How It Works

Every phase of the observation,
handled.

01 — Observe

Live Recording Engine

A keyboard-first environment for complex behavioral topographies. Score behaviors, log ABC events, and manage intervals without breaking visual contact with the student.

J. Martinez Partial Interval Math Block
14:22 / 30:00Int 8/20 · 4s left
OT
DIS
Activity
1Lg Group 2Sm Group 3Independent 4Unstructured
Off-task1
5 / 8
Disruptive2
2 / 8
Session Notes
Math class, seated near back. Working on worksheet independently.
Observation Log
14:18 Left seat, walked to window
14:12 Tapping pencil, looking around room
O add note · ⌘/ shortcuts
1Off-task
2Disruptive
3Aggression
4
OAdd note
⇧1Lg Group
⇧2Sm Group
⇧3Independent
⇧4Unstructured
Space Start / Pause
⌘Z Undo ⌘/ All shortcuts ⌘⇧F Focus mode
👁

Eyes stay on the student

Every action is a single keypress. No menus, no mouse targets, no looking away to find a button.

Timer and intervals run themselves

Audio cues signal interval boundaries. You score when prompted. The app handles timing, counting, and interval progression.

📋

Context captured alongside data

Switch activity phases with Shift+number as the classroom routine changes. Press O to drop a timestamped note without stopping.

All 8 recording methods. Choose per session based on what the observation requires.
Whole Interval
Behavior must occur the entire interval to score. Audio cue, one key, move on.
Partial Interval
Any occurrence within the interval scores it. Audio prompt at each boundary — just press and go.
Momentary Time Sampling
Glance-and-score at each interval end. Lower reactivity, faster sessions, reliable prevalence estimates.
ABC Recording
Events happen, you tag them. Number keys for antecedents and consequences as the sequence unfolds.
Frequency / Event
One keypress per occurrence. Rate-per-minute computed automatically — no tallying, no dividing.
Duration
Toggle on when it starts, off when it stops. Per-episode and cumulative time tracked across the session.
Latency
Timer starts on the prompt, stops on initiation. Measures response delay across trials without a separate stopwatch.
Narrative
Timestamped free-text notes woven into the structured data stream. Context that lives alongside the numbers.
02 — Analyze

Patterns surface.
No spreadsheet required.

Log activity phases as they happen. After the session, filter results by what was going on when the behavior occurred. Add more sessions and cross-observation patterns surface on their own.

Session Results
PARTIAL INTERVAL · OCT 21 · MATH BLOCK · 30 MIN
Activity
Lg Group · 10 min Independent · 12 min Sm Group · 8 min
All Lg Group Independent Sm Group
Showing results during: Independent work
58%
Off-task
during independent work
12%
Off-task
all activities
Off-Task % by Activity
ACROSS 3 SESSIONS
Independent
58%
Lg Group
22%
Sm Group
8%
✦ AI Portrait

Off-task behavior was highest during independent work (58% of intervals across sessions), compared to 22% during large group and 8% during small group.

This activity-specific pattern was consistent across all three observations, suggesting the behavior is tied to task structure rather than time of day or setting.

The student was most engaged during small-group instruction, where off-task intervals dropped to near-peer levels.

For FBAs

ABC sessions add antecedent-consequence flow diagrams, conditional probability tables, and pattern rankings across sessions. All computed automatically from your coded events.

03 — Write

The Write-up Workspace

Session evidence on the left, your draft on the right. Works for observation summaries and FBA narratives. Click any highlighted sentence to see exactly which session generated it.

j_martinez_obs_summary.docx
Evidence Panel
#SCATTERPLOT_01
9 instances clustered 10:00–10:30 AM over 4 sessions.
← #ABC_CHAIN_04 · Active
A: Math worksheet → B: Elopement → C: Task removed (82%)
#DURATION_01
Avg episode duration: 3m 12s. Longest: 6m 48s (Session 3).
Antecedent Distribution
Work Demand
78%
Transition
14%
Peer Denied
8%
Observation Summary Draft

Behavioral Observation Summary: J. Martinez

Four direct observations were conducted across Math, Reading, and Transition periods between October 14 and November 2.

A consistent temporal pattern was identified. Off-task behavior and elopement occurred most frequently during the 10:00–10:30 AM block across all four sessions.Source: SCATTERPLOT_019 instances logged 10:00–10:30 AM across 4 session days. The behavior was not observed at comparable rates during afternoon periods or preferred activities.

ABC recording across sessions indicates a consistent antecedent pattern. Independent academic task demands preceded the target behavior in 82% of observed incidents, with task removal as the most common consequence.Source: ABC_CHAIN_04Math worksheet → Elopement → Task removed. 82% antecedent probability.

These findings suggest the behavior may be maintained by task avoidance and are consistent with teacher interview data.

AI suggestion: Include the latency metric from Session B to strengthen the demand-onset comparison.
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