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: Run a systematic review when you’re shaping guidelines.
Use a rapid review when leadership wants an answer this quarter.

Systematic reviews:

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

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. Conceptual search is taking its place.

Here are 5 ways Scholar Labs beats traditional literature searches:

1. You search concepts, not keywords

Traditional search = “caffeine and memory.”
Conceptual search =
• caffeine consumption
• short-term memory mechanisms
• age variations

One search. Three dimensions. Better results.

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...

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.

→ "Use mixed methods approach"
→ "Throughout the project"
→ "Fill a gap in literature"

These phrases signal amateur planning.

Reviewers spot them instantly.

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: 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.

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: Evaluation systems are broken.

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

Here's the evidence:

Rejected within 24 hours.

That’s how my academic journey really started.

My writing has never been the same since.
Here’s what I learned from 300+ submissions:

Too many papers get rejected instantly. I still remember opening my inbox at 6 AM.
One line: "We regret to inform you…"
I’d spent six months on that paper.
I thought it was genius.

Well, turns out it wasn’t.
It was unreadable.

Why?

Most PhD students fail at research questions.

(I used to be one of them)

See, back when I started my research journey,
I thought coming up with research questions was luck.

Just throw something at the wall and hope it sticks.

Wrong.

After helping 100s of students with their research,
I've discovered a secret 4-step question formula: 1. Start with scope
Don't jump straight to questions.
First, outline your broad area in 1-2 sentences.

Example: "Virtual reality user interactions"
This gives you boundaries to work within.

Top researchers publish 2x more papers.

More papers, faster defence, higher grant rates.
Same effort, double output.

They all follow the same 3-pillar optimization system.

Here are 3 pillars of research superstars:
(and the research habits that compound results) Pillar 1: Cognitive Foundation
Your brain is your primary research tool.

• Mindfulness before high-stakes presentations
• Consistent sleep for memory consolidation
• Regular exercise for enhanced focus

Without this foundation, everything else crumbles.

I submitted my first conference article at 26.

It failed for one reason:

I structured it like a conclusion, not a story. I didn’t become a better writer with tricks.
I just learned to start with the problem.

My paper didn't get rejected due to too complex prose.
But because I structured my argument backwards.

Now, I've reviewed 100+ papers from PhDs.

The biggest difference here:
Structure turns unreadable into impactful research.

Over the past 16 years, I have published 20,000+ words/year in academic papers, cited 24k+ times, won many awards.

Most people don't know this peculiar paragraph writing technique that I use.

It's called PEEL (sometimes TEEL):
🧵⬇️ (1) Point (or Topic) → (2) Evidence → (3) Explanation → (4) Link.

And this is how you structure writing paragraphs. Every paragraph should be broken down into those 4 sections.

This is what goes into each section:👇

Every successful CHI author uses these 7 rules of writing.

Most graduate students do not know them.

I'm releasing them to you here for free to help you become a better writer.

🧵⬇️ 1. Do not use contractions in academic writing.

It makes you sound informal and takes away the professionalism required in an academic paper.

Research success looks impressive from the outside.

But the real work happens under water.

These tricks separate thriving from struggling scholars.

Most researchers ignore them completely.

Here are 7 actions that actually drive career growth: 1. Write Every Single Day

Train writing consistently.
Fifteen minutes beats weekend marathons.
Daily writing builds thinking muscles you didn't you had.

• Creates momentum that compounds weekly
• Reduces writing anxiety over time
• Clarifies complex ideas faster

Consistency trumps intensity every time.

Most PhD students stare at a blank page for months.

They have smart ideas but no mindmap.

The difference between finishing and forever-editing?

A bulletproof thesis structure.

Here's what successful PhDs know from day one: 1. Introduction sets expectations

Don't bury your thesis statement.
Page 5, not page 50.

2. Literature review proves necessity
Show the gap.

Then point to the problem.

3. Methodology builds trust

Reproducibility is credibility.
Details matter more than smarts.

I watched my mentee restart his introduction 10 times.

"I just can't get the flow right," he said.

His manuscript had been stuck for three months.
That's when I showed him my writing framework.

The same framework that helped me publish my papers.
(And it works for writing bits in ChatGPT 5 as well.)

The problem was just the process.
I'll break it down for you here: 1. Context Mapping First

I always suggest we map before we write.
Context is a powerful frame.

Start with your publication areas and field.
Analyze successful papers in your venue.
Never start with your introduction.

After 15 years in academia, I'll tell you in 30 seconds:

1. Perfect presentations don't pass vivas.
(Confident discussions do.)
2. Your weaknesses are actually opportunities
(to show academic maturity)

Here's the viva slide playbook that works every time: Your viva isn't about memorizing your thesis. 👀

It's about demonstrating three things:

1. You understand your research deeply
2. You can defend your choices confidently
3. You can think critically under pressure

Most students focus on 1 and ignore 2 and 3.

90% of academic papers I read are now AI-assisted.

Most researchers are in complete denial.

I'm a professor who's been brutally using AI for 18 months.

Here's what I learned that could save your career: The ancient superpower is gone.

Remember when knowing obscure citations was our academic flex?

When students looked at us in awe as we casually referenced that crucial 1976 paper?

Those days are vanishing faster than free wine at receptions. ⬇︎

I've been a Prof 13+ years and have 300+ citations.

It took me a decade of reviewing terrible literature sections and deep analysis to learn what I'm about to tell you in 3 minutes: The Problem:

Most PhD students organize related work completely wrong.

They create random catalogs:

Paper A did this.
Paper B did that.
Paper C found something else.

Sound familiar? 😅

In 20 years, I've published 300+ papers: 41k+ citations.

It all started with just 3 simple writing tips per section.

The best researchers know this secret.

Great papers tell great stories that keep readers hooked. How?

Here's my academic storytelling framework: INTRODUCTION
Start with curiosity, not conclusions.

Your introduction should make readers think:
I've never considered that.

• Contrast an intriguing fact to existing work in your field
• Introduce a thought-provoking problem
• Focus on a little-known perspective

This creates immediate engagement.

As a professor I've worked with dozens of high-performing researchers.

The secret to thriving in modern academia?

Most early-career researchers think:
Academic success = publish papers + teach classes.

Wrong.

What actually creates breakthrough careers: Traditional academia is dying.

The professors thriving today don't just publish—they:

• Get really good at AI to 10x research effectiveness
• Design transformative curricula (not just lectures)
• Lead innovation ecosystems beyond campus

Here's the playbook: 👇

ChatGPT will die.

Gemini will die.

Claude will die.

Grok will die.

But your research skills won't.

Every PhD student faces the same dilemma:

(I'll send you a mind map if you repost & comment) Use AI tools for everything or build core skills?

Most choose the shortcut.
Smart students choose differently.

Here's the 4-Step Foundation Framework: