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If you are offended by the word bull**** you might want to stop reading now.  However, if you think the main purpose of education is to teach human capital to be useful in the global economy, you know that this premise is indeed bull****.  If you believe the current education reforms of ‘data driven’, non-direct instruction, Social Emotional Learning are not the wonder drugs for educational woes, you can spot bull****.  If you still are asking for the research/data that the Common Core architects and thought leaders insisted were present in the writing of the standards (but never produced even eight years after those claims were made) you are a bull**** detector.

If you can label the nonsense coming out of the education reformers (and other public/private partnerships) for what it really is (bull****) then keep reading and peruse the syllabus prepared by two University of Washington professors, Carl Bergstrom and Jevin West to teach students how to determine if what they are reading is factual or bull****.  From Calling Bullshit, In the Age of Big Data:

 

 

The education reformers should be absolutely delighted ‘data driven’ now means using their data mining information to determine if they are telling the truth or giving us more BS.  The course includes tools to spot BS.  This is helpful since the ‘evidence’ illustrating the need for the Common Core States Initiative and ESSA is sketchy at best and the conclusions reached for the need for these reforms is not based in scientific data:

Those of us concerned more about the truth of educational claims may want to take advantage of the syllabus and resources available from Professors Bergstrom and West to learn to more quickly call bull**** when we see it and respond to refute it with facts.  From the Syllabus and Links to Reading:

Calling Bullshit in the Age of Big Data

Logistics

Course: INFO 198, University of Washington
To be offered: Spring Quarter 2017
Credit: 1 credit, C/NC
Time and Location: Wednesday 3:30-4:20 MGH 389
Enrollment: 150 students
Instructors: Carl T. Bergstrom and Jevin West
Synopsis: Our world is saturated with bullshit. Learn to detect and defuse it.

The course will offered as a 1-credit seminar this spring through the Information School at the University of Washington. We aim to expand it to a 3 or 4 credit course for 2017-2018. For those who cannot attend in person, we plan to videotape the lectures this spring and make them them freely available on the web.


Learning Objectives

Our learning objectives are straightforward. After taking the course, you should be able to:

  • Remain vigilant for bullshit contaminating your information diet.
  • Recognize said bullshit whenever and wherever you encounter it.
  • Figure out for yourself precisely why a particular bit of bullshit is bullshit.
  • Provide a statistician or fellow scientist with a technical explanation of why a claim is bullshit.
  • Provide your crystals-and-homeopathy aunt or casually racist uncle with an accessible and persuasive explanation of why a claim is bullshit.

We will be astonished if these skills do not turn out to be among the most useful and most broadly applicable of those that you acquire during the course of your college education.

Schedule and readings

Each of the lectures will explore one specific facet of bullshit. For each week, a set of required readings are assigned. For some weeks, supplementary readings are also provided for those who wish to delve deeper.

Lectures

  1. Introduction to bullshit
  2. Spotting bullshit
  3. The natural ecology of bullshit
  4. Causality
  5. Statistical traps
  6. Visualization
  7. Big data
  8. Publication bias
  9. Predatory publishing and scientific misconduct
  10. The ethics of calling bullshit.
  11. Fake news
  12. Refuting bullshit

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If you are weary and done with the bull**** masquerading as truth and fact, this might just be a good course online to take when available.  Maybe virtual education will actually be the one positive development in education reform.

 

You can follow the professors on twitter here.

 

 

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