Task design
Initial tasks prioritize visual reasoning, pattern recognition, attention and speed. This reduces dependence on language, school curriculum or general knowledge.
Methodology
Designed for repeatability, transparency and responsible interpretation.
The project begins with simple, explainable cognitive tasks and clear limitations. The goal is not to announce an exact IQ number, but to build a long-term cognitive profile that can improve as data quality grows.
Timing
Response time is stored per item because two identical scores may mean different things if one result is fast and stable while another is slow and inconsistent.
Context
Sleep, stress, device type and environment are collected because online testing is sensitive to conditions outside the test itself.
Longitudinal value
The most meaningful signal is personal change over time, especially when the participant repeats tests in similar conditions.
How scores should be interpreted
Early scores are orientative. They can show which categories were easier or harder for a participant, but they should not be presented as a final IQ value. Percentiles require a sufficiently large and clean dataset, stratified by relevant factors such as age range, device type, language and education level.
For more meaningful comparisons, results should be repeated over time in similar conditions. See Annual Tracking and Research Data for context and data principles.
As the project matures, the methodology can include item calibration, reliability estimates, test-retest consistency, demographic normalization and specialist review.
What the methodology avoids
- Claims of clinical diagnosis.
- Culture-heavy trivia or school-specific knowledge.
- False precision in early scoring.
- Hidden research participation inside commercial terms.
Future validation path
The responsible path is to collect clean pilot data first, publish methodology clearly and later collaborate with psychologists, neurologists, psychometricians or academic researchers.