A Conceptual Basis for Educational Applications of Virtual Reality
William Winn
Human Interface Technology Laboratory,
Washington Technology Center,
University of Washington.
August, 1993.
Copyright (C) 1993. All Rights Reserved by William Winn.
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I. Introduction.
Virtual Reality (VR) has caught the imagination of many people. Frequent
reports in the popular and technical press describe the hardware and
software that permit people to "enter" a computer-created "world" and
give accounts of what the VR experience is like. Invariably, these
reports end with claims for the applicability of VR to all manner of
activities, including education. This paper discusses the potential
value of VR to education. It does so in the light of research conducted
at the Human Interface Technology Laboratory at the University of
Washington and on the basis of recent developments in cognitive theory
that are relevant to human learning. The case is made that immersive VR
offers very different kinds of experience than those students normally
encounter in school. The psychological processes that become active in
immersive VR are very similar to the psychological processes that
operate when people construct knowledge through interaction with objects
and events in the real world. Such a convergence of learning processes
with experiences permitted by technology is relatively rare and requires
that we rigorously examine both the psychological and the technological
sides of the equation. This paper therefore starts with a description
and analysis of VR. It then describes recent psychological theories of
knowledge construction. Finally it examines the nature of the confluence
of VR and constructivist learning theory -- the "goodness of fit"
between the two, concluding that constructivism is the best basis for
building a theory of learning in virtual environments.
II. Virtual reality.
As a new technology seeks its identity, there is bound to be ambiguity
in early attempts to define it. The roots of the field, at least in its
popular conception, can be traced to the development of head-mounted
devices (HMD's) for use by fighter pilots (Furness, 1989) and for
computed-aided design (Sutherland, 1965). The point of these early
projects was to place participants in environments that provided them
with just the information they needed and with which they could interact
as naturally as they could with the real world. This required: 1) HMD's
with a wide field of view so that objects in the world could be detected
by peripheral and well as foveal vision, ideally subtending a visual
angle of 200 degrees horizontally and 120 degrees vertically (Furness,
1989); 2) tracking the position and attitude of the participant's body;
3) transducers that interpreted participants' natural behaviors, such as
looking and pointing, as commands to the computer; and 4) negligible
delays in the rate at which the virtual environment was updated in
response to participants' movements and actions. These four conditions
are necessary for immersive VR. As a result of total immersion in a
virtual world, participants report a very real sense of being in another
place -- a phenomenon known as "cognitive presence" (Bricken, 1990) --
as well as a conviction that a virtual world is a valid, though
different, form of reality. Recently, the term "Virtual reality" has
been applied more widely (Heim, 1993) to include graphics applications
that allow users to walk through a simulated environment and, possibly,
to interact with objects in it. However, "desktop VR" (e.g. Lavroff,
1992) does not meet the four necessary conditions for immersion
mentioned in the previous paragraph and therefore does not engender
presence. The user interacts with it, as with any other computer
program, by a mouse or keyboard or joystick rather than by looking or
pointing. HMD's and position-tracking are usually not used. Although
this kind of non- immersive VR has a great many potential uses in
education, and costs but a fraction of immersive systems, it offers no
more than a few modest extensions of computer graphics programs. The
following discussion is concerned only with immersive VR.
III. Immersion.
The VR systems that Furness (1986) developed for the Air Force were
designed to simplify the interface through which pilots interacted with
the airplane. The "Super Cockpit" was one in which the pilot could
access the data he needed and could operate some of the aircraft's
controls by performing natural actions, such as looking, pointing, and
touching. The interface was simplified to the point where it became
totally unobtrusive. In fact, for immersive VR, the interface has ceased
to exist altogether (M. Bricken, 1991a). The removal of the interface
between computer and user is a necessary condition for immersion in
VR. The participant "wears the computer" (W. Bricken, 1991), is inside
the data. As a result, participants can interact with the virtual world,
which might be a simulation of some aspect of the real world, an
instantiation of some abstraction that would otherwise only be
accessible as numerical data, or a creation entirely of whim or fancy,
as naturally as they do with the real world. It is largely on the
advantages of the natural interactions that occur when the interface
disappears that many writers have based their endorsements of VR. Two
other less obvious but more profound changes occur as a result of
immersion which are particularly important for education. First, the
subject-object distinction that exists between people and information in
computers, or between students and much of what they learn in school,
disappears (W. Bricken, 1991). Second, immersion permits entirely
non-symbolic interaction with the world. Both of these deserve comment.
First-person experience in virtual worlds.
