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Incorporating Data Analysis into Undergraduate Courses

Preparing for an Academic Career in Geosciences Workshop: Summer 2013. Incorporating Data Analysis into Undergraduate Courses. Rachel O ’ Brien, Allegheny College Rajul Pandya, AGU. Data sets are flexible. Data and assignments can be tailored to reach a broad range of student groups

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Incorporating Data Analysis into Undergraduate Courses

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  1. Preparing for an Academic Career in Geosciences Workshop: Summer 2013 Incorporating Data Analysis into Undergraduate Courses • Rachel O’Brien, Allegheny College • Rajul Pandya, AGU

  2. Data sets are flexible • Data and assignments can be tailored to reach a broad range of student groups K-12 Graduate courses • Can be used in one class/lab session or throughout an entire course

  3. Data sets are cost-effective • Majority of online sources are now free • Simple, low-cost field and lab work Data sets are concept-effective • Allow for compare/contrast work at a range of spatial & temporal scales • Single or multi-concept patterns

  4. Data sets are engaging • Allow students the opportunity to practice science and promote active learning Data sets are real • Require students to grapple with issues of complexity, uncertainty, and outliers

  5. Ocean Circulation Profiles Classic textbook Pacific high latitude Atlantic low latitude http://www.epic.noaa.gov/epic/ewb/

  6. Data sets are diverse in topic , scope, and format • Newly created datasets • Field work and/or lab work in your course • A genuine research experiment • Data from published literature • Journal articles, government documents, NGO reports • Online datasets • Teach particular concepts and/or skills • Recreate research, test hypotheses

  7. A great place to start http://serc.carleton.edu/usingdata/resources

  8. Data sets are not stand alone resources • Design how you’ll use data • Identify clear learning outcomes for content, concepts, and/or skills • What steps in the process are most important for your students to practice? (collection and reduction vs. analysis and reporting) • How will you address uncertainty, outliers, etc.?

  9. Data sets are not foolproof • Logistics • Work through all steps of the process ahead of time • Envision and create “Plan B” • Evaluation Did the use of data help student learning? How will you know?

  10. A partial list of Web sites with earth science data CUAHSI-HIS EPA NSIDC GEOROC UNAVCO IPCC USDA LDEO USGS NCAR NOAA

  11. Geodetic Data UNAVCO EarthScope Plate Boundary Observatory

  12. Earthquake Data USGS Earthquake Hazards Program & SCEC So. California Earthquake Center

  13. Hydrologic Data USGS Water Resources Division

  14. Satellite ImageryNASA Earth Observatory

  15. Earth, Ocean, & Climate Data NASA Eyes on the Earth 3D

  16. Atmospheric Data (from NCAR) Climate Data Guide offers critiques of data sets and their use by experts from the broader research and education community The Community Data Portal is a comprehensive index of weather, climate and atmospheric data. The NCAR GIS Program has a range of climate and demographic data, including IPCC scenarios, available in GIS

  17. Sample Activity: Radiation Budget Learning Outcomes: Students construct global and local energy balance from observed longwave and solar radiation and relate that to spatial and temporal variations in Earth’s temperature. Time: Takes about 3 hours for students in teams, requires familiarity with GIS or MyWorld A complete description of this activity is available at SERC, called Earth’s Energy Budget by Dave Dempsey

  18. Sample Activity: Ice Core Analysis Learning Outcomes: Students use Excel to graph and analyze ice core data and learn about past variations in CO2, temperature, and climate cycles Time: Takes about 4 hours A complete description of this activity, called Vostek Ice Core by Robert MacKay, is available at SERC

  19. Exploration activity • Choose a course: Introductory level • or advanced course (grad or undergrad) • Identify a website with datasets that could be used in the course –OR- identify new datasets that the students can generate • What concepts(s) and/or skill(s) do you want the students to learn by using the data?

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