At the core of evidence-based education is data-based decision making. Once an empirically-supported intervention has been adopted, it is necessary to monitor student performance to determine if the program is being effective for an individual student. Educators report needing assistance in determining what to do with the student performance data. Often, external support for educators to successfully navigate the decision-making process is necessary because many training programs are not sufficient. <\/p>\n\n\n\n
A recent meta-analysis by Gesel and colleagues (2021) examined the impact of professional development on teaches knowledge, skill, and self-efficacy in data-based decision making. The knowledge was assessed by a multiple-choice test to determine if teachers understood the concepts of data-based decision making. It was not a measure of teachers\u2019 application of that knowledge. Skill was the direct measure how how well teachers applied their knowledge of data-based decision making. In most instances, this was assessed under ideal conditions with intense support from researchers and consultants. Self-efficacy was a measure of the teachers\u2019 confidence to implement data-based decision making. The overall effect size for the combined measures was 0.57 which is generally considered a moderate effect; however, the effect sizes for the individual items varied significantly (Knowledge range of effect size from -0.02 to 2.28; Skill range -1.25 to 1.96; self-efficacy range -0.08 to 0.78). The ranges for each of the measures suggests that the average effect size of 0.57 does not adequately reflect the effects of professional development. The variability could be a function of the specific training methods used in each of the individual studies but the training methods were not described in this meta-analysis. It should be noted that all of the studies in this meta-analysis was conducted with intensive support from researchers and consultants. It is not clear how the results of this meta-analysis are generalizable to more standard conditions found in teacher preparation programs and professional development.<\/p>\n\n\n\n
Given the importance of data-based decision making to student progress, there is considerable work to be done to identify effective and efficient training methods. It appears that we are a long way from this goal. Ultimately, the goal is for data-based decision making to be standard practice in every classroom in the United States. This will require identifying the critical skills necessary and the most effectiveness method for teaching those skills.<\/p>\n\n\n\n