“I’d become a teacher in large part because I wanted to spend time with young people’s writing, honouring it with close attention,” writes Peter C Baker in this piece for The Guardian. But what happens when writing—and even reading—without the help of AI becomes a foreign concept in the classroom? This topic is not new, but Baker’s passion for creating AI-free teaching is inspiring.
Emily’s students all had school-issued laptops, and her computer had a program that allowed her to surveil the content of every one of her students’ screens; they all appeared on the screen simultaneously, in a grid that recalled a bank of CCTV monitors. Using this program was always discomfiting – Big Brother, c’est moi – and always transfixing. Some students didn’t use AI at all, at least in class. Others turned to it every chance they got, feeding in whatever question they were working on almost as a reflex. At least one student was in the habit of putting every new subject into ChatGPT, having it generate notes that he could refer to if called on. Often, I saw students getting funnelled toward AI use even when they hadn’t necessarily been looking for it. I got used to watching a student Google a subject (“key themes in Romeo and Juliet”), read the AI-generated answer that now appears atop most Google search results, click “Dive deeper in AI mode” – and suddenly be chatting with Gemini, Google’s chatbot, which was always ready to advertise its own capabilities. “Should I elaborate on one or more of these themes? Should I draft a first paragraph for an essay on the subject?”
Picture a bizarre training exercise: A group of runners starts jogging around a circular track, with each runner maintaining a unique, constant pace. Will every runner end up “lonely,” or relatively far from everyone else, at least once, no matter their speeds? Mathematicians conjecture that the answer is yes. The “lonely runner” problem might seem simple and inconsequential, but it crops up…
Powerful generative AI tools are suddenly everywhere, embedded in many of the learning platforms students use daily. For students, they offer an irresistible shortcut: why write the essay, solve the complex math problem, or read the chapter when a chatbot can do it for you in seconds? Schools across the U.S. are scrambling to adapt. Blue books are back. So too are in-class exams and No. 2 pencils. Running student work through anti-AI checkers is standard practice. These are all pragmatic strategies by harried educators who, along with families, are on the front lines, mediating the next tidal wave of technological innovation for their students.
But these practical solutions miss a major underlying issue. The majority of American students are disengaged at school — a trend that began long before generative AI arrived. According to the U.S. census, only one in three students are highly engaged in school, a number that has been stubbornly consistent over the last decade. And while 65% of parents believetheir 10th graders love school, only 26% of students actually say they do.
AI didn’t create this crisis, but it raises the stakes considerably. AI chatbots promise to reduce the “friction” of learning by teaming up with the student 24/7. But this friction isn’t a flaw that needs to be engineered away, it’s the whole point. The effort of working something out, of sitting with a challenge and finding a way through, is an essential part of the learning process. It’s what keeps students engaged, and engagement is both a prerequisite for real learning and a predictor of outcomes that reach far beyond the classroom, including higher graduation rates and life aspirations, and lower rates of depression and substance use disorder. In a world saturated with AI, the capacity to learn — to cultivate genuine curiosity, push through difficulty, and develop independent thinking — is the essential human skill. And it’s one we can still help students build.
The good news is that student engagement isn’t a mystery, and parents and teachers have more influence over it than they realize. When students have the agency and freedom to follow their own curiosity, engagement follows naturally. The key is knowing how to help kids get there.
Academics agree that a combination of several elements shape student engagement:
What students do (e.g., showing up, turning in homework)
What students think (e.g., making connections between classroom learning and experiences out of school)
What students feel (e.g., showing interest in what they are learning and enjoying school)
Whether students take initiative (e.g., proactively finding ways to make learning more interesting, such as asking to write a paper on a topic they love versus the one that is assigned. This, in particular, is an essential skill in an AI-infused world.)
Because much of this is internal, it can be hard to see. So teachers and parents often rely on external behavior and outcomes as their gauges. But grades and attendance only tell part of the story — and they lead well-meaning parents to encourage compliance rather than real engagement.
