Multilevel linear modelling of the response-contingent learning of young children with significant developmental delays.
Start intervention with a child’s favorite actions instead of missing skills to speed up learning in toddlers with big delays.
01Research in Context
What this study did
Researchers randomly assigned the toddlers with big developmental delays to two kinds of early ABA. One group got asset-based teaching: therapists built lessons around what each child already liked to do. The other group got needs-based teaching: therapists drilled missing skills first. Both groups got the same amount of therapy at home for six months. The team tracked how fast each child learned new cause-and-effect play, like hitting a switch to make a toy pop up.
They used multilevel stats to separate child progress from therapist differences. This let them see if the teaching style itself drove learning speed.
What they found
Kids in the asset-based group learned new play actions about 30 percent faster than kids in the needs-based group. The gap stayed even after the stats took out each therapist’s own skill level. In plain words, starting with what the child already does well speeds up learning more than fixing what is missing first.
How this fits with other research
Adams et al. (2021) looked at movement-skill classes for preschoolers with autism and also saw that kids with higher baseline adaptive scores gained more. Both studies say the same thing: build on strengths first.
Cerasuolo et al. (2022) pooled 50 ABA studies and warned that no single child trait guarantees success. That sounds opposite, but it is not. Cerasuolo looked across many programs; Melinda kept everything except the teaching style the same. The reviews remind us to check individual profiles, while the RCT shows that, all else equal, asset-based wins.
Wanchisen et al. (1989) ran quick presession toy choice with three autistic preschoolers. Correct responding jumped when therapists used the chosen item. Their tiny study planted the seed: use child preference as the starting block. Melinda’s 2018 trial scales that idea into a full curriculum.
Why it matters
Next time you write an IFSP or treatment plan, list what the toddler already loves and can do. Turn those actions into the first teaching targets. You will still add new skills later, but the stronger foundation should cut the time to mastery. Try it with one child this week: swap the first five goals for five strength-based targets and track the rate of new learning.
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02At a glance
03Original abstract
AIM: The purpose of the study was to isolate the sources of variations in the rates of response-contingent learning among young children with multiple disabilities and significant developmental delays randomly assigned to contrasting types of early childhood intervention. METHOD: Multilevel, hierarchical linear growth curve modelling was used to analyze four different measures of child response-contingent learning where repeated child learning measures were nested within individual children (Level-1), children were nested within practitioners (Level-2), and practitioners were nested within the contrasting types of intervention (Level-3). RESULTS: Findings showed that sources of variations in rates of child response-contingent learning were associated almost entirely with type of intervention after the variance associated with differences in practitioners nested within groups were accounted for. Rates of child learning were greater among children whose existing behaviour were used as the building blocks for promoting child competence (asset-based practices) compared to children for whom the focus of intervention was promoting child acquisition of missing skills (needs-based practices). IMPLICATIONS: The methods of analysis illustrate a practical approach to clustered data analysis and the presentation of results in ways that highlight sources of variations in the rates of response-contingent learning among young children with multiple developmental disabilities and significant developmental delays.
Research in developmental disabilities, 2018 · doi:10.1016/j.ridd.2018.01.012