What is a key feature of A-B-C data in behavior analysis?

The key feature of A-B-C data in behavior analysis is that it involves collecting detailed information on antecedents (A), behaviors (B), and consequences (C). This approach provides a structured method for understanding the context of specific behaviors. By documenting what occurs before a behavior (the antecedent), the behavior itself, and what happens after (the consequence), practitioners can identify patterns and triggers that influence behavior. This data is invaluable in designing effective interventions since it reveals the relationships between environmental events and the individual's behavior.

In contrast, measuring the frequency of corrective behaviors focuses on monitoring specific behavior changes but does not encompass the broader context provided by A-B-C data. Assessing academic performance over time is not directly related to behavior analysis, as it typically focuses on academic metrics rather than the antecedent-behavior-consequence relationship. Documenting medical history is essential for understanding an individual's overall health but does not contribute to the analysis of behavior patterns or interventions based on the A-B-C model.