A structured approach to developing an introductory statistics course for graduate students: Using data to teach about data.

BACKGROUND/OBJECTIVE: It was identified in the largest graduate unit of the Faculty of Medicine of a major Canadian University that there was a critical unmet curricular need for an introductory statistics and study design course. Based on the collective findings of an external institute review, both quantitative and qualitative data were used to design, develop, implement, evaluate, and refine such a course.

METHODS

In response to the identified need and inherent challenges to streamlining curriculum development and instructional design in research-based graduate programs representing many biomedical disciplines, the institute used the analyze, design, develop, implement and evaluate instructional design model to guide the data-driven development and ongoing monitoring of a new study design and statistics course.

RESULTS

The results demonstrated that implementing recommendations from the first iteration of the course (Fall 2021) into the second iteration (Winter 2023) led to improved student learning experience (3.18/5 weighted average (Fall 2021) to 3.87/5 (Winter 2023)). In the second iteration of the course, a self-perceived statistics anxiety test was administered, showing a reduction in statistics anxiety levels after completing the course (2.41/4 weighted average before the course to 1.65/4 after the course).

CONCLUSION

Our experiences serve as a valuable resource for educators seeking to implement similar improvement approaches in their educational settings. Furthermore, our findings offer insights into tailoring course development and teaching strategies to optimize student learning.