by 
In the 2000s and 2010s, education technology evangelists promised that new learning media would transform schooling and education. Then, a pandemic shut down schools all over the world, and online learning face a pivotal moment, and left a global public mostly disappointed. Instead of adaptive tutors, artificial intelligence, MOOCs or other new technologies, most learners got digital worksheets on learning management systems and ZOOM lecturers. Failure to Disrupt: Why Technology Alone Can’t Transform Education explores the recent history of large scale learning technologies to explain why technology provides such uneven support—useful in some contexts but not others, to some people but not others—to learners. The book concludes by examining four as-yet intractable dilemmas that learning media researchers and designers can use to identify persistent challenges in using technology to accelerate human learning.
Justin Reich is the Mitsui Career Development Professor of Comparative Media at MIT, and the director of the MIT Teaching Systems Lab. He is the host of the TeachLab podcast, the author of Failure to Disrupt: Why Technology Alone Can’t Transform Education from Harvard University Press, and the instructor for six massive open online courses on EdX and available through the MIT Open Learning Library.
The following is a transcript generated by Otter.ai, with human corrections during and after. For any errors the human missed, please reach out to cms@mit.edu.
Scot Osterweil 00:33
turn the floor over to Eric Klopfer who’s going to introduce today’s speaker.
Eric Klopfer 00:37
Thanks, Scot. Um, so I will briefly introduce Justin, who’s gonna be talking today about “Failure to Disrupt”, his new book on educational technology and its failure to disrupt educational practices. And Justin is a professor here in Comparative Media Studies and Writing. And before that, he was a researcher and lecturer here at MIT. So he’s been associated with the community for for many years I’m doing he taught my my education courses previously, and and ran our, our partnership with the Woodrow Wilson Academy for a number of years, Justin has been doing work that I think I would describe as sort of healthy skepticism about educational technologies, for I think, most of his career, including his his doctoral work and a lot of his work more recently. And, you know, it’s it’s sort of taking this lens on educational technology that’s both sort of hopeful and, and critical in terms of looking at the ways that it ultimately influences the practices of educators, as well as the lives of the many students involved in the educational systems. Justin runs our Teaching Systems Lab here, which looks at a lot of issues in professional development of teachers use implementation of educational technologies, equity in education, and innovative practices for for training, both current and next generations of teachers. So with that, I will hand it over to Justin, and thanks for coming to colloquium today, Justin.
Justin Reich 02:09
Thanks, Eric. We have some great instructors, writing instructors, who help us teach the media studies classes to undergraduates at MIT. And they try to help Media Studies undergraduates think about what argumentation and Media Studies looks like. And one of the ways they describe it is to say that there are producers of media, and audiences of media and they sort of interact in some way through media in some kind of broader social context. And everything can get much more complex than that. The producers can become consumers, the consumers, producers, all that kind of stuff, but there, but there’s a kind of fundamental structure to a lot of common arguments. And I would say, a lot of my work is interested in that model as well. That there are people who take and facilitate media as educators, and there are people who consume that media as learners. And sometimes they pass it back and forth. In some kind of broader context. You know, the thing which distinguishes me as a learning scientist from other media studies scholars, is I tend to be keenly interested in how does that interaction change human development? How does the learner develop new capacities? How are they able to do different kinds of things than they were before on the basis of that interaction? And I’m hoping that one of the things that can come out of this conversation is, is I’ll present to you some of the ways that I see the field of education technology as a learning scientist, and I hope that folks will will ask questions from a media studies perspective and and make you know, for the graduate students make connections to the readings and other kinds of things. You’re working on faculty, the research and other practices that you see are germane. And we’ll see if we can make some some connections that way.
So one place that I start my work is that for the last 20 years, people have made some really extraordinary claims about how new media might transform the education landscape.
In 2009, a Harvard Business School Professor Clay Christensen predicted that by 2019, last year, half of all secondary school courses in the United States would be online or blended, that they would cost a third as much to provide and they would produce better learning outcomes.
In 2012, when Massive Open Online Courses exploded in higher education, edX and Coursera Udacity Sebastian Thrun, the founder of Udacity, said 50 years there’s only 10 institutions of higher education left in the world. They’re going to be you know, a concentrated set of mega universities providing the world’s best learning content all around the world and Udacity might be one of them
Sal Khan in 2011, Ted Talks said, Let’s use video to reinvent education, let’s have individual students sit down in front of computers, let’s have a personalized learning pathway around mathematics for them that sort of optimized for their individual learning rate. And we’ll still have students and teachers and things like that. But they mostly get together like to do interesting projects and to, you know, reflect on what they’re learning and build community, but the sort of heart of skills development will happen through these machines.
And then 2013, Sugata, Mitra won the TED Prize for his proposal that we didn’t even need schools or educational institutions anymore, that we could simply give kids laptops and broadband connection. And without any institutional support, they could learn anything by themselves. And then earlier this year, the world was blighted by a global pandemic and 1.6 billion learners were sent home. And to some extent, you might think that like, this was the moment that education technology was poised for, I mean, prior to the pandemic, the case that education technologists had to make was that they had a set of offerings that would be better than the existing traditional educational system. But they didn’t even have to make that claim anymore. They simply had to claim that they could offer better learning experiences, then, you know, pandemic hobbled system in the middle of an emergency pivot to remote teaching. And I think during the last 20 years, one of the reasons why the arguments of education technologists, for the transformative potential of Learning Media was so powerful is that we saw these transformations happen in other sectors. Journalism has been profoundly reshaped by media, government and civic media is in the midst of a transformation.
The word friend means something different than when I was growing up dating our relationships. I mean, some of our most intimate experiences are mediated by technology, by social media in particular, in new ways. Doesn’t it stand to reason that the same kind of thing shouldn’t happen in education as well? Like, why would education be a sector that’s different from any other sector? But I think most of you know what has happened during the pandemic, which is that, you know, education technology does not right in on, you know, a flaming horse to a winged horse to save us all. In fact, I think most people, most families, especially younger children, but I think many folks in higher education and well have have experienced something ranging from like, this is adequate to wow, this is really a disaster for us and for our families. And in fact, two of the technology, I think the two most prominent technologies of the pandemic are two of the very oldest technologies that we have.
