By Jessie Oehrlein (Fitchburg State University)
Information
The key ideas of introductory statistics are often taught in themed units (descriptive, inference, regression, etc.) where the smaller components of these larger concepts arise in quick succession with little time for students to gain confidence with one component before building on it. I will present an alternative structure that I tried in Spring 2026 of multiple parallel "strands" of those overarching statistical themes. Throughout the course, students advance through these "strands" with the component concepts more spread out in an attempt to increase opportunities for practice. Individual class periods integrated learning across the strands. For example, one 75-minute class period began with brief individual practice on interpreting a confidence interval, then proceeded with the introduction of two new topics, how confidence level qualitatively affects margin of error and the structure of a normal distribution, through team guided inquiry activities, and then incorporated a few minutes of team practice with writing hypotheses before returning to an inquiry activity on finding probabilities in a sampling distribution. In the guided inquiry activities, students answer questions to explore a visual model of a new idea, and as a team, they define new terms or ideas for themselves. They then apply those ideas to a novel scenario, evaluating and constructing arguments about how the ideas apply. The main goal of the topic order change was to give students a stronger foundation from which to discover and apply each new idea. This approach has not changed, which broad topics in the course the students find most challenging, but based on student reflections and conversations, it is helping them to pinpoint the particular aspects that are tricky for them. That has helped me to provide more timely, targeted practice that improved student confidence. However, the "strands" approach has sometimes sacrificed cohesion of ideas within a class period. This implementation was at a small regional comprehensive university in a 25-student introductory statistics course with no prerequisites/background assumptions. While particular activities used vary in scalability, the idea of increasing mixing of topics and opportunities for practice with smaller component skills can be used across course sizes. The motivations here were driven by the low-prerequisite context, but considering a broader range of ways to sequence course content could help us to better support students across courses.