<\/p>\nIf you\u2019re staring at a blank page wondering how to pick an Extended Essay (EE) topic, breathe. The single most useful lens to use when choosing is not whether a topic feels exciting in the abstract, but whether it invites evaluation\u2014meaning it lets you weigh evidence, compare perspectives, judge claims, and arrive at a reasoned conclusion. Your Internal Assessments (IAs), Extended Essay, and Theory of Knowledge (TOK) work best when they\u2019re connected through critical thinking. An EE that produces evaluation doesn\u2019t just describe facts; it tests ideas, analyzes trade-offs, and shows the examiner you can think like a researcher.<\/p>\n
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Evaluation in the context of an Extended Essay is the act of judging the value, credibility, or significance of evidence, methods, or arguments. It\u2019s not merely saying something is right or wrong; it\u2019s examining how strong the evidence is, where it might be biased, which assumptions underlie a claim, and how alternative explanations might change your conclusion. An evaluative EE asks “how well?” or “to what extent?” rather than just “what?”.<\/p>\n
When you scan ideas, look for features that naturally demand judgment. These features make it easier to plan research that leads to analysis rather than description.<\/p>\n
Before locking in a topic, run it through a quick reality-check. Each of these questions pushes you toward evaluation-friendly choices.<\/p>\n
Generating a research question that produces evaluation is a stepwise process. You can treat it like a mini-investigation that prepares the rest of the EE.<\/p>\n
Identify what genuinely interests you: a phenomenon, a literary motif, a social issue, a biological process, an economic policy. Interest sustains motivation. From that curiosity, ask “why” or “to what extent” questions rather than “what happened?”<\/p>\n
Skim articles, books, lab reports, or case studies to find recurring debates, contradictory findings, or gaps. The presence of debate is gold\u2014debates mean evaluative work is possible.<\/p>\n
Transform a descriptive idea into an evaluative one by framing it around degree, impact, or comparison. For example, instead of “What are the causes of X?” consider “To what extent is X caused by A rather than B?” or “How effective is intervention Y in reducing X?”<\/p>\n
Decide how you will judge evidence: accuracy, predictive power, explanatory scope, ethical implications, cost-effectiveness, etc. These criteria become the backbone of your evaluation.<\/p>\n
Ask whether you can access the evidence you need. Try a miniature pilot\u2014collect one dataset, analyze a short text, or run a small experiment. If that pilot produces usable material for analysis and shows multiple plausible interpretations, your question is on the right track.<\/p>\n
Below are example research questions crafted to encourage evaluation. They\u2019re written broadly so you can adapt them to your interests and resources.<\/p>\n
| Subject<\/th>\n | Example research question<\/th>\n | Why it invites evaluation<\/th>\n | Suggested methods<\/th>\n<\/tr>\n<\/thead>\n | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| History<\/td>\n | To what extent did economic factors drive policy X compared to ideological motives?<\/td>\n | Allows weighing different causes and evaluating documentary evidence.<\/td>\n | Primary source analysis, comparative archival study.<\/td>\n<\/tr>\n | ||||||||||||||||||
| Biology<\/td>\n | How effective is treatment A at reducing measureable symptom X under controlled conditions?<\/td>\n | Invites experimental data collection and critical discussion of controls and limitations.<\/td>\n | Lab experiment, statistical analysis, discussion of validity.<\/td>\n<\/tr>\n | ||||||||||||||||||
| Economics<\/td>\n | To what extent did policy Y influence consumer behavior compared with global trends?<\/td>\n | Requires data interpretation and causal inference, with room for counter-explanations.<\/td>\n | Quantitative analysis, regression or comparative time-series review.<\/td>\n<\/tr>\n | ||||||||||||||||||
| English\/Literature<\/td>\n | How convincingly does author Z use narrative structure to critique social theme T?<\/td>\n | Encourages comparative textual evidence and assessment of literary devices.<\/td>\n | Close reading, comparative analysis, theoretical framework application.<\/td>\n<\/tr>\n | ||||||||||||||||||
| Chemistry<\/td>\n | Which catalyst yields the highest efficiency for reaction R under comparable conditions, and why?<\/td>\n | Experimental results invite explanation and assessment of error and mechanism.<\/td>\n | Controlled experiments, measurement of yields, error analysis.<\/td>\n<\/tr>\n | ||||||||||||||||||
| Psychology<\/td>\n | To what extent does variable M affect behavior N in a sample population?<\/td>\n | Allows hypothesis testing, statistical evaluation, and discussion of generalizability.<\/td>\n | Survey\/experiment, statistical tests, ethical reflection.<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\nCommon pitfalls and how to avoid them<\/h2>\nEven well-intentioned topics can lead to descriptive essays if you don\u2019t guard against common traps. Here\u2019s how to steer clear of them.<\/p>\n Pitfall: A question that\u2019s too descriptive<\/h3>\n“What happened?” questions often produce narrative summaries. Redraft them into evaluative forms: “How significant was X in causing Y?” or “To what extent did X contribute to Y?”<\/p>\n Pitfall: Too broad or too narrow<\/h3>\nOverly broad topics drown you in material; overly narrow ones give nothing to evaluate. Use geographic, temporal, or conceptual limits and ensure there is enough evidence within those bounds.<\/p>\n Pitfall: No clear criteria for judgment<\/h3>\nWithout criteria you\u2019ll end up with unsupported assertions. Define what counts as convincing evidence for your question and apply those criteria transparently throughout the essay.<\/p>\n Pitfall: Methodology mismatches question<\/h3>\nChoose methods that can answer the question. Qualitative questions need interpretive evidence; quantitative questions need measurable data. If you mix methods, explain why and how that strengthens evaluation.<\/p>\n Working with your supervisor and weaving in TOK<\/h2>\nYour supervisor is an ally in shaping a question that produces evaluation. Use their feedback to tighten scope, test feasibility, and refine the criteria you\u2019ll use. Supervisors can point you to sources and warn you when a question will be difficult to assess fairly.<\/p>\n Make TOK connections explicitly<\/h3>\nTOK offers useful language and structures for evaluation: consider knowledge claims, evidence, methods, perspectives, and the role of bias. If your EE discusses how methodology shapes conclusions, or compares ways of knowing in different disciplines, you\u2019re also deepening TOK connections\u2014use that to enrich evaluation rather than distract from it.<\/p>\n Time management: milestones and a sample plan<\/h2>\nA topic that produces evaluation requires time for collecting, testing, and critically analyzing evidence. Below is a simple milestone table you can adapt to your timeline.<\/p>\n
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