So I would argue that the two technologies that have dominated the pandemic are learning management systems, which are basically platforms that allow people to pass documents back and forth with one another thick Canvas Schoology Google Classroom. These were theorized in the 60s and 70s. They were commercialized in the 1990s, they will made open source in the 2000s. And then the other you know, perhaps dominant technology of the pandemic has been what in the 1930s, when it was introduced was called video telephony now goes by the term of video conferencing. And I think what we saw both in higher education and in K 12 education was, you know, a series of collective acts of conservatism, small c conservatism, the likes of which we will never again see in our lifetime, faced with dramatically changing circumstances, you know, most of the professor it like walked away from their lecterns and sat down in front of their home office video cameras, and kept teaching, you know, roughly the same way that they were teaching beforehand, despite all the transformations happening in the world, and despite the promises of people that technology would rearrange those relationships even in normal times, let alone pandemic times. So my task as a writer in this book is to explain why that is to explain why these arguments of transformation can be so tractable at times can be so compelling at times. But also the argument is that they shouldn’t be so compelling because they’re routinely not true, and that there are more productive stances to take towards the role of technology in schools.
Last year, before the pandemic, Sal Khan gave an interview to a little trade magazine called this administration. So I’m sure millions of people have seen Sal Khan’s TED Talks, I promise you that it was like me and four other people who read this interview. In district administration magazine, it turns out that in the last decade, Sal Khan had not only built Khan Academy, this library of videos on instructional topics, and an adaptive tutor and other kinds of tools, but he actually built a regular in person school. As a private school, I think it’s in Silicon Valley area, it costs 20 or $25,000, a year to attend. And his observation after working on this project for a long time was now that I run a school, I see that some of this stuff is not as easy to accomplish compared to how it sounds theoretically. And his new argument was that actually a better way it was, it’s not going to be the case that Khan Academy is going to transform relationships in schools, we are not going to have students who are spending all you know most of their time developing skills through these individual pathways. And at the end of their skill development coming together for rich, intricate project based learning. Instead, the model that he’s recommending is to teach about the way you had been teaching four days a week, and then use Khan Academy his practice problems one day a week. And he says that’s doable, that’s tractable. And it’s also has some benefits for students math learning.
Um, the thing that struck me in a powerful way about that argument was how incredibly well established it was. So you can go back to the 1990s. Here’s an article from 1997, published by Ken Koedinger at Carnegie Mellon University, where they had done in the Pittsburgh schools the exact thing. They had built a series of cognitive tutors, adaptive tutors that responded to students responses and gave them progressively easier harder or properly sequence math challenges. And they told teachers to use it three or four days a week, I think they told him to use it three days a week, or they told him to use it one to two days a week and teach in a regular way, three or four days a week. And they ended up for the most part if they use it using it one day a week. And they found the same kinds of things that Sal Khan found 25 years later, which is that if you have people teach in a regular way, four days a week, and then use adaptive tutors as practice problems one day a week, it works a little better than what had come before. You know, another way to frame this is that, you know, kind of Academy I think, is raised like 100 and $50 million in philanthropic support over the last eight or nine years. And you know, what they what they learned from that investment, you could have discovered with it with a trip to the library
So, when I contrast Sal Khan of 2011 with Sal Khan of 2019, I see two different kinds of stances towards education, technology at work. And over the last two decades. One of the most powerful stances has been the charismatic stance, and I borrow this term from Morgan Ames, who did a really lovely anthropology of the One Laptop per Child program that was situated from the media lab here at MIT. And she wrote a book called the charisma machine. And and talked about charismatic technologists, people who envision technology as tools that can disrupt and transform and rearrange existing systems, and who imagined futures that are brand new and different because of new technologies. And she contrast that with actually sort of what I see in Sal Khan in 2019. With the tinkering stance that she draws from a book from from two historians David Tyack, and Larry Cuban called tinkering towards utopia. And in the tinkering stance, the assumption is not that new technologies will disrupt and transform educational systems, but rather that these existing conservative complex political systems will domesticate new technologies, they will take new technologies and they will slot them into particular niches for particular students, particular contexts, particular subjects, and that the future in many ways can be seen as an extension of trends from history that things change, but they don’t change disruptively. They change incrementally. They change step by step. And in some ways the the book failure to disrupt you know, is like a love letter to the tinkers or, or a passionate plea for honoring and respecting the work of tinker’s. And that is to say that that the charismatic stance leads us to sort of boom and bust hype cycles around education technology, in which we miss allocate our resources.
And by contrast, there are ways that technology can help improve existing systems for learning. But they tend not to be breakthroughs, like a lot of things in human development, they tend to be a few steps forward and a couple steps back and kind of maddeningly slowly plodding. But perhaps, ultimately, you know, leading to improvements, or potential improvements in human capacity, or at least, if we’re going to make investments in education technology, that’s the sort of stance to bring to it. So the first half of the book, sort of reviews what I think is one of the most useful disciplines for the Tinker kind of personal discipline, which is to start from the assumption that any new technology is situated in some kind of history. And if we know something about that history, we can make some pretty good guesses about how a new technology will operate.
So to illustrate that principle, I look at a set of technologies that I call learning at scale, learning environments for many, many learners and few experts to guide them. Typically, education technology, evangelists have not promoted calculators as transformative tools of teaching and learning. Because there’s not a sense that calculator kind of on its own provides a you know, a personalized, individualized curriculum that is scalable to many millions of people. But there are other technologies we’ve created in which edtech evangelists have made that promise. And they tend to fall into three different categories. And you can define those categories by who guides the sequence of learning activities. So there are learning environments in which an instructor selects the suggested sequence of activities. And those are things like Massive Open Online Courses. There are algorithm guided large scale learning environments like adaptive tutors, where a computing algorithm measures student performance on some dimension. And on the basis of that measure, select some new learning activity to suggest for a student. And there are peer driven, peer guided network learning communities. You know, at MIT, I use the example of the Scratch programming language and community where the learning experience of Scratchers is in profound ways shaped by the community of peers that they interact with. On the Scratch platform, almost all of us participate in these kinds of networks in some way, if you’re interested in how to do makeup on your face in new ways, or how to style your hair, or how to beat a level in a video game, or how to do different kinds of handicrafts. If you’re watching videos, posting pictures, reading Reddit threads, you’re probably participating in one of those kinds of networks. Each of those three genres has a history behind it. They tend to have similar kinds of pedagogical proclivities, they tend to use similar, you know, to borrow the terms of software developers, sort of similar technology stacks.
So the first and the other thing is that for most of them, we have a kind of track record of efficacy behind them. As the example of Ken Koedinger’s 1997 research and Sal Khan’s 2019 proclamations point out that, you know, we human beings have been using computers to try to teach other human beings for as long as we’ve had computers. This is not a brand new field. This is a 60 year enterprise conducted with substantial funding by super bright people at research labs all over the world. And so if you find a new piece of education technology, I argue that you can sort of ask this question who guides a sequence of learning activities here, and you can see how it sort of slots into one of these three genres. And if you know something about the street three genres, you can make a good guess about how some new technology will shape the future. I think I won’t spend a ton of time with this, although we can come back to it. except to say that, you know, for instance, I think that instructor guided and algorithm guided genres of learning technology, they tend to be inspired by pedagogies that emphasize direct instruction, and experts communicating information to novices, where by contrast, peer guided learning environments tend to be interested in pedagogies of apprenticeship, where you learn not so much from the received wisdom of experts, but through the process of trying things interacting with others sharing your experience. In the in the middle slot here, I indicate some technologies that I think are quite common to these genres.
