The Use of Behavioral Skills Training to Teach Graph Analysis to Community Based Teachers

The team used a four-step BST package to teach community teachers how to read discrete-trial percentage graphs. They ran a multiple-baseline across teachers and tracked how many data-based decisions each teacher got right.

No kids were in the study. Only adults who already taught in classrooms.

After BST, every teacher made more correct decisions and cut their errors when looking at graphs. The gains stuck without extra coaching.

Clayton et al. (2019) and Matos et al. (2020) show the same four-step BST can lift staff accuracy from below 25 % to above 90 % on different skills. Maffei-Almodovar et al. (2017) keeps the pattern: BST moves teachers from shaky to solid on graph calls.

Ampuero et al. (2025) flips the script. They found brief performance feedback works as well as full BST and saves time. This looks like a clash, but the jobs differ. Ampuero trained paraeducators to run trials; Maffei-Almodovar trained teachers to read graphs. Graph reading may need the full model-practice-feedback loop, while trial running can skip to quick feedback.

Briggs et al. (2024) map 51 studies where teams trimmed BST to save minutes. Maffei-Almodovar (2017) is one of the papers they count, showing the field already hunts for leaner ways to train.

You can copy this exact BST script next PD day: explain the graph rule, show a correct call, let teachers practice on real graphs, give praise and correction. In under an hour your team will stop guessing and start making data moves that help kids progress faster.