We know the world in two ways. First, we know the world as a result of
our everyday interactions with it. This knowledge is direct, personal,
subjective and often tacit in the sense that we often do not know that
we know something (Polanyi, 1958). Second, we know the world as it is
described to us by someone else. This knowledge is vicarious, communal,
objective and explicit. We always know when we have acquired this kind
of knowledge, because it has been taught to us. The experiences that
lead to the first, subjective, kind of knowledge are called
"first-person" experiences, experiences and knowledge of the second kind
"third-person" (Clancey, 1993; Searle, 1992). Here is an example. A
first-person account of my listening to a piece of music would express
in some way my enjoyment of the melody and harmony. A third-person
account would include an explanation of how vibrations in the musical
instruments cause sound waves to form in the air, which create
sympathetic vibration of my eardrum, which causes small amounts of
electrical current to flow through my auditory nerve to my brain. I
could, of course, give a third-person account of my first- person
enjoyment of the music by describing it to a friend. However, that
account would be qualitatively very different from my personal
experience. The experiences and actions that arise from first-person
knowledge are normally characterised by an absence of deliberate
reflection. This means that action flows directly out of perception of
the world without the intervention of conscious thought. In fact, most
of what we accomplish in our daily lives is achieved without our
deliberately thinking about it. Heidegger (1962) refers to this
phenomenon as "throwness". We are "thrown along" the busy course of our
lives with no time to reflect on what we do until after the event, if at
all. Lave (1988) and Suchman (1987) present extensive evidence that
thinking in the real world about real-world problems, such as using a
Xerox machine or making a recipe, is non-reflective in this way. People
do not usually plan ahead about how they will solve day-to-day
problems. They simply use what is on hand at the time and attempt to
perform the task. A recipe problem involving liquid measures is
therefore solved very differently from one requiring the measurement of
solid quantities. Even professionals only reflect when a dilemma
confronts them, and even then the reflective act is not dissociable from
action (Schon, 1983, 1987). Winograd and Flores (1986) go further and
imply that, until things go wrong and we are forced to attend to a
problem, reflection gets in the way of action. And Varela, Thompson and
Rosch (1991) propose that all cognition is based on real-time action in
the world, going so far as to claim that perception itself is not
possible without action. Recently, neuroanatomical evidence has been
cited as grounds for removing reflection from the perception-action loop
(Clancey, 1993; Edelman, 1989, 1992). The idea is that connections among
perceptual and motor groups of neurons are "re-entrant". This means
that they are connected bi-directionally and can interact with each
other and simultaneously with new information from the senses, without
the intervention of what Edelman (1992, p. 89) calls a "supervisor" that
summarizes and interprets the information the neural groups send back
and forth. The higher areas of the brain that are implicated in active
thought do not appear to be involved at all. First-person experiences
are therefore natural, non-reflective, private, and predominate in our
everyday interactions with the world. On this view, interacting with a
computer through an interface is a third-person experience. Even though
we may master the keyboard or mouse to a level of skill where we use
them automatically, the information the machine presents always requires
reflection before we respond to it, is always objective, usually comes
from someone other than ourselves, and precludes interactivity on the
basis of natural behavior. We experience the computer as an object "out
there" in the world. The information it gives us is contained in it and
is not directly accessible. It is for this reason that software
designers are frequently concerned, first and foremost, about our mental
model of the system projected by the interface (Norman, 1986), and only
then with the functionality of the program. The interface creates a
boundary around the computer and its information, and establishes the
distinction between us -- "subject" -- and it -- "object". In short, it
defies first-person experiences. As we have seen, however, immersion in
a virtual world effectively removes the interface allowing us to cross
the subject-object boundary that exists between us and the machine
(W. Bricken, 1991). Once this has happened, our experiences in the
virtual world can be of exactly the same quality as our experiences in
the real world. The knowledge they engender is direct, personal,
subjective and often tacit, in other words first-person. Immersive VR
allows us to create from our experiences the kind of knowledge that has
hitherto been accessible only through direct experience of the world,
never through computer interfaces, desktop VR, or any of the
third-person experiences that predominate in school. Non-symbolic
interaction. From my description of first-person and third-person
experiences, it is clear that the latter are symbolic and the former
