Ep 62. Why more classroom technology is making students learn less
This transcript was created with speech-to-text software. It was reviewed before posting but may contain errors. Credit to Canadian Podcasting Productions.
In this episode, Anna is joined by Dr. Jared Cooney Horvath, a cognitive neuroscientist, educator, and bestselling author of The Digital Delusion. They examine what decades of research and international data reveal about classroom technology, screens, multitasking, attention, and memory, and why more technology often leads to less learning.
Jared explains how offloading knowledge to devices can undermine higher-order thinking, why human teachers’ expertise, and practice, remain central to learning, and when technology may help or hinder students. The conversation also tackles how schools and families can navigate an increasingly tech-saturated education system.
This is a thoughtful, evidence-informed episode for educators, parents, and anyone questioning whether digital tools in the classroom are helping students learn or holding them back.
This episode is also available in video at www.youtube.com/@chalktalk-stokke
Order The Digital Delusion here: https://www.lmeglobal.net/digital-delusion
TIMESTAMPS
[00:00:22] Introduction
[00:04:50] Cognitive decline among Gen Z
[00:09:14] The decline international test scores and the correlation with technology
[00:11:28] Screen usage in schools
[00:13:03] Relationship between EdTech and countries that invest less in it
[00:16:16] Effect size in education in the context of EdTech
[00:20:49] What forms of EdTech work?
[00:25:17] When EdTech is a better than nothing
[00:32:57] Practise and producers are essential to learning
[00:33:30] What is creativity?
[00:34:20] Why offloading learning to technology harms creativity
[00:38:50] AI: The Tool Nobody Asked For
[00:44:17] Difference between K-12 and university students using EdTech
[00:47:14] EdTech creates multi-tasking
[00:54:27] Advice: Responding to “digital devices are ubiquitous”
[00:55:50] Advice: Responding to “these students learn differently”
[01:00:32] General advice for parents and school leaders
[01:03:46] Laptops vs iPads vs notetaking by hand [01:06:48] Being a Luddite in the 21st century
[00:00:00] Anna Stokke: Welcome to Chalk & Talk, a podcast about education and math. I'm Anna Stokke, a math professor and your host. Welcome back to another episode of Chalk & Talk.
This episode is available in both audio and video. You'll find a link to my YouTube channel in the show notes and please do give the show a follow-on YouTube. Before we get started, I'd like to acknowledge new support through a grant from La Trobe University.
This support helps me to continue to share evidence informed conversations that connect research with practise and advance the goal of improving student learning, particularly in math. I've got an important episode today. My guest is Dr. Jared Cooney Horvath, a cognitive neuroscientist, educator and bestselling author.
His new book, The Digital Delusion, examines the impact of classroom technology on learning and raises serious questions about whether screens in schools may be harming learning. In this conversation, we examine what decades of research and international data tell us about screens, multitasking, attention and memory. Jared explains why more technology often leads to less learning, how offloading knowledge to technology undermines higher order thinking, and why human teachers' knowledge and practise remain central to learning at every age.
We also discuss when technology may be helpful and when it's not, and what this means for educators and parents navigating a tech saturated education system. This episode raises serious questions about what the widespread use of education technology may be doing to learning and what we can do about it. I found this conversation informative and thought provoking, and I hope you do too.
Now, on with the show. I'm delighted to be joined today by Dr. Jared Cooney Horvath. He is a cognitive neuroscientist, an educator and bestselling author of several books.
His latest book is called The Digital Delusion, How Classroom Technology Harms Our Kids' Learning and How to Help Them Thrive Again. And it was just released in December. He has a PhD in cognitive neuroscience from the University of Melbourne and has expertise in human learning and memory and brain stimulation.
He currently serves as an honorary researcher at the University of Melbourne and St. Vincent's Hospital in Melbourne. Jared works at the crossroads between the lab and the classroom, spending most of his time working directly with teachers and students or helping schools, organisations and companies improve learning and engagement. His research has been featured in popular publications, including The New York Times, Wired, BBC, The Economist and PBS's Nova.
And I'm really looking forward to talking to him today about his great new book. Welcome Jared. Welcome to the podcast. It's great to have you here.
[00:03:19] Jared Cooney Horvath: It's awesome to be here, Anna. Thank you so much for having me on.
[00:03:21] Anna Stokke: I was lucky to get an advanced copy of your book, and I read the whole thing cover to cover. And I want to say it's a great book. It's a fascinating read.
It's troubling, but it's fascinating. And I think it's an important read for any parent or educator. So, we're going to talk a lot about that today.
Let's set the scene. The screens are everywhere, including in schools. And your book specifically takes a critical look at the promises of edtech.
You start by arguing that we do have a problem, that there's evidence that edtech harms learning. You then explain why, drawing on your background in neuroscience, and then you give practical advice for what we can do about it. So, would you say that sort of summarises the roadmap in the book?
