Prof Lennart Nacke, PhD Profile picture
Sep 3, 2022 β€’ 8 tweets β€’ 29 min read β€’ Read on X
Sure, IMRaD is a scientist's ballgame, but have you heard of IRMReDiLiFuConcR?

That's how we roll at #chi2023.

Here's what's in that tongue-twisting paper structure:
πŸ§΅β†“
Introduction:

β†’ What is known?
β†’ What is unknown?
β†’ How and why should we fill the gap?
β†’ Why should people care?

Use @Grammarly @HemingwayApp @languagetool @Writefullapp @TheQuillBot @ReadableHQ @whoisjenniai when editing this section (and the rest of your paper) to rock.
@Grammarly @HemingwayApp @languagetool @Writefullapp @TheQuillBot @ReadableHQ @whoisjenniai Related work:

β†’ Prepare the state-of-the-art you will talk about later in your discussion.

Use tools like @paperpile, @pure_suggest, @ConnectedPapers, @RsrchRabbit, @scite, @scholarcy, @elicitorg, @LitmapsApp, @sci_hub_, @Science_Open to make this easy for yourself.
@Grammarly @HemingwayApp @languagetool @Writefullapp @TheQuillBot @ReadableHQ @whoisjenniai @paperpile @pure_suggest @ConnectedPapers @RsrchRabbit @scite @scholarcy @elicitorg @LitmapsApp @sci_hub_ @Science_Open Methods:

β†’ What did you do?

β†’ Present all specifics.

Write this first!

Nothing like @NotionHQ to keep track of things while you run your experiments.
@Grammarly @HemingwayApp @languagetool @Writefullapp @TheQuillBot @ReadableHQ @whoisjenniai @paperpile @pure_suggest @ConnectedPapers @RsrchRabbit @scite @scholarcy @elicitorg @LitmapsApp @sci_hub_ @Science_Open @NotionHQ @rstudio @jamovistats @JASPStats @figma @inkscape Discussion, Limitations, Future Work:

β†’ Meaning and implications of this research.
β†’ How do the results fill the gap?
β†’ Where do your results not apply?
β†’ What should we do next?

Check my last thread for an in-depth dive into how to write a discussion section.
@Grammarly @HemingwayApp @languagetool @Writefullapp @TheQuillBot @ReadableHQ @whoisjenniai @paperpile @pure_suggest @ConnectedPapers @RsrchRabbit @scite @scholarcy @elicitorg @LitmapsApp @sci_hub_ @Science_Open @NotionHQ @rstudio @jamovistats @JASPStats @figma @inkscape Conclusion: 5Cs

β†’ Why did your advancement matter?

1. Close the loop.

2. Conclude. Show what your final position is.

3. Clarify. Why it's relevant.

4. Concern. For whom does it matter?

5. Consequences. End by noting in one final sentence why this is of such importance.

β€’ β€’ β€’

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More from @acagamic

Nov 25
Most researchers waste months on a systematic review

(when a rapid review would have been good enough.)

Two review types. Same question.
Completely different amount of work.

According to this paper, 14 literature review types exist.

If you get started, focus on 2 main types: Table listing 14 literature review types with descriptions and columns for methods: search, appraisal, synthesis, and analysis.
Run a systematic review when you’re shaping guidelines.
Use a rapid review when leadership wants an answer this quarter.

Systematic reviews:

β€’ Multi-database + grey literature search, no date limits
β€’ Typically used for guidelines or high-stakes decisions
β€’ Dual screening + full critical appraisal, validated tools
β€’ In-depth narrative synthesis to explain heterogeneity
β€’ Detailed evidence tables, if possible, meta-analysis
β€’ Formal, pre-registered protocol (e.g. PROSPERO)
Rapid reviews:

β€’ Typically used for time-sensitive service (1–6 months)
β€’ Output a short decision brief, slide deck, or summary
β€’ High-level narrative summary with minimal detail
β€’ Focused search (fewer databases, tighter limits)
β€’ Single-reviewer screening with spot checks
β€’ Streamlined or internal-only protocol
Read 8 tweets
Nov 19
Google just killed keyword search

But most researchers haven’t noticed yet.

