IB DP EE Topic Selection: How to Avoid Topics That Become a Wikipedia Summary

Why so many EEs read like a Wikipedia summary (and why that’s a problem)

There’s a moment early in the Extended Essay (EE) journey when enthusiasm meets reality: your initial idea is exciting, the topic feels meaningful, and a dozen search results flood your screen. It’s tempting to stitch those search results into a tidy narrative, and suddenly your draft reads like a carefully rewritten encyclopedia entry rather than an original investigation. That’s not just stylistically dull — it also misses the heart of what the EE (and strong Internal Assessments and TOK work) are designed to reward: precise questions, critical thinking, and an argument driven by evidence rather than summary.

Summaries are comfortable: they feel safe, they’re easy to assemble, and they often appear to tick the boxes of “research” because they collect facts. But examiners are trained to look for analysis, methodology, and the kind of intellectual risk that shows up in a clear research question and a disciplined investigation. If your EE, IA, or TOK essay ends up as an informative paragraph with little to no interrogation of sources, assumptions, or method, you’ve likely slipped into the Wikipedia trap.

How a Wikipedia-style topic usually shows up

Large scope: “The causes of X” or “The impact of Y” without a specific angle.
Descriptive aim: the project promises to “explain” or “describe” rather than to compare, evaluate, or argue.
Reliance on secondary summaries: sources that also summarize (textbooks, overview websites) rather than primary or analytical material.
No clear method: it’s unclear how you will answer the question beyond “reading and summarizing.”
Predictable structure: an introduction that reads like a definition, followed by topic-by-topic description, ending with a one-line conclusion.

What examiners actually want — and how that differs from a summary

Examiners are looking for evidence of sustained investigation. That means a question that can be answered through a reasoned method, evidence that is interpreted rather than merely reported, a structure that supports an argument, and an awareness of limitations or counter-evidence. In short: you need a clear research question, a plan for how you will collect and weigh evidence, and a narrative that advances an analytical claim.

Three short diagnostic questions for your topic

Can the question be answered by one paragraph on a reputable website? If yes, it’s probably too close to a summary.
Does your plan include at least one method of original engagement with material (case study, experiment, close reading, dataset analysis, interview, survey, archive search)?
Is there room for argument and evaluation, not just description? Could you reasonably disagree with the conclusion based on different evidence?

Practical steps to turn a vague interest into a focused research question

1. Start by shrinking the scope — the power of a narrow slice

Big topics invite summaries. Narrow topics compel analysis. If your initial idea is broad, slice it down along these axes: time period, location, population, outcome, or causal mechanism. A narrow slice doesn’t make your work trivial — it makes it manageable and more interesting.

Broad: “The effects of social media on teenagers.”
Narrower: “How does Instagram influencer culture affect notions of body image among suburban teenagers in one high school?”

The narrower version opens the door to school surveys, interviews, or focused content analysis — real methods you can describe and justify.

2. Choose a research approach or lens

Approach is your backbone. Decide whether you will do a comparative study, a case study, an experiment, a close reading, a statistical analysis, or a theoretical critique. That choice determines what “counts” as evidence and steers you away from a descriptive sweep.

Case study: collect focused primary material and dig deep.
Comparative analysis: compare two instances to highlight differences and test hypotheses.
Empirical method: collect data (experiment/survey) and analyze it transparently.

3. Seek primary engagement

Primary material is the antidote to summary. In sciences, primary = experiments, original datasets, or carefully executed observations. In humanities, primary = texts, interviews, archival documents, artworks. Even secondary material becomes valuable when used critically — to contrast interpretations, not to supply simple facts.

Primary engagement also means documenting method: how you collected data, the instruments you used, sampling decisions and limitations. That level of procedural transparency places your work in the realm of genuine research.

Transforming bad topic formulations into strong research questions

Seeing side-by-side examples is often the fastest way to learn. Below is a simple table showing common weak topic starts and how to pivot them into analytic research questions.

Weak topic	Stronger research question	Why it improves the project
“Causes of the French Revolution”	“To what extent did bread prices, rather than political ideology, precipitate unrest in a specific Paris district during the late-18th-century food crisis?”	Narrows time/place and foregrounds a measurable factor; invites primary sources and debate.
“The impact of smartphones on learning”	“How does scheduled smartphone restriction during math classes affect short-term test performance among a cohort of Year 12 students?”	Allows a simple experimental or quasi-experimental design and measurable outcomes.
“Shakespeare’s use of imagery”	“How does the imagery of water in Scene X of play Y function to shape the protagonist’s moral choices?”	Focuses on a close reading and supports text-based argumentation rather than broad summary.

