From February, 2018
This is a remarkable thing-- someone has expressed clearly in a few paragraphs what I have tried to say over the course of multiple posts. The subject-- personalized [sic] learning-- is not remarkable, but the source -- Larry Berger, CEO of Amplify-- is. The following is excerpted from a note that Berger sent to Rick Hess (AEI) which Hess just posted in his EdWeek blog.
Until a few years ago, I was a great believer in what might be called the "engineering" model of personalized learning, which is still what most people mean by personalized learning. The model works as follows:
You start with a map of all the things that kids need to learn.
Then you measure the kids so that you can place each kid on the map in just the spot where they know everything behind them, and in front of them is what they should learn next.
Then you assemble a vast library of learning objects and ask an algorithm to sort through it to find the optimal learning object for each kid at that particular moment.
Then you make each kid use the learning object.
Then you measure the kids again. If they have learned what you wanted them to learn, you move them to the next place on the map. If they didn't learn it, you try something simpler.
...
Here's the problem: The map doesn't exist, the measurement is impossible, and we have, collectively, built only 5% of the library.
Yes.
Berger gets into the specifics of the problems with the map, the measurement and the library, and he further notes that even if all those parts worked, you'd still have to deal with what the live human child actually wanted to learn next.
This failed model for personalized learning grows out of a failed model of learning, the idea that there is a train that runs from Ignoranceville straight to downtown Smartland, and everyone needs to ride a train along those same tracks. In this model, "personalized" just means that we'll let people get on the train at different stations.
True personalized learning is a whole bunch of territory, and everyone sets their own destination and everyone starts from a different place and everyone has their own particular means of transportation. That's why you need a human teacher-- someone who functions as native guide who knows the whole territory, can find people where they are, and can help them navigate whatever sorts of challenges they face on their particular journey.
So why does the engineering model persist? Partly because of the flawed notion of what education is, but also because the engineering model can produce a good ROI at scale. You describe the ideal set-up of map, measure and library, and then, like a designer hawking a ready-to-wear knockoff of a Fashion Week hit, you sell folks the scaled down version. The engineering model may not be achievable, ever, but it is definitely marketable and, until folks catch on, profitable.
This is a great explanation - and explains much of what is wrong when many policymakers get intimately involved in prescriptive education policy. Any NP exec who wants to earn some cash from eager donors can take something like this, get business-minded funders excited, and distill it into just the sort of one-pager policymakers love - complete with soundbites and even some "early evidence" that it works. Does it help kids? Not really- does it make the NP exec money and get the politician re-elected? Yes - 1000 times yes.
This is an important post for all educators to read, especially those decision-makers whose inclination is to manage schools using business models while ignoring the human variables that impact learning.