[00:04:06] Jared Cooney Horvath: That sounds perfectly right. I went with the data mechanisms applications angle to it, because data only says so much. Mechanisms gives you a good grounding, but then everyone says, cool, so what? I hopefully we answered some of those questions too.
[00:04:20] Anna Stokke: You open the book with this hard-hitting statement, our children are less cognitively capable than we were at their age. And you argue that Gen Z, that's the cohort between around 1997 and 2012. Is that right?
[00:04:37] Jared Cooney Horvath: Yeah, right around 2012 was when we flipped into Gen A.
[00:04:40] Anna Stokke: You argue that Gen Z is less healthy, less happy and less knowledgeable than previous generations.
And I have two children that are Gen Z, by the way.
[00:04:50] Jared Cooney Horvath: I'm not trying to make a bad argument.
This is average of all kids across that generation. So, there will be some who are flying and some who are absolutely sinking. But in the middle, by and large, we're seeing declines in basically every base of cognitive measure we would care about.
[00:05:05] Anna Stokke: Can you walk us through some of the evidence behind that claim?
[00:05:08] Jared Cooney Horvath: I think if you take a look, there was a book recently called The Anxious Generation, which I think most people read. That shows a lot of great statistics about the health and the happiness angle of the next generation. Kids are just far more lonely than we ever were.
And this is not their fault. This is the world that we've built around them. The food they eat is not good for them.
The sedentary lifestyle has not been good to them. I mean, you've got kids with eye and back problems before they hit teenage years. That ain't great.
I mean, granted, when we were watching TV, I'm sure some of us got scoliosis or eye problems sitting too close to the screen. But the sheer volume of that happening now is getting a little alarming. What I really then like to focus on was the cognitive aspect, because I think other researchers have really taken the health, the mental stuff.
I wanted to say, well, what about learning? One of the weirder things is if you take a look at cognitive measures across the 20th century, so I'm talking memory span, I'm talking attention span, I'm talking creative abilities, critical thinking, even general IQ, every generation has gained on their parents. Every generation is doing better cognitively than their parents. And that's great.
And we attribute a lot of that to school. Each generation spends more time in school. School cuts your cognitive teeth.
Congratulations, you're doing better than your parents. That's exactly what we want. Gen Z is the first gen to flip.
That was their the first generation in over 100 years to do worse than us in all of these measures. In fact, they're only doing better than us in one measure, really rapid visual processing, which if you've ever seen what kids do on a phone, that shouldn't be surprising. That's what they do.
They process visual scenes incredibly fast. Everything else, memory, attention on down, including IQ, they are now lower than us. And Gen A seems to be going lower as well.
And there's no reason to assume that it's biological. You can't see that big of a biological flip so quickly. And that generation is going to school more than any other generation was in the past.
Somehow in right around 2002, attending school and cognitive development decoupled. And we haven't seen that decoupling in a century. My goal was to figure out why.
What the heck caused that split there?
[00:07:11] Anna Stokke: Where is the data coming from? Are you going with PISA data or experimental studies or what kind of data are you looking at?
[00:07:20] Jared Cooney Horvath: All across the board. We'll use international testing data. So, PISA, TIMSS, PIRLS, all that international stuff you've got here, in the U.S. We have NEAP.
You can use that. But there's also since 1962 was the very first meta-analysis published on the use of digital technology in schools. Back then it was called ICT, informational computer technology.
We have actual research lab data and on the ground practise data for over six decades now. So, tap into as much of that as you possibly can. And what's good about some of the cognitive stuff, too, is you're also able to tap into pure psych data like IQ testing.
They don't really do that much in schools anymore, but we still do that in universities, in lab settings. So, you can also tap into there to kind of see what's going on cognitively with all these different people.
[00:08:07] Anna Stokke: I did look fairly closely at one point at the most recent PISA data because they do analyses on this kind of thing.
They ask students and they ask teachers how much time is spent on screens or phones and that sort of thing. I actually usually mention this to my students when I start at the beginning of the year. Even having a phone on the desk beside you or even someone that's beside you using a phone seems to be correlated with lower scores, right?
[00:08:37] Jared Cooney Horvath: It's the digital, penumbra or like a zone of influence.
Or if you're sitting close to somebody who's using digital tech, you will learn less than somebody who's sitting further away from that person. There is something about these tools that seem to, they have a radius and they're just going to do what they can to take away your attention and harm your learning.
[00:08:56] Anna Stokke: So, about the PISA scores and the TIMSS scores and the PIRL scores, there's actually been declines pretty much everywhere.
How sure are we that there's a link to technology? That's one of the contributing factors to the declines.
[00:09:14] Jared Cooney Horvath: You can see this brings us into a very interesting question is correlation and causation. There are some scientific fields where you can do randomised controlled trials, and you can absolutely do your best to link the two.
With that said, it's very rare that you're going to find pure causation anywhere. But in the social sciences, especially if we're talking about learning classrooms, schools, performance, it is all correlation. We will never be able to run randomised control.