So for instance, most adaptive tutors, they really have two main parts. They have an auto grader, and the auto grader is what allows us to determine the level of human performance so we can select some other tasks. And almost all of them, no matter how fancy they purport to be, no matter how many billions of cells of data they purport to collect, no matter how fancy you know, the algorithms or the parameterization they claim to have, at their core, they almost all use I’m variant of a statistical toolkit called item response theory. And item response theory was developed by the Educational Testing Services in the 1980s. And I’ll describe it to you now. But I take maybe three pages in the book to describe it to readers, with the point being that that this is not intractable.
This is not impossibly complex, which is what education technology evangelists often try to convince us of, like, the fundamental building blocks of this are well known. And they’re usually old, you know, if you see a sort of Ed Tech roadster coming your way, like lift up the hood, and you will see like, Oh, that’s a pretty old engine, or that’s a pretty old chassis, or there’s some well established pieces here. And if we understand those well established pieces, then we can make some good guesses about how a new technology will operate in the future. Or we can identify the pieces of a new technology that are in fact, distinctly new, like, it’s very unlikely that the whole thing that we’ve created is going to reimagine, you know, pedagogies, that we’ve been working on for thousands of years in our society. But maybe they have some particularly interesting tweak. And if you can identify that particularly interesting tweak, then you can think of that as a place for study and exploration and other kinds of things. No, and I can talk in more detail and do in the book about, you know, how I think math department head should examine this history of technology when making a decision about how to implement a new piece of math software in their school, how a Vice Provost for information technology might do that, how a researcher might identify what kinds of interesting problems are out there, how a designer might think about how to approach the development of new software.
So in the in the second half of the book, that what I try to tackle are, is making clicking work are what I call for as yet intractable dilemmas, for issues that come up time. And again, across all of these different genres of technology, problems that if people interested in technology at different levels, funders, developers, researchers, implementers, teachers, students, if we thought about these problems in in creative ways, if we were diligent about trying to address them, that would be our best chance of sort of tinkering our way to success. And they and the problems emerge from three key features of educational systems. three key features of these systems that I think are really central to understanding why technology doesn’t lead to disruptive society, shifting change in education, in the way it does in other fields. And the first piece of the education landscape is that education is just immensely almost unfathomably complex. Somewhere today, there was a teacher, it was a seventh grade earth science teacher who is starting a new unit on plate tectonics. And somewhere else, there was a kindergarten teacher who across a zoom video conference was trying to explain to students how to open a new tab in a browser or how to tie their shoes. And somewhere else, there was an advanced Mandarin class being taught in a in a liberal arts college somewhere else, and you know, and then somewhere else, there’s a two year degree program where people are learning how to be radiology techs, the you know, and it’s not just that those subject areas and those contexts are different. But what you do the interactions you have with your students day to day, the the content that you cover the skills that you address, they’re constantly changing across the 180 days of a K 12 school year or the 28 weeks of a two semesters of higher education. It’s extremely difficult to think about how technologies could be built to address all of those kinds of diverse use cases.
And indeed, the technologies that we have, are very uneven. They work well in some circumstances, but not others for some people, but not others, in some contexts, in some subjects, but not others. And I think that is one of the you know, sort of fundamental misunderstandings that people often have of when they predict sweeping changes from education technology. They’re imagining that our technologies and I haven’t found the right metaphor here, but they’re like bulldozers, or they’re like Swiss Army knives, they sort of clear everything out or they do everything. But our technologies are not that way. They solve very particular problems. Typically, they’re like very specific head pegs. And the complexity of education is just this like manifold, huge sweeping landscape of lots and lots of different kinds of holes. And then our education system is especially here in the United States, but certainly in Lots of other places in the world is shaped by profound inequality. We provision students in their schools and students in their homes, very, very different levels of resources with which to approach the challenge of education. And that shapes every part of our education system. And certainly some of the some of the saddest thinking and reflecting to be done about the pandemic, is how it is both revealed and exacerbated those inequalities.
So I’ll briefly talk about these four dilemmas. And then maybe I’ll stop for a bit and and see what questions or thoughts that folks have. But here, here are four of the kinds of things that I think whether you’re interested in network learning environments, or learning games, or adaptive tutors, or MOOCs, I think these are problems that sort of cut across these different kinds of approaches to learning at scale. So one has to do with complexity, and I call it the curse of the familiar. If you build a technology that is familiar to people, you can get that technology adopted. The most widely used technology, education technology, maybe in American schools, is a tool called Quizlet, which was created by an MIT dropout and and a former students of Eric’s and the terrific guy. And Quizlet lets you generate online flashcards. And when you glance at the operation of the Quizlet website, you will instantaneously understand what’s going on, you go Oh, this is a flashcard. Like I’m gonna write question on one side and answer on the other side, I’m gonna test myself, I’m gonna share the decks with other people. These are flashcards because it is instantaneously recognizable, it can spread very, very widely. But if we sat down a bunch of experts in the American education system and said to ourselves, like, what are the real problems that we face here in education with inequality? With the challenges of the future of the labor market? What do we really need to work on here? I think very few experts would come up with the answer like, man, we really have a dearth of flashcards out there in the schools like we really have to improve flashcard access for children across the United States. The new flashcards are neat, but they because they don’t offer any kind of substantial change in the way that teachers and students interact with one another with the content, they are very unlikely to lead to substantial improvements. They gain a certain number of inefficiencies, and they help students memorize some things better. But they’re, they’re not sort of unlocking new pathways of teaching and learning. By contrast, we do build things that unlock new pathways to teaching and learning. Users often find them confusing. So if we create things, new technologies that incorporate alternative pedagogies, or create new routines or relationships between teachers and students, it’s often the case that this confuses teachers and students. And these things sometimes get passionately adopted in small niches, but very rarely spreading scale across systems. In the cases in which we do have some of our most interesting technologies, sort of get into schools and start to spread and start to change the way teaching and learning happen, they tend to do two things.
