I need to write a strong discussion section. Guide me: 1) Start by restating main findings in plain language

Prompt
I need to write a strong discussion section. Guide me: 1) Start by restating main findings in plain language
ClaudeAnthropic
I need to write a strong discussion section. Guide me: 1) Start by restating main findings in plain language

How to Restate Your Main Findings in Plain Language

Purpose


The opening of your discussion should immediately remind readers what you discovered, without making them flip back to your results section. Think of it as your "here's what we found" moment.

Key Principles

1. Lead with a clear, direct statement


Start with a sentence like:
  • "This study found that..."

  • "Our results demonstrate that..."

  • "We observed that..."


2. Focus on the PRIMARY findings first


  • What was your main research question?

  • What's the most important thing you discovered?

  • Don't bury the lead with secondary findings


3. Use plain language, not statistical jargon


❌ Avoid: "We found a statistically significant correlation (r=0.67, p<0.001) between variables X and Y"

✅ Instead: "We found that as X increased, Y increased substantially"

(You can reference the statistics parenthetically if needed, but lead with the meaning)

4. Keep it brief


  • 2-4 sentences typically

  • One short paragraph maximum

  • Save the detailed interpretation for later


Example Template

"This study examined [research question]. We found that [primary finding in plain language]. Additionally, [secondary finding if crucial]. These results [one-sentence preview of what this means]."

Concrete Example

Research question: Does sleep duration affect academic performance in college students?

Good opening:
"This study examined the relationship between sleep duration and academic performance in undergraduate students. We found that students who consistently slept 7-9 hours per night earned significantly higher GPAs than those who slept less than 6 hours. This relationship held even after accounting for study time and prior academic achievement."


What are your main findings? I can help you craft your opening statement.

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GrokxAI
I need to write a strong discussion section. Guide me: 1) Start by restating main findings in plain language

Guide to Writing a Strong Discussion Section

The discussion section of a scientific paper, thesis, or report interprets your results, connects them to broader literature, and highlights implications. It's where you move beyond raw data to explain why your findings matter. I'll guide you step by step, starting with your requested point. This structure assumes a standard empirical study (e.g., in sciences, social sciences, or humanities), but adapt it to your field.

1. Start by Restating Main Findings in Plain Language


Avoid jargon or stats dumps—treat this as a bridge from results to interpretation. Summarize 2–4 key findings concisely, in 1–2 paragraphs, using everyday language to make them accessible. This sets the stage without repeating the results section verbatim.
  • Why it works: Readers (especially non-experts) need a clear reminder of what you found before diving into implications. It shows you understand your own work.

  • Tips:

  • Use active voice and simple sentences.

  • Frame positively but objectively: Focus on what supports your hypotheses, not just surprises.

  • Example (hypothetical biology study on plant stress): "Our experiments revealed that drought-stressed plants produced 30% fewer seeds than controls, but applying a soil fungus boosted seed output by 25%, suggesting the fungus acts as a natural protector against water scarcity."

  • Common pitfalls: Don't introduce new data. If your findings contradict expectations, note it briefly here (e.g., "Contrary to predictions, X did not occur").


2. Interpret the Findings: Explain What They Mean


Now, unpack the "so what?" Link results to your research question, hypotheses, or theory. Discuss mechanisms, patterns, or unexpected outcomes.
  • Key elements:

  • Support or refute hypotheses: E.g., "This aligns with Hypothesis 1, as the increased enzyme activity explains the observed growth."

  • Mechanisms: Speculate reasonably on why (based on evidence, not wild guesses). Cite related studies.

  • Unexpected results: Address limitations or alternative explanations without undermining your work.

  • Length: 2–4 paragraphs.

  • Tips: Use transitional phrases like "These results suggest..." or "This may indicate...". Balance confidence with caution (e.g., "While promising, this requires further validation").


3. Compare to Existing Literature


Situate your work in the field. Show how your findings build on, challenge, or fill gaps in prior research.
  • How to do it:

  • Cite 5–10 key studies: Agree with some (e.g., "Consistent with Smith's 2020 meta-analysis..."), contrast others (e.g., "Unlike Jones et al., we found no effect of Y due to our larger sample size").

  • Highlight novelty: "Our study is the first to examine Z in urban vs. rural contexts, revealing..."

  • Tips: Organize chronologically, thematically, or by agreement/disagreement. Avoid a laundry list—synthesize (e.g., "Building on prior work, our results refine the model by adding variable W").

  • Pitfall: Don't over-cite or ignore contradictions; address them head-on.


4. Discuss Implications


Explore real-world, theoretical, or practical impacts. This is your chance to argue significance.
  • Types:

  • Theoretical: How does this advance knowledge? (E.g., "This supports a revised theory of climate adaptation.")

  • Practical: Applications? (E.g., "Farmers could use this fungus to improve crop resilience in dry regions.")

  • Policy/Societal: Broader effects? (E.g., "Findings urge policy changes in water management.")

  • Tips: Be specific but realistic. Limit to 1–2 paragraphs. If interdisciplinary, note cross-field relevance.


5. Address Limitations and Future Directions


Honesty builds credibility. Acknowledge weaknesses, then pivot to opportunities.
  • Limitations (1 paragraph): Be brief and non-defensive. E.g., "Sample size limited generalizability; future studies should include diverse populations." Avoid blaming external factors.

  • Future research (1 paragraph): Suggest extensions, like "Larger trials or longitudinal designs could test long-term effects."

  • Tips: Frame limitations as stepping stones, not flaws. This shows thoughtful science.


6. Conclude Strongly (Optional Wrap-Up)


End with a forward-looking statement reinforcing the study's value. E.g., "Overall, these findings underscore the potential of microbial interventions for sustainable agriculture." Avoid new info or grand claims.

General Best Practices


  • Length and Flow: Aim for 20–30% of your paper's total length. Use subheadings if allowed (e.g., "Interpretation," "Implications"). Ensure logical progression.

  • Tone: Objective, confident, and concise. Write in past tense for your study, present for general truths.

  • Editing: Read aloud for clarity. Get feedback. Check for bias—balance positives and negatives.

  • Field variations: In qualitative research, emphasize themes over stats; in reviews, focus more on synthesis.

  • Resources: Consult style guides like APA, MLA, or your journal's instructions. Tools like Grammarly or EndNote help with citations.


If you share more details about your study (e.g., field, key findings), I can provide tailored examples or refine this guide!
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Analysis

This comparison demonstrates the different approaches each AI model takes when responding to the same prompt. Here are the key differences observed:

Response Characteristics

Claude: Provides a direct response with 29 sentences.

Grok: Provides a concise response with 112 sentences.

Key Takeaways

  • Each model brings unique strengths to this type of query
  • Response styles vary significantly between models
  • Consider your specific use case when choosing between these models

Try This Comparison Yourself

Want to test these models with your own prompts? Visit SNEOS.com to compare AI responses side-by-side in real-time.


This comparison was generated using the SNEOS AI Comparison ToolPublished: October 15, 2025 | Models: Claude, Grok