Over the last few weeks, there’s been a flurry of blog posts debating “personalized learning.”
- Benjamin Riley, “Don’t Personalize Learning”
- Dan Meyer, “Don’t Personalize Learning”
- Michael Feldstein, “‘Personalized Learning’ is Redundant”
- Mike Caulfield, “Why Personalized Learning Fails”
- Alex Hernandez, “Personalize Learning, Please”
- Dan Meyer, “Personalized Learning Software: Fun Like Choosing Your Own Ad Experience”
- Benjamin Riley, “The Ideology of Personalization”
- Alex Hernandez, “Personalized Learning: More Than a Feeling”
I can’t help but notice it’s all men weighing in here (and that another man, Dan Willingham, is being summoned to enter the discussion). Such is ed(tech) punditry, perhaps.
And, I have to say, perhaps that should be enough right there to give us some pause, to make us consider how much “personalization” may be something (in framing and in practice) that works in tandem with privilege and power. Who gets to define “personalization”? Who writes all these algorithms that will “personalize” our learning through technology. Who writes the curriculum? For whom is “personalization” defined (and by extension, for whom is “personalization” programmed)?
So when Riley asks “Is personalization a scientific theory or an ideology?” I’d argue it’s certainly the latter, whether you can marshall scientific evidence to support it or not.
I’m spending the summer working on my book, Teaching Machines – a cultural history of the drive to automate education; and it’s clear that this idea of using machines to enable students to “learn at their own pace” is hardly new. It predates the learning theorists that are invoked in these blog post, for starters. Indeed, it’s at the heart of ~100 years of educational technology.
A couple of nights ago, I tweeted some screenshots from Teaching Machines and Programmed Learning: A Source Book (1960). (Tweet, Tweet)
Technology and "learning at your own pace" - the 1960 version pic.twitter.com/z2rWoMIhMx— Audrey Watters (@audreywatters) June 30, 2014
Admittedly, I’m less interested in the “science” behind “personalization” today than I am in the long history of constructing devices (mechanical then, computerized now) for “personalized self-instruction.” The earliest (US) patent for education: “Mode of Teaching to Read,” 1809.
The history of public education in this country, particularly in the 20th century, is deeply intertwined with the development of teaching machines. (Despite the reluctance - then and now - to adopt technology in the classroom.)
Of course, “science” has been invoked all along the way to justify this and to demonstrate that these machines “work” (the science of intelligence testing, for example, or the science of behaviorism). But I don’t think of teaching machines as simply the application of scientific (learning) theories; they are the application of scientific management as well.
“Efficient.” “Labor saving.” Again and again, teaching machines are touted as tools to better manage production (of students).
From B.F. Skinner in “Teaching Machines” (1953): “Will machines replace teachers? On the contrary, they are capital equipment to be used by teachers to save time and labor. In assigning certain mechanizable functions to machines, the teacher emerges in his proper role as an indispensable human being. He may teach more students than heretofore—this is probably inevitable if the world-wide demand for education is to be satisfied—but he will do so in fewer hours and with fewer burdensome chores.”
It’s become quite commonplace to hear our current education system decried for its being a “factory model.” New technologies, particularly technologies that offer “personalization,” are positioned as the future, the way to “modernize” schools by letting students move at their own pace through the curriculum. And yet these are precisely the arguments that technicians have been making for teaching machines for almost a century. “The Coming Industrial Revolution in Education” predicted Sidney Pressey in 1932.
The "science" behind teaching machines (both the cognitive science and the computer science) might have changed over the course of the last few decades. But we still are faced with a powerful ideology that views students as objects to be manufactured by education - and thanks to "personalization" via teaching machines, at different and hopefully more efficient speeds.