Choosing Your Research Topic

Finding the Right Topic

Prefer AI assistance? See the Building with AI cluster for a prompt-based approach.

The most common mistake is choosing a topic that's too broad. "Philosophy" isn't a topic—it's an entire discipline. "How 20th-century phenomenology shaped human-computer interaction" is a topic.

Questions to Ask Yourself

1. Can I Name the Canon?

For any well-established intellectual domain, there's a rough canon—the works that everyone in the field has read or at least knows they should read.

• In social construction theory: Berger & Luckmann, Searle, Douglas
• In media ecology: McLuhan, Postman, Ong
• In design thinking: Norman, Cross, Schön

If you can rattle off 5-10 names that "everyone in the field knows," your topic has the infrastructure for a research curriculum.

If you struggle to name foundational works, either:

• The field is too new to have a canon
• The field is too broad (you're thinking of a discipline, not a topic)
• You may not know the field as well as you thought

2. Do the Sources Reward Close Reading?

Some texts are meant to be read once for information. Others reveal more each time you return to them.

Research curricula work best with texts that:

• Have density that rewards slow reading
• Contain ideas that connect to other texts
• Provoke questions that send you elsewhere
• Remain relevant despite being older

Popular science books, how-to guides, and news articles rarely have these qualities. Classic monographs, foundational papers, and theoretical works often do.

3. What's Your Entry Point?

You don't need to be the world's leading expert. But you do need:

• Personal engagement: You've read the core texts yourself
• A perspective: You have views on what matters and why
• Enough distance: You can see the field, not just your position in it

If you're just starting to explore a topic, that's fine—but consider building the curriculum as you learn, adding lessons as you complete readings yourself.

Scoping Your Curriculum

Too Broad

"A curriculum on sociology"

Problems:

• No clear endpoint
• Too many foundational texts to include
• No coherent central question

Too Narrow

"A curriculum on chapter 3 of Being and Time"

Problems:

• Not enough material for multiple lessons
• Learners need broader context
• Feels incomplete

Just Right

"A curriculum on how Heidegger's tool analysis applies to digital technology"

Why it works:

• Clear central question
• Identifiable foundational texts (Heidegger, plus technology philosophers who build on him)
• Specific enough to complete, broad enough to be valuable
• Has practical relevance while maintaining theoretical depth

Examples of Good Topics

Topic	Why It Works
Social construction of technology	Clear lineage from Berger/Luckmann through SCOT theorists
Ritual and habit formation	Draws from Bell, Bourdieu, clear primary sources
Philosophy of information	Floridi and predecessors, defined field with canon
Media effects on cognition	McLuhan through Carr, established debates
Organizational sensemaking	Weick's work plus extensions, clear theoretical tradition

Examples of Topics That Need Refocusing

Original Topic	Problem	Refocused Version
"Technology ethics"	Too broad, no canon	"How virtue ethics applies to algorithmic decision-making"
"Leadership"	Too applied/practical	"Theories of distributed cognition in teams"
"AI"	Too current, moving target	"Historical philosophy of machine intelligence"
"My productivity system"	Too personal	"Theories of attention and deep work"

Ready to Proceed?

Once you can confidently describe:

• Your topic in one sentence
• 10-15 foundational texts
• Why this topic rewards depth

You're ready to identify your core readings and start building.