian Qualifications Framework.
How content gets built
The course developer downloads the unit of competency from Training.gov.au and identifies all elements, performance criteria, knowledge evidence and assessment conditions.
The unit is entered into VCCMS at vccms.cybertafe.com with training package classification, AQF level, and all performance criteria mapped into the system.
The developer uses the built-in AI generation tool — Claude API reads the performance criteria and generates draft resources across all five types in seconds.
Every generated resource is reviewed against the original unit standard, edited for accuracy, and mapped to specific performance criteria codes before approval.
The built-in compliance checklist verifies coverage against all knowledge evidence and performance criteria — producing an audit trail before the unit is published.
Approved resources are deployed into the Moodle course structure — grader rubrics uploaded, activities configured, and the unit marked active for enrolment.
A hosted, secure platform
All CyberTAFE tools run on a hosted Ubuntu 24.04 server, protected by Cloudflare Tunnel — no open ports, private data stays on-premises.