Tuesday, January 23, 2007

Liveblogging: ELI Session on "Emerging Educational Technologies and Neomillennial Learning Styles"

with Chris Dede, Timothy E. Wirth Professor in Learning Technologies, Harvard Graduate School of Education

The evolution of education:
-shifts in the knowledge and skills society values
- development of new teaching and learning

The Next Fifteen Years

- The last 15 years: the WWW and more
- Beyond tactical (e.g. blogs, podcasts, wikis, sociosemantic networking) to strategic (transformations in mission)
- "big picture" vision illustrated by leading-edge examples in present

What will we be thinking about tactically 15 years from now? We need to imagine this so we can make good strategic decisions now.

Emerging interactive media empower not only countries and corporations, but also individuals, to collaborate, accomplish, and learn in new ways.

Devices: cell phones, PDAs, HDTV, etc.
Applications: WP, intelligent tutroing systems, educational simulations
Medium: shared virtual environments, interactive TV, WWW
Infrastructure: Internet, phone system, cable and broadcast television, cyberspace

Distributed Work, Cognition and Learning
- Very definition of "information" technology keeps changing.
1940s: huge number crunching machines
later: data processing era w/punch cards
still later: suite of productivity technologies
then: information and web communication technologies
Definition will morph again within the next 15 years.

We now use these for personal experience and exploration, but also for collaboration.

Cognition is now distributed across human minds, tools/media, groups of people, etc.

He collects images of the future--"intellectually kinky videos." Showed Microsoft marketing video from last fall, a takeoff on The Devil Wears Prada. (Trillwing comment: Stupid and not very well done tie-in, though older folks in the room seemed to really enjoy it.)

Book: F. Levy and R. J. Murnane, The New Division of Labor: How Computers are Creating the Next Job Market. Princeton University Press, 2004.

Two concepts from the book:
- Expert decision making - work may be automated, but expert decisions won't be automated
- Complex communications

Evolving toward distributed learning

- guided learning by doing
- apprenticeships, mentoring
- more

"Next generation" interfaces for distributed learning
- world to the desktop: accessing distant experts and archives for knowledge creation, sharing, and mastery
- multi-user virtual environments: immersion in virtual contexts with digital artifacts and avatar-based identities
- ubiquitous computing: wearable wireless devices coupled to sart objects for "augmented reality"

His and his colleagues' research:

Multi-User Virtual Environment (MUVE)

virtual spaces
computer-based agents
digital artifacts

Massively Multi-Player Online Games (MMOGs) and complementary fan fiction (rich learning, identity formation peripherally linked to life)

Learning processes in the games by and large are outstanding, exactly what we'd want to see in any learning situation, tech-based or not: collaborative learning, mentoring, learning by doing, etc.

The content of the games by and large is garbage or, worse, pathological.

Seven years ago, Dede and his colleagues built a virtual environment, immersive and collaborative and game-like. But with deep academic content and higher-order skills.

So far used by 8,000 middle-school students, River City is the resulting environment. Teachers asked that it improve students' science fair projects--students become lost in the transition between problem-solving (classroom) and problem-finding (21st-century skill, outside the classroom).

Showed movie about River City.
- aid hypothesis formation
- assist collaboration
- meet national science standards

Students go back in time to a virtual place called River City. 19th century. Students investigate a virtual town with institutions (hospital, library), houses, and more. Students form hypotheses about illnesses that are sweepng the town. At the end of the project, students compare their research with other teams' findings and they find a web of competing hypotheses.

Target population is bottom 1/3 of students, who don't see themselves as learners in science.

Findings from research:
- enhanced motivation
- reaching learners who don't do well in conventional classroom settings
- learning both sophisticated content and higher-order skills
- building fluency in distributed modes of communication and expression

More info: River City project

It's not the technology that made it work. It was the powerful pedagogical models: guided inquiry learning with active construction of knowledge, collaboration, situated learning (constellations of architectural, social, organization and material vectors that aid in learning culturally based practices)
- apprenticeship (the process of moving from novice to expert within a given set of practices)
- legitimate peripheral participation (tacit learning similar to that involved in internships or residences)

Learning community: a culture of learning in which everyone is involved in a collective effort of understanding
- share and develop a repertoire of resources

How to build distributed-learning communities like this one?
- mostly across distance, sometimes face-to-face
- asynchronous media helpful: convenient participation and deeper reflection
- range of participants' skills and interests goes beyond geographic boundaries

Ubiquitous computing:

- one-to-one student tool ratio
- wireless mobile devices offer approx. 60% of the computer power of laptops of a few years ago at 10% of the cost
- "smart objects" and "intelligent contexts" enable animistic environments with distributed cognition (augmented reality)

Motors invisible to us, but in Victorian era, people were fascinated with motors. 20-30 years ago, people impressed by computers. Today we don't know how many microchips are in our homes and cars. Yet automakers spend more on silicon than steel.

This technology literally goes into the woodwork. Fascinating possibilities.

But negative consequences, too: Minority Report. Negotiating with objects, an animistic environment with distributed cognition. Walking down street where objects greet you--very intrusive.

Yet also some interesting opportunities, e.g. augmented reality.

Location-aware mobile device (pocket PC and GPS device that talks to the PC). Target in 2-3 years is the cell phone. Team walks around and investigates.

