ELASTIC and reasoning under uncertainty: Final Report to NSF

Rubin, A., Rosebery, A. S., & Bruce, B.

Our analysis identified problems both with the subject matter of statistics (e.g. multiple levels of abstraction, difficulty mapping statistical representations to real-world situations) and with its pedagogy (which typically does little to help concertize abstract concepts or illuminate the mapping process). Drawing on research in education, cognitive psychology and statistical computing, we designed, implemented, and pilot-tested software (ELASTIC) and a curriculum (Reasoning Under Uncertainty) to address these problems. Our approach was successful in many of the problem areas identified above; in addition, our experiences in classrooms helped us better understand the difficulties students have in understanding and applying statistical reasoning.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education