It's just ethically, you can't do it. The only way to turn correlation into causation at the social level is basically through mechanism. If you can gather enough correlation over enough time, over enough parts of the world, and they're all showing the same thing, that gives you good stead to say, we think these are probably causative.
But then once you can explain, here is the mechanism by which it would be causative, that is about as far as social sciences can ever go. And that's when we put our stamp and say, we think we've got this solved. If we go back to say, like the PISA data back in 2012, that was the last time they did a pen and paper test.
That was the first time they also asked kids, how often are you on a computer for learning purposes at school? And that was when they first saw this big, massive decline in every single country. Kids who were not on a computer did best. Kids who were on it for an hour did a little worse.
Two hours, a little worse than that. Three hours. And it just was almost straight slope down.
2015, same exact data. 2018, same exact data. It all came back looking the same.
And now you can start to say, well, cool, it's just correlation again. But no, you remember. So that's over three testing years, over 90 countries, over millions of kids.
And the percentages will have changed each year. So, the percentage of kids who used a computer in 2012 for three hours a day versus the percentage of kids who used a computer for three hours a day in 2018 will have grown. But the ratio stayed the same.
So that was our good sign that this data is showing us. This is probably the variable that's changing things. The computer variable is the only one that's not changing year on year.
We better take a closer look at what's going on. Can we find a mechanism? And if you can, then you've got yourself a good argument.
[00:11:17] Anna Stokke: When you talk about screen use, you're not just talking about phones, right? You're talking about laptops, Chromebooks, iPads, any type of screen in school, right?
[00:11:28] Jared Cooney Horvath: This is desktop. Because go back the first year that they were asking this in 2012, 2015, we didn't even have tablets then. Those were pure desktops.
How often do you use a desktop computer at school? So, this is not just cell phones. This is anyone who's using a screen or digital tools for learning. To be fair, we should say recently that term has now come to mean any student facing internet connected device.
You can imagine there might be a digital piece of digital technology that allows surgeons to practise surgery, right? That way you don't have to cut open an actual person. You can practise on this machine. That is not an internet connected device.
That's a digital tool that would be in a completely different realm. So today when we say digital tools, we're going to say any screen that also allows you access to other programmes on the internet.
[00:12:12] Anna Stokke: Is it the access to the other programmes that's the issue?
[00:12:16] Jared Cooney Horvath: That is one of them. That is the intractable issues. That is going to be one of them.
[00:12:19] Anna Stokke: There's other things though, like just maybe looking at a screen all day, that sort of thing that's maybe contributing to some issues.
[00:12:27] Jared Cooney Horvath: So that's where you get to see. There are usage issues and one of them is going to be the attention thing due to distraction. But then there's also pure biological issues is does the tool itself correspond with how human beings have evolved to think, to learn, to interact? And in a lot of cases, no, the tool was never built to do those things.
It's not a usage issue. When people say it's just a tool, it's how you use it.
Mate, no, it ain't. Cigarette is just a tool. I'm pretty sure the tool itself can be dangerous too.
The tool itself has its own problems that will, we think so long as our biology is our biology, it will never be able to overcome.
[00:13:03] Anna Stokke: Back to just sort of this international data. So, are there countries that don't use tech in schools as much as others?
[00:13:13] Jared Cooney Horvath: Yes. So, there's interesting data showing that any country that invests less in ed tech improves more on every outcome. And it's a very tight correlation, something like 0.6. It's very good. So, basically the more your country invests in tech, the worse your kids are going to perform on these international tests, which is another correlation here.
And somebody asked me the other day, well, how do you explain countries like Singapore or Japan or South Korea? These countries that are always performing better than everyone else. And yet they embrace tech. If you go look at the scores, they are showing the exact same patterns as everyone else.
The kids who use tech more in those countries are doing worse. It's just, it turns out they're talking about tech. They're just not using it in school.
They're using it out of school more than in school. And I think another big thing to take home here, and this is an interesting one for your listeners. If you go and try and look this data up now, it will look as though our kids have been performing about the same every year.
You'll think to yourself, hmm, they may be dropping a point or two a year. What is this dude talking about? There's something very important that we do with these tests that no one talks about. It's called ‘renorming’.
Basically, what happens is every time we give the test, we reset the scores to make things look equivalent across years. Let's say a bunch of kids took it this year and they got 90 percent. A bunch of kids next year take the same test, and they only get 80 percent.
What we're going to do is we're going to give them a bonus 10 percent. We're going to call their 80, 90 to make it look the same as last year. That way we can compare year on year whether we should be or not.
When people look at these tests to say it doesn't look like it's changing all that much, that's because no one accounts for the ‘renorming’. When you go in and you do the data analysis, and some people have thankfully done this, when these tests moved online. So anytime a test moves digital, like the PISA in 2015 became an online test.
The TIMSS in 2018 became an online test. Scores drop significantly for everyone. As soon as you bring the testing from pen and paper to online, you can expect a 14 to 20 percent drop in every single person who takes it.
But they just eliminate that, so we don't notice it. And the next year they do lower and the next year. So, there are more drops than most people would assume just by looking at the pure data.
