I started this blog five years ago now. I can’t believe it’s been that long. It’s taken me from Chicago to San Francisco and back. But somewhere over this five years–over the course of this journey on which I’ve so appreciated you following me–I started to lose some of my inspiration.
It started somewhere towards the end of my fifth year teaching, which also was the end of my first year working for a personalized learning start-up and network of private schools in Silicon Valley.
I had gone into the school year with unrelenting energy, thrilled to be opening a brand new micro-school and to work on technology tools that were intended to personalize my students’ learning. The idea sounded exhilarating: I was set to work with real engineers on a technology platform for the classroom. It would allow me to send individualized “cards” to a child’s “playlist.” These cards would house activities tailored to each of my children so that they could, in theory, learn at their own pace and at their own level. It sounded like the greatest idea ever known to man.
But it wasn’t long before the challenges of this brand of personalized learning set in.
Not only were we a brand new school, encountering the issues that new independent schools generally do, but in addition to that, we were tasked with the never-before-done vision of individualizing every child’s education. The workload was immense and unsustainable, and even when I felt like I was doing what we set out to do–curate educational playlists of cards that were specifically chosen for them–I didn’t feel like it was entirely effective. It was isolating with every child working on something different; it was impersonal with kids learning basic math skills from Khan Academy; it was disembodied and disconnected, with a computer constantly being a mediator between my students and me.
It seems like a lot of new information is coming out now–information I wished I’d known a few years ago. When I began working in Silicon Valley, personalized learning was very new. No one really knew what it meant, and as a result, it led to us having unrealistic expectations for what we could really achieve in the classroom and what was actually best for kids.
Most recently, Diane Ravitch, research professor of education at NYU, wrote about 5 risks posed by the increasing misuse of technology in schools, one of which being the ongoing threat of personalized learning. Additionally, Syndey Johnson, assistant editor of EdSurge Higher Ed, wrote that personalized learning practices promoting hyper-individualized technology could actually have negative effects on student learning.
Interestingly enough, I noticed this within my first year, well before these resources were made available. I noticed that we didn’t have the data to back up our approach. I noticed that my results in the first year were no better than those of mine in public school, and in some cases, worse than my results in public school. And simultaneously, I noticed that I was more burnt out than I had ever been–and with half the class size I’d had the year before.
Risk-taking means failing, and I think that’s okay to a certain point. When I got to the end of the school year that first year, hardly recognizing myself or the classroom that I came to every day, I realized that I had failed. I did my best to be kind to myself, to acknowledge the risks I’d taken, and to communicate the fruitful learnings of failure to my superiors.
After all, we tell our children it’s okay to fail, despite how crushing it may feel sometimes. And failure in this context felt absolutely crushing to me.
I should have known better, I thought to myself.
With time, I forgave myself and tried to learn from my mistakes. I moved away from hyper-individualized learning. I implemented more class-wide practices, learned more about the workshop model, and tried to hone my assessment practices so that I could meet the needs of individual learners sustainably through small-group work and more systematized feedback.
And while I felt as though I had begun to learn my lesson, slowly navigating away from hyper-individualized, industrialized personalization and more towards a humanized classroom that focused on student-driven practices, formative feedback, and engaging, project-based learning, my company traipsed forward with ultimately the same sexy theory: that personalization meant hyper-individualization, and that big data and a playlist would provide that.
I look back now, and I wish I would have said more. I wish I would have been even more outspoken. But I know how outspoken I was. I know how much I said. I shared my experience and my feelings so much that my words became white noise: an inconvenient truth that my superiors did not want to hear.
It broke my heart, to be frank.
I was so inspired by the company at the outset, excited to be in a private organization that truly valued teachers as 21st century knowledge workers. But as every month passed, my naïvete became resoundingly self-evident. This company I had joined was just that–a company. And their primary concern was not the children’s education: their primary concern was monetizing the tools. Their primary stakeholders were the investors who’d invested a great deal of money in this–albeit interesting–idea.
I’ve been gone from San Francisco for over half a year now, and my time in Silicon Valley is becoming but a distant memory. And as a result, you might wonder why I’m writing about this now.
I’m writing about this now because it’s still important.
I started a new job this past fall in Chicago. Upon my arrival, I was almost immediately known as the “personalized learning” guy. People knew about my resumé, my associated work, my blog, and other places I’d published online. When I discovered this, fear coursed through my veins. I was worried that, yet again, the same expectations would be placed upon me–to build 21 individualized curricula for 21 individuals. Luckily, my team and my superiors shared my vision for personalized learning–a vision that is less a trending fad and more focused on student agency and engineering a learning environment where all learners are welcome and able to succeed. And with that alignment, I shared my experiences and my learnings around personalization with my families within the first weeks of school.
I share this now publicly because I want teachers around the country to know that the vision for personalized learning that Silicon Valley preaches does not work. We proved it time and time again. Hyper-individualization does precisely what the emerging body of research says it does and more: it isolates children, it breeds competition, it assumes that children can learn entirely on their own, and it dehumanizes the learning environment, reducing the human experience of learning down to a mechanistic process, one where children become the objects of learning as opposed to the subjects of their own educational narrative.
Moreover, I share this now because I don’t want to see this pressure put on teachers–well-intentioned, hard-working teachers who already have trouble meeting the needs of the children in their classrooms. It breaks my heart to see this pressure being put on teachers, and it breaks my heart even more to know that I was once a part of the proliferation of this brand of personalized learning.
But I now can share what I wish I would have known some three-and-a-half years ago.
We must walk away from this hyper-individualized brand of personalized learning. We must walk away from its reductionism, assuming that education is simply an arrangement of individualized playlist cards or isolated experiences. We must run from the idea that technology is necessary to make the classroom a more personal and humanized place, because what personalizes the classroom is not fancy technology and big data: truly knowing children is what personalizes and humanizes a modern classroom.
Within the last year of my time in Silicon Valley, I spoke with an engineer about an idea he had. He fantasized about the notion that artificial intelligence (AI) technology could, in fact, play a role in personalized learning in the near future. I pushed back immediately, knowing full well the engineer would assure me that AI could very well do some of the jobs that teachers do now. And surely he did. He told me that, some day, the “future Paul France” would look back and see that AI could, in fact, do some of the jobs I do now.
I believe him. I’ve seen what’s possible in Silicon Valley, and I don’t doubt the ventures to which ambitious humans set their minds. That said, I’d never want a computer to do what I do. What I do requires curiosity, compassion, and heart. What I do requires a yearning to contribute to something greater than myself.
I’m sure that an engineer well-versed in AI would tell you that this–curiosity, compassion, heart–that it’s all theoretically possible. And I’m sure it is. But technologists know that good technology is only built to fulfill needs that didn’t previously have solutions. Curiosity, compassion, and a love for learning are needs that are already accounted for.
They are accounted for by teachers–not computers.