14 students: 6 Seniors, 6 Juniors, & 2 Sophomores. Of which:

• Double majors:
  • Environmental Sciences-Econ
  • Econ-Linguistics
  • CS-Econ
• Single majors:
  • Economics x 4
  • Molecular Bio & Biochem x 3
  • International Politics and Econ, Neuroscience, Bio, CS

• Mixture of lab & lecture: students bring their own laptops to class.
• Use real, messy, complex data.
• Discussions in class.
• This class uses R, but is not a class on R. I try to teach things in a language agnostic fashion.
• "Minimizing prerequisites to research.", quote by George Cobb.

Doing data analysis is part art/part science. There is

• Substance: what is trying to be said
• Style: how it is being said i.e. writing/coding

There is no instruction manual or code book for good writing/good data analysis.

Two goals:

• Have students learn to code the way people learn in real life.
• Fascilitate giving feedback.

Solution:

• Lots of collaboration and peer learning.
• Homework as practice rather than evaluative.
• GitHub.

GitHub is a web based repository for code widely used by the open-source coding community. It provides tools for

• Version control
• Collaboration

From a colleague in the humanities:

"Don't give feedback on everything. Focus on the top 5 things they need to work on, and drill down."

Both for their sake and for your own.

Example of a student's recent HW.

The thing about GitHub…

• When it works, it works great.
• When it doesn't, its… xkcd