Adapting interventions based on learner progress is paramount to the effectiveness of interventions in special education and applied behavior analysis. Although there is some research on effective methods for training practitioners to make general instructional decisions (e.g., modify an intervention) based on graphed performance data, research on training individuals to make specific decisions (e.g., how to modify an intervention) is more limited. Our purpose in this study was to evaluate the effects of a training package, consisting of a brief online training and a visual decision-making model, for increasing preservice teachers’ and behavior analysts’ accuracy in making specific instructional decisions based on graphed performance data. In a multiple baseline across participants design, all participants increased their decision-making accuracy on novel graphs during assessment sessions and maintained accuracy at 1-month follow-up. The implications of these findings for training and future research on data-based decision-making are discussed.

根据学习者的进步调整干预措施对于特殊教育和应用行为分析中干预措施的有效性至关重要。尽管有一些关于对培训从业人员基于图形化绩效数据做出一般指导性决策（例如，修改干预措施）的有效方法的研究，但是对培训个人做出特定决策（例如，如何修改干预措施）的研究更加有限。我们在本研究中的目的是评估由简短的在线培训和可视化决策模型组成的培训包的效果，以提高职前教师和行为分析师在基于图形效果数据的基础上做出特定教学决策的准确性。在跨参与者设计的多个基准中，所有参与者在评估会议期间提高了他们在新颖图表上的决策准确性，并在1个月的随访中保持了准确性。讨论了这些发现对基于数据的决策的培训和未来研究的意义。