As a professor and a parent, I have long dreamed of finding a software program that helps every student learn to write well. It would serve as a kind of tireless instructor, flagging grammatical, punctuation or word-use problems, but also showing the way to greater concision and clarity, says Randall Stross for the New York Times. Now, unexpectedly, the desire to make the grading of tests less labor-intensive may be moving my dream closer to reality. The standardized tests administered by the states at the end of the school year typically have an essay-writing component, requiring the hiring of humans to grade them one by one. This spring, the William and Flora Hewlett Foundation sponsored a competition to see how well algorithms submitted by professional data scientists and amateur statistics wizards could predict the scores assigned by human graders. The winners were announced last month — and the predictive algorithms were eerily accurate. The competition was hosted by Kaggle, a Web site that runs predictive-modeling contests for client organizations — thus giving them the benefit of a global crowd of data scientists working on their behalf. The site says it “has never failed to outperform a pre-existing accuracy benchmark, and to do so resoundingly.”

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