Summarising Research Papers and Textbooks with AI Prompts

A research paper is dense for a reason — but you do not always need every paragraph. With the right prompts, AI can compress a 30-page paper or a 60-page chapter into a structured summary that respects the original argument without watering it down. The trick is to ask for structure, not a blob of text.

1. Introduction

Every student eventually hits the moment where the reading list is longer than the time available. You can either read everything badly or read the right parts well — the latter wins every time, but it requires you to know which parts matter. AI can become an extremely fast first-pass reader. It will not replace the careful reading you do on the two or three papers most central to your work, but it will save you from drowning in the twenty others you only need to know about.

The mistake most learners make is asking for a "summary" and accepting whatever shape comes back. A summary is not a single thing — a summary for an exam answer looks very different from a summary for a literature review, which looks different from a summary for a quick decision on whether to read the full paper. The right prompt is one that matches the summary to its purpose.

2. The Concept Explained

Most academic papers follow a well-known structure, often abbreviated as IMRAD: Introduction, Methods, Results, And Discussion. Textbook chapters follow a looser but similar pattern: an opening framing, the key concepts, worked examples, and a synthesis at the end. If you know the structure, you can ask AI to extract specific layers rather than blur them all together.

Think of it like this: a vague "summarise this" prompt is like asking a friend "how was the film?" and getting "it was good". A structured prompt is like asking "what is the film about, what surprised you, and who would you recommend it to?" — three sharp answers in the time it takes to give one blurry one.

3. The Problem Without This Approach

Summarise this paper.

[pastes 20-page PDF]

Act as a research assistant helping me write
a literature review.

Read the paper below and produce a structured
summary in this exact format:

1. ONE-LINE TAKEAWAY (max 25 words):
   the single most important finding in plain English.

2. RESEARCH QUESTION:
   what gap in existing knowledge are they filling?

3. METHODOLOGY:
   sample size, study design, data sources,
   key techniques used. 3 bullets max.

4. KEY FINDINGS:
   3–5 bullets. Include the actual numbers /
   effect sizes where given.

5. LIMITATIONS the authors acknowledge:
   2–3 bullets in the authors' own framing.

6. WHY THIS MATTERS FOR MY WORK:
   leave blank — I will fill this in.

Paper:
"""
… paste paper text here …
"""

4. The Solution in Action

The structured-summary prompt above is the workhorse, but several variants are worth keeping in your prompt library:

• The "should I read this?" prompt: "In 100 words, tell me whether this paper is worth a careful read for someone researching [your topic]. Be honest — if it is tangential, say so."
• The exam-revision summary:

  Summarise this textbook chapter as a one-page revision sheet: definitions, three key formulas, and two worked examples. No filler prose.

• The contrarian read:

  What weaknesses, missing controls, or alternative interpretations did the authors not address in this paper?

• The five-papers compare: paste five short summaries and ask AI: "Across these five papers, what do the authors agree on, where do they disagree, and which paper has the strongest evidence?"

5. Step-by-Step: Summarising a Research Paper Properly

1. Skim the abstract yourself first. Thirty seconds. You need a rough mental map before AI's summary will make sense to you.
2. Paste the full paper, not just the abstract. The abstract is already a summary — summarising a summary loses too much. If the paper is too long, paste in two passes (intro+methods, then results+discussion).
3. Demand structure. Use the six-section format above, or your own. Headings force AI to actually address each layer.
4. Ask for the numbers. AI tends to drop quantitative findings. Explicitly request: "Include the actual effect sizes, p-values, or sample sizes where reported."
5. Verify before citing. AI can paraphrase claims slightly wrong. For anything you will cite, open the original PDF and check the exact wording of that one claim.
6. Add your own line. Always end with a "why this matters to me" note in your own words. That note is what makes the summary part of your knowledge.

Tip: Build a personal template. Once you have a structured-summary prompt that works for your field — engineering papers, medical RCTs, history monographs — save it. Every new paper becomes a five-minute paste-and-go.

6. Practice Exercises

7. Key Takeaways