That’s where a clearer framework helps. In our research for our recent book, The Disengaged Teen, we identified four distinct modes of student engagement and disengagement in school: Passenger, Achiever, Resister, and Explorer. These modes give teachers and parents language and a deeper understanding of where their students get stuck, and offer practical tools to help reignite their motivation.
In Passenger mode, students are coasting — doing the bare minimum. Parents of kids in Passenger mode often get a one-word response from their kids when they ask about school: “boring.” Students in Passenger mode may rush through homework and barely study for exams, yet some still get straight As. For these students, school can feel too easy, offering little challenge or excitement. Their coping strategy is to check out and focus on friends, gaming, sports — anything more interesting. For students stuck here, AI is an easy shortcut to finish homework faster and get back to hanging out.
Students in Achiever mode are trying to get a gold star on everything — academics, extracurriculars, service, you name it. They are driven and impressive but often exhausted. Fear of failure haunts these students, and many wilt when their performance dips even slightly. A common frustration among students in Achiever mode is, “My teacher didn’t tell me exactly what to do to get an A.” A B+ can trigger alarm, extra studying, late nights, and lost sleep. Achievers are focused on the end goal — the grade — not the learning process, and for many, cheating was already common before AI came along. Now, chatbots make it even easier to power through their pile of work.
Students in Resister mode use whatever influence they have to signal — to both teachers and families — that school isn’t working for them. Some actively avoid learning. Others disrupt their learning by derailing lessons and acting out, becoming the “problem child.” But they have something going for them that students in Passenger mode do not: agency. They aren’t taking their lot lying down, they are influencing the flow of instruction, though in a negative way. If given the chance, we found that those in Resister mode can move to Explorer mode — the final and most engaged mode — more quickly than students stuck in Passenger or Achiever mode.
The peak of the engagement mountain is Explorer mode, where students develop the willingness and desire to learn new things. Here students’ agency meets their drive. Their involvement runs deep and they find meaning in the effort required to learn. Explorer mode includes the active curiosity Jonathan Haidt calls “Discover Mode.” Students in Explorer mode feel confident enough to take creative risks, generate their own ideas, and solve problems in the classroom. When a student in Explorer mode is asked “How was school?,” their answer is not a monosyllabic “fine” but an excited breakdown of how tornados work or how they calculated Taylor Swift’s net worth using newly acquired math skills.
A key way to build engagement is to give students some autonomy in the classroom. Across 35 randomized controlled trials in the U.S. and 17 other countries over three decades, when teachers give students opportunities to engage by having a small say in the flow of instruction — such as choosing among homework options, providing feedback at the end of a lesson, or asking questions about their curiosities — learning, achievement, positive self-concept, prosocial behavior, and numerous other benefits increase. To develop initiative, which builds agency, kids need to practice it. For that they need to get into Explorer Mode.
In academic terms, this is agentic engagement — the ability and desire to initiate learning, express preferences, investigate interests, solve problems, and persist in the face of challenges. It is the foundation of a meaningful life and the life skills required to navigate an AI-saturated world.
The modes of engagement are dynamic: students move around them all the time based on their environments, their “efficacy” — i.e., how successful they think they can be — and their emotions. When students are given the freedom to explore, they often take it, and with it they can develop agency. Parents and educators also play a massive role influencing what mode kids show up in, often without knowing it.
Kia, one of the students we interviewed for our book, is a classic example of how agency can pull a student back from the disengagement brink. In elementary school, she was vibrant, reading incessantly and debating Percy Jackson plot points with her dad. But by middle school, she was bored, stifled, and completely checked out — stuck squarely in Passenger mode.
Worried about her profound disengagement, a creative teacher tried an unusual strategy: he invited her to join a learner advisory panel to tell the school board what it really felt like to sit at a desk all day. As Kia put it, her brain flipped from “This is useless, and I hate everything,” to “Hold on, maybe I have a say.”
A key way to build engagement is to give students some autonomy in the classroom.
