Frequency Recording

Frequency recording (also called event recording) tallies each discrete instance of a target behavior as it occurs. sight·line counts automatically and calculates rate in occurrences per minute or per hour.

This makes it easy to compare observations of different lengths — a 10-minute and a 30-minute session become directly comparable once you convert raw counts to rate.

Scoring behaviors

During recording, each behavior appears as an on-screen button labeled with its assigned keyboard key (default: 1, 2, 3…).

To score an occurrence:

• Press the number key (1, 2, 3…) corresponding to the behavior
• Or click the button on screen

Each press increments the count by 1. The running total updates immediately. Frequency recording is designed for eyes-on-student, keyboard-only operation — you can score without looking at the screen.

Reviewing during the session

On the recording screen, a running tally shows:

• Count — total number of occurrences so far
• Rate — automatic calculation of occurrences per minute based on elapsed time

The rate updates continuously as the session progresses. If you need to scroll back and view past scores, press Escape to return to the current session.

After recording

sight·line automatically calculates and displays:

• Total count — sum of all occurrences
• Rate per minute — count ÷ elapsed minutes
• Rate per hour — count × (60 ÷ elapsed minutes), useful for comparing to baseline or peer data
• Session duration — total time observed

Results appear as:

• Summary statistics — text display of count, rate, and duration
• Trend chart — cumulative count over time, showing whether behavior is accelerating or decelerating as the session progresses
• Rate comparison — if a peer was observed using the same procedure, side-by-side rate comparison

Interpreting frequency data

Always convert to rate when comparing across sessions of different lengths. A student with 10 instances in 20 minutes (0.5/min) is not equivalent to 10 instances in 10 minutes (1.0/min).

Raw count is less meaningful than rate. A 30-minute observation may yield higher raw counts than a 10-minute observation simply because more time has elapsed, even if the actual rate (occurrences per unit time) is identical or lower.

Report three numbers:

1. Raw count
2. Observation duration
3. Calculated rate

This allows readers to verify your calculations and compare fairly to other data sources.

Frequency paired with duration recording

A complete behavior picture often requires both frequency and duration data:

• Frequency: How often does the behavior occur?
• Duration: How long does each episode last?

A behavior might decrease in count but increase in episode length, or vice versa. Recording both gives you the full picture of how an intervention is affecting the behavior.

Example: calling out might decrease from 14 times to 6 times per session (frequency improvement), but each call-out might last longer as the student becomes more insistent (duration increase). Frequency data alone would look like improvement; duration data reveals a more complex picture.

Common mistakes to avoid

1. Confusing frequency with duration — don’t use frequency recording for behaviors like “off-task” or “tantrum” that have variable or extended length. Use Duration Recording instead.

2. Starting the count mid-observation — if you miss early instances, note this in your report. Don’t adjust the count to account for unseen behavior — report what you actually observed.

3. Failing to define the behavior operationally — vague definitions (like “disruption” or “noncompliance”) lead to inconsistent scoring. Spend setup time writing a clear definition.

4. Not pairing with context data — frequency alone tells you how much, not where or when. Pair with Activity Context tracking to identify whether behavior is stable across settings.

Tips for accurate frequency recording

1. Pick discrete, clear-cut behaviors — if you’re unsure whether an instance counts, your definition isn’t clear enough. Go back to setup and refine it.

2. Use double-observer IOA — frequency data can be influenced by observer alertness and attention. Conduct inter-observer agreement checks with a peer observer using the same setup to verify your accuracy.

3. Don’t score inferred intent — score what you see and hear, not what you assume caused the behavior. Example: score “hand raised,” not “seeking attention.”

4. Consider the behavior’s natural rate — a behavior occurring 2 times per minute might be high-rate for “transitions completed” (good) but low-rate for “off-task episodes” (expected). Frame your interpretation relative to classroom norms or your intervention targets.

5. Use peer comparison — if available, have a same-age peer observed using identical procedures. The discrepancy ratio (target rate ÷ peer rate) contextualizes your data within classroom expectations.

Exporting frequency data

Frequency data export includes:

• PDF report — summary statistics, trend chart, and clinical interpretation
• CSV data file — raw count-by-interval data for analysis in external tools

See Exporting for detailed export options.