Once you do your digging, you realise there's a lot. It's only getting worse. The more we keep relying on tech to kind of do this and learn for it and perform it, everyone is just suffering from this one.
[00:15:38] Anna Stokke: And this is, we do have access to data over a lot of years, right? Like how long has EdTech been around? Like 60 years or something.
[00:15:47] Jared Cooney Horvath: ‘62 was the first meta-analysis.
[00:15:49] Anna Stokke: It always feels with technology that it's new. It just always feels like that.
But actually, we do have a lot of data. And you wrote about this meta-analysis of over 21,000 studies. There was a positive effect size, 0.29, right? That's actually not that much.
When you're thinking about meaningful impact in education, you want, like 0.4, positive effect size of at least 0.4.
[00:16:16] Jared Cooney Horvath: That's how the researchers will get you. Is a lot of people, as soon as you start talking about tech, they're like, well, here's a meta-analysis that says it has a positive effect size.
This study says, and for the listeners who don't know, an effect size basically is just if you run research on something. You can give it a number. Zero means your research had no impact.
Like, let's say I'm testing a drug. Everyone takes a drug. No one had any impact.
That's a zero-effect size. As soon as people start getting healthy from my drug, now I start getting a positive effect size. And the higher the positive effect, the better impact I'm having.
But you can also go negative. If I give you a drug and people start getting sicker, I can go into the negatives as well. So, it's just basically a measure of how much impact that I have.
So, people will always come out and say, look, you have a positive effect size of digital tech. That means it helps learning. The dirty little secret of educational research that no one ever talks about is everything works in education.
Human beings are wired to learn. If you change your socks, people will learn. If you lock a kid in a cage, they will learn.
So, John Hattie, he's a statistician. He recently meta-analysed over 350,000 effect sizes in education. Over 95% were positive.
And the only ones that were negative were very specific things that you would guess, like prolonged illness. Will harm learning. Divorce in the family will harm learning.
Those kind of things. But everything else is positive. In medicine, we can say positive, good, negative, bad, zero, neutral.
In education, you can't say that because everything is positive, which means everything works. So, we need a different baseline in education. Now, what baseline you choose, that's going to be different depending on who you talk to.
But what you'll see almost universally is it's going to sit between positive 0.4 and positive 0.5. You need to be sitting in that realm there if you want to say we're having a positive impact on education. Otherwise, you're doing worse than just status quo. If you even go with just the easiest one, let's say 0.4 is our new baseline, you see that tech has an effect size of positive 0.29. You're under the level you need to be at to say we're actually having a positive impact.
You would be better off doing nothing with tech and you would still see a 0.4 growth if you never touch those tools. So that's where we start to see that they can lie to you by saying we have a positive effect size. But if you know a little bit more about educational research, you can say, yeah, at what level? And now you can push back and say, I'm sorry, that's not good enough.
[00:18:35] Anna Stokke: I think that's good for listeners to know because there are a lot of people, of course, selling ed tech. So, we do have to be really careful. It always sounds really good and really shiny and lots of great fads.
But you have to be really careful about what people are telling you about effect size.
[00:18:53] Jared Cooney Horvath: I think, too, what you're going to find with ed tech vendors, they're going to pool effect sizes from K through 12 and university. They always get pooled together.
But we know learning at the university level is different than learning at K through 12, simply because once you hit college, you develop what are called self-regulated learning skills. You can do more on your own than kids before they enter the university system. If you look at there was a new meta-analysis published on ChatGPT in education, and it says we have a positive effect size of 0.68. Everyone use it.
Yay, 0.68. That's over my 0.4. That sounds awesome. Only five papers in that entire meta-analysis were done with K through 12 kids. The rest were done with university or adults.
When you only take out those five studies with K through 12 students, the impact of ChatGPT on learning was 0.16, way below the 0.4 we need. The next way they're going to try and trick you is they're going to pool data from your kids with university kids, where we know you're always going to get better impact of tech. And they're going to say, look, now use it across the board.
And it's like, no, you need to kind of divvy those out if you want to make sense of this.
[00:19:58] Anna Stokke: And I would also question like what kind of tech they're talking about. For example, I would think something like, Anki.
Have you heard of that one? It's like a flashcard app that does space practise. Basically, you can put your flashcards into it, the things that you want to test yourself on, and you can do retrieval practise, and it will do space practise or interleave practise, and it will adjust based on how well you're doing. And so, for a university student, that is actually a really useful tool.
But is it a useful tool for a grade four student? They're not mature enough to use something like that, right? I'd kind of question even, there are a lot of different types of ed tech. Some could be really helpful, and some aren't. Actually on that note, like what forms of ed tech actually do work?
[00:20:49] Jared Cooney Horvath: You'd see there are basically three levels where ed tech will work, but they're a lot less powerful than people assume.
