Can a simple marshmallow test predict how children will perform on their SATs and across health, finance and well-being later on in life? Is delayed gratification the key to future success? Find out in my latest interview with Dr. Tyler Watts, an Assistant Professor of Research and a Postdoctoral Scholar at NYU. Listen now.
Read the Transcript
Tyler: Sure. I got my PhD in education from the University of California at Irvine (right by you), and I am now at NYU. I’m what’s called a research assistant professor, which basically means that I’m here to do research work. One of the first things that I worked on was this study that you just mentioned, and it’s kind of in line with the rest of the research work that I do. I’m really interested in what happens early on in life and how early life experiences shape the kind of people that we become. That’s kind of a fundamental question to economics, and it’s a fundamental question to developmental psychology; my work is really right in the middle of that, and I’m really interested in what kinds of programs and what kinds of interventions we should be investing in if we want to alter – in particular – disadvantaged kids’ lives in a way that’s going to lead to a lot of return on investment. So that’s the way that I came to the marshmallow test work, and that sort of broadly describes the other stuff that I’m interested in.
Robert: Thank you so much for that. And sometimes, what I like to do is something that I’ve done with my young daughter for many, many years. I find it’s a great way to get to know somebody a little bit better. I call it one-on-one, where I ask: what’s one thing that you’re grateful for that you’ve experienced over the last week or so, and then also, what’s one thing that you’re looking forward to?
Tyler: Sure. Well, this is a lame answer, but I mentioned this when we just got on the phone. I’m grateful for the weather that we’re having in New York City right now, because I know that winter is coming and I’m trying to soak it in. I wish I could jar it up and save it for when I really need it, in the dark days of January. And then, what was the other question?
Robert: What’s one thing that you’re looking forward to?
Tyler: You know, I’m traveling to Phoenix later this week, and I’m actually really looking forward to getting some Mexican food.
Robert: Before I started recording, we talked about how you are a graduate of UC Irvine, which is right near me. And of course, Irvine is in Southern California, and Southern California is known for its beautiful weather and its wonderful Mexican food. So, are you saying that you can’t find decent Mexican food in New York City?
Tyler: You know, it’s not that it’s not here, but it’s not everywhere the way that it is in California. It’s a little bit harder to find. Just about every other kind of food here I feel like can hang with California – and some of it’s even better. But yeah, that’s the one thing that I feel like we’re sort of behind in. And actually before California I was in Texas. So it’s really something that good Mexican food, it’s like deep, deep in my soul. It’s something that I really miss.
Robert: Wonderful. Well not only Mexican food, but potentially marshmallows. So basically I came across an article recently that talked about this marshmallow study, and when I think about my education in psychology, there are a handful of these really significant, memorable psychological studies. For example, there’s the Zimbardo prison experiment on perceived power; that one is just sort of etched in my mind. There’s Milgram’s experiment on obedience. There’s the Bandura study on the Bobo dolls, which is all about modeling. And then there’s this one, the marshmallow experiment. I have a feeling we all have an idea about what it’s about and what the takeaway is, but can you tell us a little bit about the original study and what they concluded?
Tyler: Yeah. This work was done by Walter Mischel, who actually spent a large part of his career at Stanford, and then he later moved to Columbia (up the street from where I am now). Mischel was interested in personality. I think one of his big contributions to the field of psychology ultimately ended up being his view that personality was less trait-like than people thought at the time. So that means that contextual factors and change over time (plasticity) were things that people hadn’t really appreciated, and they thought that you’re born with this personality or it’s determined very early in life and then it’s sort of fixed. And Mischel was interested in the limits of that, and he did a lot of work to undo that notion.
In the press and pop psychology, I would say his most famous work is the marshmallow test. What he was doing at Stanford was looking at very young children. He was recruiting them from the Bing Nursery School at Stanford (which is the preschool for people that work at Stanford), and he was interested in trying to figure out how to measure delay of gratification in really young kids. And he devised this thing called the marshmallow test, which is really just a way to measure a young child’s ability to wait in the presence of something tempting or something distracting.
