The application of Herrnstein's law of effect to disruptive and on-task behavior of a retarded adolescent girl.
Track payoff rates and you can predict—and shift—how students split their time between work and disruption.
01Research in Context
What this study did
Researchers tracked one teen girl with intellectual disability during regular class.
They timed how long she stayed on-task and how long she disrupted.
The team then fit the numbers to Herrnstein’s matching-law curve to see if the math predicted her choices.
What they found
The curve explained most of her behavior.
When on-task earned more teacher attention, she worked longer.
When disruption paid off faster, she disrupted more.
How this fits with other research
Robinson et al. (2019) later showed the same rule works for kids with ADHD.
They used token piles instead of teacher time, yet the payoff rate still steered choice.
Lord et al. (1997) cut disruption in a group home by boosting positive comments.
That study changed the payoff ratio by hand, while Martens et al. (1989) simply measured it, so the papers fit like two sides of the same coin.
Together they tell us: whoever controls the reinforcers controls the response rate.
Why it matters
You can now treat the matching law like a calculator.
Count how often a behavior earns payoff, tweak the rate, and forecast the new split between work and disruption.
No extra staff, no tokens, just timing attention.
Want CEUs on This Topic?
The ABA Clubhouse has 60+ free CEUs — live every Wednesday. Ethics, supervision & clinical topics.
Join Free →Time how many seconds of teacher attention follow on-task versus disruptive acts, then slightly delay attention after disruption while immediately noticing work.
02At a glance
03Original abstract
The purpose of the present study was to evaluate Herrnstein's law of effect as a description of socially significant behavior in an applied setting. The subject was an 18-year-old retarded girl with a history of autistic-like and aggressive behavior. Using a baseline design for two response classes and stimulus conditions, eight categories of subject and staff behavior were monitored over a 3-week period. A computerized observation system, developed for use in the present investigation, was used to obtain real-time durations of the behavior categories alone and in combination. Overlapping durations of teacher and subject behavior were then correlated to yield approximations to a functional definition of reinforcement. Plots of behavior by contingent reinforcement revealed a hyperbolic relationship for each response class, the shape of which varied as a function of extraneous reinforcement r0. In addition, estimated parameters in Herrnstein's equation did not differ significantly from those obtained through independent observation. Finally, Herrnstein's equation accounted for an average 63% of variance in response allocation. Results are discussed in terms of the relevance of matching-law theory to behavior in applied settings.
Journal of the experimental analysis of behavior, 1989 · doi:10.1901/jeab.1989.51-17