Last week on the Core Knowledge blog, Robert Pondiscio called for the end of seven classroom practices that don’t work. Four of the seven practices dealt with standards- and data-driven instruction—or, really, the bastardization of standards- and data-driven instruction. The crux of Pondiscio’s argument is right on the money: Standards-driven instruction is only as good as the standards and assessments that are used to drive instruction, and reading standards (and/or assessments) that prioritize empty reading skills over content are sure to steer our teachers wrong.
Unfortunately, Pondiscio’s post distracts from that point by deriding some practices that, when done well, can be used to powerfully drive student achievement.
Take, for example, data-driven instruction. Pondiscio is right that “using data in half-baked or simplistic ways” is going to do very little to drive student learning. But the answer is not to abandon data-driven instruction writ large, but rather to encourage teachers to use data thoughtfully and purposefully. There aren’t nearly enough examples (or quality PD purveyors) that demonstrate how this can be done and done well. We need more.
There is no question that test prep is virtually useless.
Similarly, Pondiscio derides both “dumb test prep” and “reciting lesson aim and standard.” There is no question that test prep is virtually useless. In fact, the fact that test prep is used so widely, but that reading scores have remained essentially flat for more than a decade, should help demonstrate just how ineffective it is. Why it is still the go-to method for preparing students for state tests is beyond me.
By contrast, the practice of organizing lessons around a clearly-defined aim is critical. And putting that aim in student-friendly language, while not absolutely necessary, can be useful. Unfortunately, the aim is too often added at the end, often as a compliance measure only because it is required by school and district leaders. And, as a result, there are countless examples of laughable “aims,” chief among them the one Pondiscio cites in his post. (“Through this lesson I will develop phonemic awareness and understanding of alphabetic principles.”)
But, as the Cheshire Cat explained to Alice: if you don’t know where you’re going, it doesn’t matter much which way you go. And so it is in teaching: aimless lessons are too often guided by ill-chosen activities—including the kinds of “overused teaching strategies” that Pondiscio warns against in his post—exactly because the teacher hasn’t clearly defined the outcome s/he is driving towards. In fact, perhaps the best way to avoid the overuse of ineffective teaching strategies is to organize lessons around clearly defined aims. (And to use formative data to drive short and long term planning!)
That said, writing great aims—particularly in reading—is incredibly difficult. But getting it right is essential.
Writing great aims—particularly in reading—is incredibly difficult. But getting it right is essential.
In the end, Pondiscio is right about one thing: poorly conceived and implemented standards- and data-driven instruction will do little to drive achievement, particularly in reading. But, the best way to improve instruction—and to discourage the practices that Pondiscio rightly derides—is not to abandon it entirely, but rather to improve the foundation upon which that instruction is built. Specifically: we need to change the way we assess reading and the way we present data from those assessments to teachers.
In the end, the main reason that reading instruction is driven by skills is that reading assessments are designed to assess mastery of reading skills in isolation. This can’t be done well and should be abandoned. Instead, assessments should be organized around genres and mastery of critical, genre-specific content. And the data from the assessments should not be presented in terms of whether students have mastered particular skills—but rather how that comprehension differs depending on the genre or content covered.