I would encourage anyone who isn’t familiar with the marshmallow test to look it up on YouTube; there are tons of really entertaining and interesting videos of kids doing it. You basically have an examiner in a one-on-one situation with a kid, and the examiner places a treat – which famously we think of it as a marshmallow – in front of a kid, and then they make sure that the kid likes it, and they make sure that the kid would like to have more of it rather than less of it. Then they tell them, “I’m going to leave you here with the treat, and I’m going to leave the room for some period of time. If you can wait to eat it until I come back, then I’ll double the amount that I’m going to give you, so I’ll give you two marshmallows instead of one.” So then the examiner leaves the room, and that’s really where the rubber hits the road with the measure.
Mischel was really interested in both observing how kids handled the situation and observing how they behaved as time went on; some of them would just immediately eat the marshmallow, while some of them would disintegrate into tears immediately. Then you would see these other kids who would find really interesting and productive ways to get through the 10 minutes or 15 minutes or 20 minutes – however long he was going to leave them there at that particular time. Then he would record the amount of time that they had waited, or if they’d made it to the end of the task, they were given the maximum amount of time.
So, that was the original marshmallow test work. He published a number of studies recording what kids did during the task, and then he would do little things to change up the task along the way to figure out and probe the limits of kids’ ability to do that. So he would do things like suggest strategies for the kids. Like, if he gave kids the idea that they could turn around in their chair and not look at the marshmallow or sing a song to distract themselves, would that help them wait longer? So he was interested in those kinds of questions at first.
Robert: And so that was the structure of the test. That’s how it was done, almost like looking at coping skills. You know, how can I resist eating this so I can get more later? And what were the findings?
Tyler: Yeah. So I may be wrong in this, but my read on his original work from the late sixties and early seventies (almost 50 years ago) was that the initial finding was that there’s variation in kids’ ability to do this, which means that I’ve probably come up with an interesting measure, and I’ve found something where there are individual differences.
In psychology you’re always interested about finding variation in people, and it can be very difficult. This is still a problem in psychology today: to measure things that you think describe differences between people. So you can imagine, when he was trying to come up with a way to measure delay of gratification, the marshmallow test was a really big innovation, because you can’t just ask a kid at four years old, “Are you able to delay gratification – especially in tempting situations?” That’s not going to produce anything for you. So that was the first finding. Then, he wrote a lot about the contextual factors that drove kids’ ability to wait longer.
And then, I think a number of years later (I don’t know if this was originally his intention or if it’s something that he decided to do a few years after he was done giving the test) he decided to follow up with the kids who originally participated in the studies. He was able to contact the parents of a number of kids who originally participated. Of course, it was a smaller group; only some fraction of them were able to be contacted successfully. And he asked the mothers of the kids to report how their now teenagers or young adults were doing in life. And he found through correlational methods that kids who had waited longer at age four were much more successful across a bunch of different measures as young adults or as teenagers. They had higher SAT scores – that was the big finding. They were also rated by their parents as being more disciplined and having more self-control later on in life. And that’s when I think the findings from this study really started to take off, because then people’s interest was really peaked. Like, what is this thing, delayed gratification? And is it something that’s really important to do early in life? And those studies were published in the early nineties, and then I think interest in the marshmallow test snowballed from there.
Robert: Yeah, I think you’re right. Prior to that, the experiment was ingenious; it talked about how to cope, and that there are different ways one can cope, and how some are more successful than others. But I think you’re right. I think what really made the marshmallow test famous was this idea that we went back, and we looked at some of these kids, and those that were able to delay their gratification (those who didn’t eat that marshmallow) were somehow much better off on a number of different scales, like the SATs. I know that some of them were on average in better shape fitness-wise, health-wise and just across a broad spectrum. Those who were able to delay gratification seemed to do better. It’s an amazing finding. It makes sense, you know. Well, if you’re able to delay gratification, if you’re able to say, “No, I’m not going to reach for that seventh slice of pizza,” then you’re probably going to be fitter. Or if you can go back to school or work late – all of these things are about future planning. It’s about goal setting and not wanting something right now, but instead waiting and getting something better in the future. These all seem like important findings, and they make sense.
So what got you to the point of looking at this study? Why did you want to replicate it? Did you look at something and go, “This just doesn’t make sense.” Was there research that was done after this that somewhat contradicted it? Or what was your motivation?
