It's obvious that learning games should
work. Not only as we hear in prognostications from James Gee, Marc
Prensky, and others, but our own intuition tells us (as well as
watching kids), that when learning is done right, it can and should be
fun. Learning should be hard fun.
The
question has always been, how do you systematically, and reliably,
design fun learning? Previous attempts have been pretty hit or miss, at
best. Just cramming game designers and educators in a room hasn't
worked. What can we do?
A lot, I want to suggest, but to do that, I have to tell a wee bit of a story.
I
saw the potential connection between learning and computers as an
undergraduate, and ended up designing my own major specializing in
that. Back then, it was known as Computer-Based Education. My first job
after college was designing and programming educational computer games
for the Apple ][, TRS-80 (Model 1, shudder), etc, first in Basic, then in Forth (FaceMaker and Spellicopter were two of the games I created). It set a theme that has continued in my work.
I
went back to grad school to get a Ph.D. in applied cognitive science,
and then pursued the academic route for a while. Though my passion was
now called instructional technology, I was hired to teach interface
design. I continued to look at what led to learning, but was also
looking at what created engaging experiences (e.g. Brenda Laurel's Computers as Theatre).
At
that time, I was approached by the Australian Children Welfare Agencies
(I was teaching in Sydney) about designing a game to help kids who grow
up without parents learn to live independently. We did so, successfully
enough that it was released (and ported to the web as another student
project, albeit in the original CGI implementation with all the
limitations that implies: http://www.quinnovation.com/quest).
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Web implementation of Quest.
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The
interesting part of this is that in the course of designing the game, a
realization coalesced. I had already begun to identify the significant
components that contributed to an effective learning experience.
Extracted from a wide variety of theories of learning, these were the
elements that surfaced again and again across the theories.
At
the same time, I had also been looking at the elements that led to
engaging experiences. Trolling a wide variety of ideas across theatre,
writing, games, etc, I again found a series of repeated elements.
The
important thing that emerged was an incredible synergy between the two
lists, in fact a perfect alignment: the things that make an experience
engaging are also those that make for effective learning! Learning can be hard fun!
Which
should raise in your minds the question: just what are those elements?
Here is the learning list, expecting that you will know the
counterparts (I use Quest as an example, but the same would hold true for any game you'd use):
Contextualized
- the learning should be in a setting where the learners actions make
sense. A story, if you will. Learners learn best when it's in a
meaningful context. In Quest, you are released into a city, and you have to survive.
Clear Goal
- the learner should have an end state that they are motivated to
achieve. (Note that the goal doesn't have to be obvious at the
beginning, in fact some research suggests the contrary.) Learners are
better able to take action when they have an outcome they know they're
trying to achieve. In the Quest game, you're trying to achieve a stable existence: sufficient money, a decent job, and a place to reside.
Appropriate challenge
- the level of difficulty has to be beyond the learner's capability,
but not so far that the learner can't accomplish the task; learning
happens best in the space just beyond the learner's capability where,
with some effort and support, they can accomplish the task. Learners
learn fastest when the challenge is significant but not impossible. In Quest,
you can't easily get a job; there are few, you need credentials for the
good ones, and if you lie you'll eventually get caught.
Anchored
- the actions that the learner takes have to have a meaningful effect
on the outcome. There can't be meaningless actions by the learner after
which the story proceeds, but instead there have to be real
consequences in the story line of the actions they take. Learners learn
best when they're operating in ways they recognize are meaningful. The
actions you take will use, or provide you with, money to survive on the
streets of Quest.
Relevant
- in addition to the actions taken being meaningful to the story, the
story and actions have to be meaningful to the learner. We need stories
that appeal to their interests and motivations. Learners learn best
when the setting is one they viscerally care about. In Quest, learners are very interested in finding ways to survive in the streets they'll soon be facing.
Exploratory
- the environment has to have a wide variety of possible choices (or at
least a perception of same), and the ability to try different things
and explore the internal relationships. Learners learn best when they
have to make choices and face the consequences of those choices. In Quest,
you can go where you will, and there are contingencies to discover
(e.g. you can sign up for the government's support while you search for
a job, but you can't actually get the money till you open a bank
account).
Active manipulation
- a related facet is having the learners active in exploring those
relationships, and operating on the world in ways that are similar to
the way you operate in the real world and that reflect the story
setting. Learners learn best when there is minimal overhead between
their intentions and the actions taken to achieve them. In Quest
(albeit with its limited interface circa 1995), you have arrows to
navigate, and icons to represent basic actions like asking for a job or
buying food and drink.
Appropriate feedback
- the feedback from the world has to come in a way that makes sense in
the world. They need to know they've acted, even if they don't
immediately get to know the final outcomes of their action. Learners
learn best when they get feedback about how they're doing. In Quest,
there's an explicit representation of the state of your wallet, and
your health (hunger and sleep). There's also a small coaching agent
that can provide hints, and if things get desperate will recommend
actions.
Attention-getting
- the action can't be totally deterministic, there needs to be some
randomness and probability. Total determinism isn't desirable. Learners
learn best when their attention and curiosity is maintained. In Quest,
random events can happen like opportunities to take drugs or have sex,
or getting mugged or having a friend/relative buy you a meal.
None
of this should sound new, it should sound very like the elements you
know go into a game. What should be of interest is that this list
suggests that what you do to design an effective game is also what
makes an effective cognitive (or attitudinal) change!
I've
now been testing that design framework in a series of applications,
mostly for corporate training or higher education (and smaller scale
than full console games) such as a project management game. The lessons
learned include that the principles work, but that there's a lot of
"finesse" behind the application. I've also been finding that the
design approach is learnable, though it takes some time to get up to
speed with the nuances.
James
Gilmore has suggested that we've moved from an information economy to
an experience economy (we pay to have interesting experiences; e.g.
theme restaurants, computer games.), and that the next stage is the Transformation
economy, where you want experiences that change your skill set or
beliefs or understandings of the world. That's what computer games can be, if we have and apply the tools.
Of
course, it's not quite that easy. There's depth behind each of these,
and an associated design process that systematically integrates these
elements. However, knowing that these elements exist and align gives
you an understanding of why: Learning can, and should, be hard fun!
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