usually are not. Any medium, like the computer, has its own symbol
system (Salomon, 1979) without which it can convey no information at
all. We read text symbols and pictorial icons from the screen. We are
shown data as charts and graphs. We hear earcons which tell us something
about the state of the system or direct the next step in our interaction
with it. All of these are conventional and have to be learned at some
time or other. In fact, in many school subjects learning the symbol
system of a knowledge domain is a prerequisite to learning its content,
as in mathematics or music. Unfortunately, mastery of the symbol system
is often mistaken for mastery of the content, and teaching stops before
students really "get into" the material. They learn a lot about
Mathematics without really learning Mathematics at all. If mastery of a
symbol system is a necessary, though not sufficient, condition for
learning through third-person experiences, it is not so for learning
through the first-person experiences of immersive VR. Immersive VR
allows students to interact with the world using what W. Bricken (1991)
calls the "natural semantics" of the world. It is perfectly possible,
for example, for students to learn the conceptual basis of Algebra
without learning its conventional symbols (Winn & Bricken, 1992)
provided that the learning experience is direct, personal and
implicit. If students learning Algebra in immersive VR are forced to
symbolize their experiences so that they can be communicated in the
third person -- to a teacher or in a test, perhaps -- the reflection
this requirement imposes gets in the way of the natural course of
learning, just as any unbidden reflection destroys first- person
experience. (Heidegger [1962] calls this "breakdown".) It is therefore
the case that immersive VR can allow students to learn concepts and to
solve problems non- symbolically. Indeed, the symbol system can be
learned subsequently once the concepts have been mastered. However,
knowing the symbol system is neither a precondition nor a catalyst for
learning, an eventuality that is certain to be beneficial to students
who have particular predispositions to learn that are not supported in
third-person symbol-based classroom activities. These observations
anticipate a more extensive examination of educational uses of VR in
section V below. Before dealing with that issue, we first turn to a
review of relevant aspects of psychological theory underlying learning
and instruction.
IV. Learning by Constructing Knowledge.
The chances are that VR would be little more than another educational
gimmick were it not for the fact that the theory that directs the design
and use of technology-based educational systems is currently undergoing
a radical revision. In fact, educational computing has gone through
three generations and, coinciding with the advent of VR, is entering a
fourth. The first generation was shaped by the same enthusiasm for
behavioral theory that gave rise to traditional approaches to
instructional design (e.g. Gagne, Briggs & Wager, 199?; Dick & Carey,
19??). The assumptions underlying this "first generation" of
computer-based education were: 1) Student behavior is reasonably
predictable if enough is known about the intended outcomes of
instruction, the methods it employs and the conditions under which it
occurs (Reigeluth, 1983); 2) The knowledge and skills students are to
master can be reduced, using appropriate analytical techniques, to
"atomic" components (Landa, 1983), the mastery of which will, in
aggregate, produce the intended behavior; 3) Prescriptive instructional
theory is sufficiently reliable for the procedures of instructional
design to ensure that instruction developed by their systematic
application will work effectively without further intervention from
designers or teachers (Gagne & Dick, 1983). Arguments that these
assumptions are seriously flawed have been made on a variety of grounds
(Streibel, 1991; Winn, 1990, 1993). Nonetheless, a great deal of
computer-based education still goes on that follows this
content-oriented approach based on the traditional procedures of
instructional design. The "second generation" of computer-based
education saw something of a shift from the instructional designer's
emphasis on content to the message designer's emphasis on how
information is presented to students (see Fleming & Levie, 1993). This
emphasis arose from the realization that how students process
information has a greater impact on what they learn than the accuracy of
task reduction and the prescription of instructional strategies on the
basis of content. The focus on the design of instructional messages
arose from psychologists' realization that behavioral theory provides an
incomplete account of human learning, leads to inadequate prescriptions
for instructional strategies, and that cognitive theories of learning
and instruction are more satisfactory sources for instructional
designers to draw upon for guidance (Bonner, 1988; Champagne, Klopfer &
Gunstone, 1982; DiVesta & Rieber, 1987; Tennyson & Rasch, 1988; Winn,
1990). The emergence of the second generation got a considerable boost
from the realization that no two students are alike in their
psychological make-up (see Gardner, 1983, 1993) and that sometimes these
differences among individual students are sufficiently important to
require the prescription of instructional methods matched to their
aptitude (Cronbach & Snow, 1977) and their ability (Tobias, 1976,