Tyler: That’s a good question, because it definitely has this kind of common sense element to it (like you said), and I think that probably contributed to how popular it’s become and how popular it remains. There’s also something to it that’s very American, right? It’s in line with pulling yourself up by your bootstraps a little bit, right? Like, if you can just delay gratification and really set yourself to a task, get to work and then play later, you’ll be better off. And I think it makes sense, and we all know that that has to be true to some degree. Like I said earlier, what I’m really interested in are our early interventions. And there’s this large world right now that’s out there (that I think people are also somewhat familiar with) around early childhood programs and early childhood care. A lot of states and cities are investing in Pre-K, and the question is if you’re going to develop a program to help kids’ chances early in life, then what are you going to do with that program? What are you going to teach kids when you have them in preschool?
I actually did a lot of my work in graduate school – and I still do work on this problem today – around early math development. So that seems really different than the marshmallow test, but the problem was actually really similar. We had correlational studies that were showing us that kids who were really good at math when they started school tended to be really successful students and then successful adults later in life. So it’s a very similar kind of problem.
When kids start kindergarten, there some kids who can add and subtract a little bit; they’re very good counters, and they have some basic mathematical skills. On the other hand, there are kids who start school and barely know any numbers at all; they don’t have any math skills to speak of when they start kindergarten. That tends to breakout along socioeconomic lines, so kids who are from more privileged families tend to start school much better at math and reading. Based on those findings, the conventional thinking was that if we developed an intervention that provided high-quality, early math curriculum to lower income kids, then when they started kindergarten, they’d have the same math skills as a middle- or higher-income, more advantaged kid. Then, our longitudinal findings, our correlational work suggests that they should be able to keep up in school, right? Because how good you are at math at the beginning of kindergarten is highly predictive of how well you’re going to do in school later on. So if we provide them with those skills when they start kindergarten, then they should be in good shape going forward.
What we started to figure out based on evidence from interventions where we did this, was that the benefit didn’t last. When we looked at preschool programs that did a great job teaching low income or disadvantaged kids math, the effect didn’t last later on in their education. Although they were caught up at the beginning of kindergarten, by the end of kindergarten, first grade, second grade, and so on, they started to fall behind again. You sometimes hear this called “fade out,” which basically means that the benefits of the intervention go away.
In the meantime, I had become interested in the marshmallow test story, because it was actually very similar. When I started to look into the work that had led to the conclusion that early delay of gratification ability was uniquely important for a kid’s later life outcomes, I found that that correlational work was even less statistically rigorous than the work that we had found was really problematic for math achievement. That’s what led me to say, “We need to take a closer look at this.” You can find pop psychology books, charter schools, TED Talks – all sorts of different places where people were saying the ability to delay gratification early in life is really important, and we need to find ways to help kids do that. When I hear that way of talking, I start to think, “Okay, they’re setting out a causal expectation that if we have an intervention that teaches kids how to delay gratification early on, then we expect to see benefits of that throughout their life.” Does that make sense?
Robert: Yes, that’s a fascinating way that you came to that. And I have to be honest. I have a 13-year-old daughter, and I recall when she was either five or six years old, I did the marshmallow experiment with her because again, I love psychology. I love these tests. I did a lot of the psychological tests on her. No, I did not shock her at any point, just so you know, but the marshmallow test was something that I did, and I was so proud when she delayed and didn’t want that marshmallow, and I thought, Yes, she’s going to succeed in life! And then of course, I read your findings and I’d say, Oh darn it, maybe not. And so, I think the way you approach this is very interesting.
Before we started recording, I was talking to you about how I’m starting my dissertation, and coming up with an idea and coming up with a new way of looking at data is very, very difficult. And the way you approached it was quite smart, because the math study that you did was very similar – and yet the results were quite different. I guess that’s part of the shortcoming with a correlational study: there is no causation that you can study. So when you did the marshmallow test again, what did you find?
Tyler: There was this other dataset out there that I had used for other purposes in the past. A lot of people don’t realize that social science research works this way. There are a number of really large datasets where there’s a large sample of people who have been followed over time. These longitudinal data collection efforts are ongoing today. I’ve never known anyone who has participated in them, but you actually may know someone because there are a number of them out there. Basically what they do is they take a sample of kids and they start to collect measures on them at some early point in life, and then they follow them throughout their lives and depending upon the focus of the study, they’ll check back in and collect information on if they graduated high school, if they were employed in adulthood, what their earnings were, if they’re married, health outcomes, etc. – all sorts of stuff like that.