So, one is exactly what you're talking about is what we're going to call intelligent tutoring. Some programme that gives you questions, immediate feedback, organises questions in a way that allows you basically to deal with recall, feedback, spacing, interleaving, that brings all those together. That's basically what you would call drill and kill, which everyone used to hate in school.
And if you're a teacher who does drill and kill, you're evil. But if you're an ed tech product that does drill and kill, we love it. And that actually works.
The only thing to remember about that is that type of training works really well at surface based learning. Now, surface based learning is key. You need that.
You can't go deep without it, but that's not where you want your learning to end. Surface is where you start your learning. Then you have to start taking it deep.
How do you conceptualise how you apply your knowledge? That's where that tool no longer has any impact. So, if you're still at the surface, if you're just learning something brand new time, time to lock those facts down, bam, that's one place where ed tech can be useful. The next is learning disorder remediation.
If you've got someone who's struggling with phonemic awareness, you can use tech to just drill them on phonemes. And you see why this works is because it's doing the same thing as intelligent tutoring. It's basically just let's get into drill and kill.
We need to lock some skills down so we can do stuff with them later. So again, if you're at the surface with learning disorders, still works. The third aspect that tends to work is what we call procedural training.
So basically, you have declarative learning, which is learning of facts, and you have procedural learning, which is learning how to do things. Learning the circulatory system, declarative. Learning how to cut open a heart to perform surgery, procedural.
If you have tools aligned directly to procedural training, it tends to work as well. So, like if you're an F1 driver and you can't shut down Monaco to practise your laps, use tech to drive that simulation. If you're a surgeon and you don't want to kill a patient, if you're a pilot learning how to land an aircraft, use a procedural simulation.
They work. Now, the trick to recognise about all these three things is one. They do not work as well as doing these things live and in person.
If you could land an aeroplane, you would learn more in an actual aeroplane than a simulator. If you could make your own flashcards and understand how to do interleaving and spacing yourself, that would be better than a tool. But a lot of people don't.
They're not as good as other methods. They just, you use them because we have them. The other thing to recognise is what's called the transfer issue.
The very first intelligent tutor, believe it or not, was created in 1926. That was the first time someone built a machine that basically asked questions, gave feedback, asked questions, gave feedback. It went nowhere.
The next guy to do it was Skinner in the forties. His went nowhere. Someone did it in the sixties.
Theirs went nowhere. We see versions of it in the eighties through the nineties. It didn't really take off till now.
And people keep wondering, why did it never take off in the past? All of those people will tell you, transfer issue. Go back to the very first machine. The guy stopped working the machine.
We have a letter from him that he wrote to B.F. Skinner where he says, kids did great when they were using my machine. But as soon as I ask him the same exact question in a different context off of the machine, they can no longer answer the question. So, it was like they couldn't move their skills from my programme off of the programme.
And we see that same thing now. If you train, do a lot of training on a programme, you also have to supplement that with offline training. Otherwise, you will be very good.
So long as you got your flashcards on your phone, you're doing fine. I ask you that question now on a test in a quiet room. You won't be able to answer it because you've tied it to the wrong context.
You've got to be very careful about the transfer issue when you're using these online training tools and practising getting it offline as much as you can.
[00:24:32] Anna Stokke: A couple of things there. The first thing is the human teacher is always better than the ed tech is what you're saying.
And I 100% believe that. I think maybe you're saying that there might be times that when supplementing might be OK.
[00:24:50] Jared Cooney Horvath: Yeah. If you're at home and you're studying and you don't have a teacher there to help you and you go to town.
[00:24:55] Anna Stokke: Here's an example. We have online homework at university.
Now, is online homework better than written homework that's going to be marked by a marker? Absolutely not. It'll always be better if it's marked by a marker. But if your budget doesn't allow you to do that, I think it's better that you use the online homework instead of no homework feedback at all.
[00:25:17] Jared Cooney Horvath: I always say my rule of thumb when it comes to tech is something is going to be better than nothing. If you don't have a choice, if it's tech or nothing, of course you use tech. Let's imagine there's a kid with a learning disability who literally cannot engage with learning unless they have tech.
I'm not an idiot. Bring in tech. If let's imagine there's some global pandemic and we shut schools down.
I know that'll never happen. Of course, we use tech. Something is going to be better than nothing.
But kind of, as you said, if you are lucky enough, if you're fortunate enough to have the choice between two somethings, always pick the something that aligns better with your goal. And if your goal is learning, that's something you pick will almost never be tech. Tech will never be, by other methods we have, if learning is your goal.
Because I think you made another good point there is I think what's a good term for it? Like administrative is a concern. It's like, look, it takes time to grade papers. It takes time to edit work.
So administrative work, that is an outcome that some people want, in which case, if that's your primary goal, use the tool that makes it easier for you. But again, if your ultimate goal is learning, then sometimes ease of administration might have to take a backseat to these harder tools, these more analogue tools, because it's going to help your goal of learning a little bit more.