1989). The "third generation" of computer-based education arose from
the belief that the nature of the interaction between the student and
instruction is a determinant of learning of equal if not greater
importance than content or how information is presented. This
orientation is also strongly grounded in cognitive science. Indeed
cognitive theories, such as Anderson's ACT* (Anderson, 1983), have
formed the basis of just about all attempts to develop highly
interactive "intelligent" computer-based tutors (Wenger, 1987). The
strongest and one of the most recent expressions of this approach is
Merrill's (1991, 1993) "Instructional Transaction Theory" which is based
on the idea that all learning results from an interaction
("transaction") between student and program. From an approach to
computer-based education that relies on an understanding of how students
interact with courseware, it seems, at first sight, to be but a short
step to the assumptions of the "fourth generation", that knowledge is
constructed by the students themselves, not delivered by the
courseware. The idea of knowledge construction is by no means new to
cognitive science. Bartlett (1932) was among the first to propose that
learning occurred as people constructed "schemata" that represented the
world for them. Neisser (1976) extended this idea to suggest that
schemata guide the way people search the environment for information,
causing them to anticipate what they might find there. Today, most
textbooks on teaching and learning describe the tenets of cognitive
science in some detail. And many of the recent theories that deal
specifically with knowledge construction are soundly based in cognitive
theory, for example Spiro et al's (1991) "Cognitive Complexity Theory",
and Bransford et al's (1990) theory of "Anchored Instruction". However,
many "constructivists" are taking the more radical tack of rejecting
cognitive science as a basis for instructional design and technology
(Allen, 1992; Bednar, Cunningham, Duffy & Perry, 1992; Cunningham, 1993;
Streibel, 1991). The emergence of this fourth constructivist
"generation" is driven by a vigorous criticism of the assumptions of
cognitive science. It is in this criticism, and in the theories that are
promoted as the hiers of cognitivism, that the confluence of educational
theory and VR technology is becoming apparent. The accounts of learning
provided by cognitive science are built around the ideas that the mind
works like a computer, and that cognition consists of the mental
manipulation of symbols (Boden, 1988; Jackendoff, 1987; Johnson-Laird,
1988; Pylyshyn, 1984). For example, Marr's (1982) seminal work on vision
is based on the premises that the brain is too complex to understand and
that therefore we must explain cognition by means of computations based
on mathematical functions that purport to model cognitive
processes. (Marr was extremely successful in explaining low-level vision
in this way. The question is whether a computational approach is
appropriate for higher-level processes.) As a second example, Larkin
and Simon's (1987) account of how people process the information in
diagrams desribes a production-system model of how people store and
inspect nodes in an internal information network. The criticism of
cognitive science is aimed particularly at its computer metaphor for
mind and at the inevitable consequence of this assumption, that
cognition is essentially symbol manipulation. You will recognize that
these two grounds for criticism are exactly those that we saw above to
be the reasons why the presence of a computer interface limits students'
experiences in computer-based education to the "third person". The
corollary, of course, is that non-symbolic, non-reflective, first-person
psychological activity that occurs when people interact directly with
worlds, whether real or virtual, has no place in the theories of
cognitive science. This is a fatal omission according to the
constructivists and to critics of cognitive science generally (Dreyfus,
1972; Edelman, 1992; Searle, 1992). Criticism of the dominant paradigm
cannot be taken seriously unless those making it propose a valid
alternative. The constructivists offer a variety of accounts of how
knowledge is constructed and learning occurs. While these accounts have
not yet been drawn together into a unified theory, the following three
assumptions about knowledge construction provide a basis for guiding the
design of learning experiences and for implementing VR. Humans are
informationally closed systems. The work of the biologist Maturana
(Maturana & Varela, 1987; Varela Thompson & Rosch, 1991) has been
particularly influential with some constructivists (e.g. Cunningham,
1993). Maturana proposed that living organisms, including humans, do not
take information in from the outside, but rather react to
"perturbations" in the environment through the adaptation of existing
structures within them. Interaction with the environment therefore does
not add "ingredients" to an organism's physical structure or symbols to
its mental structure, but causes qualititative and quantitative changes
in the structures that already exist. The ability to detect
perturbations and the kind of structural change that they bring about is
determined by the phylogeny of the species and the history of the
individual's previous adaptations. The world as each of us understands
it is therefore the product of structural adaptation to perturbations.
