Increasing accurate preference assessment implementation through pyramidal training.

The team trained one lead teacher to run three kinds of preference assessments. Then that teacher trained two more teachers. Then those teachers trained others. This is pyramidal training.

They used Behavioral Skills Training: explain, model, practice, feedback. They checked each teacher with a checklist until they hit a large share accuracy.

All 27 teachers reached a large share accuracy after one or two coaching rounds. The skills stuck in their real classrooms weeks later.

Kids got better reinforcers because the assessments were done right. That meant smoother lessons and fewer problem behaviors.

Solares et al. (2019) later copied the pyramid online. They used Zoom and video feedback to train incidental teaching. Same ladder, new rung.

Ortega et al. (2015) shows why accurate assessments matter. When an infant’s toy was paired with mom’s attention, crying dropped and head lifting rose. Bad assessments would have picked the wrong toy.

Siegel et al. (1970) ran an early classroom token system. It proved teachers can run behavior plans, but it took one-to-one training. Pyramidal training now lets one expert seed a whole school.

You no longer need to train every staff member yourself. Train one champion to mastery, then let them train the rest while you supervise. Schools cut training costs and keep high fidelity. Try it next in-service: teach one aide the full BST package for preference assessments, then watch them cascade it to peers.