Researchers and statistics educators consistently suggest that students will learn statistics more
effectively by conducting projects through which they actively engage in a broad spectrum of
tasks integral to statistical inquiry, in the authentic context of a real-world application. In keeping
with these findings, we share an implementation of discovery projects for students in elementary
statistics classes. We delineate the purpose and scope of two types of projects— one covering
linear regression analysis and the other covering comparisons with basic t-tests (matched pairs or
two independent samples). We describe a set of curriculum materials developed to help
instructors facilitate such projects and share access to these materials. We give examples of how
the curriculum materials guide each stage of project implementation. We detail the requirements
and student activities during each phase of the student-directed projects: Students select their
own research topic, define their own variables, and devise and carry out their own data collection
plan before analyzing and interpreting their data. Students then articulate their results, both in a
written report and in a brief formal presentation delivered to the class. We give examples of
specific projects that students have conducted. Finally, we discuss the potential benefits of such
projects, including possible factors mediating those benefits.
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