Monday, March 4:
8:30 AM Breakfast
9:00 AM Welcome & Introductions
- Welcome on behalf of SIO and NAGT
- Overview & Goals of the Workshop: Kim Kastens (Goals ppt (PowerPoint 2007 (.pptx) PRIVATE FILE 1.4MB Mar4 13))
- To build EarthCube in such a way that will bring the power of learning through Earth data and models within reach of novices
- To use EarthCube to educate future geoscientists who will be unprecedentedly facile with data and models, and "native speakers" of interdisciplinary systems.
- Introduction to EarthCube: Barbara Ransom, NSF (Ransom's ppt (PowerPoint 2007 (.pptx) PRIVATE FILE 690kB Mar4 13))
10:00-11:30 AM Learning Goals & Learning Performances (Learning Goals Introductory PPT (PowerPoint 2007 (.pptx) PRIVATE FILE 226kB Mar3 13))
Learning goals: What should an undergraduate geoscience major know, understand, and be able to do by graduation?
Learning performances: How will we know a data-savvy graduate when we see one?
11:45 AM - 12:45 PM Employers' Panel
What knowledge/skills/habits of mind do you want to see in your data-using employees?
12:45-1:30 PM Lunch
1:30-2:00 PM Survey results from Joel Cutcher-Gershenfeld (Cutcher-Gershenfeld ppt (PowerPoint 2007 (.pptx) PRIVATE FILE 1.1MB Mar4 13))
2:00-3:30 PM Obstacles and Challenges (Obstacles Intro ppt (PowerPoint 2007 (.pptx) PRIVATE FILE 8.3MB Mar4 13))
What is getting in the way of being able to achieve such data-savvy graduates?
3:45-5:30 PM Instructional Sequences (Instructional Sequences Intro ppt (PowerPoint 2007 (.pptx) PRIVATE FILE 662kB Mar4 13))
What will the data-using lesson of the future look like?
And what are the technology/social engineering implications for each of our envisioned instructional sequences?
Tuesday, March 5:
8:00-8:30 AM Breakfast
"Oceans of Data" recommendations for student-friendly data access
How we would like to improve on existing data access interfaces
10:30-11:00 AM Break
11:00 AM - 12:30 PM Geosciences models session (Modeling intro ppt (PowerPoint 2007 (.pptx) PRIVATE FILE 3.4MB Mar5 13))
How will students compare empirical/observational data with model output?
How could EarthCube support students' learning to become critical users of model?
How could EarthCube support students' learning to be model-builders?
12:30-1:15 PM Lunch
1:15-3:00 PM Blue skying the future of EarthCube-enabled education (BlueSky ppt (PowerPoint 2007 (.pptx) PRIVATE FILE 1.8MB Mar5 13))
Imagine trying to create a new kind of undergraduate, someone who is a "native systems thinker," someone whose thinking ranges readily from discipline to discipline, from model to field to lab, across spatial and temporal scales, using digital cognitive tools as effortlessly as I ride a bicycle or drive a car. Could we do this? And if so, how?