This article first appeared in the St. Louis Beacon, June 24, 2013: “If you don’t define your terms, someone else will define them for you.” A wise teacher once taught me this. I am going to re-visit a term I used last week and unpack it with greater care: Big Data.
Big Data, says Wikipedia, are information assets characterized by high volume, high velocity and high complexity. It’s all the stuff people know and learn about what’s going on. Big Data exist in amounts that are too big to manage by traditional data processing tools.
Depending on how and where we go about our lives, Big Data is like an ocean into which flows all that we watch, do, observe, and buy. Once in the ocean, Big Data can be unstructured (like e-mail messages and telephone conversations) or structured in such a way that makes meaning (who we are and how we are likely to vote, for example). Once structured, Big Data can be used by people who have access to it.
In this oceanic sense, Big Data are all the linked and accessible ideas, images, people, stories and information (marvelous and lousy alike), an ever-expanding, ever-morphing postmordial goop. I seldom get through a day without tapping the goop. I know people who can hardly get through dinner without tapping it (wait -- who was the Oscar runner-up for Best Supporting Actor in 2003 again? Wait — how many people in Missouri have Internet access, anyway?).
In this sense, Big Data and certain kinds of learning are co-extensive — in reality for some and theoretically for others. We can learn a whole lot if we have an urge to know; if we are plugged into the goop; if the information we want to learn has been structured in a way we can understand it; if the structures are made public (available to all).
Thanks to all the brilliant people making the goop richer and more expressive every day, the goop connects us with each other all over the world and, through an ever-expanding archived digital culture, back through time. In this sense, Big Data make up the most amazing thing we've got going.
This is why it really matters who has access to and control of Big Data and how it is used on and around the people who do not have this control. (Consider what we’ve learned about the National Security Agency in the past couple of weeks and have another look at William Freivogel’s Law Scoop from June 11.)
In public schooling, Big Data are quiz scores, tests-scores, demographic information on students, teachers, and communities, frequencies of special services received by students, behavior infractions, absences, and many other facts.
In writing about Big Data last month, I was referring to market-driven processes and discourses determining what and how people teach and learn in schools. Teachers are very busy pulling data that other people will, in turn, use on them.
Dutiful data delivering is not teaching. Commercial curricula and high-stakes tests are profit-generating products. They are not necessary for good teaching; in fact, such products often obstruct good teaching.
I was referring very specifically to a world that looks like this in the places where children and their teachers spend 7 or 8 hours every day.
This banner caught my eye in a faculty resource room in a metropolitan elementary school. The "we" is the passive object of this statement; "data" are the subject. "Data drive us" is actually what this sentence means. The quotation marks highlight the slogan’s booster voice, which is meant to indicate school pride at being state-of-the-art around "data use" in the sense dominant in public schools across the country.
WE ARE DATA DRIVEN is a phrase spoken by the school to itself, as well as a public display of compliance with a non-negotiable message: "Yep, see? We're data driven just like they say we need to be." Data such as test scores don’t drive themselves.
Which gets to the crucial distinctions we need to be making at all times among these slippery conceptions of Big Data—what it is, how it works, who’s out there playing with it, who’s relying on it, and – most germane to what I am talking about – what’s happening to some people on account of what other people are doing with it. (Let alone why.)
The hegemony of business models in education (which rely on tracking and metrics in vast and seemingly inescapable ways) are slowly but surely extinguishing the ability of young people who are poor to develop a sense of agency in school. Asked why she is learning what she is learning in school, a fourth grader I met said, “To take the MAP test.”
It can be really great when teachers turn to the digital domain for meaningful pedagogical purpose. A 21st-century educator must prepare children to recruit words and worlds from outside the classroom. This means that ownership of and engagement with this stuff has got to originate from people who develop their own paths. That’s not what we have in the high-stakes, metrics-bound landscape of today.
Here in Missouri (as in the nation overall), we have an infrastructural lag. You can’t get online if you haven’t got decent Internet access. The digital gap in Missouri is associated with both income and region. In particular, only 63 percent of rural Missourians have access to broadband Internet compared to 82 percent of people in non-rural communities. Have a look at a recent report put out by MOBroadbandNow for details on this disparity.
What does digital inclusion mean with respect to school curriculum and learning?
Digital inclusion means that people might extend what they’re learning in school in their own ways. It means that communities can be made less vulnerable to the single-voiced message about their children delivered to them by a test-scoring company. It means that geographic or economic segregation will not necessarily determine and stratify intellectual achievement.
When it comes to Big Data in public education, those who can do; those who can’t are done to. Radically revising our current practices should make kids and teachers data drivers — not data driven.
Inda Schaenen is a teacher and writer in St. Louis.