D.4. Identify the defining features of single-case experimental designs.
This post is for behavior analysts, clinicians, and supervisors who need to know whether a specific intervention causes change for a single learner. It explains the defining features of single-case experimental designs (SCEDs) and how they establish experimental control beyond a graph that merely looks like improvement. It offers practical guidance on using repeated measurements, baseline stability, phase changes, and replication to turn ABA data into clear, ethical decisions for client welfare.
D.1. Distinguish between dependent and independent variables.
This post helps practicing BCBAs, clinic leaders, senior RBTs, and clinically informed caregivers distinguish independent from dependent variables in ABA, turning data into clear, ethical decisions. It covers operational definitions, temporal order, measurement fidelity, and practical designs (e.g., ABAB) to show functional relations and avoid common mistakes. The focus is on turning ABA data into reliable, ethical decisions that protect client welfare and dignity through honest, reproducible reporting.
D.7. Distinguish among reversal, multiple-baseline, multielement, and changing-criterion designs.
Designed for BCBA candidates, practicing clinicians, and graduate students, this post clarifies how to distinguish among reversal, multiple-baseline, multielement, and changing-criterion designs. It explains what each design demonstrates about experimental control, when to use it, and how to avoid common pitfalls that threaten ethics or validity. The focus is on turning ABA data into clear, ethical decisions about intervention effects for real clients.
B.23. Identify ways the matching law can be used to interpret response allocation.
Clear, clinician-friendly guide for behavior analysts, educators, and students applying ABA. It shows how the matching law explains response allocation across concurrent options, helping you interpret client choices and shift behavior through contingencies rather than punishment. It offers practical, ethical steps to turn data into decisions: measure allocation and reinforcement, compare proportions, and tailor reinforcement to support functional independence while safeguarding autonomy.
Radical Behaviorism Explained: Definition & Examples (BCBA)
What is radical behaviorism? Plain-English definition, examples, and how it differs from methodological behaviorism. Plus a mock question and free BCBA CEUs.
A.5. Identify and describe dimensions of applied behavior analysis.
Designed for BCBAs, clinic directors, and senior RBTs, this post explains the seven dimensions of ABA and how to apply them as a practical quality checklist. It shows how to turn ABA data into clear, ethical decisions about target selection, intervention design, and evaluation. You’ll learn to write replicable procedures, justify choices with behavioral principles, and plan for maintenance and generalization.
Behaviorism vs EAB vs ABA vs Practice: A.4 Explained
The 4 domains of behavior analysis — behaviorism, EAB, ABA, and professional practice — distinguished with examples for BCBA task list item A.4.
Philosophical Assumptions of Behavior Analysis (BCBA A.2)
Selectionism, determinism, empiricism, parsimony, pragmatism — the 5 philosophical assumptions of behavior analysis with examples and a study mnemonic.
A.1. Identify the goals of behavior analysis as a science (i.e., description, prediction, control).
This post is for practicing clinicians, clinic leaders, and senior supervisors—BCBAs, RBTs, and caregivers—who want to apply ABA data ethically. It clarifies the three goals of ABA—description, prediction, and control—and shows how to turn data into clear, testable decisions while upholding informed consent, least-restrictive practices, and social validity. By emphasizing objective description and data-driven interventions, it helps you move from observation to reliable action that respects client dignity and improves outcomes.
Teaching nonarbitrary temporal relational responding in adolescents with autism
This post reviews a study on teaching nonarbitrary temporal relations—“before” and “after”—to autistic adolescents with early verbal skills, including a telehealth protocol and MET (multiple exemplar training). It translates the data into practical, ethical ABA steps: baseline checks, varied exemplars, precise error correction, and clear mastery, maintenance, and generalization criteria. For clinicians, BCBA/SLPs, and educators, it offers a data‑driven framework to decide when and how to teach sequencing skills that matter in daily life, while preserving learner dignity.