AI tutoring and learning support

In short

Building a tutor that teaches instead of answering: grounding to the actual course material, refusal and Socratic behaviour, age-appropriate guardrails, and how you evaluate whether it helped anybody learn.

4 pages

definitions

A misconception library: the wrong answers you author on purposeA catalogue of the wrong ideas learners hold, the answers that betray each one, and the response that argues with the idea instead of reteaching the whole topic.definition6 min
Fading: the point where a tutor is supposed to become less helpfulFading is the planned withdrawal of support once a learner has earned it. Left to prompt drift it never happens, and the result is dependence that reports as engagement.definition6 min
The hint ladder, and why it belongs in the content rather than the promptA hint ladder is authored content attached to an item, not an instruction in a prompt. The model should choose a rung, not invent one, because an invented rung cannot be tested.definition6 min

diagnostic

The method is correct and the arithmetic is wrongSound explanation, wrong number. Re-execute the numeric steps of fifty transcripts before changing anything: the split between method errors and computation errors decides which repair is worth making.diagnostic9 min

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Student data privacy, engineeredWhat FERPA, COPPA and GDPR for minors actually do to an architecture — which records may reach a model at all, who can see what, how long anything is kept, and what a school's security review will make you prove.8 pages Admissions, enrolment and student-services assistantsEnquiry and advising assistants grounded in the institution's own documents: where deflection is genuinely safe, where a human has to take the question back, and what the CRM has to know once the conversation ends.7 pages

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