That's a mistake.
The era of guessing keywords is over.

Google released Gemini 3 yesterday and it's amazing.

But Scholar Labs changes how gaps are discovered. Website mockup showing a Google Scholar Labs interface with Gemini 3 logo, a semantic search query about hydrogen cars, AI summaries and session search history.
Conceptual search is taking its place.

Here are 5 ways Scholar Labs beats traditional literature searches:

1. You search concepts, not keywords

Traditional search = β€œcaffeine and memory.”
Conceptual search =
β€’ caffeine consumption
β€’ short-term memory mechanisms
β€’ age variations

One search. Three dimensions. Better results.
2. Context comes built-in

Every paper comes with an explanation of how it answers your question.

No more reading 30 abstracts to find 3 relevant papers.
Quick summaries get you sorted.
Read 9 tweets
Nov 14
Most academics stare at blank pages for hours.

They wait for clarity before writing.

They check email first.

They convince themselves they need more research.

All wrong.

Writing creates clarity. Not the other way around.

Here's the 20-minute routine that fixes this...
Step 1: Write 3 sentences in 2 minutes

Problem:
What needs solving?

Gap:
What's missing in current research?

Contribution:
What will your work add?

Don't edit. Don't perfect.
Just get these three on the page.

This anchors everything that follows.

But here's where most people quit...
Step 2: Freewrite for 10 minutes on one subsection

Pick any part of your paper:

Introduction.
Methods.

One paragraph of results.

Write without stopping.
Don't delete. Don't fix grammar.

The goal isn't good writing.
It's getting your thinking out of your head and onto the page.

Once you have raw material, then...
Read 7 tweets
Nov 12
Research objectives are promises.

Vague promises signal amateur planning.
So, don't wonder why reviewers reject them.

After reviewing 100+ proposals,
I built a 5-question validator
that eliminates weak objectives.

Here's the framework:
The Real Problem:

Weak objectives hide behind vague language.

β†’ "Use mixed methods approach"
β†’ "Throughout the project"
β†’ "Fill a gap in literature"

These phrases signal amateur planning.

Reviewers spot them instantly.
Question 1: Why does this matter?

Weak: "Fill a gap in literature"
Strong: "Solves X problem affecting Y people"

The difference?

Weak answers describe process.
Strong answers quantify impact.
Read 9 tweets
Nov 3
After reviewing almost 100 papers for CHI,

I've noticed awesome research get killed on page 1.

Your paper has 8,000+ words.
Reviewers spend < 3 minutes to form an impression.

If they can't see why your work matters,
how you proved it, and what changes.

They reject it.

Most papers try to prove everything.
Everywhere.

Here's the 3R framework that wins best paper awards:The three Rs.
Every section serves ONE purpose:

Relevance: Why this study matters now.
Reasoning: How you built and tested it.
Resolution: What changes from your work.

Never all three at once.
Relevance = Your Introduction

Your intro answers one question:
Why should anyone care RIGHT NOW?

Not "this topic is important."
Not "previous research suggests."

The gap + problem that make your study urgent.
Read 11 tweets
Nov 1
Harvard just admitted their grading system is broken.

About 60% of grades are now As.

Two decades ago? Only 25%.

Faculty say grades don't match work quality anymore.
Sound familiar? Your PhD program faces the same crisis.
Grade inflation is everywhere.

But Harvard's new report confirms what I've known:Grades don't measure learning anymore.
Evaluation systems are broken.

Well-intentioned pedagogy created perverse incentives.
The culprit? Loss aversion + grade compression.

Here's the evidence:
Harvard's median GPA hit 3.83 for the Class of 2025.
For the Class of 2015?
Just 3.64.

Since 2016, the median GPA has been an A.
Read 14 tweets

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