We used a multi-component single-subject experimental design across three preschool teachers to examine the effects of video self-monitoring with graduated training and feedback on the accuracy with which teachers monitored their implementation of embedded instructional learning trials. We also examined changes in teachers’ implementation of learning trials. In each self-monitoring condition, teachers observed and recorded their implemented learning trials using video and a coding form. Conditions differed in the specificity of prompts on the coding form and the type of training and feedback provided. The combination of training, coding forms with specific prompts for learning trial components, and external feedback generally resulted in more accurate self-monitoring for two of three participants and increases in the fidelity of implementation of learning trials. Findings suggest self-monitoring can be effective for increasing the fidelity with which teachers implement embedded instructional learning trials, but systematic training and feedback are important for ensuring self-monitoring accuracy.

Data sets from large-scale longitudinal surveys involving young children and families have become available for secondary analysis by researchers in a variety of fields. Researchers in early intervention have conducted secondary analyses of such data sets to explore relationships between nonmalleable and malleable factors and child outcomes, and to address issues of measurement. Survey data have been used to a lesser extent to examine plausible causal relationships between variables, perhaps due to the increased likelihood of selection bias that results with nonexperimental data. In this article, we use National Early Intervention Longitudinal Study data to demonstrate the use of inverse probability of treatment weighting, a quasi-experimental methodology based on propensity scores that can be used to reduce selection bias and examine plausible causal relationships. We discuss the advantages and disadvantages of this approach, and implications for its use in early intervention research.

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