Title: Data-Driven Decision-Making: Is It the Mantra of the Month or Does It Have Staying Power?
Abstract: DATA-DRIVEN DECISION-making: the term falls trippingly off the tongue. It has become a school-reform mantra that is celebrated but widely misunderstood, and is often ignored (despite its hype) or actively feared. The term almost conjures up images of Bartleby the Scrivener, the protagonist of Herman Melville's eponymous tale. One can see the modern Bartleby, his green eyeshade, arm garters and three-legged stool gone; his quill pen replaced by Microsoft Excel spreadsheets; sitting in his district office, faced with the daunting task of harnessing student data to inform instructional decision-making; and saying with all the ambivalence of Melville's scrivener, I would prefer not to. Much ballyhoo, even hype, surrounds data-driven decision-making, which is the process of collecting student data--academic performance, attendance, demographics, etc.--in such a way that administrators, teachers and parents can accurately assess student learning. They can then make decisions based on the data to improve administrative and instructional systems to continually promote student achievement. Governors, state legislators, reform-minded school superintendents, eager school board members, the occasional teacher, policy wonks and entrepreneurs wax enthusiastic. Used wisely and well, they say, data-driven decision-making will permit school boards to step back from their fixation on micromanagement and concentrate on effective policy formulation. They also tell us that practitioners in the trenches, from principals to classroom teachers, will be able to improve practices by pinpointing problems and transforming them into new opportunities. At its best, data-driven decision-making is much more than an accountability tool; it is a diagnostic tool that permits--nay, encourages--teachers to tailor instruction to student needs. Thus, it finds that they can better and more easily direct their students toward success. So far, despite data-driven decision-making's many vocal proponents, it is equally clear that the message has not yet gotten to the front lines. Why Educators Resist It Why have some educators been resistant to a concept that has so much support from the government, businesses, parents and other stakeholders? Not to put too fine a point on it, the first reason is fear and loathing. With only slight exaggeration, it is safe to say that most educators view data as the enemy. Data is something a third party requires you to gather about yourself with the expectation that it will be used to embarrass you down the road. Does this sound familiar: doing poorly? Fire the bum! Kids doing well? They're so smart they could do well anywhere. The second and collateral reason for educator resistance is that, with few exceptions, educators see data as a burden, not an asset. Even if it is not going to be used to hold you up to ridicule, it has little utility. A teacher needs to spend time with his or her students, not with data entry and arcane analysis, the argument goes. With the notable exception of attendance data, which in most districts generates revenue, school data neither simplifies life nor increases a sense of professional efficacy. The importance of this phenomenon cannot be overemphasized: Only when data becomes genuinely useful and commonplace in the classroom will teachers and administrators welcome it. And only when it is useful will data quality improve. This lack of clean data--i.e., data that is timely and accurate--is the bane of researchers and analysts. Up until this point, no one cared too deeply if a student name on a school record didn't exactly match the student name on a test record, because no one was really doing anything with the test data. However, if we really want to follow how a particular child performs on tests over time, we need all of his or her data to align. The benefits to districts are palpable as well. For instance, districts in Texas improved their graduation rates dramatically when students who were listed as dropouts were matched with the other names they were enrolled under and taken off the dropout list. …
Publication Year: 2003
Publication Date: 2003-05-01
Language: en
Type: article
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Cited By Count: 28
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