coisas da educação... "It’s “Big Data vs. Standardized Tests"...!

"It’s Not “Big Data vs. Teachers” — It’s “Big Data vs. Standardized Tests”

People often think that big data for education is a new thing. And it’s true that using big data the way Knewton does sounds almost like science fiction — our engine passively “norms” content at scale, uses normed content to determine students’ conceptual proficiencies to the percentile, and makes granular content recommendations for each student based on the combined anonymized data of all the other students in our network.

But there is an older, bricks-and-mortar type of big data for education: standardized tests.

People always ask me whether I think standardized tests actually measure anything. I used to give nerdy statistical answers about scoring validity and such. Eventually I realized that all they want to hear is that standardized tests are useless, possibly corrupt.

Standardized tests are increasingly unpopular, and not without reason. But when used properly they do, or at least should, serve important purposes. There are two main kinds of standardized tests: admissions and state assessment. Admissions tests like the SAT were built to predict academic performance in college and graduate school. Grades and transcripts also do this, but academic standards and programs differ so greatly from school to school and region to region that a central standard measure is extremely useful. State assessments help demonstrate whether students are graduating from high school with basic literacy and math skills. They exist because society, which pays for every child to have free K-12 education, has a right to know that kids are actually learning.

To fill its only purpose (and to have a shot at being fair), a standardized test must yield totally consistent scores across administrations. If Maria takes the SAT in May, takes the summer off (and, let’s assume, doesn’t gain or lose any knowledge), and then takes the SAT again in September — she should get the exact same score both times (plus or minus the margin of error).

It is a nearly impossible technical challenge to build a test so well that it yields totally consistent scores across multiple examinations. Try holding a dinner party and giving every guest a 50-question test on any topic. Then invite them back the following week and give them another test on the same topic, but with different questions. Spare your friends the ordeal and trust me: most of them won’t receive similar scores. Yet the big U.S. test makers have figured out how to do exactly this, except they can do it repeatedly, at much larger scale, and with examinees about whom they know almost nothing.1

The reality is that standardized tests are effective predictors of academic success in college or graduate school.2 That’s a fact of statistics, whether anyone likes it or not. It’s also just an average, and anyone could be an exception one way or the other. Standardized test scores, in my opinion, are more reliable at the top end of the scale than they are lower down. High scores generally indicate that someone is quite capable; but low scores may not mean very much at all. For these reasons, among others, standardized tests should be just part of the admissions process, and should never be the most important part.

The problem isn’t with the tests themselves, or their goals."

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