At home, her father — who had gone straight to work after high school — refused to let her intellect become dormant. He treated her questions as worthy, whether she was asking why water towers are round or for a definition of “pedagogy.” He treated her like a thinker even when school made her feel like a failure.
When her school eventually introduced “studios,” where students design their own projects, Kia leaned into her love of storytelling, creating a podcast on mythology and an escape room about presidential assassinations. That agency rewired her, allowing her to fully enter Explorer mode. Even when she later landed in dry, lecture-heavy college classes, she still thrived. “I learned that you can learn anything. You just have to know how you work and how to teach yourself.”
This shift from compliance to choice, from helplessness to agency, supported by her dad and her teachers, took Kia from Passenger mode to Explorer mode and helped her rediscover the curiosity and drive she had in elementary school.
Our Brookings–Transcend study found thatfewer than 4% of students in middle and high school regularly had in-school experiences that supported Explorer mode.
The shift in student engagement during the transition from 5th to 6th grade — when most students in the U.S. enter middle school — is striking. More coasting, less achieving, more resisting, and less exploring all characterize the move from elementary to middle school.
Why does this happen? One key factor is lack of agency and a school system that, for most learners, undermines Explorer mode. At a moment of peak brain development, when young people seek meaning about themselves and the world, many are shuffled through classes like factory workers, pounded with content that feels standardized and irrelevant, and pressured to win a race they don’t want to run. Despite all the energy they expend, they increasingly feel like they have little say in how they spend their days.
Some have proposed that generative AI could unlock students’ motivations and interests. But recent global Brookings Institution research examining the benefits and risks of AI on student learning found that current use — especially open-ended discussion with AI chatbots and AI “friends”— undermines students’ cognitive development, motivation to learn, and, ultimately, engagement with the material.
The solution is not a better algorithm. It’s centering human connection, creativity, and student agency, which parents and teachers are uniquely positioned to do.
Six Actions to Get Kids into Explorer Mode
When kids are in Explorer mode they are motivated to learn, and motivation is crucial. “Biology doesn’t waste energy,” says Mary Helen Immordino Yang, a psychologist and neuroscientist at the University of Southern California. “We don’t think about things that don’t matter.” Students are motivated by having authentic opportunities to contribute and learn meaningful things.
Families and schools can work together here. When adults at home and educators in schoolwork collaboratively, kids’ outcomes routinely improve. Schools are ten times more likely to improve when this strong collaboration exists. Today, there are six actions families and schools can take to help our children have more Explorer moments.
1. Model the thrill of learning.
“Curiosity is contagious,” writes author Ian Leslie. “So is incuriosity.” It may sound simple, but one of the most powerful ways parents at home can support student engagement is by letting their kids see them having Explorer moments of their own.
John Hattie, a professor from the University of Melbourne, calls this being your child’s “first learner,” namely modeling the thrill of learning in everyday activities. This, much more than parents’ well-intentioned hovering around homework completion, helps students engage and do well in school. When Hattie examined the effects of parental involvement on student achievement across almost two thousand studies covering over two million students around the globe, he found “[w]hen parents see their role as surveillance, such as commanding that homework be completed, the effect size is negative.” In other words, parental nagging and controlling makes things worse, not better.
2. Know your child, know their mode.
Parents and educators will have more success getting their kids and students into Explorer mode if they truly know the child they have in front of them, and tailor their support accordingly. The modes are dynamic, and kids move between them, but when kids get stuck in one mode it can become an identity. The kid in Passenger-mode becomes the “lazy kid,” the kid in Achiever-mode the “smart kid,” the kid in Resister-mode the “problem kid.”
Kids don’t need a label, they each need a slightly different nudge to help move them into Explorer mode. The Engagement Toolkit in our book provides a host of practical strategies unique to each mode. For example, the kid who frequently procrastinates because they’re stuck in Passenger mode may need help developing study and planning skills. The student deep in Achiever mode may need help learning that failure is not the end of the world, something they can develop by taking small risks. Kids in Resister mode often need help developing a pathway out of the rut they are in — what Daphna Oyserman calls a vision of a “future possible self” — as well as a plan to get there.
