Designing an iPad App to Monitor and Improve Classroom Behavior for Children with ADHD: iSelfControl Feasibility and Pilot Studies
An iPad token app tracked ADHD self-ratings fine, yet produced no behavior change because it skipped backup reinforcers and teacher praise.
01Research in Context
What this study did
The team built an iPad app called iSelfControl. Kids with ADHD tapped it every 30 minutes to rate their own behavior. The teacher also rated each child on the same app.
The app gave tokens when the two scores matched. No extra teaching or prizes were added. The goal was to see if kids would use the tool and how their ratings compared to the teacher’s.
What they found
Every child used the app without fuss. Self-scores were almost always higher than teacher scores. The gap stayed the same across the pilot, so behavior did not change.
The study showed the tool is doable, not yet helpful. It flagged a bias: kids over-rate themselves even when tokens hang on matching the teacher.
How this fits with other research
Quilitch et al. (1973) already proved that student self-recording plus tokens can raise work accuracy. Their paper version worked; the 2016 iPad copy did not. The difference is that the 1973 study also gave extra praise and backup prizes when targets were met.
Dallery et al. (2013) ran an internet voucher system for adults quitting smoking. Vouchers tripled clean breath tests while they ran, but gains vanished when the pay stopped. The same fade-out risk faces classroom apps that lack strong backup reinforcers.
Hackenberg (2018) warns that token systems fail unless you pick the right exchange rate and backup prizes. iSelfControl skipped those steps, so the weak result fits the taxonomy review.
Why it matters
If you want self-monitoring tech to actually improve behavior, add real backup reinforcers and teacher praise. Use the app to collect data, but pair it with Hackenberg’s checklist: what can the child buy, when, and at what cost? Start small, watch the gap between child and teacher scores, and adjust prizes until the gap shrinks.
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Join Free →Keep the self-rating feature, but add a 5-token menu the child can buy at lunch and praise when teacher and child scores match.
02At a glance
03Original abstract
Children with Attention Deficit/Hyperactivity Disorder (ADHD) receive approximately 80% of instruction in the general education classroom, where individualized behavioral management strategies may be difficult for teachers to consistently deliver. Mobile device apps provide promising platforms to manage behavior. This pilot study evaluated the utility of a web-based application (iSelfControl) designed to support classroom behavior management. iSelfControl prompted students every ‘Center’ (30-minutes) to self-evaluate using a universal token-economy classroom management system focused on compliance, productivity, and positive relationships. Simultaneously, the teacher evaluated each student on a separate iPad. Using Multi Level Modeling, we examined 13 days of data gathered from implementation with 5th grade students (N = 12) at a school for children with ADHD and related executive function difficulties. First, an unconditional growth model evaluated the overall amount of change in aggregated scores over time as well as the degree of systematic variation in scores within and across teacher-student dyads. Second, separate intercepts and slopes were estimated for teacher and student to estimate degree of congruency between trajectories. Finally, differences between teacher and student scores were tested at each time-point in separate models to examine unique ‘Center’ effects. 51% of the total variance in scores was attributed to differences between dyads. Trajectories of student and teacher scores remained relatively stable across seven time-points each day and did not statistically differ from each other. On any given day, students tended to evaluate their behaviors more positively (entered higher scores for themselves) compared to corresponding teacher scores. In summary, iSelfControl provides a platform for self and teacher evaluation that is an important adjunct to conventional classroom management strategies. The application captured teacher/student discrepancies and significant variations across the day. Future research with a larger, clinically diagnosed sample in multiple classrooms is needed to assess generalizability to a wider variety of classroom settings.
PLoS ONE, 2016 · doi:10.1371/journal.pone.0164229