Common ed-data myths: Teachers are just data consumers

In the age of big data, when advances in our ability to slice and dice data promise a revolution in measurement comparable to advances that accompanied the invention of microscope, education data myths hurt teachers and students more than any other single constituency.

That’s why we broke classroom data myths into a separate infographic. A commenter on our Facebook (a teacher, in fact) summed up our view of this particular brand of education data myths best as “common knowledge amongst those of us in the trenches, yet foreign to those who make the decisions affecting us and our profession.” Let’s take a look:

Education data myth #5: Teachers are just data consumers

School districts, charter management organizations, and state agencies often talk about how they are going to “deliver data to teachers.”  This is a nice sentiment, but is misses a bigger truth.  Teachers are already generators of massive amounts of data every day. (See next myth, below).  And the data that teachers generate in their classrooms is often much more useful to their daily and weekly teaching than the static data provided through more standardized methods.  The real leaders in the coming years will be the schools and tool makers who recognize the “teachers as data generator” idea, develop ways to enable and accelerate the practices teachers already use, and run with it.

Education data myth #6: More data creates more work for teachers

Does using data in the classroom steal precious time from a teacher’s already-stretched day? Does it create more work?

Deconstructing this myth is a little complex. Why? Because the answer depends on how tools are implemented. In many schools, the expectation that teachers use data to inform teaching creates a very real problem: Teachers have to access multiple, disjointed data tools and products (including paper files!) to get a complete picture of a student. In fact, our experience in several Texas districts revealed that teachers were signing on to anywhere from six to twelve screens to find information for a student profile – what teacher has that kind of time?

But the multiple tool problem is something that vendors and education agencies can address. The key is adoption and implementation of a common data standard – a translator that enables tools and products to work together to tap the rich stores of data already stored in various places.  Once the ‘data scavenger hunt’ is solved, holistic “snapshot” views of critical data can make lesson planning faster and more targeted.

Before we leave this particular topic, it’s important to remember one other fact: Data-driven instruction doesn’t depend on teachers collecting more data than they already do. Attendance, grades, assignments, test scores – all of this data they gather today. Instead it depends on giving teachers ready access to the personalized, student- and subject-level information they need to hone in on and address clear gaps in individual student’s learning.

Education data myth #7: Tools alone lead to student growth

So, once a school has put in place easy-to-use tools that capture and display student data on an ongoing basis, data driven instruction will take place, right? No. The fact is that tools alone won’t generate change. Why? Because most schools of education don’t adequately prepare teachers to use data. So we now have an army of our most important knowledge workers operating without any real training in 1) how to analyze and understand data, and 2) how to respond once they understand what the data are telling them.

Intentional efforts need to be made in schools and systems to build educator capacity to understand and respond to data. Attention must be paid to the five building blocks of data-driven instruction – especially the requirement that school leaders define process and structures that allow teachers the time to integrate data analysis and data-informed planning into their daily work. Our experience shows that the effort to weave data into the fabric of existing school processes and structures must be well-planned. If it isn’t, we can almost guarantee you that there will be little to no impact on student learning.

The final post in the series (scheduled for Monday) will take a look at some of the hottest issues out there: the ideas that test data is a good tool for evaluating teachers, that classroom data is useful for teachers only and that data-driven instruction limits teacher creativity.

• Download the related infographics: Making the Data Grade and Classroom Data Myths.
• Read Joe Siedlecki’s post on Education data myths 1 & 2: Data = test scores and data-driven education is new.
• Read Lori Fey’s post on Education data myths 3 & 4: Data rich is data driven; software is the solution.