3. Support ways for young people to make authentic contributions.
Adolescence is a period of profound opportunity as well as vulnerability. Teens ask important questions like “Who am I in the world? What matters to me? Do I matter? What kind of future can I build?” They need actual experiences to get data on the answers and build the muscles of being a respected contributor to a community. Cultural anthropologists call the process of gaining that status “earned prestige.” Too often young people default to social media to seek this status. Families and schools can both counteract that by giving kids opportunities for real-life contributions. When families rely on students to help get dinner made, bedrooms cleaned, the dog walked, or a meal delivered to an elderly neighbor, it helps young people know they matter for more than their latest test grade.
At school, when kids engage in experiential projects like “What happened in that abandoned factory?” or “Who lies beneath a headstone marked with only a single letter?” — as they did in Amenia, New York — they do work that matters in their communities. Connecting learning experiences to real life, from asking questions about how their local economy works to their community’s cultural norms, gives students opportunities to make meaning of their assignments while learning about themselves and their place in the world.
4. Never take away extracurriculars because of poor academic performance.
Too often, schools make participation in extracurricular activities contingent on good grades. A nationally representative survey found that nearly 60 percent of students earning all As participate in arts-related extracurriculars, compared to just over 30 percent of students with Cs and Ds. A similar divide exists in sports. The logic may seem sound — a child struggling with algebra doesn’t need more time on the basketball court. But this approach is misguided.
Struggling students need something to be excited about: a place to explore, connect, and shine. When students discover their “spark,” as the late youth advocate Peter Benson called it, that passion can sustain them through life’s ups and downs and boost engagement in school. If that spark is athletics or theater or music and that gets taken away because of academic performance, most kids in Passenger or Resister mode will not suddenly shift to Explorer mode so they can participate again — they’ll become even more disengaged. To foster more Explorer moments, schools should make extracurricular participation contingent on attendance and positive behavior — not grades.
5. Help students manage technology.
Another key is helping students escape the seductive power of tech distractions. Parents can set limits for children’s technology use at home, which can help ensure they are well rested enough to tap into their curiosity and creativity. They can advocate that their students’ school and community limit cell phone and social media use, as Jonathan Haidt recommends in The Anxious Generation. Parents can also check their own tech use at home. Children learn from what we do, more than what we say.
6. Hold a workshop or book group on the four modes of engagement.
You can’t fix what you can’t see. Only a third of 10th graders report having opportunities to develop their own ideas, compared to 69% of parents who think they do. A key aim of our book is to make the invisible — learning and engagement — visible, so we can develop strategies to improve it.
According to our research, teachers and parents want language and tools to talk about learning without creating friction. The four modes can unlock the conversations we need to have with our children and students. Parents can suggest this as a topic for a parents’ evening, a school discussion with educators, or a topic for back-to-school night. So, whether it’s a book club (we have a free study guide) or a webinar, workshop, keynote, or focus group, sparking dialogue about student engagement is a great first step to boosting it.
Conclusion
Despite its powerful role in learning, student engagement is rarely at the center of education discussions. Instead, grades and attendance dominate the conversation. Our hyper-focus on outcomes over inputs is a mistake. Instead of fixating on the leaves of the tree — test scores and grades — we need to tend to the roots, the invisible network of curiosity and motivation that will keep the tree growing.
In an increasingly AI-saturated world, Passenger mode is a seductive trap — a path where thinking is outsourced and agency atrophies. More than ever, we must prioritize student engagement and treat Explorer mode not as a nice-to-have, but as an essential life skill. That means giving kids the agency to follow their genuine curiosity, take creative risks, and find meaning in their own learning. Every student is capable of Explorer mode, we just have to help them get there.
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EdTechnical is currently announcing the winners of their forecasting competition, where entrants made predictions about five different questions in education. I was a judge for the “Teaching Profession” track which asked:
By the end of 2028, what percentage of non-interpersonal teacher activities (lesson planning, grading, and parent communication) will teachers routinely delegate to AI systems?
