Scot Osterweil: turn the floor
over to Eric Klopfer who's going to introduce today's speaker. Eric Klopfer: 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 term
s 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 comin
g to colloquium
today, Justin. Justin Reich: 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 everyt
hing 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 thi
ng
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
lear
ning 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 transfor
m 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
ed
ucation 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 teac
hers 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 anyth
ing 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 so
I wo
uld 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 vid
eo 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 th
at 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 th
at 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 instruction
al
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 K
han 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, tha
t'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 easie
r 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 u
se 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 st
ances
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
sy
stems, 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 system
s 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 pe
rhaps, 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 curriculu
m 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 envir
onments 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, the
y 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 ent
erprise 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 wi
th 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 educa
tion 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 f
uture. 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 mo
re 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 t
ackle 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 tec
hnologies
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 r
esources 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 dropo
ut 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 a
re 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 teachin
g 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 calcul
ator 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 scr
atch 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 c
ommunities 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 bunc
h 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 d
ifferent 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
circumsta
nces, 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 assignmen
ts. 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
evaluat
ing 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 adva
ntage 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 o
f 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, al
l 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 way
s. 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
se
nse 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 th
at 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 co
nstant 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 sali
ent 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 experienc
es 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: 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: I me
an, 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 w
ith, 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: 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: 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 differe
nt 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 ho
rizon.
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 t
hen 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
sy
stems, 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 pa
rticular 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 t
hem, 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 tea
chers 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: And I see we
have a question from Ámbar. Ámbar Reyes: Hi, Justin. Thank
you for your I was wondering, a question about relate
d 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: 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 so
me 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 yo
u 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
th
ose partnerships with students. Scot Osterweil: We do have some
questions. I can take any hands as they shoot up? Will, you ever Will Freudenheim: 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: Well, I'm always
amazed at the technologists like, you know, there's some
people who just really devoted to the ch
arismatic 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 o
f 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 to
gether 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 groun
dswell 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: Mike, you wanna
go? Mike Sugarman: 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 a
ppealing 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: 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, w
hich
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 k
now,
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: Yeah, absolutely.
That's, that's great. Thank you. Scot Osterweil: Great, Kelly. Kelly Wagman: H
i, 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: 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
loan School of Management. I ean, he wrote this book called
he Fifth Discipline. And he efines really successful
rganizations as learning rganizations, as organizations
n which the process of getting etter at things have endured in
oing your day to day jobs in erforming the function of your
irm, you should also be reating opportunities for all
f the actors in that firm to earn these issues of you know,
nti racism, bias, white upremacy, they're of keen
nterest to corporate America, ho are generating all kinds of
earning experiences, you know, hey're they're probably
illions of Americans who in heir workplace, you know, are
rivileged to participate in are ubjected to depending upon
heir point of view and the uality of the these things,
ort of learning experiences. So yeah, I
'm, I'm quite
nterested in those kinds of uestions. And when you, you
now, and part of the reason why stay in education technology
s like, I just don't know, it eems to me that all kinds of
edia are going to be central to ddressing that challenge.
nother challenge that I'm ersonally really interested in
ight now is people don't know ow to search effectively
nline, and to sort truth from iction. We, my colleague, Sam
ineburg at Stanford, has done esearch on lots of groups,
ncluding middl
e school students nd Stanford freshmen and
enured historians, who by and arge are terrible at
dentifying misinformation and alse hoods online. And he's
lso studied this one group of eople, fact checkers at
restigious new organ news rganizations who are not only
xtremely good at sorting truth rom fiction online, but are
ike quite efficient, and use a eries of fairly simple
echniques. So I'm interested in his question like, you know,
here's about 3 billion people onnected to the internet a
nd we
eed to teach them all how to do his. We need to teach them in
chools. We need to teach in ibraries, we need to teach them
n their corporations, we need o teach them in senior centers,
e need to teach them in civic rganizations like how are we
oing to when you and when you hink about the question from
hat scope, you're like, well, here's gonna be some edtech in
here somewhere. Because that is that is a huge, you know,
earning goal that we should ave for people in our society.
hat I
mean that that to me is hat's the that's the thing for
e that keeps pulling me sort of way from skepticism is just
his yawning need for learning elt by billions of people
round the world, that it seems ike we should be able to figure
ut how to use these tools to ddress. Scot Osterweil: 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
t
he 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: 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 learnin
g 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 su
pports 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: 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: 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. T
hat 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 ar
e 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: 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: And that's a grea
question. And I like just such wonderful question of the mome
t. Because so many people have een thrust in, you know, ag
inst their will, to these chal enges. And certainly it is,
t has been some of the sources of deepest frustratio
. I think, particularly for s udents and famili
es, you know, j
st feeling overwhelmed by all of the different things
ou need to learn to participate in school. And, you know, in no
mal times, you would say, you know, pace yourself. Yeah, I me
n, we have all kinds of heurist cs that we use to help people a
dress that challenge, we say t ings like, you know, if you're
a teacher, and you're thi king about incorporating
echnology, identify a target of difficulty identifying an ar
a in which you're teaching somet ing that's really important to
ou, that's really hard to teach and where you think technology
might have some leverage. And t rough that kind of three part r
bric, most faculty can identif some part in their curriculum
r syllabus where like, Oh, ye h, I'm not happy at how people
earn these things. And I bet th re's a way of doing that better
And that, you know, that's one athway for some people tha
gets them excited about working on that in a way that feels mana
eable. The challenge and pandem c times is you still have t
o
o that for everything all at onc . And, you know, I mean, my, my
main piece of advice there in t is moment, is just to, like, sh
w yourself and the other peop e that you work with a great dea
of grace. There, there re lots of conflicts that ar
happening between teachers an families, between students an
teachers, between teachers and school systems. And there b
cause, you know, we have as a c untry have failed to manage th
pandemic. And in this, one sad hing about that is you have lo
s of
local actors getting int conflicts over problems that
re created by by broader soci l systems. So, you know, there
s no magic trick to ot getting overwhelmed, pace
ourself to the degree that y u can, you know, show yours
lf and the others around you ome grace, and but then also rec
gnize, and this is the hopeful p ece I keep going back to, if y
u can find one of these oles where technology peg
its really nicely. It's onderfully satisfying, and, and,
and builds human capacity in a ay that if y
ou're, if you're
atient and willing to tak a sort of tinkerers mind f
ame and be comfortable with continuous incremental progress
Then, you know, my colleague en kading, er says that the ste
change is just what 0 years of incremental progress
looks like from a distance. Go d if folks are interested in
continuing these conversations There's a book club that we
re doing a free virtual book clu , it's 3pm on Mondays
at failure disrupt.com slash v rtual book club and would wel
ome any of you to d
rop in for on session a lots of sessions. I
you go to the webpage. Ther 's a whole list of guests and
ther kinds of things that ar there. If people have other qu
stions you can find me on Twitt r at @bjfr or MIT and other fol
s know how to find me Thanks fo some some great questions. An
thanks to Scott and Eric and Andrew f Scot Osterweil: 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
Comments
Thanks a lot for sharing.
The prof can talk.............................