Transforming science education through research-driven innovation
August 10, 2020
Written by: Dr. Chris Wilson, BSCS Director of Research
As DRK-12 researchers conducting empirical studies of interventions in science education, the findings from our studies are important to multiple audiences. While the dissemination plan might be one of the last sections we write in our proposals, and one of the last pieces we consider during the timeline of a project, it is probably the most important activity we engage in. I’ll always remember the advice my wife’s PhD advisor gave her during her studies on adolescence and animal behavior: “If you’re not publishing, you’re not doing science, you’re just watching hamsters mating in a basement.” The former presumably more justifiable than the latter.
At BSCS Science Learning we’re finding that the results from our research studies are important to an increasingly broad range of audiences. In the past we might have begun projects with the expectation that in the final year we’d be starting the often-endless process of publishing papers in research journals, and presenting findings at national research conferences. Remember those? In more recent years, as the evidence base for the efficacy of instructional materials or professional development programs has become more established, we’ve become more involved in scaling up these effective interventions. Successful scale-up requires that all elements of a program are communicated effectively to decision makers at multiple levels, such as teachers, principals, district science leads, and state science supervisors. That includes the structure of the program, the learning theory behind the program, and importantly, research on its impact. Demonstrated evidence of effectiveness, particularly on student achievement, is an increasingly important consideration for decision-makers tasked with choosing between adopting different interventions, and in investing sparse district resources.
Needless to say, research findings need to be presented differently for different audiences. Most science education researchers shudder a little when presented with hierarchical linear models, never mind those who work closer to the classroom. Presenting a series of Greek letters with multiple subscripts rarely indicates that one is concerned with the findings being accessible to a wide range of audiences. Graphing data to show differences in means between groups can make findings infinitely more digestible. The same goes for measures of statistical significance or effect sizes, which can be quite abstract. Instead of p-values and Hedges’-g, we often strive to demonstrate impacts in more meaningful units, such as...
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This blog was written by Dr. Chris Wilson, BSCS director of research, for the Community for Advancing Discovery Research in Education (CADRE) July 2020 Newsletter.