Programming for efficiency: the effects of motion economy on vocational tasks for adults with severe and profound mental retardation.

Four adults with severe or profound intellectual disability learned two simple factory jobs.

The jobs were putting clips in bags and packing cups into boxes.

Researchers wrote two task lists for each job. One list cut out extra arm moves. The other list kept the normal steps.

They flipped the lists every session to see which one made the adults work faster after they already knew the job.

Both adults finished the jobs just as quickly with either list while they were still learning.

After they mastered the job, the short-move list made them 20-a large share faster.

Less walking and fewer arm swings saved about one minute per five-minute task.

Speed stayed high when they went back to the short-move list weeks later.

Buskist et al. (1988) used constant time-delay to teach kitchen chains to teens with ID. They cared only about correct steps. Hogg et al. (1995) shows you can add motion-economy tweaks after mastery to boost speed.

Chen et al. (2001) built math fluency in a child with ADHD by setting a rate goal. Both studies prove fluency grows when you target speed after accuracy is solid.

Chen et al. (2018) found that autistic teens move slower even when they imagine moves. That looks like a clash, but they studied a different group and no training. J et al. trained adults with ID and saw gains, showing motion-economy helps when you actually teach it.

You can shave seconds off any mastered vocational task by redrawing the step map. Look for extra walks, turns, or hand switches. Write a second data sheet that removes them. Start using it only after the learner hits a large share accuracy. The speed bonus shows up right away and lasts.