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.
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.”