Think of a particular case or intervention that piqued your curiosity about practice effectiveness. Design a single-case experiment that is relevant to that case or intervention. Try to design it in a way that would be feasible to implement.
Case: A child with ADHD is struggling to stay on task and complete their schoolwork.
Intervention: A token economy system is implemented, where the child earns tokens for completing their work and following the rules. Tokens can be redeemed for rewards, such as extra recess time or stickers.
Single-case experiment:
Feasibility:
This single-case experiment is relatively feasible to implement. It does not require any specialized equipment or training. The only materials needed are a data collection sheet and tokens (which can be anything from stickers to candy).
Data analysis:
The data from the single-case experiment can be analyzed using a variety of methods, such as visual inspection, percentage of nonoverlapping data (PND), and trend analysis. Visual inspection is the simplest method, and it involves looking at the data graph to see if there is a clear change in behavior after the intervention is implemented. PND is a more statistical method, and it involves calculating the percentage of data points in the intervention phase that are above or below all of the data points in the baseline phase. Trend analysis is another statistical method, and it involves looking for a linear trend in the data.
Conclusion:
This single-case experiment can be used to evaluate the effectiveness of the token economy system in improving the child’s on-task behavior and task completion. The results of the experiment can be used to make decisions about whether to continue using the intervention or to try a different one.