And this is where in the second half of the book I tried to propose, you know, some so not sort of pat solutions. But some approaches to addressing these intractable dilemmas. They tend to be able to be used for familiar ways initially, and then span out into new kinds of opportunities. So Quizlet gets in in a very simple way with flashcards, but doesn’t really take you anywhere beyond flashcards. I have colleagues who built this graphing calculator tool called Desmos, which is at first glance just does everything a ti 84 calculator does on your computer for free. But then beyond that, there’s a whole set of ways of using this graphing software that enables a whole different kind of approach to teaching and learning and mathematics. And so it meets people in a familiar place and takes them somewhere else. And then the second thing that people do when they successfully navigate the curse of the familiar, and this is sort of a theme that cuts across both the book failure to disrupt. And a lot of my current critiques of how we’re addressing online learning during the pandemic, is that the people who are good at taking technologies and spreading them and having new pedagogy spread with them. They don’t assume that new ideas will travel with the technology. They assume that they have to engage communities of faculty members, teachers and learners in pedagogical exploration about how to do new things. So the you know, MIT Media scratch lab, they built scratch, but they are also in the midst of building this giant apparatus to teach people all over the world. What are the pedagogies of computational creativity that are associated with scratch because scratch by itself, if you sort of drop it into schools, it will be it will be, you know, domesticated by those schools for conventional teaching and learning. But it provides an opportunity for allowing people to remember And those ideas, but only if faculty and students and communities are supported in doing that learning and doing that rethinking you know, it’s a, it’s a way of thinking about the scaling of new ideas, not through technology distribution, but through movement making, through community building through the kinds of things that we see in other forms of social movements. A second challenge I call the edtech, Matthew effect. And Matthew effects are commonly observed across sociology, they, you know, it comes from a line in the book of Matthew, which is paraphrasing, like, he has much, much more given, and he who has little more will be taken away. There is a persistent story in education technology that will have the capacity that new technologies will democratize education, that they will make education more free, more fair, more, just, my colleague, Larry Cuban, who’s an emeritus professor at Stanford, has marked how these arguments go back to the days of radio is a great book called teachers and machines, in which he has a picture of a bunch of young people sitting around a radio receiver, that’s the size of a small child, you know, one of the big stand up units, and the caption is, you know, with radio, the underprivileged school becomes a privileged one. And you all know that radio did not, you know, squash the inequalities that occur between our schools, the United States, and nor will other technologies that we develop on their own new technologies disproportionately benefit the athlete, because those people have the financial and social and technical capital to take advantage of new innovations. And it’s only through deliberate efforts at really thinking about what would it look like to create technologies that close gaps rather than spread us further apart? through things like do our technologies, you know, can we measure and assess, or observe how people from different backgrounds and life circumstances use technologies differently?
A tragic thing that we’re going to research over the next year, and and learn in different ways is that white children in American schools and black children in American schools are not going to be treated the same way on zoom, that the behaviors of the you know, the subjectively inappropriate behaviors of black students on zoom calls will be policed in ways that they are not for white students. And if we don’t find ways of looking at what’s happening during the current pandemic, and looking at it through the lens of how do people from different backgrounds and life circumstances, experience technology differently, then we will miss the opportunity to learn about those things and figure out how we might be able to address them. A third challenge relates to unevenness, which is the trap of routine assessment, which is that many of our large scale Learning Technologies depend upon automated assessment. And we have some domains in which we do really good automated assessment and some domains where we don’t if you ask someone a question with a well defined right answer, computational question, a question in a physics system where the laws of physics are well defined, we can build good auto graders that evaluate those responses from learners. One of the fields in which we’ve built the most impressive auto graders in the field of computer programming, where computer science professors and teachers can assign their students computer programs to write that have to meet certain engineering challenges. And they can create computer programs that grade those assignments. And when you can do that in an automatic way, you can build systems where people at their own pace and time can participate learning experiences, get some feedback from an automated system, be motivated and inspired by their progress or be supported by different kinds of feedback, and then proceed and move forward in their learning. There are lots of domains we can’t do this very well, probably the most important one is that we really don’t have good tools for evaluating writing, for evaluating people’s ability to reason from evidence. This is a problem because much of what we teach in the liberal arts education is how to reason for evidence.
Perhaps most problematically, the things that we’re good at building computers to assess tend to be the kinds of things that computers are already good at. They’re highly structured, highly routine kinds of problems, that arguably, we don’t really need people to do that much anymore. By contrast, the things where humans have a competitive advantage over machines in the labor market, or sort of equivalent contact concept in the Civic sphere, are areas in which we don’t have very good automated assessment. So you know, the problem here is that we’re we’re really good at creating assessment systems for things that we don’t need people to do anymore. And this is not because there aren’t smart people who are working on this problem. decades of work by very, very smart people in technology companies and universities have thrown all kinds of resources at this challenge. And instead of having, you know, some kind of Moore’s Law, like exponential growth and improvement, we’ve seen very, very little progress here in decades.
And I think that should give us some humility and caution about about our predictions for the future for lots of education technology evangelist, it will, we’ll make a prediction and then when doesn’t come true, they’ll say add just we just need a little longer. Thomas Edison in 1913, said that by in 10 years, all textbooks would be replaced by the films that he was producing. And then in 1923, he gave, I think it was in front of the FCC. And he made a similar argument, except he said, Well, actually, it’s going to take 20 years, but it’ll happen that all the textbooks will be replaced by filmstrips. And we still have not replaced, you know, 100 years later, all of the all of the textbooks with video materials, because it turns out that print is a pretty good media for learning in a lot of different ways. Then the last challenge that I mapped out is that if you’re someone who’s excited about building and improving software platforms, you’re probably very interested in the large amounts of data that these systems can collect. And then the ability to rapidly run experiments that let you test how changes the software platform affect people’s experiences. You know, there are all kinds of regulatory issues with this. And there’s all kind of, you know, sort of cultural policy issues. There’s some sense in society, that if I go to Amazon, to buy a book, that they should be able to collect some data about my experience there. And that, you know, if I find out that sometimes they’re doing, you know, randomized control trials to see if I’m more likely to buy a book with a blue button, or a red Buy button, that, you know, at least I as an individual entered into that learning experience into that software experience, somewhat of my own free will and volition, not entirely. But But as wicked as the problem is in retail, it’s much, much worse in education. Because you know, right now, all across the world, young people are both compelled to go to school. And they are compelled to use the software platforms that are assigned by their teachers and school systems. And so there are all kinds of reasons to be very seriously concerned, both about the immediate risks of surveillance in these systems, but also about the long term, kind of educational social risks of normalizing and socializing young kids to live in surveillance cultures.
There are lots of circumstances in the social sciences where we think experiments are like generally good, we tend to not intuitively think of experimenting on young children learning as a thing, which is good, I think, I think there are ways to do these things responsibly. But I also think that there are real serious concerns that are that are embedded in these practices. And if we want to see the same kind of improvements in learning technologies that we’ve seen in other kinds of retail software platforms, we’re gonna have to resolve and negotiate some of these kinds of challenges. So that’s what the second half of the book tries to address, it tries to chart out, you know, the first half is really more of a history, the second half is more of a have an engineering text of trying to say, Here are four common problems that we run into all the time. And here’s some approaches that I think might be able to solve them. And, um, you know, as I reflected on, you know, what the lessons of this, you know, in the prologue, I mentioned that the final copy edits of the book were done, like March 23, the book was written right at the end of one era, and just at the beginning of this new one, and a lot of what I’ve done over the last eight months is both try to be helpful, but also try to reflect on what do we learn from the pandemic. That’s, that’s, that’s salient from history.
