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Teaching Matters: Avoiding Good Mistakes in Using Infographics
“Correlation is not causation but it sure is a hint.”
– Edward Tufte (1942-), American Statistician and Professor
We live in an age of big data, powerful algorithms and infographics. Significant decisions are being made daily based on data input, and adults – including our students – have to analyze and understand statistical information. Knowing this, what are the challenges that data could present to English teachers? How can we make sure we accurately classify, analyze, interpret, and take action based on such big volumes of information? What are some “good mistakes” that our English language learners often make in using and explaining infographics?
The March 31st, 2016 article “Career development: Six common errors when using data” provides practical advice on what not to do when using data. It’s an insightful article that I often assign to my advanced ESL classes at the University of Southern California.
Things to avoid
When it comes to synthesizing data, author Simon Wicks addresses a few common missteps:
1. Not all information is created equal
First, the author highlights the importance of not treating all sources of information with the same level of importance, suggesting “there’s room for all kinds of evidence when compiling a case, but not all are of equal value.” Wicks adds that context is of extreme importance when it comes to valuing data. For instance, he questions if data collected by a commercial business and a peer-reviewed study hold equivalent significance.
2. Don’t let your bias show
The second point Wicks calls attention to is the different types of cognitive bias, including anchoring (dependence on the first piece of data), conservatism (rejecting new information), and confirmation (focusing more on information that supports your own point of view over other evidence). The author states, in clear language, that cognitive bias can negatively impact the decision-making process.
3. The danger of false predictions
Third, making exact predictions from data is a common mistake to avoid. In academia, students often use estimates to give false certainty in order to sound more eloquent or persuasive in their statements. This issue might weaken accuracy and nuance. One possible solution? Promote and emphasize the importance of hedging language with your students. For instance, words such as assumption, probability, possibly, perhaps, usually, may, and might can improve the clarity and accuracy of statements. Teaching students how to develop a skeptical framework and move from the poetry of false certainty to the pros of possibility and probability remains essential. How many mistakes could be avoided if everyone – including our political leaders – learned the dangers of false certainty?
Do you teach your English language learners how to use and interpret infographics? What advice do you offer? Do you have favorite articles that you share with students? What points do you emphasize?
O’Brien, P. (2016, March 28). How Big Data is Finding its Market in Texas. Retrieved from SEO’Brien: https://seobrien.com/how-big-data-is-finding-its-market-in-texas
Wicks, S. (2016, March 31). Career development: Six common errors when using data. Retrieved from The Planner: https://www.theplanner.co.uk/advice/career-development-six-common-errors-when-using-data
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