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Data Science for the Masses - Lightning Talk - Kirk Borne - RDAP12

ASIS&T
ASIS&T

Data Science for the Masses: start small, think big Kirk Borne, GMU School of Physics, Astronomy, & Computational Sciences

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Data Science for the Masses: start small, think big
     Kirk Borne, GMU School of Physics, Astronomy, & Computational Sciences
• Data Science (Informatics) in Education
    • Work with data in all learning settings.
    • Use data for inquiry-based classroom learning experiences.
    • Learning is enhanced when students work with real data and information (especially
      online data) that are related to the topic (any topic) being studied.
        http://serc.carleton.edu/usingdata/ (“Using Data in the Classroom”)
• An Education in Data Science (Informatics)
    • Data Scientists are specifically trained …
          … to access large distributed data repositories
          … to conduct meaningful inquiries into the data
          … to mine, visualize, and analyze the data
          … to make objective data-driven inferences, discoveries, and decisions
•   Teach by Example: follow an evidence-based “forensics” approach
    • Science is data-driven (evidence-based).
    • The Scientific Method does not begin with “hypothesis formulation” …
         • … neither should any reasoning process start with pre-conceived conclusions.
    • Big Data provide an excellent framework and environment for dealing with this.
    • By including Data Science in all of our education programs, we train the next-generation
      workforce in the art of informed, objective, data-driven, evidence-based decision-making.
    • Isn’t this what we expect from all of our citizens?

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Data Science for the Masses - Lightning Talk - Kirk Borne - RDAP12

  • 1. Data Science for the Masses: start small, think big Kirk Borne, GMU School of Physics, Astronomy, & Computational Sciences • Data Science (Informatics) in Education • Work with data in all learning settings. • Use data for inquiry-based classroom learning experiences. • Learning is enhanced when students work with real data and information (especially online data) that are related to the topic (any topic) being studied.  http://serc.carleton.edu/usingdata/ (“Using Data in the Classroom”) • An Education in Data Science (Informatics) • Data Scientists are specifically trained …  … to access large distributed data repositories  … to conduct meaningful inquiries into the data  … to mine, visualize, and analyze the data  … to make objective data-driven inferences, discoveries, and decisions • Teach by Example: follow an evidence-based “forensics” approach • Science is data-driven (evidence-based). • The Scientific Method does not begin with “hypothesis formulation” … • … neither should any reasoning process start with pre-conceived conclusions. • Big Data provide an excellent framework and environment for dealing with this. • By including Data Science in all of our education programs, we train the next-generation workforce in the art of informed, objective, data-driven, evidence-based decision-making. • Isn’t this what we expect from all of our citizens?