Learning & explanation · Learning method
Self-explanation & teach-back
Explain a mechanism in your own words, then check the explanation against evidence.
What it helps you do
Reveal gaps between recognizing a polished answer and being able to explain why its steps work.
Starting knowledge: No specialist knowledge is required.
- Explain a step without merely repeating its wording.
- Connect the step to a principle or prior fact.
- Check the explanation, correct it, and try a new case.
The problem it came from
Chi and colleagues’ 1989 study investigated explanations learners generated while studying mechanics examples. It connected the quality of those explanations with how the learners used the material.
Teach-back is a related practice of explaining understanding to someone else. Popular “Feynman technique” labels are informal shorthand; they are not a standardized assessment or proof of understanding.
Work through an example
“After comparing the target with the middle value, I keep the half that could still contain it. This only works because the list is ordered. If the target is smaller, every value above the middle is also too large.”- The explanation names the condition that makes elimination valid.
- It connects an action to a reason.
- A new task is still needed to check performance.
Where it helps. Where it stops.
Use it when
- Studying an example or verifying a mental model after an explanation.
- A learner says an answer makes sense but struggles to predict a result.
Potential benefits
- Articulating a causal link exposes a missing justification.
- Comparing explanations with a source supports targeted correction.
Limits and common mistakes
- A fluent explanation may still be wrong.
- An AI tutor can give mistaken feedback; use a reviewed answer or an independent check.
The prompt below asks for this structure. It does not guarantee accuracy, complete coverage, better learning, or conformance to a standard. Treat those outcomes as separate checks.
Practise the judgment
Try a choice, inspect a boundary, then explain a case yourself. Hints and answers are available whenever you need them.
Which teach-back gives stronger evidence about a learner’s model?
Hint
Look for an explanation of a boundary.
Explained answer
Best answer for this case: Explaining why an unsorted list breaks binary search
The learner must connect the ordering assumption to the elimination step. That is more informative than reproducing wording.
A model praises your explanation but a small test contradicts it. What should you trust next?
Hint
A fluent evaluator can be mistaken.
Explained answer
Best answer for this case: Investigate the contradiction against the source and test
Feedback is evidence to inspect, not authority that overrides observations.
Explain why “removing half the items” alone is not a sufficient description of binary search.
Hint
What stops the algorithm discarding the answer?
Explained answer & self-review rubric
The retained half must be justified by order and comparison. Randomly removing half can discard the target. Correct elimination preserves the possibility of finding every remaining valid candidate.
- State the ordering assumption
- Explain comparison-based elimination
- Describe what must remain possible
Take it into your own work
Manual template
Use this structure yourself, with a colleague, or in your preferred writing tool.
# Explain it back
Concept or step:
My explanation in my own words:
Why does this step work?
Assumptions:
Prediction for a new case:
Check against source or observation:
Correction:
Review the result
- Did I explain why, not only what?
- Which assumption supports the step?
- Did a prediction agree with the result?
Use this approach with your own AI tool
Help me apply Self-explanation & teach-back to the material below.
Reader and existing knowledge: [describe]
Task and desired outcome: [describe]
Use these principles: Explain a step without merely repeating its wording.; Connect the step to a principle or prior fact.; Check the explanation, correct it, and try a new case..
Preserve source facts, identifiers, quantities, conditions, exceptions, and uncertainty.
Separate supplied facts from assumptions. Ask for missing information instead of inventing it.
Explain your representation choices and provide a review checklist. Do not claim formal compliance or correctness from formatting alone.
Material: [paste only information you are permitted to share]Go to the source
History and the underlying approach are grounded in these references. Examples, prompts, and practice cases here are original educational adaptations. Edition-specific details should be checked against the referenced publication.
Last editorial review: 2026-10-24. An overview is not certification, and this guide is not a reproduction of a standard.