Collaborative Intelligence, Part 5A: Social Learning

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Del curso dictado por University of Illinois at Urbana-Champaign

e-Learning Ecologies: Innovative Approaches to Teaching and Learning for the Digital Age

83 calificaciones

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University of Illinois at Urbana-Champaign

e-Learning Ecologies: Innovative Approaches to Teaching and Learning for the Digital Age

83 calificaciones

For three decades and longer we have heard educators and technologists making a case for the transformative power of technology in learning. However, despite the rhetoric, in many ways and at most institutional sites, education is still relatively untouched by technology. Even when technologies are introduced, the changes sometimes seem insignificant and the results seem disappointing. If the print textbook is replaced by an e-book, do the social relations of knowledge and learning necessarily change at all or for the better? If the pen-and-paper test is mechanized, does this change the nature of our assessment systems? Technology, in other words, need not necessarily bring significant change. Technology might not even represent a step forward in education. But what might be new? How can we use technologies to innovate in education? This course explores seven affordances of e-learning ecologies, which open up genuine possibilities for what we call New Learning – transformative, 21st century learning: 1. Ubiquitous Learning 2. Active Knowledge Making 3. Multimodal Meaning 4. Recursive Feedback 5. Collaborative Intelligence 6. Metacognition 7. Differentiated Learning These affordances, if recognized and harnessed, will prepare learners for success in a world that is increasingly dominated by digital information flows and tools for communication in the workplace, public spaces, and personal life. This course offers a wide variety of examples of learning technologies and technology implementations that, to varying degrees, demonstrate these affordances in action. -------------------------------- Recommended Background -------------------------------- This course is designed for people interested in the future of education and the "learning society," including people who may wish to join education as a profession, practicing teachers interested in exploring future directions for a vocation that is currently undergoing transformation, and community and workplace leaders who regard their mission to be in part "educative." -------------------------------- Take this Course for Credit at the University of Illinois -------------------------------- This course has the same content and anticipates the same level of contribution by students in the e-Learning Ecologies course offered to graduate certificate, masters, and doctoral level students in the College of Education at the University of Illinois. Of course, in the nature of MOOCs many people will just want to view the videos and casually join some of the discussions. Some people say that these limited kinds of participation offer evidence that MOOCs suffer from low retention rates. Far from it – we say that any level of engagement is good engagement. On the other hand, if you would like to take this course for credit at the University of Illinois, apply here: http://education.illinois.edu/online-offcampus/programs-degrees/ldl-online If you have already taken this course in Coursera, you can prepare a portfolio of work created there and request that this work is taken into account for your University of Illinois course.

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Module 3: Recursive Feedback + Collaborative Intelligence

Two further e-learning affordances are explored in this module: "recursive feedback," or the rapid and repeatable cycles of feedback or formative assessment now available, including machine feedback and machine-mediated human feedback; and the "collaborative intelligence" fostered by the very social nature of Web 2.0 and contemporary e-learning environments.

Collaborative Intelligence, Part 5A: Social Learning8:12

Collaborative Intelligence, Part 5B: Collaborative Learning Dynamics5:47

Collaborative Intelligence, Part 5C: Extrinsic and Extrinsic Motivation6:02

Collaborative Intelligence, Part 5D: Success and Failure in Performance Based Assessments6:02

Conoce a los instructores

Dr William Cope
Professor
Department of Education Policy, Organization & Leadership, College of Education
Dr Mary Kalantzis
Professor
College of Education

[SOUND]

Another area where we believe there

are enormous potentials in these new technologies of

learning is what we call collaborative intelligence.

Again, I wanna emphasize that point of affordance.

The opposite of collaborative intelligence is individual intelligence.

Here's classic individual intelligence.

I watch my video delivered through an e-learning platform.

It's the flip classroom so-called.

Somebody's recorded a lecture for me, and I watch the lecture which they

recorded for me, and then I do a quiz which tries to identify what I've

remembered of that video, or what I've understood of that video.

Okay so here, we've used something very radical, technology, web-delivered,

perhaps.

And we've done something very innovative a flipped classroom, but

in terms of the kinds of intelligence that I'm using,

it's just a traditional idea of individual intelligence.

The stuff I can hold in my head, and demonstrate that I've held in my head.

So here we've got technology and it's doing nothing new.

It's doing same thing that a teacher lecture did, and

it's doing the same thing that a textbook did.

So my question then is, what is collective intelligence?

What is collaborative learning, and what's different about it?

And what I'll do, is I will come back to my example

of students doing a volcano project in the classroom.

So what we're doing is the intelligence that we're demonstrating

when we do that, when we offer that, when we do that project,

is intelligence which is collective in two very important senses.