Example: Mystery@MIT. Players briefed about rash of local health problems linked to the environment: possibly a poison leaking into the environment. Provided with background informtion and video briefings. Need to determine source of pollution through various means in 3 hours. How? Drilling sampling well, interviewing virtual people, accessing virtual databases, analyzing water samples.

On screen of handheld device is a map of the MIT campus with a blinking "you are here" dot. Other dots on the screen reflect other resources--virtual people, databases, etc. If you walk to one of those places, you come into interaction with that virtual resource. Virtual people might be streaming video files or text files.

Each player on a team is either an environmental scientist, engineer, and reporter. And your role determines what you hear from the virtual resources. What a person says to the reporter, for example, is different from what they say to an engineer. And what they say varies depending upon where you've already been. Students must synthesize to solve the mystery.

Drilling virtual wells: shallow or deep, superficial or in-depth analysis. But sampling methods influence budget, time, accuracy. So students must decide which to use.

Students have created panics on the campus when they were overheard talking about people who had been poisoned. So students cautioned to speak quietly.

Emphasizes importance of discourse to science, combination of desk and field work.

A different model of pedagogy:
- experiences central, rather than information as pre-digested experience (for assimilation or synthesis)
- knowledge is situated in a context and distributed across a community (rather than within an individual: with vs. from)
- reputation, experiences, and accokmplishments are measures of quality (rather than tests, papers)

What we do now to remediate students is what some of us do when we travel abroad: when someone doesn't understand English, we say the same thing twice as loud and twice as slowly. That's exactly what we're going with our students who are failing, and it works just as well.

When you teach with virtual simulations, context and collaboration provide a richer learning experience.

Assumptions about learning
A spectrum of approaches:
sleeping (simple - basic needs, fairly universal)
eating (cultural)
bonding (cultural, psychological, biological, etc.)

We approach learning as if it's sleeping, but it's really more like bonding. We're providing a homogenous environment like a motel room provides for sleeping. A few of us provide learning environments akin to restaurants. But we need to provide contexts like those necessary for bonding. Complexity.

"Millennial" learning styles come out of the world-to-the-desktop interface. But what learning styles (neomillenial) will emerge from a virtual environment interface?

- fluency in multiple media, valuing each for the types of communication, activities, and expressions of power.

- learning based on collectively seeking, sieving, and synthesizing experience, rather than individually locating and absorbing information from the single best source.

"Cyberinfrastructure" from NSF: computing, data and networks, etc. All integrated. Funding coming from NSF.

Potential to transform teaching and learning:
- Content and Research: ubiquitous, pervasive access to resources; real-time data collection through smart sensors managed by virtual collaboratories
- Interactivity and Individualization: single, customizable, personal platform for distributed learning; formating assessment of students' educational gains via microgenetic data.

It's really not about us learning these new things--we need to unlearn our old beliefs and values (traditional pedagogy).

Beyond McLuhan:
- Media shape their messages.
- Media shape their participants.
- Infrastructures shape civilization.

Much easier to imagine dark futures than bright futures. Easy to imagine a future where people let the real world rot around them while they live fantasy lives in a virtual environment. Easy to imagine a world where objects make decisions for us that makes Orwell look like Rebecca of Sunnybrook Farm.

We need to shape this technology to our world while minimizing the side effects.

Q: So far, simulated environments haven't tended to last. They get dated quickly, and higher ed hasn't tended to adopt them. Are we still looking at transient technologies, or will environments such as River City stick?

A: We need to differentiate between virtual environments for entertainment vs. for learning. We need to go beyond novelty experiences that eventually bore us because the novelty wears off. We want our environments to be purposeful.

So yes, technology itself will evolve, but as we learn to design these environments for education, the rewards may be very large, especially for those students who don't usually thrive in a traditional classroom environment.

Q: What about students engaged in a beautiful virtual simulation while their physical classroom crumbles around them?

A: Students still need to go out into the real world to, for example, collect water samples. A virtual simulation is a bridge to real-world engagement, not a substitute for a real-world ecology. Real world is much more complex.

Q: Great expense in creating these environments: what are the best disciplines in which to invest limited resources?

A: Once you've built the virtual world, you can re-use it for different stories, different characters, just as a movie set might be reused. As educators and the gaming world build up a huge digital archive of objects, artifacts, landscapes, etc., it becomes easier, from a technological standpoint, to create new stories. Much more difficult is the intellectual work behind coming up with good stories that support quality learning. These technologies are scalable.

Q: How do we help faculty help students learn to use these technologies so that students are critically engaged users of these technologies?

A: Someone once said it's harder to change a university than move a cemetery, even if those two tasks employ similar skills. It can be hard to change faculty behavior. And yet faculty would be outraged if a physician didn't prescribe antibiotics created after 1991 because that's when she graduated from medical school, or an accountant who used laws and regulation from the 1970s. Yet faculty don't want to adopt new technologies. It helps if faculty have someone working with them who gets the technology. But faculty aren't going to adopt simulated environments if they haven't experienced these worlds themselves, learning how to identify and solve problems collaboratively. And yet most faculty researchers collaborate with one another in virtual research communities that make use of communication, if not immersive, technologies. But this collaborative behavior doesn't get carried back to the classroom.

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