There is no "standard" objective world. It follows that the world each
organism constructs is unique. To give an extreme example, a bat is
equipped to adapt to very different perturbations in its environment
than humans. A world constructed primarily from ultrasonic reflections
from objects in the environment will be very different from one built
from information limited to the visible portion of the electromagnetic
spectrum. As Nagel (1974) has pointed out, even though we may be able to
construct a third-person description of the bat's sensory and
information-processing apparatus, we can never know first-hand what it
is like to be a bat. The same is true among humans. Although we can
communicate with each other, we usually do so symbolically. This means
that my experience of someone else's world can only be my experience of
a description of that world. It is inevitably a third-person
experience. I can never really know the true nature of someone else's
world. This conclusion has been the basis of claims by constructivists
that instructional designers are wrong to assume that they can base
instructional strategies on the analysis of an objective, standard world
(Duffy & Jonassen, 1992) and that evaluation of learning can only tell
us what students appear, or pretend to know (Winn, 1993), not what they
really know. Meaning is negotiated socially. The previous two
assumptions bring constructivism dangerously close to solipsism. If we
are informationally closed and if there is no standard objective world,
then it is tempting to conclude that we cannot ever communicate with
each other. However, we know this is not the case. Communication is made
possible by what Maturana and Varela (1987) call "structural
coupling". Organisms of the same species have basically the same
apparatus for detecting and adapting to perturbations. Also, they
inhabit similar environments and are likely to encounter the same
perturbations. As a result, the history of their structural adaptations
will be similar. Their structures are "coupled", which is why we can
communicate with other humans but not with bats. Communication between
people separated in time or space occurs when we place symbols into the
environment that act as perturbations of other people who share the
environment through structural coupling. However, in spite of structural
coupling, each person's construction of the world is unique with the
result that the symbols I place in the environment will mean different
things to different people in the group. In order to make communication
possible, we therefore have to come to an agreement about what the
symbols mean (Vygotsky, 1978). The negotiation among members of the
group over meaning may lead to compromises and may result in only
temporary agreements. Nonetheless, in practice constructivists
frequently insist on providing opportunities for learning that require
students to work in groups and arrive at a consensus about meaning
(McMahon & O'Neil, 1993). These three assumptions tempt one to conclude
that instruction cannot be designed -- that prespecifying content, or
message format, or the kind of interaction students have with an
instructional system is to no avail because learning takes place
entirely within the student who is impervious to the influence of
instructional strategies. However, the environments within which
students construct knowledge still have to be provided. These
environments may be natural environments. For example, proponents of
situated learning recommend apprenticeships (Brown, Collins & Duguid,
1989; Brown & Duguid, 1993; Lave & Wenger, 1991) and reflective practica
(Schon, 1987) as means for allowing students to construct knowledge from
"authentic" activites. These environments may also be artificial
environments that simulate aspects of the real world which may not be
accessible through direct experience. Zucchermaglia (1993) describes
such artificial environments as "empty technologies", or shells, within
which students, teachers and designers can construct anything they
want. ("Full" technologies are content specific, like computer-based
tutors.) Kozma (1991) makes the point that technologies can create
learning environments that cannot be created using traditional
strategies, and that it is this quality that makes them superior to
other kinds of pedagogical method. The emerging "fourth generation" of
computer-based education is therefore founded on constructivist theories
of learning. With it, the focus shifts from the design of prescribed
interactions, or "transactions" (Merrill, 1993) with the learning
environment to the design of environments that permit students any kind
of interaction the system is capable of. Such environments are
characterized by a potential for interaction rather than by prespecified
instructional transactions. This is precisely what VR affords.
V. VR Applications in Education.
With some exceptions (among them M. Bricken, 1991b; Bricken & Byrne,
1993; W. Bricken, 1990; Winn & Bricken, 1992), educators have not made
the connection between constructivist theories of learning and VR,
thereby missing the opportunity to provide a theoretical basis for
applying VR in education. In this section, I make the case that the
characteristics of immersive VR and the axioms of constructivist
learning theory are entirely compatible and claim that constructivist
theory provides a valid and reliable basis for a theory of learning in
virtual environments. The key to the compatibility of VR with
constructivism lies in the notion of immersion. We have seen that
first-person experiences account for a great deal of our activity in the
world and our learning about it. We have also seen that first-person
experiences occur when our interaction with the world does not involve
conscious reflection or the use of symbols. According to constructivist
theory, knowledge construction arises from first-person experiences that
can never be entirely shared. Immersive VR allows first-person
experiences by removing the interface that acts as a boundary between
the participant and the computer. In this, VR technology is unique. It
alone allows a synthetic experience to capture the essence of what it
really means for a person to come to know the world. Immersion in a
virtual world allows us to construct knowledge from direct experience,
not from descriptions of experience. Any learning that is mediated by a
symbol system, whether text, spoken language, or computer, is inevitably
a reflection of someone else's experience not our own. Any requirement
that we use a symbol system to communicate about the world we have
constructed to someone else can never permit that other person to know
our world as we know it. Constructivist theory describes how first-
person worlds come into being, and argues that the imposition of
symbolic representations for the sake of communication require
negotiation about meaning leading to compromise. However,