And I think two important lessons, at least come through. One constant mistake that education technologists make is to describe technology as sweeping to describe it as something that can sort of sweep away existing systems and usher in new ones. And instead, for a variety of reasons, our education systems are our conservative institutions, because they’re extraordinarily complex. And they’re managing all these different, competing interests. And as a result, new technologies tend to be domesticated, we tend to slot them into existing functions, which is why we perhaps shouldn’t be surprised that all the faculty walked away from their lecterns and went to their home webcams. And you can decry that as you know, a sort of pitiful conservatism and a system. Or you can say, Wow, this system is so well honed to meet its competing interests, that it’s actually kind of found a local maximum a local optimization of all the different resources and competing constraints. And then the second problem that I think technology Just often make, which is quite salient to our moment now is that technologists often describe education technology as a switch that you can flip on and on, you sort of buy it, install it, and then it works. And that’s not at all how education technology works. Education technologies are only as useful as their communities of users are well supported and strong. They are powerful tools for rethinking, learning for imagining iterative and continuous improvements to learning.
But there’s very, very few things that we’ve created that just kind of instantly in meaningful ways benefit learning. Rather, they become useful. And we’re seeing now all over the world, millions of faculty members engaged in the process of asking themselves, okay, I’m forced to use this new technology now, what are what am I doing? What am I colleagues, my discipline, or my subject or my school doing? And how do I have to rethink my practice or rethink my approach to have more powerful, more effective, more connecting more expired inspiring experiences from learning. So those those two things of technology is particular and domesticated by systems rather than sweeping. And the strength of technology not being its instantaneous effects, but by its ability to be absorbed by, by community of learners, are perhaps the two things that I’ll leave you with before, before taking some questions.
Scot Osterweil 41:43
And I just want to invite everybody. If you’re up, if you’re currently a panelist, I think it’s fine to just unmute yourself and call out at this moment. Just be mindful of someone who speaks up before you. If you are a guest, feel free to put a question in the q&a. So I’m going to start with a question then, because no one else is calling out. I know, in the beginning of my work in educational technology, I realized it was a fallacy. But I had this sort of way, I guess it was a wish, that of a technology in my case game sort of made, that it could somehow make people who used it aware of whole different models of pedagogy, and when in fact, what we must learn is that teachers tend to even if they’re using something as radical for them as a game, they’re going to tend to fall back on the same pedagogy they’ve always used. Are there exceptions that are is that as Yeah, as Eric point yes, mentioned the Trojan mouse that was that was a term that he has used? Are there no, is there no evidence of that? Is there some evidence of that of the technology actually shifting the thinking of the people who adopt it?
Justin Reich 43:15
I mean, my view is that there’s not good evidence of the technology, or maybe three things, there’s not good evidence of the technology in and of itself, shifting people’s views. A second thing that there that there, there is good evidence of is that technology has an ability to catalyze thinking about those kinds of issues. So it’s possible to you know, you could you can go into a group of faculty members and say, the future is going to be really different. The world is changing, our learners have a whole set of new experiences. And as a result, we think you should rethink your relationships, your curriculum, your pedagogy, all those kinds of things. And many faculty respond with like, No, thank you, we’re doing fine. And then you bring a learning game into that same community experience, you know, or some other form of technology. And it, you know, operates as kind of like a symbol of the future to be able to say, oh, like, we could do things really differently here. We could, you know, this gives us new opportunities and new affordances new ways to rethink things. And so I think it can catalyze those conversations. And then another thing that we know is if people do move from more familiar practices to new practices, it’s a developmental process.
You know, Judith Sandholtz did this project in the 1980s, called the apple classrooms of tomorrow, where she, with a team of folks, you know, got some k 12 classrooms and got a bunch of Apple two plus computers and had wired network with, you know, some of the first network computing environments and they had robots and printers and things like that. And she described teachers going along a developmental trajectory from you. Things in more familiar ways to using things in slightly novel ways to doing really imagine at work. Faculty members travel along that continuum at different rates. to a limited extent, they start in different places, but really a lot of them start at that first spot, like what is the moat? You know, how do I use this to extend existing practices? And then I can think about new and different and interesting kinds of things. So I, you know, and that’s, and that’s why I think it’s so important to pair the idea of technology integration with the idea of Community Learning at the same time, like, Can games do that? Sure. But not when games fall from the sky, it’s more likely to happen when games arrive with a community of people who are interested in teaching and sharing these ideas. I mean, Mitch Resnick has a great line that he’d had it with the release of scratch 3.0, which was something like, you know, we’re gratified at how widely scratch has spread in schools. And we’ve been somewhat surprised at how challenging it’s been not to spread the technology of scratch, but to spread the ideas and the pedagogy behind scratch. And, you know, one of the things I admire about that group is that, you know, rather than saying, like, oops, disruption didn’t work, like let’s go try something else. They’re like, Okay, great, you know, let’s work in a really diligent, devoted way on that human development problem as well.
Scot Osterweil 46:31
I have, again, pure Feel free to talk but I’ve got some questions in the q&a. Someone said, I very much enjoyed large scale MOOC. What do you see regarding the future of this platform?
Justin Reich 46:47
So I have a chapter about MOOCs instructor guided learning and AI. And I claimed that they had three big bets, that they would provide new pathways for different kinds of people into higher education, that they would unbundle and rearrange higher education systems. And that they would usher in a new era of data driven learning science. And I think none of those things basically has happened. I was one of the people who’s working pretty hard on trying to usher in a new era of data driven learning science. And I don’t think that we’ve been particularly successful.
And I think we may make incremental progress, but I don’t see like breakthroughs on the horizon. What ended up happening with MOOCs is that they were domesticated into the existing higher education system. For the most part. Many, I have a whole section of that many MOOC providers have started describing themselves as online program managers. These are people who largely create professional master’s degrees in a set of topics that are amenable to being taught online. And they have a familiar business model of paying up front for the costs, of course, and curriculum development, and then taking an ongoing fraction of student tuition revenue.
