Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.

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49th Annual Convention; Denver, CO; 2023

Event Details


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Panel #5
CE Offered: BACB
Is Applied Behavior Analysis Ready to Enter the 21st Century? A Discussion on Data Collection
Saturday, May 27, 2023
10:00 AM–10:50 AM
Convention Center Mile High Ballroom 4E/F
Area: AUT/DDA; Domain: Service Delivery
CE Instructor: Paula Ribeiro Kenyon, Ph.D.
Chair: Paula Kenyon (Northeastern University and Grupo Método)
MARIA ANDRADE (Grupo Método - Intervenção Comportamental)
COBY J. LUND (Archer Behavioral Health)
LAYLA SUMP (DAXTA)
Abstract:

Data collection is important for a variety of reasons: it is the primary basis for clinical decisions, it is required by the Ethics Code for Behavior Analysts, and it is required by many, if not most, payors of ABA services. As such, data collection is the backbone of applied behavior analysis (ABA). Data can be recorded automatically or recorded by the observer. The prevalence of observer measurement in ABA settings raises many interesting questions: how accurate are data being recorded? Are we using the best measurement systems? Are we measuring data collection integrity (DCI)? Are data being recorded as the behavior occur? Who records data? What level of training is provided to those recording data? Is data being recorded by paper and pencil or electronically? What are some of the available data collection platforms? Can we aggregate data? What levels of analysis can be conducted with data recorded? This panel will invite the audience to participate in an active discussion on data collection, the options available, and some pros and cons of varied systems.

Instruction Level: Intermediate
Target Audience:

The audience should be well-versed in multiple data collection practices as described by the BACB task list.

Learning Objectives: (1) Differentiate between data recorded automatically or recorded by observer. (2) Differentiate between paper and pencil and electronic data collection. (3) List potential concerns with current data collection systems: integrity of data collection, accuracy of data collection, barriers to aggregated data collection analysis.
 

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