We had access to a really interesting dataset that was collected in the nineties. They sampled about 1500 kids at birth, and this study was run by psychologists, so they were collecting a bunch of really intensive psychological measures on these kids throughout their lives. When this study started, the longitudinal work from Walter Mischel was just coming online. So when the kids turned four years old, somebody had the idea (which I’m sure was well-received among the group of principle investigators) to do the marshmallow test with the kids.
At that time they had contact with about 1100 of the kids, and they gave them the marshmallow test. Then they continued following up with the kids, and we had a full set of data on these kids at age 15. So we had really early life data (because they started the collection at birth), we had a record of how long each kid waited for the marshmallow test at age four, and we had data on high school achievement and later behavioral outcomes – things like risk taking in adolescence. So in adolescence, risk taking is like sexual risk taking, drinking, smoking and things like that. We were able to set up the same sort of thing that Walter Mischel did and just say, “Okay, do we see a correlation between how long the kids waited at age four on the marshmallow test and their later outcomes, adjusting for nothing?” Just a simple correlation, right? And sure enough, we saw that at least in the case of later achievement, we saw that kids who waited longer were predicted to have higher test scores in adolescence. Interestingly we didn’t find much of a correlation between how long they waited and later behavioral outcomes – which we were really surprised by – and that’s not adjusting for anything. We just found that there wasn’t much of a relationship between the marshmallow test at age four and behavioral outcomes in adolescents. We can come back to that in a second.
The next thing – and this was really the innovation for us – is really a pretty simple thing in statistical and (especially) longitudinal work today. Next, we introduced statistical controls. What these basically do is say, “Okay, what if I take two kids who have the same socioeconomic status?” I can identify in the data information on parental income. So I can say, “Basically, let’s now take two kids who have the same parental income and see if differences in their marshmallow test performance still predict later achievement or later behavior.” And then on top of that, I can adjust for race and gender and other early stuff in a kid’s life, like birth weight. I had a really early measurement of temperament, where the mother rates if the baby was fussy or kind of quiet. I also had an early measure of IQ taken at 24 months. So if we’re able to adjust all of that and hold constant all of those factors and then see if the marshmallow test has a predictive validity on top of it, then we’re able to get more at the question, is there a causal relationship between being able to wait on the marshmallow test or having delayed gratification ability and later outcomes? And that’s where we found that most of the predictive relationship really dried up.
So in the case of achievement, there was still a statistically significant effect, but it was much smaller. And then we added even more controls and we said, “Okay, what if we control for other stuff measured about the kid at age four? So what if we control for how good they are at math at age four or their reading ability at age four? Then do we see prediction later on?” And then at that point, it was pretty much zero. So the interpretation of that is a little bit nuanced. But the main idea is that if you were to develop a program that taught kids how to delay gratification, but you didn’t change this other stuff in their life, then you’re probably not going to have a very big long-term effect of that program based on just changing the gratification delay control.
Robert: Yeah, I think this idea of controls can be lost on people; they don’t understand exactly what it means. And I think your explanation was a good one: you have achievement in adolescents, and there might be a thousand different reasons why one child has higher achievement than another. And so the idea of using a control (or many controls) is that you’re trying to check off those thousand different items and get to the one that’s really the main factor that’s driving this achievement. And it sounds like in the initial marshmallow experiment, there weren’t really any controls; it was simply, did they delay gratification or did they not? And we’ll just look at them in the future and see how they did. Yet, in your pre-education work, you found that those who got the math early on to try to get them up to speed, they did get up to speed, so they were on this level playing field, but then life got in the way, right? There were other factors that were at play here that caused that fading to occur. And so with your version of the marshmallow experiment, you controlled for all these different factors. And after you did that you discovered that there’s really no difference between those who delayed and those who didn’t. But what do you think that tells you then, that there are these other factors, and these other factors are really what’s driving that difference of achievement?
