Effects of reinforcer rate and reinforcer quality on time allocation: Extensions of matching theory to educational settings.
Equal reinforcer quality is required for the matching law to predict student choice between concurrent classroom tasks.
01Research in Context
What this study did
The teacher set up two school tables. Each table paid tokens on a different schedule. Kids could move freely and choose where to work.
The study flipped the token rates back and forth across days. Sometimes both tables paid the same kind of prize. Sometimes one table paid a better prize.
What they found
When both prizes were equal, kids' time matched the token rates. Twice as many tokens bought twice as many minutes.
When one prize was better, kids stayed at that table even when it paid fewer tokens. The matching law broke down.
How this fits with other research
Johnson et al. (2009) saw the same under-matching in college basketball. Players hooped more three-pointers than the points-per-shot math predicted. Quality bias trumped pure rate.
Schenk et al. (2020) got cleaner matching in a video-game lab. All prizes were virtual points, so quality stayed equal. Their tighter control let the law shine.
Xenitidis et al. (2010) used a token board too, but asked if kids wanted to pick their prize. Choice alone did not boost work for every child. The new study says the prize itself, not who picks it, drives the choice.
Why it matters
If you want kids to split time across two tasks, first make the prizes the same. Equal quality keeps the matching law alive and your data tidy. When prizes must differ, expect kids to camp at the better one. Plan extra tokens for the less-fun task or accept that rate alone will not guide them.
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02At a glance
03Original abstract
We examined how 3 special education students allocated their responding across two concurrently available tasks associated with unequal rates and equal versus unequal qualities of reinforcement. The students completed math problems from two alternative sets on concurrent variable-interval (VI) 30-s VI 120-s schedules of reinforcement. During the equal-quality reinforcer condition, high-quality (nickels) and low-quality items ("program money" in the school's token economy) were alternated across sessions as the reinforcer for both sets of problems. During the unequal-quality reinforcer condition, the low-quality reinforcer was used for the set of problems on the VI 30-s schedule, and the high-quality reinforcer was used for the set of problems on the VI 120-s schedule. Equal- and unequal-quality reinforcer conditions were alternated using a reversal design. Results showed that sensitivity to the features of the VI reinforcement schedules developed only after the reinforcement intervals were signaled through countdown timers. Thereafter, when reinforcer quality was equal, the time allocated to concurrent response alternatives was approximately proportional to obtained reinforcement, as predicted by the matching law. However the matching relation was disrupted when, as occurs in most natural choice situations, the quality of the reinforcers differed across the response options.
Journal of applied behavior analysis, 1992 · doi:10.1901/jaba.1992.25-691