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AI Skills: From Attendance to Demonstrated Practice

AI Skills: From Attendance to Demonstrated Practice — Original analysis and practical exercises from Mustanef.

العربية — المادة المقابلة

Attendance counts do not show what learners can do. Capability requires a task and rubric distinguishing polished responses from sound decisions.

The decision to examine

Assess task framing, verification, data minimisation and review. Ask learners to fix a weak answer and explain their changes, with a paper alternative where needed.

Worked example

Instead of recalling tool names, present an unsupported claim and ask what needs evidence and how to check it. Credit verification quality rather than response length.

From idea to practice

  1. Describe the problem as a need, not a product name.
  2. Specify evidence needed before a decision and who reviews it.
  3. Test a non-personal example and log failures as well as successes.
  4. State whether to continue, improve or stop and why.

Your exercise

Design a three-part rubric: identify, correct and explain limits. Apply it to one hypothetical example.

Review rubric

A useful answer identifies a context, checkable evidence, a boundary and an owner for the next step. If it fits any organisation unchanged, add a detail specific to the case. This is a learning rubric, not automatic marking or official assessment.

Further reading: Readiness Assessment Methodology — UNESCO · 2023; RAM portal reviewed 2026 · Checked: 8 October 2026

Your next step

Open the readiness notebook · Explore policy sources

Institutional DJAIRI material prepared with AI assistance. Learning examples are hypothetical; analysis and recommendations are Mustanef’s. Citing a source does not imply partnership or endorsement.