The first sense is, I couldn't write it if I hadn't sourced a whole lot of stuff,

I found videos, I've read articles, I've searched the web, I've collected stuff.

And don't pretend that anything about volcanos is stuff that's in my head,

it's a social inheritance,

and what it's about is demonstrating my capacity to use that social inheritance.

So the social inheritance is the structure of a scientific report,

the structure of a geographic report and all the evidence,

the empirical matter that I find to put into that which I've collected, right?

So, in a sense, what I've done, it's a unique project,

nobody's ever written this particular project before.

It says something about me.

It says something about my capacities.

It's very much my own work.

But it's also the product of the collectivity,

which is the information resources around us and the conceptual resources that we've

developed around the practices of science, or the practices of geography.

So it's collective in that sense, and don't try and pretend it's individual.

It's about the way in which I source, or recognize that collective inheritance.

It's like the wonderful phrase of Isaac Newton's, which is he said look,

you know, what we do is we stand on the shoulders of giants.

Yes, we've innovated stuff, but we have to recognize that we're standing on other

people's shoulders in all knowledge work, all learning, all intellectual work.

So it's about acknowledging that.

Now, if you do a test which just says, yes I got this answer right.

That assumes that it's your answer, an individual answer it doesn't actually go

back and trace the collective provenance of all knowledge.

So that's the first point.

The second point is, that in these new media environments, we can build highly

collaborative processes of learning, where in fact it's not just your own work.

Remember the old days, where you sort of put your hand like this so

the person beside you wouldn't see your work, right, in the old days.

It's not like that.

It's actually deliberately producing work that others review, give you feedback on.

And the result of that is, by the time you've got feedback, perhaps

from multiple perspective amongst your peers, and then you've done a revision.

The quality of the revision is partly due to the quality of the feedback

you've received, and the quality of other people's work

is partly the result of the feedback you've given them.

So you're in a collaborative process of give and take around knowledge.

Now I would argue that this is exactly the kind of person we need for

the workplace of the near future,

the scientist of the near future, the teacher of the near future.

These are the kinds of people we want to develop,

who can work in these highly collaborative,

constructive relationships with other team members with peers and so on.

So what we've been doing is, now the question then is, okay the final product.

Well whose is it?

Who are we gonna give them out to?

Because it's been a collective process where other people have helped you.

Well, you know, the thing about these e-learning environments via version

controlling, you can actually track exactly all the feedback that was given

and the extent to which you've taken other people's feedback.

Now we might actually then value the extent to which you took

other peers comments seriously, and you took on board their feedback.

And rather than saying, oh you copied something,

that someone else gave you that idea, or you copied it.

We might say, well what a great thing that you took on board this constructive

criticism, and you reworked your work based on that constructive criticism.

And we might say, oh, my goodness that was fantastic

feedback you gave to that other person, and we're gonna value that.

So we're gonna assess not just the work you do individually, but

because we can see all the changes you've made,

we can see all the comments you've made, the change you take onboard.

We can value your work as a collaborative player in a knowledge environment.

So, in a sense, these are these two quite fundamental aspects

of what I call collective intelligence.

Now, this is a really profound shift away from the historical and

traditional, individualized approach to assisted learning,

and even defining what learning is.

All right, just to mention briefly, off on a tangent,

some of my educational heroes, which are sort of on the sidelines.

This particular hero here is Maria Montessori,

a very, very important person in the history of education.

And in a way, a lot of what we're trying to do aspirationally in these learning

environments are ideas that she invented and

thought through at the beginning of the 20th century.

So in a way, what we're doing with technologies now are things that have

always been a bit hard to do.

But in a way, her aspirations back then

things that we now can do somewhat more easily and therefore we should do them.

So what were her ideas?

Well, she worked in very, very poor neighborhoods in Rome in the first years

of the 20th century, and she built up a system of experiential education

where the technologies then were actually artifacts.

So rather than learn stuff off by heart, rather than memorize stuff,

you work with rods, where you concretely felt geometrical concepts.

You had maps of the world where you move the things around,

where students worked in little activity groups.

So what there was around a Montessori classroom,

people probably know this pretty well, but there are different stations,

activity stations where small groups of students work on particular activities.

Now, in the traditional classroom, this wasn't that easy to do.

In fact, it's ideally suited for very young children, and

that's why it was adopted to a large degree with younger children, but

it became impractical for logistical reasons with all the children.

But now what we're saying is that a lot of these ideas around experience,

around group work around active learning that she was devising, and

thinking about over 100 years ago are themes now which we can

do very nicely in our e-learning environments.

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