[00:26:27] Anna Stokke: I'm going to ask one other situation. In math, there can be a wide range of students in the classroom. Making it difficult for the teacher to cater to every student's need. Let's say you have some students who are very advanced and they're always ahead of the class and these students could use extra challenge.
And two things kind of sometimes happen in that situation. One thing can be that sometimes, particularly in elementary, the teachers are not like they're generalists. They're not really trained in math.
And so, it can be hard for them. To come up with challenging problems for these students. And then the other thing is they'd have to work with those students somehow, and they're trying to help all the other kids.
If you have a programme that's set up pretty well and it's giving contest problems and things like that, and students can work through those instead of doing no math, that might be a good situation. Do you think?
[00:27:25] Jared Cooney Horvath: Look, there's no right or wrong to any of this is Neil Postman said something really cool back in the 80s. I think that guy was the best thinker.
I wish I could have met that guy. He said, I have no doubt that a good teacher can use tech to help kids learn in an incredible way. I also have no doubt that that same good teacher could use a pen and paper to help kids learn.
What you're talking about is good teaching versus time poor or less constructive teachers. In which case, yeah, look, you can't work if you're using it. Well, sure.
Will it work if you're using it poorly? Sure. Now you get to say, what is my context? Exactly. As you said, as look, if I know my 50 minutes for this class, I need to work with remediation with these three kids.
Do I leave these other 27 kids doing nothing? Of course not. Something is better than nothing. Then you might have to bring in tech.
That's where it's, it's just going to be a context by context thing. And I wouldn't argue, but I'd say go back to the nineties. If you were lucky enough to be in school in the nineties, congratulations, you caught the golden age of education.
That was right pre-tech. That was when we peaked on every measure of everything. So, we're doing, that was fun.
We were, had the same problems back then, but we didn't have tech to lean on. So, what were teachers doing back then? You get super creative when you start to realise, wait a second. Textbooks exist for a reason.
Those are still completely useful tools. Having outreach programmes, allowing schools to stream during certain classes. There are reasons why these things existed that might feel archaic today, but no man, they worked an absolute treat and they're working better than what we're trying to do now.
I'd say if we just look in the past, our ingenuity is more than we give ourselves credit for.
I always say, remember that the atom bomb was built without any computers. We built the aqueducts. We built the mechanical clock.
The amount of things humans were able to do without the help of computers. We've just basically stopped thinking. We even made it to the moon using the only computer they had for the moon landing.
It has less computing power than one of those singing birthday cards today. This is what we can do. And we say, hey, we're humans.
We got a problem. Let's solve it. And I think right now we're just, we're so used to saying, hey, we're humans.
We have a problem. Let's let the computer solve it. I was like, ah, how much better could we be if we just started relying on ourselves again? That's an interesting side story here.
Across the U S over the next year, you're going to see a couple of states are going to start enacting laws that allow opt out for parents. So, if you've got a kid in a K through 12 school and you do not want them on tech, you are allowed legally to opt them out of non-essential tech. If they have to take a test online, fine, whatever, but nothing else.
A couple of schools in Australia have already tried that. And what they found was if you have a percentage of kids who opt out, those teachers now basically have to do two things. They have to have analogue versions of everything and digital versions of everything.
And almost to a person, all of those teachers after a couple of months will stop doing the digital. And every kid now has to do the analogue because the teachers remember how much better it was when they were actually thinking, what do I need to actually ask you? What answer are you actually giving me? When you force them to do both analogue and digital, even the teachers were like, yeah, it's more work, but gosh, the kids are doing much better with it and they go to analogue. So, I have the same hope that might happen here.
We remember what we're capable of.
[00:30:37] Anna Stokke: You have to have everybody doing it.
[00:30:39] Jared Cooney Horvath: Yeah.
[00:30:40] Anna Stokke: And I'll tell you a story. We as parents were kind of the ones who were the last parents to let their kids get a phone. And we didn't want our kids on Instagram and the social media platforms and stuff like that.
And they were kind of annoyed at us at the time. And it's all fine. They were good kids.
But I asked them not too long ago, like they're grown up now, right? They're in university. Are you glad we didn't let you go on Instagram? And they said, no, absolutely not. I was surprised by that because I thought, you know, this will pay off later.
And maybe it did like in ways that they don't see. But their answer to it was, well, all our friends were on Instagram and we missed out on a lot because of it.
[00:31:25] Jared Cooney Horvath: I guess when you get up to the forties and fifties, I'd be lucky if I remember any of my friends from high school.
I think things change. Hopefully, as you get older and you start to remember it, there's more to high school than what happens in front of those lockers.
[00:31:37] Anna Stokke: You know what? They're pretty good at concentrating and focussing. So maybe it helped.
[00:31:41] Jared Cooney Horvath: They'll pay dividends in the end when they're around their first work space and they're looking around and other kids or other employees can barely string a sentence together and they're doing all right. I think they'll say, all right, that was a good idea.
[00:31:52] Anna Stokke: I want to talk about, so I don't sound like a tech apologist because I said some things positive about tech, because I'm not completely anti-tech like you. You call yourself pro-education and that's the same with me. I want to think about the situation and whether it's good in that situation or not.
