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Feb 21, 2017 08:39 AM EST

University Of Washington To Teach Course On Critical Thinking About Big Data

UW to launch course on big data and critical thinking
UW to launch course on big data and critical thinking
(Photo : Peter Macdiarmid/Getty Images for Somerset House)

The University of Washington will be launching a course that aims to help students think critically about big data. It is expected to facilitate the development of students' analyzing skills.

Stat News reported that two professors from the University of Washington have developed a new course that is intended to help students see alternative facts and fake news with a critical eye. The course is entitled "Calling Bullshit In the Age of Big Data."

The official website of the class was launched last month and has become quite popular. Carl Bergstrom, a biologist and one of the professors who helped create the course, said that they had 20,000 visitors, several emails and even got book offers the morning after the website went online.

His teaching partner is assistant professor in UW's Information School, Jevin West. Both of them are longtime scientific collaborators and have invested years in investigating inflated claims, manipulated algorithms as well as twisted interpretations.

The course will initially be a 1-credit seminar this spring. There are already plans to expand it to a 3- or 4-credit course for the next school year. It is expected that students will be able to remain vigilant and know how to discern fake news or data from information fed to them.

The professors also expect students to be able to figure out why certain information is inaccurate or fake and be able to provide a technical explanation for it. Moreover, they expect the skills that students gain from this course to be the "most useful and most broadly applicable" out of everything they learned in college.

Speaking to Recode, West said that he and Bergstorm believe that science may be a bit at risk because of inaccurate information being provided by the media. They saw that methods of statistics intended for smaller data sets were being applied to big data sets, which makes it easy to manipulate a correlation that is not always accurate.

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