multi-participant VR, in which a group of participants inhabit the same
world at the same time, allows the negotiation of meaning to take place
should communication among participants be required. Immersion in a
virtual world allows the same kind of natural interaction with objects
that participants engage in in the real world. If cognition is
non-symbolic and learning intimately tied to action, then it is through
interaction with the virtual world that knowledge is constructed. Papert
and his colleagues (Papert, 1991) use the word "constructionism" to
describe knowledge construction that arises from physical interaction
with objects in the world. Immersive VR permits both physical and
perceptual interactions to occur. To the extent that VR can simulate
the real world, it allows students to learn while they are situated in
the context where what they learn is to be applied. As we have seen, the
case has been made that situated learning is both more relevant and
successful than learning out of context (Brown, Collins & Duguid, 1989;
Lave & Wenger, 1991). Because a virtual environment is computed from
data, it allows the participant three kinds of knowledge-building
experience that are not available in the real world, but which ahve
invaluable potential for ecuation. These concern what I call "size",
"transduction" and "reification". Size. Immersion in virtual
environments permits radical changes in the relative sizes of the
participant and virtual objects. In the real world, an object appears to
become larger as I approach it and smaller as I move away. However,
there are limits to both extremes. There is a point at which I can get
no closer to a physical object and this point sets the object's maximum
apparent size. Likewise, there is a point where an object disappears as
I move away from it. In a virtual world, on the other hand, I can get
infinitely close to and far from objects allowing extremely large
changes in size. For example, rather than bumping into a virtual wall, I
can keep getting closer to it so that smaller and smaller details of the
material from which it is made are revealed. I can see the cellular
structure of the wood panelling, and can even enter the molecules and
atoms of which it is ultimately composed. At the other extreme, I can
"zoom out" from the wall, out of the house, the city, the country and
the planet if I want, while still not violating any of the four
conditions for immersion. (Some readers may be familiar with the film
Cosmic Zoom, produced by the National Film Board of Canada, which
conveys this idea far better than any written description.) The
advantages of such changes of size for education are significant. On the
one hand, it is possible for students to enter an atom, inspect and
replace the electrons in their orbitals, thereby altering the atom's
valence and its ability to combine to form molecules (a project that is
currently under development at HITL). At the other extreme, it is
possible for students to get a sense of the relative sizes of and
distances between the planets of the solar system by flying from one the
other. Transduction. Transducers such as eyephones and earphones are
used in VR hardware to present information to participants, and to
convert participants' behavior into commands to the rendering
software. The notion of transduction discussed here is concerned with
the first of these functions. Transducers are devices that convert
information that is not available to our senses into forms that are. A
depth sounder on a ship bounces sounds that we cannot hear off the
bottom of the ocean that we cannot sea and converts the echos into
digital or analog displays for us to read. HMD's convert data into
images on CRT's and sounds in earphones. But the data from which these
transducers construct visual and auditory displays need not be
originally obtained through the human senses. It is perfectly possible
to construct a world from data that represent the spread of the
Mediterranean fruit fly and to move around a virtual population
distribution superimposed over a virtual California. It is possible to
convert the ultrasonic echolocation data from a bat into lower-frequency
sounds or into visual displays so that we may indeed experience the
world of the bat, albeit in the third person. What is important for
education is that as soon as students put on HMD's, they put on an
infinite array of transducers. They can see the world as if through
infrared or ultraviolet light. They can lay trails of pheromones and
watch the behavior of the moths that they attract. They can journey to
the center of the sun and observe or alter the convection currents that
move material from the core to the surface. They can slow down the speed
of an atom and, like Rutherford, watch what happens when it hits a sheet
of gold foil (another project that is under development at HITL). And
all the time, they are enjoying first-person experiences and
constructing first-person knowledge about objects and events that are
accessible to them in the real world only as third-person descriptions.
Reification. Changes in size and transduction give first-person access
to experiences that students could not otherwise have. Some of these
experiences arise from simulations of aspects of real objects and
events, such as atoms or bats. Others arise from representations in
perceptible forms, through transduction, of objects and events that have
no physical form, such as algebraic equations or population
dynamics. "Reification" is the process of creating these perceptible
representations. Reification stands in contrast to simulation. In
simulations, virtual worlds contain facsimiles of real objects and their
behavior. Their advantage is that students can interact with them safely
and that often virtual simulations are cheaper to build than full-blown
physical simulators. However, it is often the case that the power of VR
is wasted when it is used for simulation. For example, if you enter a
virtual world in which there is a virtual microscope through which you
can look at a virtual drop of water, you gain nothing. Learning about
the microscopic life-forms that live in the droplet is accomplished far
more effectively by using a real microscope in the biology
laboratory. The microscope in the virtual world is a transducer
(revealing to the eyes what would not otherwise be revealed), and the
participant is on the wrong side of it! VR comes into its own when,
through a massive change of size, the participant jumps through the
virtual microscope's eyepiece and into the drop of water, attaining the
same relative size as the microorganisms that live there. At this scale,
the experience is first-person. But then you do not need the microscope
at all. As a general principle, the construction of virtual transducers
with which participants can interact gains you nothing. VR is not used
wisely when it used to create simulations that can be realized by
traditional simulators.
