Shaping academic task engagement with percentile schedules.

Fyfe et al. (2007) tested a percentile schedule in classrooms. The teacher watched each student for 20 past responses. If the current on-task bout was longer than the best 20, the student got a point. Points traded for prizes. The study compared 5-, 10-, and 20-response windows to see which shaped longer engagement best.

The 20-response window won. Students stayed on task longer when the rule looked back at 20 past responses. Shorter windows helped a little, but the 20-observation history gave the clearest boost over baseline.

Aman et al. (1993) first showed the mechanism works. Their rats learned long lever-press runs under the same percentile rule even though it cut total food. The classroom study copies that logic with kids and worksheets.

Diaz de Villegas et al. (2020) and Diaz de Villegas et al. (2024) look like rivals at first glance. They praise synchronous reinforcement — reward the instant you see on-task behavior. Their preschoolers did better with immediate tokens than with saved-up bonuses. Yet both camps agree: tight, response-based rules beat loose timing. Fyfe et al. (2007) just spreads the rule across 20 past responses instead of one.

Kim et al. (2024) used a progressive ratio schedule. Math problems had to get longer to earn each next token. Like Fyfe et al. (2007), they leaned on a quantitative schedule, but Kim’s ratio climbed while S’s percentile stayed flat. Both raised effort, showing multiple arithmetic routes to the same goal.

Pick your window size with purpose. A 20-response history gives a sturdy benchmark for shaping longer work bursts. Set a timer or clicker to track the last 20 on-task intervals. If the student beats the best of those 20, deliver the reinforcer right then. You now have rodent-lab proof and classroom proof that the rule works. Try it next period and watch sustained engagement grow.