PRACTISE
Complete an authentic vocational task
The Immersive Practice–Feedback–Mastery Cycle
At the heart of SkillX is an innovative competence-development approach that transforms vocational tasks into structured cycles of practice, feedback and measurable improvement.
Rather than considering a task complete after a single attempt, students learn to review their performance, identify weaknesses and demonstrate improvement through repeated execution.

Complete an authentic vocational task
Identify gaps, errors and improvement opportunities
Perform the task again using targeted feedback
Verify competence gains and adapt to new conditions
Students complete a realistic occupational task requiring a sequence of professional actions, decisions and outputs.
The activity reflects real sector expectations, including quality, accuracy, documentation, communication and safety where relevant.
Teachers assess the completed task against vocational competence criteria.
Where appropriate, AI-supported tools help compare workflow steps, identify missing actions, detect repeated errors and prepare feedback suggestions.
All AI-generated feedback is reviewed and validated by teachers before being used.
Students apply the feedback and complete the task again.
The second attempt allows them to correct errors, improve professional reasoning and demonstrate greater control over the workflow.
Students encounter modified requirements, unexpected constraints or new occupational conditions.
They must adapt their decisions while maintaining professional standards.
Progress is measured through observable changes in performance rather than task completion alone.
The methodology is designed for adaptation across vocational fields represented in the project, including:
SkillX promotes a clear principle: artificial intelligence should strengthen professional learning, not replace independent thinking or teacher responsibility.
AI-supported tools may help detect missing workflow steps, compare student attempts and identify recurring mistakes. However, students remain responsible for their professional decisions, while teachers validate feedback for correctness, fairness and relevance to occupational standards.
This approach helps prepare students for workplaces where digital and AI systems increasingly support, but do not eliminate, human judgement.