Data guide our clinical decisions, but collecting more data doesn’t always mean collecting better data. The right measurement system should give us meaningful information without interfering with teaching or taking our attention away from the learner.
We explore how to choose ABA data collection methods based on what we actually need to know and the decisions those data will help us make. We cover rating scales, frequency, duration, interval recording, probe data, and trial-by-trial data, along with situations where each approach may be useful.
We also discuss why percentage correct isn’t always the best fit, especially during naturalistic or play-based teaching. Ultimately, our data collection should be individualized, practical, and aligned with the learner’s goals. When data start getting in the way of engagement, behavioral momentum, or meaningful learning, it may be time to rethink how we’re measuring progress.
What's Inside:
Mentioned In This Episode
Episode 046: Data Collection for Behavior Management
Data with Purpose: Making Data Collection Meaningful (and Manageable)
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