VI. Summary and Conclusion.
This paper has made the following points: 1) Immersive VR furnishes
first-person non-symbolic experiences that are specifically designed to
help students learn material. 2) These experiences cannot be obtained in
any other way in formal education. 3) This kind of experience makes up
the bulk of our daily interaction with the world, though schools tend to
promote third-person symbolic experiences. 4) Constructivism provides
the best theory on which to develop educational applications of VR. 5)
The convergence of theories of knowledge construction with VR technology
permits learning to be boosted by the manipulation of the relative size
of objects in virtual worlds, by the transduction of otherwise
imperceptible sources of information, and by the reification of abstract
ideas that have so far defied representation. This leads to the
conclusion that VR promotes the best and probably only strategy that
allows students to learn from non-symbolic first-person
experience. Since a great many students fail in school because they do
not master the symbol systems of the disciplines they study, although
they are perfectly capable of mastering the concepts that lie at the
heart of the disciplines, it can be concluded that VR provides a route
to success for children who might otherwise fail in our education system
as it is currently construed.
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References
Allen, B. (1992). Constructive criticisms. In Duffy, T., & Jonassen,
D. (Eds.). Constructivism and the technology instruction. Hillsdale,
NJ: Lawrence Erlbaum.
Anderson, J.R. (1983). The architecture of cognition. Cambridge, MA.:
Harvard University Press.
Bartlett, F.C. (1932). Remembering: A study in experimental and social
psychology. London: Cambridge University Press.
Bednar, A.K., Cunningham, D., Duffy, T.M., & Perry, J.D. (1991). Theory
into practice: How do we link? In G. Anglin (Ed.) Instructional
Technology: Past, present and future. Englewood, CO: Libraries
Unlimited.
Boden, M. (1988). Computer models of mind. New York: Cambridge
University Press.
Bonner, J. (1988). Implications of cognitive theory for instructional
design: Revisited. Educational Communication and Technology Journal,
36, 3-14.
Bransford, J.D., Sherwood, R.D., Hasselbring, T.S., Kinzer, C.K., &
Williams, S. (1990). Anchored instruction: Why we need it and how
technology can help. In D. Nix &
R. Spiro (Eds.), Cognition, education and multimedia: Exploring ideas in high
technology. Hillsdale, NJ: Lawrence Erlbaum Associates.
Bricken, M. (1991a). Virtual worlds: No interface to design. In
M. Benedikt (Ed.), Cyberspace: First steps. Cambridge, MA: MIT Press.
Bricken, M. (1991b). Virtual reality learning environments: Potentials
and challenges. Seattle, WA: Human Interface Technology Laboratory
Technical Report HITL-P- 91-5.
Bricken, M., & Byrne, C.M. (1993). Summer students in virtual reality: A
pilot study on educational applications of virtual reality
technology. In A. Wexelblat (Ed.), Virtual reality applications and
explorations. Cambridge, MA: Academic Press Professional.
Bricken, W. (1990). Learning in virtual reality. Seattle, WA: Human
Interface Technology Laboratory Technical Report HITL-M-90-5.
Bricken, W. (1991). Extended abstract: A formal foundation for
cyberspace. In S.K.
Helsel (Ed.), Beyond the vision: The technology, research and business
of virtual reality. (Proceedings of the second annual conference of
virtual reality, artificial reality and cyberspace, San Francisco,
September.) Westport: Meckler.
Brown, J.S., Collins, A., & Duguid, P. (1989). Situated cognition and
the culture of learning. Educational Researcher, 18, (1), 32-43.
Brown, J.S., & Duguid, P. (1993). Stolen knowledge. Educational
Technology, 33 (3), 10-15.
Champagne, A.B., Klopfer, L.E., & Gunstone, R.F. (1982). Cognitive
research and the design of science instruction. Educational
Psychologist, 17, 31-51.
Clancey, W.J. (1993). Situated action: A neuropsychological
interpretation: Response to Vera and Simon. Cognitive Science, 17,
87-116.
Cronbach, L.J., & Snow, R. (1977). Aptitudes and instructional
methods. New York: Irvington.
Cunningham, D. (1993). Tools for constructivism. In Duffy, T., Lowyck,
J., & Jonassen, D. (Eds.). Designing environments for constructive
learning. New York: Springer.
Dick, W., & Carey, L. (1985). The systematic design of instruction
(second edition). Glenview, IL: Scott Foresman.
DiVesta, F.J., & Rieber, L.P. (1987). Characteristics of cognitive
instructional design: The next generation. Educational Communication and
Technology Journal, 35, 213- 230.
