Project Flow and Trial Management

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Beyond individual trial parameters, Testable provides several columns that control the higher-level structure of an experiment: when to insert breaks, how many times to repeat rows, which trials count towards the score, and which blocks to include.

Inserting breaks: break

Add a rest screen after a specified number of trials or after a time interval:

Value	Inserts a break
100	After every 100 trials
100s	After 100 seconds of task time
3m10s	After 3 minutes and 10 seconds

Participants see a pause screen and can continue when ready.

Repeating trials: repeat

Set repeat to the number of times a row should appear:

repeat = 3

A value of 3 presents that trial three times in total, with the copies placed one after another. Combine with random if the repetitions should be spread out; see Randomisation.

Including trials in the score: select

Set select = 1 on rows you want included when computing the participant’s average correct score (displayed on the completion screen if enabled):

select = 1

Rows without select (or with select = 0) are excluded from the summary score.

Conditional block selection: rules

Use the rules column to randomly select a subset of blocks at the start of the session:

rules = block.sample(A, B, C, 2)

This randomly picks 2 of the 3 named blocks (A, B, C) to show to this participant. The block names are the labels you assign to rows in the block column.

Tip

rules is evaluated once at session start before any trials run. Use it to implement between-subject or within-session counterbalancing without manually creating subjectGroup rows.

Organisation columns

These columns pass through unchanged to your results file and help you filter data during analysis:

Column	Purpose
test	Top-level experiment section label
subTest	Sub-section label
condition1	First condition label
condition2	Second condition label
condition3	Third condition label
trialNo	Custom trial number (overrides auto-numbering)
label	Named label used with then in logic columns

None of these columns affect the trial’s display or timing; they exist solely to add structure to your data.

Next steps

• Randomisation: shuffle trials and blocks
• How to Inject Logic: create conditional branching
• How to Read the Results Files: use organisation columns in analysis