As teachers of statistics we know the fundamental components of statistical enquiry, be it classical or exploratory. When we turn the focus on ourselves as statistics educators, we run the risk of forgetting some of the fundamental principles of good research - principles that are broader than carrying out statistical significance tests. In this talk I want to present some examples of research in statistics education to illustrate the stages and outcomes that contribute to results that have a scholarly impact on the statistics education community. As a single teacher with a good idea on how to teach "confidence intervals," I do not expect anyone to pay much attention to me. If I can, however, place my ideas in the context of others' ideas or research on teaching confidence intervals; conduct a study - maybe a case study or a controlled experimental<br>design - that is valid for considering the issue I want to promote in teaching about confidence intervals; and have my results refereed by peers in the field; then I can expect people to pay attention to me.
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