We spoke with Leslie Hendrix, a Clinical Professor in the Management Science Department at the Darla Moore School of Business. She teaches a large-scale statistics course that sees approximately 1,700 students per academic year. Leslie tells us how she sets up a course of this size, offering a valuable framework for educators aiming to teach statistics to business students effectively.
Understanding the Course Structure
Hendrix's course is a second-level statistics class with a strong emphasis on interpreting outputs and gaining insights to enhance business profitability. According to Hendrix, the primary learning objectives include:
- Building programming skills in R
- Interpreting statistical outputs to make data-driven business decisions
- Applying statistical methods to solve real-world business problems
"We want to send out students that aren’t afraid to try an algorithm in their future job and be able to have that sort of effect," Hendrix emphasizes.
Assessment methods
The course includes several assignments varied in type and length:
- Homework Assignments: Approximately ten assignments, focusing on coding in R, designed to reinforce content from weekly lessons.
- Case Studies: Four comprehensive projects integrating concepts from the homework assignments, allowing students to solve practical problems individually. These are untimed and with unlimited attempts to reinforce concepts.
- Exams: Three multiple-choice quizzes, administered through Canvas, to assess understanding of statistical outputs and concepts without the stress of timed coding.
CodeGrade is used for assignments and case studies, giving students instant feedback. Leslie is looking into incorporating CodeGrade’s Interactive Quiz feature for exams in the upcoming iteration of her course.
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