Tyler: Yeah, I think that’s exactly what it tells you. And again, there’s kind of a common sense element to this, which is that kids who have a lot markers of advantage early in life tend to have a lot of markers of advantage later in life, right? And what we see in longitudinal studies is that there’s a lot of stability in kids’ achievement trajectories over time, and there’s a lot of stability in socioeconomic status, right? That’s not to say that there isn’t important variability, and that we shouldn’t study that, and we shouldn’t try to understand that, and we shouldn’t try to develop programs that promote mobility, right? I think that’s all obvious and that’s all important. But you have to be careful that you’re not interpreting stability for something else, and I think that’s really what the work on math achievement suggested, and that’s what the work here suggests too. So it’s the case that kids early in life who have a lot of markers of advantage, including better socioeconomic status and being more apt cognitively, they also tend to be good at the marshmallow test; those kids also tend to be high achieving and better rated on measures of behavior later on in life. And if you only look at the marshmallow test and those later outcomes, then you’re going to be drawn to the interpretation that it’s the marshmallow test that’s producing the later success, right? And until you take those other factors into account, you can think that if we can just improve kids’ delay of gratification ability early on, then we’re going to get more success later in life. And what these other kind of statistical controls will do is they bring you back down to earth and say, Actually, it’s really a lot of these other factors that are the dominant forces driving success later in life. And if we don’t really address these other factors, than just addressing the ability to delay gratification is probably not going to be enough.
Robert: On one hand, there’s something American about the original experiment, because delaying gratification is entirely in someone’s control. That’s something that they can choose to do or not choose to do it. It doesn’t really matter what your parents are like, how much money they have, their education – even your own education. It’s this willpower – this grit – that if I can just hunker down and work hard and focus on this better future, then I’m going to achieve more. Yet, the finding is, well, not really. There’s all these other external factors that you just don’t have very much control over, like the amount of income your parents make and how much schooling they’ve had. And so it’s a little depressing because there are a lot of things you can’t control for – these kids cannot control for – and you can’t even educate on those things, like you could delaying gratification. And so as a result of that, how do you develop programs that produce these better achievements later on in life, even though they’re somewhat out of the child’s control?
Tyler: Well, there are a couple things I think are interesting that you mentioned that I’ll take issue with, because I like to play devil’s advocate. There’s one thing that’s important to remember before we get too caught up in a deterministic way of thinking about this and these types of predictive studies. I don’t know how much data you work with or how much your listeners work with. When I’ve taught statistics in the past, I always teach it to kids that want nothing to do with it. And I’m always trying to tell them that the world that we’re living in now unfortunately forces us to deal with data and statistics, whether you like it or not. But there’s this concept of the amount of variation explained, which means basically that if I observe a variation in say, test scores later on in life. So you can imagine the bell curve right in your head, right? Where there are some kids that are really good at it on one tail, some kids who were really bad at math on the other tail, and then in the middle there’s a bell-shaped curve, right? Our models – and mine included in the paper that we’re talking about – don’t actually explain a ton of variation later in life. So that means that even your early IQ, cognitive skills, gender, race and all of this other stuff that we have measured – I can’t remember exactly what the r squared is, but it’s something around 20-30% percent of the variation is explained, which means that all of the other variation there is not explained by anything we can measure about you early in life. Right? Which is really important to remember. Economists have always found this with studying people’s earnings. Everything you can measure about a person early on will only get you to something around 20-30% percent of variation explained.
There is something there; you can read into something kind of depressing into these findings, but the other thing is looking at the optimistic side. There’s still a lot of variation that we can’t explain. It means that there is way more stuff going on in people’s lives that really ends up being key factors that determine how you end up on some of these things. So that’s important to remember.
Secondly, when we think about what we can control and what can we change, these are really important and big ideas that get at the fundamentals of economics and developmental psychology. And there’s this concept about what you can personally change, and then there’s these concepts about what programs can do to help kids, right? I think one problem that we sometimes have in education – which I think you were speaking to – is that we try to put a lot of responsibility on the education system for dealing with big social problems that we have. For instance, most of the work that I do is focused on how we can find levers in the education system to combat a societal or economic inequality. Can the education system be used as an engine of social mobility that could make the country a more equitable place? And I think that we all believe that to some degree, but what a lot of this work suggests is that we may be putting too much onus of responsibility on the education system to really do that. That doesn’t mean that the education system can’t work better and that it can’t meet those goals better than it is now. That doesn’t mean we shouldn’t consider consistently trying to improve it, but I think we have to be realistic about our expectations.
