By Anne Hackman (University of Minnesota)
Information
The dose-finding activity is a one-hour lesson that allows students to engage in probabilistic thinking by playing the role of a cancer researcher conducting a first-in-humans study to identify the best dose of a new cancer drug. It is intended for middle and high school students. Students are asked to consider what “best dose” means in the context of a cancer drug and to practice identifying the “best” dose given perfect knowledge of the properties of different doses. Students plan and carry out a simulated clinical trial using an R Shiny applet, which generates random outcomes for each trial participant from an underlying model. Finally, students use the outcome data to select a “best” dose and justify their choice using evidence.
This activity was designed by members of the Biostatistics and Health Data Science Community Outreach and Engagement Committee (BCOE), a group of faculty members, staff, and graduate students at the University of Minnesota School of Public Health. BCOE members create biostatistics-focused classroom activities to introduce K-12 students to Biostatistics and Health Data Science as potential career fields. A group of six high school teachers piloted the dose-finding activity and provided qualitative feedback. Twelve rising eleventh and twelfth grader participants in a cancer research summer institute then completed the activity. Pre- and post-surveys administered to the high school students revealed engagement with and curiosity about the statistical concepts introduced in the activity along with a small increase in interest in pursuing a career focused on Biostatistics and Health Data Science.
Activity link: https://bcoeumn.shinyapps.io/dosefindingapp/