A feedback-based classification task that measures how participants induce and apply category rules from trial-by-trial feedback.
Configure parameters and run an interactive preview exactly as participants will experience it. No data is recorded.
Adjust parameters below, then start the preview on the right.
Include practice trials
Shown with feedback before the main task
Task parameters
Outputs: accuracy, median RT, perseveration errors after rule shift.
This is a researcher preview. No participant data is recorded.
Simulated participant view
A feedback-based classification task that measures how participants induce and apply category rules from trial-by-trial feedback.
No data is recorded
A coloured geometric shape appears on each trial and the participant assigns it to Category A or B, then receives correct/incorrect feedback.
Useful when the study needs an active rule-induction measure rather than pre-learned instruction following. The optional rule-shift condition provides a flexible cognitive measure of perseveration.
Not suitable for high-frequency EMA because rule induction requires a learning phase that only makes sense at lower measurement frequencies.
Enable the rule-shift condition to capture perseveration and flexible updating. Pilot the task to ensure stimuli are discriminable on the target device size.
Pre-shift and post-shift accuracy are the most interpretable outputs. Perseveration errors reflect continued use of the superseded rule.