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Math AI IA Research Question Evaluator

Use the tabs below to generate a new Math AI IA idea or evaluate your current research question.

Compare High-Scoring vs. Flawed Math AI RQs

Below are examples of evaluated RQs from recent Math AI IAs. Review the strengths and weaknesses to understand the scoring criteria, and feel free to evaluate your own RQ using the form above.

10/10 Score
Analysing the relationship between shoe size and sprint time by fitting and comparing exponential and power-law models to a dataset of 200 high-school sprinters aged 15–18 in Ontario, Canada.
Strengths:
4

Clearly identifies two quantitative variables (shoe size and sprint time).

Weaknesses:
0
10/10 Score
Predicting daily bicycle-sharing demand at a specific docking station in central Amsterdam over one month by constructing and evaluating a time-series ARIMA model using historical hourly usage and weather variables (temperature, precipitation).
Strengths:
4

Clear focus on a mathematical prediction task (ARIMA modelling)

Weaknesses:
0
5/10 Score
How does Modelling the optimal work?
Strengths:
3

Uses modelling as the central mathematical task, signaling an explicit computational approach.

Weaknesses:
6

Specify a single clear aim by rewriting as a direct question or title that states the mathematical goal (e.g., "Model how to achieve the optimal work output in a defined task").

5/10 Score
What are the effects of Math AI on society?
Strengths:
2

It signals a broad, relevant topic (AI in society) and is presented as a question suitable for an essay-style title.

Weaknesses:
5

Specify the primary mathematical aim by using a clear action verb (e.g., Change to: Investigate...).

How to Evaluate Your Research Question

Simply choose your subject and enter your research question. Our evaluator will then analyze your question against the IB requirements and return a report with any issues or improvements you can make. Trained on thousands of IB RQs marked by official IB examiners, our evaluator is able to provide accurate and helpful feedback.

Frequently Asked Questions

Yes. Our Research Question Generator was trained on thousands of high-scoring IB exemplars, and the ideas it generates are designed to align with IB criteria so you can develop research questions that meet the standards.

Select your subject and category (IA or EE), optionally enter a few keywords or interests, then click Generate. The AI returns research question ideas tailored to your subject, which you can refine further with the tweak tools.

No. You can leave the keyword field blank for instant inspiration, or add a few words about your interests to get more targeted ideas.

Generated questions are starting points aligned with IB expectations. Similar research questions appear across cohorts—what matters is that your investigation or essay content is your own work.

The Research Question Evaluator was trained on thousands of research questions marked by IB-certified examiners. It evaluates your research question using the same IB criteria, helping you understand its strengths and areas for improvement.

Free users get a limited number of generations per week. Your limit resets weekly. Upgrade to Pro for higher limits and full access to Clastify AI tools.

Try combining a dataset or context, a specific technique (like regression, probability, or optimisation), and the decision or pattern you want to investigate.

Generic contexts with no personalised data or extension. Engagement shows in meaningful modelling choices.

Real-world modelling or statistics with technology-supported analysis and interpretation in context.