IB Physics IA Source Checker

Physics IA sources should support quantitative physical analysis with clear variables, units, uncertainty, and limitations. Simulations or secondary datasets need provenance and evaluation, not just screenshots.

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Physics IA source check

Marksy reads the links or notes you give it, applies the rules for your IB assignment, and only stops to ask you something when the answer would change the verdict.

  1. Assignment
  2. 2Sources
  3. 3Clarify
  4. 4Verdict

Checking against

Physics IA

What usually works for Physics IA

Usually strong

  • Student-collected mechanics, waves, electricity, thermal, fields, or modern physics data.
  • Simulation data when model assumptions, variables, and limitations are transparent.
  • Official or academic datasets with units, uncertainty, and collection context.

Example

A student-collected oscillation dataset with repeats, uncertainty, and a model fit.

Needs a second look

  • Simulation outputs with no explanation of the model or assumptions.
  • Datasets missing units, calibration, or measurement conditions.
  • A classic practical repeated exactly without extension.

Example

A simulation dataset where assumptions are documented but measurement uncertainty is indirect.

Avoid or replace

  • AI-generated numerical tables.
  • Screenshots of graphs with no raw data or method.
  • Sources that only teach theory and provide no evidence for analysis.

Example

A revision page about Newton's laws.

Where to find better Physics IA sources

If a source gets a warning, don't just add more websites. Search for sources that match the assessment rule and can carry real analysis.

Searches to try

If a source is weak

  • Replace ai-generated numerical tables. with student-collected mechanics, waves, electricity, thermal, fields, or modern physics data..
  • Use simulation outputs with no explanation of the model or assumptions. only as context unless your teacher confirms they can carry evidence.
  • Add one source that gives direct evidence for the IA, not just general background.

Good places to look

  • Student-collected mechanics, waves, electricity, thermal, fields, or modern physics data
  • Simulation data when model assumptions, variables, and limitations are transparent
  • Official or academic datasets with units, uncertainty, and collection context

Questions people ask