Exam Physiology: Wearable Data
Overview
This module introduces data analysis of physiology data. Students work with real physiological data collected from college students wearing stress-monitoring devices during exams. The data includes skin conductance (EDA), heart rate, and skin temperature measurements. The eventual goal of the researchers was to predict students’ grades from stress measurements.
Students will use Posit Cloud (an online version of R programming language and R Studio) to load and explore the data, calculate correlations between variables, visualize individual student data, compare two students side by side, and finally explore other students and form hypotheses about how physiological data is related to actual grades.
Duration: 1.5 - 2.5 hours
Learning Objectives
Work with data related to functional cardiovascular activity, temperature homeostasis, and stress
Experiment with technical R skills
Think scientifically (interpret data, form hypotheses)
Understand correlation and causation
Prerequisites
Students will benefit from being enrolled in an anatomy and physiology course. They do not need to have programming experience (code is largely copied and pasted).
Evaluation
GEMs is an NIH-funded program. Part of our mission is understanding the impact of our materials. Please take the time to review our program as an instructor after this activity. This activity’s evaluation is a bit different, as it’s not part of the core GEMs curriculum.
TipHelp Us Improve!
You can view our IRB approval here. Feel free to contact the GEMs team with any questions (gems at fredhutch dot org).
Materials
Student Activity
You can use this module in several formats. Feel free to adapt to your needs!
Students will need a device that accesses the internet.
WarningThis content contains URLs
We suggest confirming links are still active prior to running this activity:
Instructor Materials
An answer key is available here. Please message Ava Hoffman (ahoffma2 at fredhutch dot org) to get access.