ABA Fundamentals

Animal cognition + optimal choice = behavior: A review of <i>adaptive behavior and learning, 2<sup>nd</sup> Ed</i>., by J. E. R. Staddon

McDowell (2017) · Journal of the Experimental Analysis of Behavior 2017
★ The Verdict

Skip the mental goals—environmental contingencies already explain adaptive choice.

✓ Read this if BCBAs who like conceptual clean-ups and hate mentalistic jargon.
✗ Skip if Clinicians looking for new protocols or data sheets.

01Research in Context

01

What this study did

McDowell (2017) read Staddon's big book on adaptive behavior. He wrote a short review. He asked one question: do animals need goals inside their heads to explain choice?

The paper is a think-piece, not an experiment. No kids, no rats, no data tables.

02

What they found

Staddon likes goal-based models. McDowell says we can skip the goals. Plain operant principles do the job.

The review sides with function, not hidden purposes.

03

How this fits with other research

Morris et al. (1982) said the same thing earlier: keep cognition out. McDowell's 2017 review echoes that call.

Spanoudis et al. (2011) showed pigeons shift choice when the payoff changes. That lab result gives legs to McDowell's argument that environment alone can explain flexible behavior.

Furrebøe et al. (2017) also in 2017 argue behavior analysis gives behavioral economics its missing tools. Both papers push a clean, contingency-first view of choice.

04

Why it matters

When a client keeps 'making the wrong choice,' check the payoff first. Add or remove reinforcement, then watch behavior shift. You don't need to guess about hidden goals or plans. Let the contingencies do the talking and save session time.

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Plot the payoff rate for each choice your client makes, then tweak the richer one.

02At a glance

Intervention
not applicable
Design
narrative review
Finding
not reported

03Original abstract

Staddon discusses a vast array of topics in comparative psychology in this book. His view is that adaptive behavior in most cases is the result of optimal choice acting on an animal's knowledge about the world. Staddon refers to this as a functional teleonomic approach inasmuch as it attempts to understand an animal's behavior in terms of goals. He builds mathematical models based on this idea that are designed to reproduce specific sets of empirical observations, usually qualitatively. A natural consequence of Staddon's approach is that many models are developed, each of which applies to a specific set of observations. An alternative to functional teleonomy is a functional approach that builds on prior principles. In most cases, this approach favors a single‐theory account of behavior. Prior principles can be understood as functional stand‐ins for antecedent material causes, which means that these accounts are closer to mechanistic theories than are goal‐based teleonomic accounts. An ontological perspective, referred to as supervenient realism, is a means of understanding the relationship between functional theories and the material world. According to this perspective, the algorithmic operation of a successful functional theory may be understood to supervene on the material operation of the nervous system.

Journal of the Experimental Analysis of Behavior, 2017 · doi:10.1002/jeab.262