"The Real World": Conducting Research Under Suboptimal Conditions
The Institute of Education Sciences (IES) and other federal agencies have made the use of randomized controlled trials “a research priority” (Schneider, Carnoy, Kilpatrick, Schmidt, & Shavelson, 2007, p. 4) and, yet, to receive funding to carry out such research, applicants must often provide “prior empirical evidence” such as “prior evidence suggest(ing) that the intervention is likely to substantially improve student learning and achievement” (IES, 2006, pp. 7-8). How can researchers produce such pilot evidence, especially under limited conditions (e.g., small sample, no control over selection or assignment of program participants, restricted access to district data or school classrooms)? In this presentation, we will explore this question and discuss how a study of a professional development program for K-12 mathematics teachers used a portfolio of methods, including propensity score matching and examination of plausible rival hypotheses, to provide exploratory evidence of program effectiveness under suboptimal research conditions.
Rebecca Poon teaches courses and supervises apprentice teaching in the Cal Teach program at UC Berkeley. Her primary research interests are in the mathematics content preparation and professional development of K-12 mathematics teachers. She is a recent QME graduate and holds an MA and teaching credential in mathematics from Stanford University and a BA in mathematics from UC Berkeley.