But I want to talk about offloading because this is something that has been coming up in math forever. I can remember years ago teaching a class and a student was saying to me, yeah, but Conrad Wolfram says that you can just offload all these basic things to technology and then people can concentrate on creative problem solving. OK, I've heard this argument for years and now it's worse because AI can do almost anything.
The argument tends to be that in math, that students don't need to learn procedures. They don't need to learn facts like this ends up being a waste of time. And we can use that time by concentrating on creative problem solving.
What do you think about that?
[00:32:57] Jared Cooney Horvath: That sounds to me like an expert talking about novices in a way they absolutely shouldn't. We call it the expert blind spot. The better you get at any one thing, the harder it becomes for you to teach that thing because you forget the process it took to get there and you try and teach kids where you're at now versus where you were 20 years ago.
That's why training and pedagogy when teachers train in pedagogy, they become good teachers. When you make experts teachers, they're horrible teachers because you start to realise teaching is a craft in and of itself. But let's go back.
Let me just break down real fast for you. Creativity. What is creativity? Creativity, believe it or not, is nothing more nor less than problem solving.
It's you have a set of facts or knowledge in your mind. You have an unknown problem set over here. And creativity is nothing more nor less than the mixing of matching of your current knowledge sets to this unknown set to create what we call a new knowledge structure.
Easy way to think about it. I think about it like Tangrams. If you ever played that game, you have all these little shapes over here.
Then you have this little grey figure. You need to rearrange your shapes to match this figure. And when you do, you now have a new way of understanding how these shapes work.
By the way, I just want to make clear. I say nothing more nor less because there's nothing more. I mean, I've talked to all the creativity researchers in the world.
No one has gone beyond that with their definition. But I also say nothing less because I think problem solving is probably peak human. I think that's the best thing we do.
I put that at the pinnacle of what we can achieve. But one of the funniest things that most people don't know about this creativity, critical thinking, all these higher order skills, the vast majority of their impact come when you're not paying attention, using subconscious processes when you step away. So, let's say you're working on a creative problem.
Let's say you do it for two, three hours. You can't come up with a solution. You will leave.
You'll go for a walk. You'll go cook dinner. You'll go take a nap, take a shower, do whatever.
When you leave the problem, that's when your biology gets to work. Now what happens is completely devoid of any input from you. Your brain is going to start to say, well, look, you had that problem.
You were thinking about these facts. You missed all of these. Remember in 1990, you learn this.
Remember in 2012? What if that fits here? And your brain will get to work. An hour of your brain doing its own thing. Every once in a while, your brain's going to go, oh, I just found a match that you missed.
And you're going to have this moment we call insight where you're going to be cooking dinner and all of a sudden you're going to go, oh, shoot, I have an idea. Wait, someone give me a piece of paper. That's your biology doing its thing.
That's why you get your best, go to bed with a problem, wake up with solution. You do your best thinking when you stop thinking, basically. Now the problem is, is we call that diffuse thinking mode.
All that diffuse thinking is subconscious, which means that form of thinking can only use facts. Ideas, knowledge, information that you have embedded within your brain. Your brain cannot access the internet and look things up.
Your creativity will always be limited by your knowledge, by what you know, not what you can access, not what you can have a machine do, what you have embedded within your biological system. So, people think that that's pretty crazy.
If we give, and we did this, the PISA did this back in 2018, they test 90 plus countries on factual knowledge. What do you know about math? What do you know about English? Reading, writing, what do you know about science? Then they gave all those kids a creativity test and then they correlated the two. The correlation between factual knowledge and creativity was 0.92, almost perfect, which meant the more your kids know, the more creative they will be. So now go back to the issue of offloading.
If we use tools to stop learning stuff, to stop learning procedures, to stop learning facts, don't worry about facts, just look it up. You will kill the very thing you were hoping to free up time to do. There will be no creativity.
There will be a lot of copying, pasting, but once you enter in diffuse thinking mode, your brain goes, well, you don't know anything, so I got nothing to do. So go enjoy your walk. You're never going to come up with anything new.
So, all these higher order thinking skills are dependent, they emerge from lower order knowledge. And the more we use tools to offload that lower order knowledge, this is remember when I said Gen Z is worse than us and everything? Creativity, critical thinking included. Gen A is worse than them.
Because they're learning less, they are performing less on these higher order skills. So yeah, number one way to kill creativity is to make sure we use tools to offload learning. The worst way to do it.
[00:37:08] Anna Stokke: I need to carry you around on my shoulder.
[00:37:11] Jared Cooney Horvath: Anytime that argument comes up, we can say, oh, wait a second.
[00:37:14] Anna Stokke: You describe that so eloquently. It's just something I just know. I know that you can't be creative in math without knowing a lot of stuff, but you just describe it so well. So, I really appreciate that.
And I'm going to be sharing that clip all over the place.