Now, one last thing I want to say is that we can develop programs that have big effects on kids’ lives. There are programs that have been shown to do it, but they are programs that are also big. What I like to say is that the program has to be proportionate to the problem. I’m becoming less and less interested in a story where we can do something really small and really cheap that might have these really big outside effects. It might work, but I’m a little more skeptical of that. I think what’s probably more often the case is that if we want to really make a long lasting impact on a kid’s life, who has a lot of systematic forces in their life that are working against them that are making them disadvantaged, then we have to have a program that really has the strength and capacity to push back against that.
There are programs that had done that, that we see in the literature and that we hear talked about a lot. I don’t know if you’re familiar with Perry Preschool or Abecedarian – those two are very old early childhood programs that were run in the 1960s. Let’s talk about Abecedarian. They started intervening in severely disadvantaged kids’ lives at birth, and these kids started going to a really high-quality center-based care at age four months. They got one-on-one individualized instruction and access to pediatricians – so better healthcare services. The parents got access to services. They were given access to nutrition, including two high-quality meals a day, plus a snack. This was a really intensive program. And guess what? From everything we can tell, it had huge effects on the kids’ lives. They were better achieving throughout school and they earned more money as adults. They had less run-ins with the criminal justice system as adults. So they really perform at a cost benefit analysis actually, because the life benefits are so huge. But if you look at the size and the scope of what that program actually entails, it’s pretty stunning; it’s massive.
So I think what we can fall into saying is that there’s this one skill, right? There’s this one thing that if you can just do this, then everything else in life will fall into place. We can unlock all of these advantages by doing this one thing, and teaching a kid to do this one thing seems like it should be relatively easy to teach. And I think this paper is really a bucket of cold water on that.
Robert: Yes, it is. Yet it’s needed, because the last thing we want to do is spend more time and money on something that we think is going to work when it actually doesn’t work. You’re talking about how much can we rely on the education system? In in my field, it’s all about financial education: this idea that high schools and colleges are going to provide financial education to students. It might be a week-long program, it might even be two or three months of financial education, and the idea is that this is going to increase that student’s financial literacy. Then, as a result of having more knowledge, they’re going to make much better financial decisions and behaviors and they’re going to have a much better financial outcome. And yet, what we find in the research is that doesn’t actually happen very often. The results are quite mixed, yet we’re spending hundreds of millions of dollars to tackle something that can’t be solved with just a week-long financial education program.
Coincidentally, I’m not looking at focusing on financial education in schools; rather, I’m looking at the effect of parental financial education – even before someone gets to school – and the effect that might have on the students’ end result.
And I think you’re right. A lot of these problems are big, and they’re going to require very, very large and comprehensive solutions and programs. There is no magic pill; that just doesn’t exist, though we all want it to exist. If you look in the self-help area of your local bookstore, that’s what’s promised. If you do X, Y and Z, then you’re going to be much better off. But unfortunately, it’s usually much more nuanced than that.
Tyler: Yeah, and I want to be clear on one thing too. I don’t think Mischel was really responsible for selling that myth. I think that he obviously popularized the idea of the marshmallow test, and he was really big on this idea of malleability, that this is something that can change over time. In fact, there were interviews where he cautioned against it, saying that the marshmallow test performance at age four does not determine everything that comes after it. And it was oftentimes the way his work was interpreted by others that I thought it was a little bit more problematic. Partly, what I think we’re both describing is this kind of popular media problem – and this TED Talk and YouTube problem – where it’s very easy to say, “Hey, look at this flashy scientific finding out of psychology!” And they take this one little neat thing that’s overly important, and it just makes for great clickbait. So I’m not optimistic that we’re going to get away from this kind of thinking anytime soon. And in fact, the way that this article was covered had the same problem. Everybody was saying, “Oh, the marshmallow test has been debunked. Right?” And obviously, I hope that if you’ve listened to this, you’ve come away realizing that’s not really what we did, and that’s not even really an appropriate or a sensible way to talk about the findings of the study. But that’s the way to report it, right? Because people will click on it.
Robert: We’ve been talking a lot about younger children and students and adolescents, but sadly many of my listeners are not children. They should be; they might learn something. Most of my listeners are adults (of course), and they’re interested in growing themselves personally and financially. Do you have a takeaway based on your research that might assist them in their path on becoming financially and personally more developed.