After that. There are some respects involved outsourcing the core competencies of universities, which is which generally across business is thought of as a bad idea. you outsource your janitorial services, you outsource your accounting, you outsource things that are peripheral to the core operations. You don’t outsource teaching and learning. You know, I think MOOCs are just a terrific illustration of the incredible power of education systems, to domesticate to incorporate new ideas. And there are a few places where I think there’s some really neat things happening. You know, the Georgia Tech has an online Master’s of computer science, taught through a series of MOOCs, which is like 7000 people at any given time enrolled in it, you know, it’ll it’ll probably end up graduating on an annual basis 16% of the computer science, master’s degrees, but it was not a harbinger of a whole new set of higher education. There was like one particular subject area at one particular University, which has captured a modestly large niche. And they’ll probably be some other, you know, accounting degrees or data science degrees that like, kind of work the same way, probably not as well. And, and that, you know, and, and it’s, it’s better to understand, you know, I think I think the saddest part of the MOOC story is that there are lots of universities that took limited funding, and invested enormous resources and saw very few benefits of them, because they weren’t, you know, one of the lucky few early adopters or people who got things just right, or institutions at other places that have sort of bottomless funds for these kinds of things. And I still, you know, I make MOOCs Wait, we launched one last week called sorting truth from fiction, about civic online reasoning. They’re really good at teaching already educated, already affluent people. Some of the already educated already affluent ish people in society are teachers and teachers lead busy, complex lives and MOOCs are a great way to reach lots of those at relatively low marginal cost, but that’s again sort of slotting into a particular niche into systems in which we’re hoping to incrementally over time improve our practice at them, rather than arguing that, you know, we’re on the cusp of a transformation in teacher education.
Scot Osterweil 50:16
And I see we have a question from Ámbar.
Ámbar Reyes 50:20
Hi, Justin. Thank you for your I was wondering, a question about related to students? And what about advice do you have for students like in the current educational climate? To make the most out of these experience? Ah,
Justin Reich 50:40
right. Well, you know, what, what, what advice do I have for students, I had a whole set of slides that I was sort of clicking through, I was talking, I just realized that I forgot to put them up. But I also think that sometimes it’s nice just to hear people chatting, but I at least wanted to have a link to the book up there. Yeah, my advice for students is, first of all, I think students at all age levels, and around the world should celebrate all of the resilience that they’ve shown, and all of the unconventional learning that they’re doing during this period.
So I think the most common narrative around learners right now is like some kind of deficit framing around learning loss. Like, oh, man, these kids are just not learning all the stuff that they’re supposed to learn in the curriculum, they’re going to fall behind. And there are very serious issues of that. And they’re very serious inequality issues with that. But that’s not all that happened. I think there are lots of people around the world who’ve spent this time as part time or full time learners who’ve learned all kinds of awesome stuff, about negotiating technologies, learners about showing more independence and more self directed learning. And so I think, you know, I’m a big fan of sort of asset approaches to thinking about these things. They’re, they’re not, there’s not a set of good sort of simple advice along the line of study tips that make people better online learners. If there’s one basic one, it would be something like, people often do, this is true for everything. But particularly online, people do a better job learning things they really care about, and they’re interested in, then people then what they were the sort of what you’re being forced to take, you know, if you were a freshman at MIT right now, I would encourage you to save some of your GIRs, some of your required courses that you’re not that excited about for when you come back, and do the things that you’re just most intuitively interested in now, because it’s because motivation is really essential part of learning. And then a piece, you know, that I say, mostly the faculty, but I think applies to students, too, is I hope we approach this period of pandemic learning as something that we’re all in together, I’d really try to encourage faculty to say like, how can you partner with students in designing your response to this because there’s exactly one group of Americans, one group of people around the world that have been learners during a pandemic, and it’s the students who are in our classrooms this spring and this fall. And they know a lot that we don’t know about what good teaching and learning in a pandemic looks like, and we should really listen to them. So maybe that’s a plea for you all students to try to share that with your faculty and to be in those partnerships with students.
Scot Osterweil 53:23
We do have some questions. I can take any hands as they shoot up? Will, you ever
Will Freudenheim 53:28
Yes, thank you. Um, I was wondering if the the kind of like shifting views about time scale that we’ve been considering with the pandemic have like changed people’s stances from either like a charismatic stance towards like interventions, or just like a band aid, kind of, we’re just going to deal with it for a couple months. And then we’ll go back to normal to more of like a tinkering stance of you know, maybe we’re going to be in this situation for a year more. So we can think about like slower kinds of experiments and other sort of solutions that might take a longer time to figure out if that’s something that you’ve noticed, and if so, like, what does that look like if it’s coming from educators or technologists?
Justin Reich 54:06
Well, I’m always amazed at the technologists like, you know, there’s some people who just really devoted to the charismatic stance and like, nothing will stop them. So there’s a guy Michael Moe, who helps run the ASU Arizona State University’s partnership with GSV. And he had this they raised a series of events called like the dawn of online learning. It’s like, didn’t we have the dog 10 years ago, or 20 years ago, like, like, you know, maybe you don’t think Dawn is like a watershed moment in history. Dawn is just a thing that happens every day, early in the morning that we all kind of sleep through, sort of these repeated cyclical pieces. So the charismatics are still out there.
But the thing which is like really taking the wind out of charismatic sails, I think, is that like this should have been their moment. And I just see, like, no hue and cry for the kinds of large scale learning technologies to extend That is even surprised me. I mean, I was at the beginning of pandemic, I told a lot of my colleagues at MIT, the odds that you can, in the midst of a pandemic, like go home and sort of whip together a decent online learning experience for your students is pretty low. And you’ve built a bunch of stuff already on OpenCourseWare and an MIT x, like just point people to that and kind of help them out. You know, I actually thought it would have been more of a moment for MOOCs and some other kinds of things. But it turns out that at MIT, and as far as I can tell, in lots of other places around the world, as well, it’s not what people wanted. There has been nowhere that I can tech some groundswell of students saying, like, you know, my introductory microeconomics professor is doing a crappy job teaching us intro micro online, and I just want to be able to take a MOOC and learn it myself. Instead, I think what we overwhelmingly see is like, people really do want the connection to their individual professor who’s like doing lousy job managing kids in the background, and putting together their first online course. Because I think that human connections enormously important.
So I mean, you know, the whole purpose of the book is to try to inoculate educators from future hype cycles to try to convince you know, the next time someone comes around and says, like, Oh, it’s going to be AR or VR, it’s going to be, you know, data science, artificial intelligence is going to change everything is to say, well, like that’s, that’s very unlikely to happen. And they’re, and they’re going to be a lot of places that don’t spend resources wisely chasing those kinds of pursuits. So So I mean, one of my answers, your question is like, of course, the tinker’s are going to win now. But that, but you should be cautious, because that’s what I’m rooting for anyway. Thank you.
Scot Osterweil 56:47
Mike, you wanna go?