[00:37:29] Jared Cooney Horvath: Here's an easy one that I always use. So, I'm doing a documentary right now on genius.
Where does it come from? Is it born? Is it made? I love it. But one of the stats that I just love, I keep coming across is you will never find anyone who reaches the level of eminence or genius who hasn't done a bucket load of practise drilling learning. So basically, the average is about 12 years.
We say from beginning of learning to win a master, a genius will produce their first work. And then another 12 years after that, until they start to produce their best work. So, anyone who's like, oh, some people are just more creative than others.
No, you go to anyone who's done any good work and say, how long did you spend training? They will say longer than you. You, no one has ever skipped that phase. And the people who actually embrace that phase of learning, it's hard to learn math.
There's a lot of drilling. There's a lot of practise, but the people who do it are the ones who are the most creative in mathematics. As they get older, you'll never find a genius mathematician, a Nobel prize winner who hasn't spent decades learning the basics first.
You cannot skip that step.
[00:38:33] Anna Stokke: Never. Absolutely. Thank you. So, a little more about AI. You have a great chapter on this.
It's titled AI, the tool nobody asked for, solving problems nobody had. What can you tell us about AI? Give us all your thoughts on AI.
[00:38:50] Jared Cooney Horvath: This tool has no reason to exist. I've had the incredible displeasure of speaking with a lot of people in the AI development field. No, not a single one of them can tell me what this tool was built for. There used to be a time, when if I created a tool, it had to solve a problem.
And not only did it have to solve a problem, it had to solve it well, better than anything else. And I had to prove it to you. I had to say, look, my new soap will clean that stain off your shirt.
My new fridge will keep your lettuce crisp. Trust me. And if it didn't do it, no one is going to buy it.
I failed. AI, especially large language models. These things come out.
Nobody knows what they're for. If you ask the developers, they said, we just wanted to see if we could do it. It was an experiment.
They released it to the public with the express understanding that you tell us what it's good for. We don't know what you're going to do with it. Show us what you're going to do with it.
Since when did we become product testers? And then the worst was they shoved it into schools immediately and said, not use this in this way for your kids to learn, but use it and tell us how kids are learning. If I invented a drug and I just said, “Hey, go give this to kids and let's see what happens.” No one would ever do that.
Yet. That's exactly what we did with ChatGPT and all these LLMs. And it is harming kids learning reparably in some cases, I worry.
It is not a learning tool. The most important thing to recognise about LLMs, AI, and this isn't even true to an extent, A, they don't exist for any reason, but B, if it can be said that they exist for any reason, it is for expert production. They are production tools.
If you are an expert and you already know how to do something, you just don't have the time to do it. You use AI to get that done for you. And the only reason it works is because as an expert, you can vet the output immediately.
So, you know, if it's bullshitting you or not. So, like I'm really good at stats, but it might take me two hours to do stats when I could use this machine to do stats in two minutes, do it. So, I do, and I can only do that effectively because as soon as it gives me an answer, I can say that number is totally wrong.
What? Or, Oh no, that looks correct. Let's go with that. This is not a learning tool.
When we mistake production for experts for learning with novices, we make a huge error. So, T this tool to kids, they will use it to offload thinking, offload ability, and they cannot vet the output. So, all they can do is copy and paste it and send it back to us.
And now at the end of the day, they will have learned nothing. So, this tool, if you can say it's used for anything, should only be used by experts who know enough to vet the output when they're just trying to do things they don't care about pure offloading. This is not a learning tool.
No kid ever need touch it. If you want kids to learn how to read, to learn how to write, to learn how to comprehend, to learn how to make arguments, this is not a tool designed for any of that. It is designed to make sure you don't have to do any of that.
No kid should ever touch it. We can have a debate whether or not teachers should use it, but I never heard a valid argument why a kid would ever need to touch AI. For those who are now thinking to themselves, well, how will my kids ever be prepared for a job in the future? Two things to remember about that.
One, we have data for decades that shows the more kids are trained on tech, the worse their technological literacy becomes. When you train, we make a mistake of thinking using a tool is the same as understanding how to use a tool. They're two very different things.
And when we train kids on tools, they can use them just fine. They use them more than anyone else, but they don't understand them any better. You'd be much rather off teaching, learning, thinking patterns, what we do in a traditional K through 12 education, and then bring the tool in and say, hey, by the way, you know, you can use this to help you with that.
Oh, there you go. That's why if you look, man, Gen Z has the same basic digital literacy as Gen X. So basically, some of our parents have the same digital literacy as our kids. Why? Because you don't need to be trained on these tools.
You need to train in how to think and then bring the tool in. So that's number one. Number two, I would always say is this is since the iPhone, digital technology has been literally developed to be used by kids.
Steve Jobs didn't even lie. He said, I wanted babies to be able to use this phone. That's how easy digital tools are now.
Are you telling me we really need to devote K through 12 education time to training kids on a tool like AI, which is nothing more than a box you type words into? No, it is the easiest thing in the world to use. I learned it overnight. Simple.