My own prediction here would have landed somewhere quite a bit south of 50%, mostly because I think the interpersonal and non-interpersonal tasks of teaching are pretty tough to disentangle. Wess Trabelsi won with a prediction of 65%. (Congrats, Wess. I liked your entry and described it to the other judges as “a wild ride.”)
Teachers who use AI weekly save 5.9 hours per week — the equivalent of six weeks per school year. Currently, about three in 10 teachers are using AI at least weekly, with more frequent users experiencing greater time savings.
I want to offer a few reasons why I suspect that finding is wrong. In fact, if it is anywhere close to right, if this technology (which I regard as “neat”) can effectively shave off six weeks of teaching work (which I regard as some of the most taxing that exists) then I have drastically misunderstood AI or teaching or both.
Here is why I’m skeptical of the finding.
People aren’t great at self-reporting the time they save with AI.
The Gallup data is entirely self-reported. Teachers were asked how often they used AI and how much time they saved on different teaching tasks. Meanwhile, the AI research firm METR went beyond self-reports with a similar study of software developers. They randomized a set of tasks between “AI allowed” and “AI disallowed” groups. They asked for self-reports of completion time, but they also measured actual completion time.
The AI-using engineers believed their tasks had taken them 20% less time than the non AI-using engineers when in reality it had cost them 19% more time. So I’m happy the AI-using teachers feel like AI has shaved off six weeks of their work, but the METR study should make us question self-reported data of this sort.
These sample sizes are quite small.
The most common response to the question, “How often do you use AI tools to do this teaching task?” was “never” for every teaching task surveyed. Only 4% of the 2,232 surveyed teachers described using AI weekly to “analyze patterns in students’ learning,” for example. That amounts to 90 teachers whose responses were averaged across other categories and then “multiplied by the number of contracted weeks per year (37.4, on average)” to get the time savings expressed as weeks. “Margins of error for subgroups are higher,” says the methods section, which I believe. Unfortunately, those margins were then multiplied by 37.4.
Okay also: saving time is not per se good!
Students seem to be saving tons of time these days using AI. Yet plenty of adults are more worried than excited about those savings, worried that students are saving time not doing work that they should do—not writing their early drafts of papers, not struggling to remember which solution method is most appropriate, not committing knowledge to memory.
We should worry similarly about teaching. Are we happy or sad that teachers are outsourcing their tasks to AI? Which tasks? It’s true that teachers can save time giving feedback on student writing by asking an AI to do it. If saving time were our only prerogative, we could save even more time by simply not assigning essays at all. Clearly, the more stuff AI can do, the more we need to wrestle with the question, “What stuff should AI do? Are there costs besides time that we should consider?”
Thanks for reading ! I write a new email about teaching, technology, and math on special Wednesdays. Throw your email in the box. 👇
The tricky part isn’t explaining [whether the answer is “6-n” or “n-6”]. It’s getting them to stop and think about it before they answer. This is also the case with whether the slope is positive or negative or whether (x+3) has a zero at 3 or -3. It’s always about getting them to stop and take a beat before they answer instead of just mentally flipping a coin. The hard part is reminding them that they have the knowledge already if they just take a second to stop and tap into it.
The scaling that has unrelentingly continued to extend its capability on ambiguous and long running cognitive tasks hits a brick wall against... teaching?
Just so I’m not misunderstood: yep, that’s exactly what I think. Humans have—to date!—needed other humans to help them do hard things they’d otherwise rather not do. So you can file teaching alongside therapists and gym trainers as professions where the impact of AI is going to be limited compared to the rest of the economy.
Upcoming Presentation
March 13. This month I’ll be giving a keynote address at California’s annual math conference in Bakersfield, CA. We’ll be talking about why and how we can restore creativity to math, a discipline frequently perceived as a creative wasteland.
Odds & Ends
¶ Congrats to Amplify’s math curriculum team for earning an all-green rating from EdReports for Amplify Desmos Math, a curriculum that is near and dear to my heart.
