Association for Behavior Analysis International

Supporting the needs of caregivers of children with disabilities is one of the most socially important problems behavior analysts address. While there are multiple methods to address this priority, since 2020 the importance of meeting the needs of caregivers remotely has been emphasized. Project ECHO is a data based virtual service delivery model that has been used to train professionals and paraprofessionals around the world. In this paper we describe Project ECHO and how we are using to support caregivers of children with disabilities who demonstrate challenging behavior at home and in the community. We will also discuss why Project ECHO is a useful tool for behavior analysts to disseminate successful interventions.

General

The availability of inexpensive do-it-yourself electronics and 3D printing has been the catalyst for the maker movement, often defined as the involvement of individuals in the construction of objects, tools, and electronic devices that include a variety of sensors and actuators. This tutorial will describe how, for over a decade, my research group has focused on using and teaching how to use these new technologies to build inexpensive equipment to record and control behavior in operant research. One of our first objectives was to construct an operant conditioning chamber for rats that could be controlled with an inexpensive but reliable interface capable of recording responses with high accuracy under different schedules of reinforcement. Over the years, we have improved the designs and created new devices to include fixed and retractable levers, nose-poke sensors, food and water dispensers, as well as light and tone generators. Adhering to an open-source policy, we have made our designs, files, and programs freely available to those interested in building custom-made operant chambers. The possibility of building custom equipment could inspire researchers to ask questions involving complex settings and eliminate the restrictions frequently stimulated by available commercial equipment.

The tutorial is intended for graduate students and new researchers.

In physics, the study of dynamics is concerned with how forces act on bodies to change their movement—from this stems concepts involving Newton’s laws of motion, mass, inertia, momentum, kinetic energy and more. In behavior analysis, the study of dynamics is concerned with how consequences act on behavior via contingencies of selection over time. In this paradigm, behavior participates in a dynamic system with operant contingencies to produce emergent outcomes that are analyzed across multiple response dimensions, time scales, and units of analysis. Behavior dynamics provides a framework for investigating how operant behavior changes due to variation in the environment, yielding insights into the variables that underlie complex patterns of behavior—it embraces the idea that behavior is not static, but constantly evolving. This tutorial will explore the emerging application of behavior dynamics to the study of self-injury among individuals with neurodevelopmental disabilities. This discussion will center on dynamics of response competition, time, and evolution. Throughout, my emphasis will be on making these concepts, along with selected analytic techniques, approachable for applied researchers.

This tutorial is geared towards board certified behavior analysts, psychologists, and graduate students.

Recent research developments in the identification and establishment of crucial verbal developmental cusps related to learning by observation provides a clearer picture of the trajectory of language development leading to incidental language learning (Incidental Bidirectional Naming or Inc-BiN). These findings suggest that a new account of Observational Learning (OL) is warranted, with particular attention to the role that it plays in language development. This reconceptualization of verbal behavior development includes cusps that encompass the following: a) imitating (see-do responding); b) emulating (duplication of outcomes); c) changing existing behavior; d) acquiring new respondents, operants, and higher-order operants; e) acquiring new reinforcers under denial conditions; f) learning listener and speaker responses from exposure alone; and g) learning multiple responses or arbitrarily applicable relations, all as a function of observation. This presentation will focus on the establishment of observational stimulus control that makes language learning possible.

Practitioners; researchers; theorists; students

Within the domain of behavioral economic decision-making, there are two parallel but distinct frameworks of reinforcer valuation. The first is discounting, a description of the change in subjective value of a commodity as its receipt becomes more delayed, uncertain, or changed by some other factor. The second is demand, a description of the effort an organism will expend to defend its consumption of a commodity as the cost of that commodity increases. Both discounting and demand use well established quantitative models to describe behavior, but analyses are typically treated as one or the other based on the methodology used. Thus, the purpose of this tutorial is to overview similarities and differences between quantitative models of discounting and demand and how the two can be integrated when more than one functional form is suspected to underlie data with multiple factors. This will be accomplished by identifying common parameter interpretations, correlations between different parameter estimates, and how these models can be combined to describe data that encompasses two or more independent variables. Finally, how various quantitative models can be used to identify commonly used metrics in demand and discounting will be demonstrated.

Graduate students, basic researchers, translational researchers, and those interested in using behavioral economic models to describe behavior.