Computational Inquiry in Introductory Statistics

Abstract

Inquiry-based pedagogies have a strong presence in proof-based undergraduate mathematics courses, but can be difficult to implement in courses that are large, procedural, or highly computational. An introductory course in statistics would thus seem an unlikely candidate for an inquiry-based approach, as these courses typically steer well clear of proof, have a list of required topics, and depend critically on computational software. On the other hand, the American Statistical Association (ASA) has long advocated the sort of active and exploratory class design that in many respects parallels traditional inquiry-based learning (IBL). This paper reports on the author’s recent attempt to implement an inquiry-based course in introductory statistics that fuses established IBL techniques with the specific pedagogical recommendations of the ASA. A signature feature of this course is that many of the inquiry-based activities are explicitly tied to computer work in the open source language R.

Keywords:

• IBL
• inquiry
• statistics
• mathematics
• education

AcknowledgementS

The author would like to thank the editors and anonymous referees for valuable feedback on this manuscript.

Additional information

Notes on contributors

Carl Toews

Carl Toews did his graduate work in function theoretic operator theory at the University of Virginia. He subsequently worked at the MIT Lincoln Lab, the University of Minnesota, Duquesne University, the Ohio State University, and the University of Puget Sound. His research interests include composition operators, astronautics, image processing, and ecology. Participation in Project NExT has stimulated his undergraduate teaching interests, and attendance at an MAA PREP workshop on inquiry-based learning has nourished his interest in inquiry-oriented pedagogies.