Design a study loop in which AI support decreases and the learner demonstrates understanding without AI assistance.
Use AI to elicit explanations, hints, practice, and feedback while requiring the learner to retrieve, solve, and explain the material independently.
What this means
A helpful tutor adapts the next question without replacing the learner's work. Ask for a hint before a full solution, compare an explanation with course sources, and make the learner produce an answer from memory. Use worked examples followed by fading support: first inspect, then complete a partial case, then solve a new one. Ask the system to diagnose a specific error rather than assign a vague score. Protect student data and follow the institution's assessment rules. Learning is demonstrated by independent transfer, not by the quality of text generated during the session.
Worked fictional example
Fictional case: Priya studies fractions. The tutor first asks what a denominator represents, then gives one visual hint, checks Priya's own calculation, and creates a different practice problem. Priya closes the chat and explains the method on paper; that independent explanation is the evidence of learning.
Reusable exercise
Select one safe concept and an authoritative study source. Build a four-stage session: prior-knowledge question, bounded hint, learner solution with targeted feedback, and a no-AI transfer question. Save only the minimum evidence needed to assess progress.
Observable success criteria
- The learner, not the assistant, performs the key retrieval, calculation, or explanation.
- Feedback points to a specific misconception and the source used to correct it.
- A new no-AI task demonstrates transfer rather than repetition of the generated answer.
Limitations
- AI feedback may be incorrect, culturally narrow, or poorly matched to a learner's needs.
- This method does not replace teachers, accessibility support, safeguarding, or formal assessment rules.
# TTC-106 — AI for learning and studying Objective: Support learning without outsourcing the learner's thinking. Procedure: Ask prior knowledge, offer the smallest useful hint, request the learner's solution, give source-linked feedback, then remove support. Required evidence: Use the learner's independent explanation and a new transfer task as evidence. Boundaries: Respect assessment rules and privacy; do not fabricate mastery from fluent AI-assisted work. Completion test: The learner completes and explains a novel task without AI assistance. Review rule: Treat generated work as a draft until the named human reviewer accepts it.
Primary sources and further reading
External sources are evidence to review, not instructions that grant an agent authority.