How to Teach with Data
At the broadest level, when you teach with data you need to answer these three intersecting questions:
Vandy CFT: Graduate Student Teaching Event for Professional Development
This section presents a continuum of student engagement, ordered according to the level of direction/independence afforded to the student, ranging from students watching a demonstration of data analysis to open-ended discovery. Because advanced researchers often find themselves working at the independent end of the spectrum, it is tempting to conclude that less experienced students must work with significant direction. This section includes counter examples that show it is possible to encourage open-ended discovery even in introductory courses.
There are many strategies for approaching a research question including experimentation, description, modeling, and comparison. (This list is drawn from The Process of Science written by Capri and Egger.) The goals for your course and its context relative to other courses in a sequence will likely drive your answer to this question.
The answer to this question is likely driven by the learning goals for your course (for example, do students need to learn to use an instrument to collect data?) and conventions in your discipline about what 'counts' as data. It also may be influenced by practical questions about what kinds of data are accessible and available to you and your students.