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A structured approach to developing an introductory statistics course for graduate students: Using data to teach
Lisa Eunyoung Lee1, Sobiga Vyravanathan1, Tony Panzarella1,2
1Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
Journal of Clinical and Translational Science
|February 6, 2025
Summary
A new introductory statistics and study design course significantly improved graduate student learning experiences and reduced statistics anxiety. This data-driven approach offers a valuable model for educational program development in biomedical sciences.
Area of Science:
- Biomedical Education
- Medical Statistics
- Curriculum Development
Background:
- Identified a critical need for introductory statistics and study design training in a large Faculty of Medicine graduate unit.
- Utilized both quantitative and qualitative data from an external institute review to inform course creation.
Purpose of the Study:
- To design, develop, implement, evaluate, and refine an introductory statistics and study design course.
- To address challenges in curriculum development for diverse biomedical graduate programs.
Main Methods:
- Employed the Analyze, Design, Develop, Implement, and Evaluate (ADDIE) instructional design model.
- Used a data-driven approach for course development and continuous monitoring.
Main Results:
- Student learning experience improved from a 3.18/5 average in Fall 2021 to 3.87/5 in Winter 2023.
- Statistics anxiety levels decreased significantly after course completion, with weighted averages dropping from 2.41/4 to 1.65/4.
Conclusions:
- The iterative, data-driven course development process enhanced student learning and satisfaction.
- The findings provide a valuable framework for educators to improve similar educational programs and teaching strategies.
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