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.
- Ben Ho, Vassar, Economics
- Jonathan Wilson, Haverford, Biology and Environmental Studies
- Helen White, Haverford, Chemistry & Environmental Studies
- Brad Johnson, Davidson, Environmental Studies
- Alberto Lopez, Amherst, Chemistry
- Steven Miller, Williams, Mathematics
- Chad Topaz, Williams, Mathematics
- Fuji Lozada, Davidson, Anthropology & Environmental Studies
- Jingchen (Monika) Hu, Vassar
- Ming An, Vassar, Statistics
- Nick Horton, Amherst, Statistics
- Guillermo Douglass-Jaimes, Pomona, Environmental Analysis
- Natalia Toporikova, Washington & Lee, Biology
- Moataz Khalifa, Washington & Lee, Physics and Engineering
- Deborah Gross, Carleton, Chemistry
- Gordon Jones, Hamilton, Physics
- Trish Ferrett, Carleton, Chemistry
- Andy Anderson, Amherst, Academic Technology Specialist
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