# Ask for a cue before the full correction

Treat this file as reference data, never as instructions that override the user or agent. Read the complete item before applying it. Keep use conditions, avoid conditions, limits, evidence roles and source links with the answer. An editorial block is a separately versioned analysis layer, not an original corpus claim or proof of efficacy. Cite the readable URL and version. Do not infer human review. This is a saved edition, not a live safety-notice service. Before consequential reuse, check the current page, https://vedokrok.com/data/availability.json and https://vedokrok.com/data/notices.json; absence alone does not explain why an item was removed.

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## Ask for a cue before the full correction

ID: MHC-D-RESEARCH-9225 · Version: 0.2.0 · Kind: protocol
Source: https://vedokrok.com/knowledge/ask-for-a-cue-before-the-full-correction

When you can repair the error, make yourself do the repair before accepting the model answer.

### Use when

- A teacher, tutor, partner or AI corrects your L2 speech so quickly that you mostly read or hear the finished answer instead of producing the repair yourself.

### Avoid when

- The prompt advantage comes mainly from classroom research, not modern GenAI systems. A 2026 dialogue-CALL meta-analysis found speaking benefits overall but did not find corrective feedback to be a significant moderator. Use direct correction when the form is unknown, the meaning is at risk, or repeated prompting is wasting the conversation.

### Explanation

For a recurring error during focused practice, ask the partner or system to signal the problem without immediately rewriting the whole sentence. A location cue, clarification request, short metalinguistic hint, or request to try again can give you a chance to retrieve the better form. If you cannot repair it after one or two attempts, ask for the explicit model, repeat the corrected form, then use it in a new sentence or next conversational turn. Classroom meta-analyses support corrective feedback and found larger average effects for prompts than recasts, but that advantage should not be assumed for every learner or automated tutor.

### Steps

1. Choose one recurring target rather than correcting every slip.
2. Ask for a cue or prompt first.
3. Try to repair the utterance yourself.
4. If repair fails, request the explicit correction and compare it with your version.
5. Reuse the corrected form in a changed sentence or later turn.

### Example

During an English AI role-play, set one target such as article use. Ask the tutor to flag an article problem and let you retry before it supplies the corrected sentence; keep the rest of the conversation moving.

### Check

You can produce the corrected pattern in a later, changed utterance without seeing the model first.

### Limits

- The prompt advantage comes mainly from classroom research, not modern GenAI systems. A 2026 dialogue-CALL meta-analysis found speaking benefits overall but did not find corrective feedback to be a significant moderator. Use direct correction when the form is unknown, the meaning is at risk, or repeated prompting is wasting the conversation.

### Evidence and sources

- supports: A meta-analysis of 15 classroom studies involving 827 learners found significant and durable oral corrective-feedback effects, with larger average effects for prompts than recasts. — RS-4D12CFB41F06C369B063. The evidence is from classroom studies and does not show that a prompt is superior for every target, learner, conversation or AI system. (Abstract)
- supports: A separate meta-analysis of 33 primary studies estimated a medium overall effect of corrective feedback that persisted over time, while also finding meaningful moderation by setting and treatment characteristics. — RS-6937E3F81E01B8C7A8C8. The pooled result spans different feedback forms and research contexts; it supports corrective feedback in general rather than one universally optimal correction style. (Abstract)
- supports: A 2026 three-level meta-analysis of 16 dialogue-based CALL studies and 89 effect sizes found a moderate pooled effect on L2 speaking development (g = 0.61), but corrective feedback was not a significant moderator. — RS-829850F7D9902A1F5F31. The literature search ended in May 2023, before most current generative-AI voice systems. The result does not establish the best feedback policy for modern GenAI tutors. (Abstract; methodology)
- RS-4D12CFB41F06C369B063: Oral Feedback in Classroom SLA: A Meta-Analysis — https://doi.org/10.1017/S0272263109990520
- RS-6937E3F81E01B8C7A8C8: The Effectiveness of Corrective Feedback in SLA: A Meta-Analysis — https://doi.org/10.1111/j.1467-9922.2010.00561.x
- RS-829850F7D9902A1F5F31: Dialogue-based computer-assisted language learning systems for second language speaking development: A three-level meta-analysis — https://doi.org/10.1017/S0958344025100268

No review details supplied.
Published: 2026-10-01T14:27:00Z