Subject-specific refinements (quick guides)

Humanities: Avoid plot or event summary. Aim for interpretation: ask ‘how’ and ‘why,’ not only ‘what.’
Sciences: Prefer hypotheses you can test or phenomena you can model/measure. Describe procedures and limitations clearly.
Economics/Business: Identify a measurable relationship and define the market, timeframe, and variables.
Psychology: Operationalize variables and consider ethical constraints on sampling and data collection.
Arts: Let creative practice or focused analysis be your primary source — don’t write a history of an art movement.

How to plan your investigation so you don’t drift back into summary

Draft a working structure and tie sections to method

Structure your outline so that each section contributes to answering the research question. When drafting, ask: does this paragraph move the argument forward? If a section only reports facts without analysis, flag it for revision or reduce its length.

Section	Purpose	Approx. share of essay
Introduction	Present the research question, rationale, and approach.	10–15%
Methodology	Explain data collection, sources, and limitations.	10–20%
Analysis/Findings	Present evidence and interpret it in relation to the question.	40–60%
Discussion	Place findings in a broader context; acknowledge counter-evidence.	10–20%
Conclusion	Synthesize argument and note limitations and further research.	5–10%

Write with questions in mind, not answers

Approach each paragraph as an answer to a tiny sub-question. Keep linking back to the research question. If a paragraph can be removed without compromising your central argument, it’s probably serving a summarizing function rather than adding analysis.

Common pitfalls that pull you back toward summary — and how to fix them

Over-reliance on tertiary sources: If most of your sources are encyclopedias, textbooks, or summary websites, actively seek out primary material or peer-reviewed studies. Use summaries to orient yourself, not to prove points.
No method section: Describe clearly how you collected and analyzed data. Even a close-reading needs a short method note explaining selection criteria and approach.
Too many background paragraphs: Background is useful, but keep it limited. Prioritize background that directly supports interpretation.
Fear of argument: Avoid hedging every sentence. Make a claim, support it, and then qualify it where necessary.

Examples: quick before-and-after transformations

Below are short, subject-diverse examples that show the move from a Wikipedia-style topic to a researchable EE question.

History — Before: “The Industrial Revolution.” After: “How did the adoption of steam power alter labor organization in a specific textile town?” — This invites local records, factory reports, and focused analysis.
Biology — Before: “Photosynthesis.” After: “How do varying light spectra affect the rate of photosynthesis in a common houseplant under controlled conditions?” — This opens an experiment with controls and measurements.
English — Before: “Magic in magical realism.” After: “In author X’s novel Y, how does the depiction of magic function to critique social inequality?” — This centers a text and an interpretive claim.
Economics — Before: “Globalization and wages.” After: “What was the effect of the opening of port Z on average wages in industry A, using census samples from two decades?” — This gives a measurable variable and timeframe.

How IA, TOK, and EE can reinforce each other

Your IA and TOK explorations can be a laboratory for EE thinking. An IA that experiments with data-handling or a TOK presentation that interrogates knowledge claims can help you anticipate methodological weaknesses and sharpen your awareness of how evidence supports knowledge claims. Use the shorter IA cycle to test a method or a way of framing evidence before committing to it in a 4,000-word investigation.

When you feel stuck refining RQs, targeted help can make a big difference. For example, Sparkl‘s tailored study plans and one-on-one guidance are built to help students refine their question, design a method, and keep the investigation analytical rather than descriptive. Tutors can point out whether a proposed source is likely to produce analysis or merely restate known facts, and can suggest practical primary-engagement strategies.

Concrete checklist before you commit to a topic

Could a knowledgeable person write a decent answer on a single webpage? If yes, narrow further.
Do you have at least one form of primary engagement (experiment, interview, case study, dataset)?
Can you state a clear research question in one sentence that includes the variables, scope, or method?
Have you sketched a method section that explains how you will gather and analyze evidence?
Can you foresee two credible counter-arguments or limitations and how you would address them?
Does the topic allow for an argument (evaluation, comparison, causation) rather than simple description?

Final notes on drafting, feedback, and revision

Draft quickly and ruthlessly in early stages; your first full draft is a place to test the question and the method, not to impress anyone. Seek feedback focused on three things: clarity of the research question, evidence of primary engagement, and whether the analysis advances an argument. When you revise, tighten every paragraph so it serves the question. Be especially wary of long background sections that do not feed directly into analysis.

When you consult tutors or supervisors, ask for feedback that addresses substance over style. A tutor who encourages you to pursue a narrower, more analytically rich RQ is helping you earn real academic credit for critical thinking — the exact quality assessors prize. If you use mentoring services, choose help that emphasizes refining your question, designing replicable methods, and interpreting evidence, rather than simply polishing prose.

Conclusion

Choosing a strong EE topic is less about finding a flashy subject and more about designing a manageable, evidence-driven question that invites analysis. Narrow your scope, select a clear method, prioritize primary engagement, and structure each section to answer the research question. These moves will shift your work away from summary and toward genuine inquiry, the intellectual core of successful EE, IA, and TOK projects.