Teach the Earth > Career Prep > Previous Workshops > Workshop 09 > Program > Using Data: Benefits and Challenges

Using Data in Your Courses

Participants in the workshop session on Incorporating Local and Global Data into Courses (at the 2009 workshop on Preparing for an Academic Career in the Geosciences) brainstormed the lists below.

Benefits to Using Data in Courses

  • Students are motivated by real-world examples; increases student interest
  • Make connections between concepts and real life
  • Students see that datasets are not always perfect
  • Students get to participate in the process of doing science
  • Provides context for the material
  • Gives a sense of "freshness" to the material in the course
  • Students see where "numbers" actually come from
  • Students develop a more refined analysis/critique of the information
  • Physical skills learned (acquiring, measuring, organizing information, dealing with statistics and outliers, etc.)
  • Textbook data are often oversimplified; real data are complex!
  • Identify patterns and anomalies within the information
  • Students develop a sense of ownership for the data

What are particular skills and/or concepts you can teach?

  • How to make the tables and figures that illustrate data trends
  • Allows you to build, or scaffold, on the data analysis and interpretation
  • How to plan for field and/or lab collection
  • How to access and choose online data sources and evaluate their quality
  • Testing of hypotheses

Potential Challenges and Workarounds

  • How much data are enough? How much data are too much? (Constrain their search limits/options)
  • What if the class size is too large? (Make a homework assignment)
  • Missing data and/or large gaps (Teach averaging, extrapolation)
  • What learning styles are best served by this process? What should the order of instruction?
  • Inability to get online (Print out hard copies of the data; make it a HW assignment)
  • Collected data don't show the relationship you want! (Have a correct and/or calibrated data set)
  • Errors in the process—poor links, missing instructions (Have a "dry run" with a fresh pair of eyes)