Matt Harrington

Designed for BCBAs, clinic leaders, and caregivers, this post explains response maintenance—the durability of a skill after intervention ends and supports are faded. It shows how to measure maintenance over time in real-life contexts and use those data to guide fading, boosters, and ethical discharge decisions. With practical probe schedules and concrete examples, it helps you translate ABA data into clear, durable, real-world outcomes.

This post is for behavior analysts, BCBA/BCaBA students, and clinicians seeking practical guidance. It clarifies how to distinguish respondent (classical) conditioning from operant conditioning to identify what maintains a behavior. Using FBA and ABC data, it helps you make clear, ethical, evidence-based intervention decisions that target the true controlling relation.

Designed for practicing BCBAs, clinic leaders, supervisors, and others who design or monitor ABA interventions, this post clarifies how to identify and distinguish positive and negative reinforcement contingencies. It shows you how to use ABC data and functional assessment to determine what changed after a behavior—what is added or removed—and whether that change increases the behavior. The guidance emphasizes function over labels and ethical, least-restrictive decision-making to turn data into clear, effective intervention plans that protect learner dignity and outcomes.

Designed for BCBAs, clinic directors, and senior therapists, this post clarifies the difference between imitation and observational learning and why it matters for treatment planning. It shows how to identify immediate, topography-matched copying versus learning from observed consequences, and how to measure each in your data. The focus is on turning ABA data into clear, ethical decisions about modeling, reinforcement, and generalization while safeguarding learner dignity and consent.

This post is for BCBAs, RBTs, supervisors, and clinically informed caregivers seeking practical guidance on rule-governed versus contingency-shaped behavior. It shows how to turn ABA data into clear, ethical decisions about when to teach by instruction and when to shape by consequences, including strategies to blend the two. The focus is on safety, generalization, and durable learning, with concrete ethical considerations to guide everyday practice.

This post is written for practicing ABA clinicians, BCBA/BCaBA, and students conducting functional assessments. It guides you in identifying stimulus control, distinguishing it from mere correlation, and using data to inform intervention decisions. With practical, ethics-forward guidance, it helps you turn ABA data into clear, defensible choices that promote generalization and independence.

Designed for BCBAs, clinic directors, and supervisors, this post helps you distinguish concurrent, multiple, mixed, and chained reinforcement schedules so data drive ethical, effective treatment. It offers practical, plain-language criteria and measurement guidance to tell the schedules apart and choose the right design for a given goal. By centering ABA data on clear decisions and learner dignity, it supports ethical, transparent practice.

This post is for BCBAs, clinic leaders, senior RBTs, and clinicians supporting learners at home who want data-driven, ethical ABA practice. It clarifies the difference between a single stimulus and a stimulus class, and why forming stimulus classes matters for real-world generalization. It offers practical steps for planning instruction, diagnosing errors, and designing generalization probes across varied exemplars. It also highlights ethical considerations, including caregiver involvement and transparent data to guide decisions.

Designed for BCBAs, RBTs, clinic directors, and caregivers, this post clarifies emergent relations and generative performance and explains how a single well-planned teaching sequence can yield multiple untaught skills. It emphasizes testing for emergence—via systematic probes—and turning ABA data into clear, ethical decisions about what a learner can do in real life. You’ll gain practical guidance on processes like stimulus equivalence, multiple-exemplar training, naming, and probing to design efficient, durable, and flexible teaching programs.

This post is for BCBAs, clinic directors, senior RBTs, and clinical caregivers who design behavior-reduction plans. It helps you distinguish unconditioned, conditioned, and generalized punishers using functional data, guiding safe and appropriate decision-making. With practical examples and ethical safeguards, it shows how to turn ABA data into clear, responsible choices that protect learning and relationships.