The ed tech industry hopes to bring in more than $20 billion next year in sales of technology products for schools and students, and growing, but there’s a healthy share of education advocates and providers who think most of that will be a waste of money.
For the ed tech industry, which plays around a lot in the same circles as our schools but has ultimately very different goals, “personalized learning” means developing software that will pace the learning in a subject to match each individual child’s pace, as determined by formative assessments given throughout the learning process. In other words, we don’t advance kids to gravity until they’ve demonstrated a mastery of Newton’s laws of uniformly accelerated motion.
Education Week has produced an extensive report about the pros and cons of so-called “personalized learning” that takes a deep dive into the whole idea.
To begin with, the concept is still largely ill-defined. Plus, critics point out that personalized learning is not yet backed up by research and leans too heavily on technology to achieve its goals. Yet over the past five years, at least 15 states have taken legislative or regulatory steps to fuel personalized learning. A classic battle is emerging between an optimistic vision for innovation on one side, and skepticism about whether the changes will improve schools on the other.
My understanding of it is much more personal—I assume by now everybody knows what I mean by my conspicuous use of the adjective “so-called” to describe something—involving actual persons, not computers.
For me, “personalized learning” means, and has always meant, tailoring my lessons to meet children “where they are.” That’s kind of the same goal as software programs that ensure students understand one topic before moving the flowchart arrow to the next topic or that mine a student’s likes and follows to determine what context a lesson might be given in order to improve the chances that she’ll be engaged in the lesson. But it’s not exactly the same thing.
See, my way requires me to get to know my students, whereas the software approach to personalized learning requires data mining. And if anyone tried to data mine me, they might think I was a terrorist because of my searches. They might think I was a coal miner because of the Fox News stories I’ve read. They might think I was transgender or have a tendency to vote for politicians from all political stripes.
That’s because I read everything. I’m a journalist, and as such, I sign up for campaign emails from Donald Trump and Hillary Clinton. I follow both of them on Twitter, along with many other political figures of every conceivable stripe. And I wouldn’t live a day without reading Fox News, despite its bias.
The use of data mining could potentially lead to red herrings for students like me. If a seventh-grade girl is following the Cubs, for instance, it could be because she likes baseball or, more likely, because she thinks one of the players is cute. If all my data mining efforts reveal is that she follows the Cubs, I might erroneously assume she likes baseball and feed her lessons in the context of baseball, which will do nothing but turn her away if there’s no cute player involved.
That, I think, is the biggest flaw in so-called personalized learning for students where technology is concerned. As a teacher, I would know—probably from the sentence that seventh-grade girl says right after saying she likes the Cubs—that her interest isn’t in baseball but in cute sports stars. I’m not sure how I would “personalize” instruction given that finding, yet, but as a person, knowing that helps me get to know her a little better, and something might come up, some day in my class, that shows me a path to using that to help her learn something.
When Education Week rightly points out the abyss that stands in between the “optimistic vision for innovation” for technology-based personalized learning on one side and the reality in classrooms on the other, that’s what I think it’s talking about. How do you view personalized learning with technology?