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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47th Annual Convention; Online; 2021

All times listed are Eastern time (GMT-4 at the time of the convention in May).

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Paper Session #136
The Differential Outcome Effect: Exploring Predictive Models and its Relevance to Basic Behavioral Phenomena
Saturday, May 29, 2021
5:00 PM–5:25 PM
Online
Area: PCH
Instruction Level: Intermediate
Chair: Russell Silguero (PENDING)
 
The Differential Outcome Effect: Exploring Predictive Models and its Relevance to Basic Behavioral Phenomena
Domain: Theory
RUSSELL SILGUERO (University of North Texas), Manish Vaidya (University of North Texas)
 
Abstract: When two or more occasions for responding are associated with differential outcomes, the development of discriminated operants is faster relative to nondifferential outcomes. This phenomenon, first reported by Trapold (1970), is called the differential outcomes effect (DOE). This presentation will suggest that the DOE has an important bearing on many fundamental concepts in behavior analysis, such as respondent conditioning, discrimination learning, differential reinforcement, and choice. We will explore both Bayesian and more traditional approaches to modeling the relatively simple conditions under which the DOE is observed with nominal variables (e.g., Response 1 vs. Response 2; Outcome 1 vs. Outcome 2). Next, we will discuss how these models relate to current theoretical accounts of the DOE such as outcome expectancy and equivalence classes. Finally, we will consider how a generalization of this approach to modeling the DOE may be a useful framework for understanding both simpler and more complex learning phenomena.
 
 

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