Revisiting conjugate schedules.

College students sat at a computer. Each key press made a blurry picture clearer.

The team changed how much clearer each press made the picture. Sometimes one press gave a big jump in clarity. Other times it gave only a tiny jump.

They also turned the picture off for extinction and made it blurrier for negative punishment. They counted how many keys students pressed under each rule.

When each press gave a big clarity jump, students pressed less. When each press gave a small jump, they pressed more.

During extinction, pressing stopped quickly. Under negative punishment, pressing slowed as the picture got blurrier.

The schedule rule, not just the picture, controlled the pressing rate.

Jenkins et al. (1973) used a similar rule in real classrooms. They gave free time to a whole class when talk-outs stayed below five per hour. Just like the lab study, lowering the "gain" (here, the allowed rate) cut the behavior.

McKearney (1970) and AZRIN et al. (1963) showed that basic schedule patterns hold even when the consequence is electric shock. The new study shows the same for picture clarity, proving the rule works across very different reinforcers.

Landa et al. (2016) and Fuhrman et al. (2016) used multiple-schedule thinning to keep gains after treatment. The lab data give the fine-grain detail: how changing the clarity gain per response shifts rate. Together, they form a bridge from lab to classroom.

You can use conjugate rules in any digital task. If a learner gets one point of video quality per correct answer, set the gain low to keep them working longer. If you want faster work, raise the gain. The lab numbers give you a starting dial setting.