Mike Sugarman 56:50
Yeah, sure. Apologies, Justin, this is a little too heavy of a question. But it’s something I’m really curious about. So I maybe maybe like a charitable way to assess why the charismatic technology and charismatic technologists are so successful is because they are appealing to these values, which are like renewable, right? democratizing and like fixing inequities. And like, I think, with our mortgage names book is so great at showing and what your presentation could have shown me is like, you know, not just the technology, you know, if you want to fix that stuff, you have to fix in equity and to fix democracy and all that type of stuff. And this is a moment where we’re kind of having this reckoning of like, okay, there are a lot of issues that we have with our system set up a lot of issues of what we expect technology to do. And there are a lot of issues with the people who made a lot of money from technology. So I guess the question is, you know, in a system that has previously assigns the value of certain technologies and education trends to monetary value, but they can get for investors and nonprofits and all that. What might creating a new set of values or going to a more fundamental set of values, while dealing with this technological space look like? Right? Like, maybe we can’t fix we can’t democratize technology with zoom or with Khan Academy, but maybe we still need to democratize technology, what what might that look like?
Justin Reich 58:13
I mean, I think the stance that the skeptics that I find most compelling take his, you know, that the project of education is like funding is a fundamental part of civil society, it should be fundamentally thought of as a public good. It should be, you know, sort of fundamentally democratic and therefore, you know, accruing enormous power to technology firms to be able to influence these environments, no matter how well-intentioned they are, no matter how useful their products are. It’s the wrong people doing it. We, you know, I, you know, I, I think I think it matters a lot. You know, that zoom is a piece of consumer software, I use sold in a publicly traded firm. And scratch was developed in a, in a research laboratory, at a university and then transferred into a non profit entity, which is actually funded in some ways by hedge funds and other things. There’s all kinds of problems there. But But I, yeah, I mean, I think that’s the, you know, what, what you’re what you’re getting at is absolutely sort of a crucial theme of the book, which is that, you know, all of the hard technology doesn’t in and of itself, solve all of the hard problems. There are ways in which technology reveals these problems.
The fact that we can’t get broadband access, we can’t get computers to, you know, literally millions of the 57 million schoolchildren in America is is revealing exacerbating the same time but revealing new kinds of inequalities as well. So I you know, I’m hopeful that I’m hopeful that the moment leads to, you know, I more than anything else, sort of social movements that demand that we do more for children and their families and our society. And I hope that we look at them through these lens of technology. But the problem that skeptics have right now, is that, you know, like, zoom and canvas are the only games in town Zoom and Google Classroom are the only games that you can’t actually critique and resist them. Perhaps if you were to launch a full-throated critique resistance, you know, sort of Luddite smashing of them, you’d be like, well, now we’re just like mailing paper packets to kids. And that’s pretty terrible, too. I mean, you know, to go back to this idea, it’s actually you know, in other writing, I’ve sort of contrasted skeptics and tinkerers and, and charismatics, and position Tinker, is, is a middle way.
And I, you know, there’s, there’s a lot, there’s a lot of really good education, technology, skepticism that’s out there. I think it is challenged in this particular moment, by the fact that if we want schools to keep operating in a reasonably functional way, online tools, including ones created by, you know, monopolistic corporations are going to be pretty central to that. But it doesn’t, you know, I think it’s part of a broader movement in society of saying, We will not tolerate, we should we should not tolerate these monopolies operating however they want to because they’re monopolies we should regulate them. And in some cases, we may really should be looking at, you know, publicly funded alternatives to them, especially for projects that are as close to civil society of schools. Does that get at some of your issues?
Mike Sugarman 1:01:35
Yeah, absolutely. That’s, that’s great. Thank you.
Scot Osterweil 1:01:39
Great, Kelly.
Kelly Wagman 1:01:44
Hi, um, this is maybe also kind of a big question. But one thing that I wonder about is how you teach topics related to privilege and things like racism to people that are, have already left formal education. And it seems like one way to reach people is through technology. But I also kind of dislike the like, Mr. Graham sighs here’s how you learn about racism. And I’m wondering if you have any thoughts on that? Or if the answer is just you have to have individual conversations with people in real life?
Justin Reich 1:02:21
No, what what, what a great question to ask, because there’s been such a flourishing of that, you know, I think, you know, there are a whole bunch of sort of, like, white privilege syllabi by and, you know, you know, Google Docs and reading clubs and other kinds of things that have been generated in various kinds of ways. You know, I mean, and so of it in, in media, that’s not explicitly educational, you know, the New York Times put out a fabulous podcast with through cereal called the nice white parents, which is a terrific five episode, you know, investigation of those topics.
And, you know, in that one of my colleagues at MIT is a professor named Peter Senge, at the MIT Sloan School of Management. I mean, he wrote this book called The Fifth Discipline. And he defines really successful organizations as learning organizations, as organizations in which the process of getting better at things have endured in doing your day to day jobs in performing the function of your firm, you should also be creating opportunities for all of the actors in that firm to learn these issues of you know, anti racism, bias, white supremacy, they’re of keen interest to corporate America, who are generating all kinds of learning experiences, you know, they’re they’re probably millions of Americans who in their workplace, you know, are privileged to participate in are subjected to depending upon their point of view and the quality of the these things, sort of learning experiences.
So I yeah, I’m, I’m quite interested in those kinds of questions. And when you, you know, and part of the reason why I stay in education technology is like, I just don’t know, it seems to me that all kinds of media are going to be central to addressing that challenge. Another challenge that I’m personally really interested in right now is people don’t know how to search effectively online, and to sort truth from fiction. We, my colleague, Sam Wineburg at Stanford, has done research on lots of groups, including middle school students and Stanford freshmen and tenured historians, who by and large are terrible at identifying misinformation and false hoods online. And he’s also studied this one group of people, fact checkers at prestigious new organ news organizations who are not only extremely good at sorting truth from fiction online, but are like quite efficient, and use a series of fairly simple techniques. So I’m interested in this question like, you know, there’s about 3 billion people connected to the internet and we need to teach them all how to do this. We need to teach them in schools. We need to teach in libraries, we need to teach them in their corporations, we need to teach them in senior centers, we need to teach them in civic organizations like how are we going to when you and when you think about the question from that scope, you’re like, well, there’s gonna be some edtech in there somewhere. Because that is a that is a huge, you know, learning goal that we should have for people in our society. That I mean that that to me is that’s the that’s the thing for me that keeps pulling me sort of away from skepticism is just this yawning need for learning felt by billions of people around the world, that it seems like we should be able to figure out how to use these tools to address.
Scot Osterweil 1:05:38
Great, I have a couple of questions in text, I did see someone with a hand up with them put it down. If you do have a question as a past, if you put your hand up, use or use the little tool to put your hand the virtual hands up, I’ll be able to see. But in the meantime, let me get with these questions from the Q&A or from the chat. One was about you mentioned, the technology cannot be expected to work as a switch that people need support from from a community. How do you envision this kind of community to take place in an online environment with MOOCs? Have you seen any platforms today that do a relatively good job?
