Pre Survey Response Themes

Prior to the workshop, participants were asked about what opportunities and barriers exist to teaching Data Science and/or Environmental Studies in liberal arts colleges. A summary of responses is found below, and will help frame our working group time at the May 31-June 1 workshop.

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Interest in collaborations

Resources for teaching

In particular, sharing:

• real-world, data driven examples
• Examples: LACOL Q-LAB
• EDDIE
• syllabi
• teaching modules
• course structures
• recommended textbooks/websites/tutorials/placement exams/videos/simulations/deatasets/data visualization tools
• models for teaching with data in liberal arts contexts
• strategies for teaching with large datasets
• data science education pedagogy
• Examples of all of the above: Teach the Earth- Environmental Science

• develop materials in a short time frame
• create materials that everyone needs

• co-teaching
• visiting speakers
• how to account for added time needed to prepare for these (funding, teaching credit),

Research collaborations

• find research teams to work on novel datasets
• experiments across campuses (for bigger n's)
• math preparation and prerequisites
• writing about data

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Provenance: Kristin O'Connell, Carleton College
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