Slow thinking and deep learning: Tversky and Kahneman's taxi cabs |
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| Authors: | Mike Bedwell |
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| Institution: | Ukranian Education Centre, Kyiv, Ukraine |
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| Abstract: | This article is based on classroom application of a problem story constructed by Amos Tversky in the 1970s. His intention was to evaluate human beings' intuitions about statistical inference. The problem was revisited by his colleague, the Nobel Prize winner Daniel Kahneman. The aim of this article is to show how popular science textbooks can serve as a source for rich classroom activity, with a little care in the implementation by teachers. Kahneman describes the problem as ‘standard’ and answers using a fixed point number. I describe how I have encouraged my students to challenge the certainty of this assertion by identifying ambiguities that are left unexplained in the story. This way, I claim to stimulate individuals to indeed move towards Thinking, Fast and Slow, the title of Kahneman's book. |
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| Keywords: | Teaching Teaching statistics Deep learning Slow thinking Cab problem Bayesian statistics |
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