Justin Reich 1:06:17
Yeah, you know, the simplest answer to that question is that MOOCs don’t provide that support. MOOCs are good for self paced learning. And they are, and most people are not good at self paced learning. And the people who are good at self paced learning tend to have had a formal apprenticeship in the educational system. And so if we want to, you know, sort of support community learning, we should turn to other approaches on technology, I think they’re neat things that have been done, incorporate incorporating MOOCs into, you know, community based systems of learning to have people take them together in libraries, to have them built into school systems in different kinds of ways. But, but I think also to like, it’s important, when we see limits, to recognize them, and say, like, you know, don’t try to solve a problem with a thing that’s not going to work, you know, I mean, maybe keep working, maybe keep doing research and experimenting in different kinds of ways. You know, in the MOOCs that we create, we try to support people in creating those community supports and social learning environments, by encouraging folks to take our courses in groups that take them in learning circles, but we’re not. Because our our learners are teachers, we know that they are embedded in these social institutions that have mechanisms for supporting Community Learning anyway. You know, which is not necessarily the case for people who want to become computer scientists or want to become accountants or data scientists or other kinds of things like that. So you know, it’s like, having having healthy respect for the limits of technology and saying, Oh, that looks more like a social problem than a technology problem.
Scot Osterweil 1:08:06
Another question is, do you see technical innovation in means of awarding learning credit, grades, certificates, diplomas, you see that as having any significant effect?
Justin Reich 1:08:17
You know, the place where I think there’s been the most discussion around this is around some like badging and micro credentials and things like that. That has been an interesting phenomenon to me, because it’s a place where people have been able to generate supply. And demand has not followed, like people have built it and others have not come.
And it strikes me as a place where people, you know, especially for folks who are trying to use some form of micro credential in a labor market, just like fundamentally misunderstood human behavior in the labor market. You know, they’re saying like, what we want to do is like, give people who are hiring or people who are admitting people to graduate programs, like really granular data about people’s abilities. And most people hiring folks do not want really granular data about people’s abilities, they want like very simple summaries that allow them to go through hundreds of resumes at the same time. And, and by the time you get to the sort of two or three candidates that you really want to go into, you don’t want to see a micro credential or badge, you want to see like, actual evidence of that person’s performance, which some micro credentialing systems have. But, you know, I think it was an example of, you know, people saying, like, Well, here’s something it’s possible.
And, you know, if if we could change human nature, then it would allow all these like really kind of interesting things to happen. You could start sort of mixing, matching, you know, microcredentials, from different places or things like that. And it’s not to say that also that, like not all that innovation, there are still spaces for innovation, but also to recognize like, there’s lots of ways the system has already done this work. I mean, MOOC people have have been sort of crowing for a while about like, Oh, we can create these sort of like new micro credentials that are assembled in different ways. This is like a brand new innovation in higher education. But in fact, like in Britain, in, I think the end of the 19th century, they developed junior colleges and community colleges. And they invented a Greek called the associate’s degree. And that was a kind of micro credential, or a stackable credential that built into another kind of degree program.
You know, and in fact, like the heavy lifting of inventing that happened 210 years ago, and there’s, you know, the spaces for innovation that are left are sort of fewer and narrower. Most of what MOOC based degrees have done micro masters and things like that, they’ve kind of they’ve created associate’s degrees. But for people who already have degrees, they upgrade, like easier pathways into master’s degrees. But people have master’s degrees, or for the most part already Athlon already educated. So again, I mean, in the courses that I teach at MIT, especially to undergraduates, you know, the main thing that I try to communicate is that developing effective technologies requires a rich understanding of the social technical systems in which they’ll operate. And so many of the false starts in education technology are because you have people you know, who are really good at programming and react or whatever else it is. And they don’t understand complex social technical systems very well. They don’t understand actors in educational systems very well. And so they build things that don’t work very well. And I mean, that’s one of the joys of sort of teaching in in Comparative Media Studies is just having people who take these things very seriously.
Scot Osterweil 1:11:43
One more moment for I have one last question. From the chat. I wanted to see what anyone else here on panels had a question. And the question in chat is, how could teachers and students use technology without being overwhelmed? in learning and trying new things?
Justin Reich 1:12:03
And that’s a great question. And I like just such a wonderful question of the moment. Because so many people have been thrust in, you know, against their will, to these challenges. And certainly it is, it has been some of the sources of deepest frustration.
I think, particularly for students and families, you know, just feeling overwhelmed by all of the different things you need to learn to participate in school. And, you know, in normal times, you would say, you know, pace yourself. Yeah, I mean, we have all kinds of heuristics that we use to help people address that challenge, we say things like, you know, if you’re a teacher, and you’re thinking about incorporating technology, identify a target of difficulty identifying an area in which you’re teaching something that’s really important to you, that’s really hard to teach, and where you think technology might have some leverage. And through that kind of three part rubric, most faculty can identify some part in their curriculum or syllabus where like, Oh, yeah, I’m not happy at how people learn these things. And I bet there’s a way of doing that better. And that, you know, that’s one pathway for some people that gets them excited about working on that in a way that feels manageable.
The challenge and pandemic times is you still have to do that for everything all at once. And, you know, I mean, my, my main piece of advice there in this moment, is just to, like, show yourself and the other people that you work with a great deal of grace. There, there are lots of conflicts that are happening between teachers and families, between students and teachers, between teachers and school systems. And there because, you know, we have as a country have failed to manage the pandemic. And in this, one sad thing about that is you have lots of local actors getting into conflicts over problems that are created by by broader social systems. So, you know, there’s no magic trick to not getting overwhelmed, pace yourself to the degree that you can, you know, show yourself and the others around you some grace, and but then also recognize, and this is the hopeful piece I keep going back to, if you can find one of these holes where technology peg fits really nicely. It’s wonderfully satisfying, and, and, and builds human capacity in a way that if you’re, if you’re patient and willing to take a sort of tinkerers mind frame and be comfortable with continuous incremental progress.
Then, you know, my colleague Ken Koedinger says that the step change is just what 20 years of incremental progress looks like from a distance. Good if folks are interested in continuing these conversations. There’s a book club that we’re doing a free virtual book club, it’s 3pm on Mondays at failure disrupt.com slash virtual book club and would welcome any of you to drop in for one session a lots of sessions. If you go to the webpage. There’s a whole list of guests and other kinds of things that are there. If people have other questions you can find me on Twitter at @bjfr or MIT and other folks know how to find me Thanks for some some great questions. And thanks to Scott and Eric and Andrew for hosting.
Scot Osterweil 1:15:07
Thanks very much, Justin. And thanks, everyone for coming. We had a great turnout. And we look forward to seeing as many of you as possible next week when Jing Wang will be presenting. So thanks. Thanks everyone again
