Fun with Reinforcement Schedules (and Why They Matter) 12/06/22 | WEBINAR

Picture of Fun with Reinforcement Schedules (and Why They Matter) 12/06/22 | WEBINAR
by A. Charles Catania, Ph.D.

Earn 2 BACB Learning CEUs!


FI? VR? DRL? Abbreviations and other esoterica are the least important features of schedules of reinforcement. We’ll discuss how to spot them as they operate (ubiquitously) in everyday environments (including online platforms), and when they can come in handy in our behavior analytic applications.

This 2-hour LIVE WEBINAR will air December 6 at 1:30 pm Eastern Time.
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by A. Charles Catania, Ph.D.

Schedules of reinforcement arrange contingencies between responses and their consequences. Some contingencies are based on number of responses: in gambling, for example, only some fraction of total plays pays off (technically, slot machines arrange random-ratio schedules). Other contingencies are based on when responding occurs: for example, looking at a watch to see whether it is okay to leave for the noon lunch break is only reinforced after time has passed; looking more often doesn’t affect the time the watch shows (technically, looking is reinforced according to a fixed-interval schedule). Such contingencies are ubiquitous in everyday life and they can be particularly useful in our applications. We’ll discuss why they work as they do, and we’ll consider how to use them. In fact, delivering a reinforcer after every response is often the least efficient way to deploy reinforcers. Delivering a reinforcer after the last of several responses actually reinforcers several of them rather than just that last one. This can also create worries, as when a teacher reinforces a correct answer that comes right after a child has made an error: that reinforcer will strengthen the error along with the correct. We will explore a variety of examples, and will also show that it is crucial to specify not only the schedule contingency but also the response class for which the contingency is arranged whenever a schedule is identified or deployed.

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Learning Objectives

At the conclusion of the workshop, participants will be able to:

  1. Participants will learn to identify and distinguish between contingencies that depend on response properties (especially number) and those that depend on time since some event.

  2. Participants will learn to include the behavior to be reinforced and not just the consequences of that behavior when they describe schedule contingencies.

  3. Participants will be able to supply examples of response-based and time-based contingencies as they occur in everyday situations.

  4. Participants will be able to supply examples of response-based and time-based contingencies as they might be used in behavior analytic applications.

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