Tyler: That’s a good question. One thing I would say – just based on what I was saying a second ago – is to be very weary of correlational studies that are popularized by the media. These are always studies that have some headline like, “People Who Do This Are More Successful” or “People Who Do This Early In Life Are Much Better At X, Y & Z Later In Life.” These kinds of things can overwhelm us and make us distracted. I would caution against reading too much into any of that. Does delay of gratification matter for your later life? I think it probably does, right? It doesn’t really pass the sniff test to say that nobody needs the skill at all in the modern world.
Many of us have jobs where we’re sitting at computers everyday faced with tons of stuff that can distract us – our phones are lighting up, our emails are lighting up, we can click on any number of things throughout the day. I think you have to have some self-control and some ability to delay gratification just to get through the workday.
The message isn’t that you don’t need the ability to delay gratification; the message is that if you were to teach a four-year-old to delay gratification, you couldn’t walk away from the situation like job well done! Everything’s fine now! That’s really all the advice I can muster.
Robert: That’s good. We appreciate that. Are you planning on reexamining other studies, or did this just happen based on your work in the math program?
Tyler: I guess partly it’s just my orientation to research; I’m kind of attracted to reanalyses and replications. So I am working on a couple of other things like that now, but it’s nothing as flashy. I’m working on an evaluation of the State Preschool Program in Tennessee, and I’m also working on some evaluation work of an intervention that was run in Head Start classrooms about 15 years ago, and we have longitudinal follow-up data on those kids. In that particular intervention (which was actually quite comprehensive in nature), we’re looking at if it had long lasting effects on the kids that participated, and we’re finding in some cases that it did; and then, in other cases it didn’t.
I’m broadly interested in this idea that education can change people’s trajectories and can change people’s lives, and so I’m constantly looking for ways to scratch at that question – but it’s a really complicated one. You can imagine that this is an issue statistically that isn’t going to go away. I think this broader than just the educational world, but we have all of this data now. We have so much data on people, and I don’t think people fully understand how much data probably exists on them alone. Every company you interact with now is probably recording data on you – certainly the companies that you interact with on your phone and on your computer. The government has a ton of data on you. And so, there’s going to be more and more issues on how we make sense of that data, and how we use it ethically, and how we use it to try to improve people’s lives. And so, the correlational problem is going to be underwriting all of that, because what you’re going to see is that we have data on say your online habits over time, right? And a company is trying to figure out if the time of day that you log onto a website, or if the type of stuff you click on, or if the images you see on a website predict you buying something, right? Or predict you staying with the company longer or all sorts of behaviors. And it’s a correlational problem again, right?
We observe certain kinds of behaviors and then we want to know if they cause changes that we care about later on. I think this is a fundamental problem that we’re going to be dealing with for a long time. I am optimistic that we can make headway on it, but I think it’s really different.
Robert: Yeah, I think the correlational issue has been a problem for a long time. Short of doing actual experiments, we only have that association. We can only make some real guesses as far as if this is related to that. We can’t say that this causes that, but there is some relationship there that we can test.
I also think you’re right that the future is data, data analysis, statistics and being able to figure out how things are related, and how one thing might predict something else. It’s a fascinating area, and we truly need more people like you, who (while you might click on clickbait studies), you have a much more discerning eye and you can actually understand the research that’s behind it. That’s really important.
So, thank you so much for your time and your research. And the last question is, do you have a particular goal that you’re working on that you’re really excited about and that you want to share?
Tyler: Honestly, I’ll tell you my near-term goal. I have three papers right now that I need to get off of my desk, which in academia basically just means submitting them to a journal. It doesn’t sound like a very big deal, but honestly, I have to delay gratification from working on other stuff that I’m more interested in.
Robert: We got to move on to the next shiny thing. But how cool is that? You’re sitting on three completed papers. Do you know what I would do for a completed dissertation at this moment? You have no idea. So that’s, that’s pretty cool.
I very much look forward to reading your future research. I think you’re absolutely on the right track here; it’s not just interesting, but it’s also really important what you’re doing and what you’re looking at: how can I take these kids who might have some disadvantages, and how can I shift their lives early on to have dramatic effects later on in life? I truly can’t think of anything more significant and important than that, so please keep up that work.
Tyler: Thanks! We have a long way to go, but I also think it’s a worthwhile goal.
Robert: Thanks so much for joining us.
Tyler: Take care.