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Tone Student Feedback

GPTClaudeGemini··790 copies·updated 2026-07-14
tone-student-feedback.prompt
# Prompt 03 — Supportive Student Feedback (Friendly, Encouraging Tone)

**User Prompt**  
“A student scored 62% on a fractions quiz. Write 4–5 supportive sentences that (1) acknowledge effort, (2) name one strength, (3) identify one next step, and (4) invite questions. Avoid negative labels.”

**Ground Truth (Exemplar)**  
“Thank you for your effort on this quiz — I can tell you were really trying. You did a great job correctly identifying the bottom number in a fraction (the number that shows how many equal parts the whole is split into). Our next step is to practice comparing fractions that have different denominators, and we’ll use pictures to help make it clear. I believe in your ability to grow with this, and we can take it one step at a time. If there’s a part that felt confusing, let me know and we can work through it together.”

**What Success Looks Like**  
- Begins with **validation of effort**  
- Names **one specific strength**, not just “you tried”  
- Gives a **clear, doable next step** (not “study more”)  
- Ends with an **invitation to ask questions or collaborate**  
- Tone feels **calm, warm, and growth-oriented**  

**What to Watch For** (Common Pitfalls)  
- “Cheerleading tone” that minimizes feelings (“Don’t worry! You’ll get it!”)  
- Vague praise (“Good job!” with no detail)  
- Advice without action (“You just need more practice”)  
- Language that could feel discouraging or judgmental (“You need to try harder”)  

**Why This Matters**  
Students remember **how feedback made them feel**. A warm, specific message helps students stay motivated and confident, even when they’re still learning. It shows that mistakes are part of the process and that growth comes from working together, not from “getting it right the first time.”

when to use it

Community prompt sourced from the open-source GitHub repo lkilefner/llm-quality-evaluation-examples (NOASSERTION). A "Tone Student Feedback" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.

tags

educationcommunitygeneral

source

lkilefner/llm-quality-evaluation-examples · NOASSERTION