¶ You simply have to hand it to Pam Burdman sometimes. Perhaps you recall the thunderclouds above UC San Diego’s math results recently. The Wall Street Journal’s editorial board called it “A Math Horror Show” attributing increased enrollment in remedial math to “increased admissions of students from ‘under-resourced high schools.’” (UC San Diego made the same attribution.) But Pam used the Wayback machine and found another factor contributing to that increased enrollment, one which I haven’t seen reported anywhere else.
RH: What’s the one big thing a school or system leader should know when it comes to AI and schooling?
DM: The introduction of generative AI has not changed the fundamentals of your work: getting absentee students back to school; making sure kids feel supported and known; communicating results and challenges with parents; creating a positive working environment for teachers; and keeping kids safe. For all of its power in the world outside of schools, generative AI has not transformed the reality of any of those challenges and may, in the case of student mental health, exacerbate them. The work is still the work.
The fundamental problem of higher education is no longer the availability of content, but rather the availability of motivation.
Human contact, especially face to face, seems to have an unusual influence on what students choose to do, on the directions their careers take, and on their experience of college. It has leverage, producing positive results far beyond the effort put into it.
If human contact is a lever, we can think of technology as one kind of fulcrum. We see different results for kids depending on where we put that fulcrum and what kind of force we apply to the lever.
¶ Michael Pershan is correct: “most people do not want this.” Downthread he writes:
Most kids are not sitting around wishing that they could just hunker down with a tutor. They would rather be in class with their friends.
You can try to convince people to want something they do not want. You can yell into the wind. You can swim against the river. But the most prominent boosters of personalized learning do not seem to engage meaningfully with the nature of the wind or the river, with the reality that most people are not like them, that most people do not want this.
¶ Related: Ben Kornell ran an interesting webinar on the state of AI tutors. Notably, Khan Academy’s Kirsten DiCerbo said, “I will tell you, we see more ‘IDK IDK,’ more passive kinds of interaction than we would like.” That checks out. Andrea Pasinetti, CEO of Kira, offered a useful summary of the “micro-interactions that happen between students and tutors that can pull students out of the illusion of tutoring.”
Any latency. A question of two to three seconds delay between when a student asks a question and when a student gets a high-quality answer can cause distraction, it can cause a student to move on, it can cause a student to lose their own context in terms of what they’re learning and why they’re asking a particular question. An incorrect answer. A duplicative answer. An answer that maybe is not leveled properly in terms of reading level or concept difficulty or an answer that presumes knowledge that the student doesn’t have can all have a very negative impact on engagement and ultimately learning outcomes.
¶ I gave a talk at UC Davis last week and loved seeing the Better Call Saul-style advertisements for legal advice for (allegedbut let’s be real) AI plagiarists on the bulletin boards.
I was on the Teachers’ Aid podcast talking about mini whiteboards with some thoughtful folks. You can listen here.
I recently cut out student-facing technology from my teaching. Students do not use their Chromebooks at all in my class. I wrote about a bunch of the details a few weeks ago. Today I have a broader reflection on technology and teaching.
A Mental Model
Here’s a mental model implied by a lot of discourse I see about classroom technology.
The teacher makes decisions about what technology to use. The technology maybe helps students learn, maybe not, and maybe has some negative side effects on attention, etc. In this mental model, the focus is the arrow on the right. Education technology made all sorts of promises in the last ten years. Most haven’t panned out. Screens were supposed to help students learn but didn’t live up to that promise. I’ve written about some of that here, and also here.
In this model, the problems with technology are solvable. Maybe we need better education technology. Maybe we need to use it differently. That was my approach in my classroom before I went tech-free. We spent most of our time doing math with paper and pencil or whiteboard and marker. I used technology for a few specific purposes, and felt like I was getting some of the benefits without the drawbacks. I could fiddle with the technology I chose, gradually technology got better, and maybe eventually we’ll reach the promised land of tech-driven learning utopia.
Here’s a different mental model.
