Pack Ayoub AI correction: TCF criteria, analysis, and feedback

Pack Ayoub AI correction analyses written and spoken practice according to the criteria used to structure TCF preparation: task completion, organisation, language accuracy, range, clarity, and fluency where relevant.

The feedback becomes useful immediately: select the highest-impact problem, improve the passage or recording, and test the same skill on another topic. Unlimited analyses let you repeat this loop throughout your access period.

A useful comment should lead to an action: add a missing request, reorder two ideas, clarify a reference, repair an agreement pattern or ask a responsive follow-up. If a suggestion is vague, compare it with the prompt and identify the exact reader or listener problem.

Retain your original attempt. Without it, you cannot compare the decision that produced the error with the revision that repaired it.

A sophisticated phrase cannot repair a response that ignores the recipient or required action. First verify relevance and completeness, then organisation, then the language patterns that affect clarity. Stylistic variety comes after those foundations.

After studying feedback, close it and produce the passage again. In speaking, record a new answer rather than reading the suggested version. In writing, apply the same principle to a different prompt so your progress does not depend on one corrected text.

An estimate can help compare attempts made under similar conditions and highlight a skill to review. It cannot reproduce every examiner judgement, official scoring procedure or test-day condition.

Do not use a dashboard estimate as proof of an NCLC level, immigration eligibility or a guaranteed future result. Use official documents for official decisions.

A transcript can reveal structure and language, but it does not contain pace, intelligibility or responsiveness. Listen to the original recording, select a short passage and record a new answer without reading the revised text.

For interaction tasks, vary the other person’s reply. A stronger second attempt should respond to the new information rather than reproduce the first corrected exchange.

Compare every substantial suggestion with the instruction. Reject invented details, unsupported certainty and changes of register that do not fit the recipient. Ask what problem the edit is supposed to solve.

This verification is part of learning. AI output is not an authority simply because it is fluent; the learner remains responsible for relevance and truth in the response.

For each session, save the prompt, original response, one priority comment, your explanation and the independent rewrite. Add the date on which you will test the same operation again.

A compact record makes recurring patterns visible without producing an overwhelming archive of every automated remark. Promote a problem to the personal checklist only when it appears repeatedly or has high impact.