In this model, the technology has those same effects on students. But it also has an effect on the teacher. Technology isn’t neutral. When I have students pull out Chromebooks, technology changes my behavior.
When Technology Replaces Teaching
Never trust anything that can think for itself if you can’t see where it keeps its brain. - Arthur Weasley
Go talk to some regular students and regular parents about regular schools. You’ll often hear one theme: some of the teachers don’t teach.
Day after day, students show up to class, the teacher says, “open your Chromebooks and start lesson 3,” and the teacher watches the students work, or something along those lines.
Arthur Weasley warned us about this in Harry Potter and the Chamber of Secrets. He was talking about Ginny spilling all of her secrets to an enchanted diary, but it’s the same idea. When an object seems smart, humans tend to trust it to make decisions for us. We live in the era of “artificial intelligence.” We are constantly told that the singularity is near, that the computers are smart enough to take our jobs. So it makes perfect sense that teachers, when students open up those Chromebooks, kindof go on autopilot. The job shifts: rather than driving instruction, the teacher’s job is to assign the lesson through some software, and then to supervise the students and remind them to keep working.1
I think teachers stop teaching for a few different reasons. It’s in part a product of some vaguely progressive ideas that are in the water. Teachers should be a guide on the side, not a sage on the stage. Students should be doing the cognitive heavy lifting. With that mindset, it’s easy for the teacher to step back and let the computers do the work. This also happens because we can’t see where the computer or app or whatever keeps its brain, and we assume these things are smarter than they are.
And to be clear, there have always been some teachers who don’t teach. Before classroom technology it happened with packets.
My hypothesis is that classroom technology encourages this type of teaching (or, more accurately, not teaching). I’m not immune to this. I could feel the pull when I had students got out their Chromebooks. Teaching is tiring. I get students started, I go to my desk, and I watch little icons move through the lesson or percentages tick upward as students work. It seems like learning is happening. Maybe I feel like I need to monitor those dashboards, or make sure students are on the right website. There’s this gravity pulling me to stare at my screen as students stare at theirs. That gravity is powerful. That’s the biggest thing I learned from my tech-free experiment. I am not immune to the pull. Technology is my gateway drug to not teaching.
I surveyed my students after the tech-free experiment. One question was about how technology helps students learn. A student’s response:
Because it’s AI and it’s smart.
That type of thinking is everywhere right now. We assume technology is smart. We assume we should defer to the decision-making of the machines. I reject that. I am keeping technology out of my classroom in part for practical reasons: attention fragmentation, logistical headaches, and more. But I am also keeping technology out because of a moral conviction I’ve arrived at: technology is not a neutral tool. Technology changes teacher behavior. I want that out of my classroom as much as possible.
To Summarize
Here’s my summary of the education technology landscape right now:
There are already some interesting use cases for AI to reduce teacher workload. I’m sure more are coming. That’s cool! On the student side, there has never been a better time to be a self-motivated learner. If you want to learn something and you can manage your own time and effort, the current technological resources are fantastic. One reason we invented school is that not all young people are self-motivated. Many of those young people benefit from a regular routine, going somewhere with a consistent schedule and a bunch of peers of more or less the same age who learn the same things. In that context, classroom technology is at best a supplement to the human-to-human interaction that drives learning. In the classroom context, technology also affects teacher decisions and can convince teachers they don’t need to teach, or just make it easy to sit back and do a bit less. I’m writing this from personal experience — I’ve been that teacher!
Look, I read all the same headlines everyone else does. We’re on the cusp of a world-changing transformation driven by AI. Maybe! But edtech is not there. Call me when it happens. I will look at all the new technology that comes out. I’ll take it seriously. In the meantime, looking at what I have access to today, it’s not for me.
One practical note: reminding students to keep working is an unfortunate but inevitable side effect of using student-facing technology in the classroom. It’s much easier for students to “hide” behind a screen and look like they’re busy without doing much of anything, or to find any number of ways to distract themselves from doing the academic work in front of them. That means a lot of reminders, and a lot of teacher energy consumed with reminding students and not thinking about student learning.
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