Dreyfus, H.L. (1972). What computers can't do. New York: Harper and Row.
Duffy, T.M., & Jonassen, D.H. (1992). Constructivism: New implications
for instructional technology. In T. Duffy & D. Jonassen (Eds.),
Constructivism and the technology of instruction: A
conversation. Hillsdale, NJ: Lawrence Erlbaum Associates.
Edelman, G.M. (1989). The remembered present: a biological theory of
consciousness. New York: Basic Books.
Edelman, G.M. (1992). Bright air, brilliant fire. New York: Basic Books.
Fleming, M.L., & Levie, W.H. (1993). Instructional message design:
Principles form the cognitive and behavioral sciences. (Second edition)
Hillsdale, NJ: Educational Technology Publications.
Furness, T.A. (1986). The super cockpit and human factors
challenges. Seattle, WA: Human Interface Technology Laboratory Technical
Report HITL-M-86-1.
Furness, T.A. (1989). Configuring virtual space for the super
cockpit. Seattle, WA: Human Interface Technology Laboratory Technical
Report HITL-M-89-1.
Gagne, R.M., Briggs, L.J., & Wager, W.W. (1988). Principles of
instructional design. Third edition. New York: Holt Rinehart and
Winston.
Gagne, R.M., & Dick, W. (1983). Instructional psychology. Annual Review of
Psychology, 34, 261-295.
Gardner, H. (1983) Frames of mind. New York: Basic Books .
Gardner, H. (1993). Multiple intelligences: The theory in practice. New
York: Basic Books.
Heidegger, M. (1962). Being and time. New York: Harper and Row.
Heim, M. (1993). The metaphysics of virtual reality. New York: Oxford
University Press.
Jackendoff, R. (1987). Consciousness and the computational
mind. Cambridge, MA: MIT Press.
Johnson-Laird, P.N. (1988). The computer and the mind. Cambridge, MA:
Harvard University Press.
Kozma, R.B. (1991). Learning with media. Review of Educational Research,
61, 179-211.
Landa, L. (1983). The algo-heuristic theory of instruction. In
C.M. Reigeluth (Ed.), Instructional design theories and
models. Hillsdale, NJ: Lawrence Erlbaum Associates.
Larkin, J.H., & Simon, H.A. (1987). Why a diagram is (sometimes) worth
ten thousand words. Cognitive Science, 11, 65-99.
Lave, J. (1988). Cognition in practice. New York: Cambridge University Press.
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral
participation. Cambridge: Cambridge University Press.
Lavroff, N. (1992).The virtual reality playhouse. Corte Madera, CA:
Waite Group Press.
Marr, D. (1982). Vision. New York: Freeman.
Maturana, H., & Varela, F. (1987). The tree of knowledge. Boston: New
Science Library.
McMahon, H., and O'Neill, W. (1993). Computer-mediated zones of
engagement in learning. In Duffy, T., Lowyck, J., & Jonassen,
D. (Eds.). Designing environments for constructive learning. New York:
Springer.
Merrill, M.D. (1991). Constructivism and instructional
design. Educational Technology, 31 (5), 45-53.
Merrill, M.D. (1993). Instructional transaction theory: Knowledge
relationships among processes, entities and activities. Educational
Technology, 33 (4), 5-16.
Nagel, T. (1974). What it is like to be a bat. Philosophical Review, 83,
435-450.
Neisser, U. (1976). Cognition and reality. San Francisco: Freeman.
Norman, D.A. (1986). Cognitive engineering. In D.A. Norman & S.W. Draper
(Eds.), User centered system design: New perspectives on human-computer
interaction. Hillsdale, NJ: Lawrence Erlbaum Associates.
Papert, S. (1991). Situating constructionism. In I. Harel & S. Papert
(Eds.), Constructionism. Norwood, NJ: Ablex Publishing Corporation.
Polanyi, M. (1958). Personal knolwedge. London: Routledge & Kegan Paul.
Pylyshyn Z. (1984). Computation and cognition: Toward a foundation for
cognitive science. Cambridge, MA: MIT Press.
Reigeluth, C.M. (1983). Instructional design: What is it and why is it?
In C.M. Reigeluth (Ed.), Instructional design theories and
models. Hillsdale, NJ: Lawrence Erlbaum Associates.
Salomon, G. (1979). Interaction of media, cognition and learning. San
Francisco: Jossey Bass.
Schon, D.A. (1983). The reflective practitioner. New York: Basic Books.
Schon, D.A. (1987). Educating the reflective practitioner. San
Francisco, Jossey Bass.
Searle, J.R. (1992). The rediscovery of the mind. Cambridge, MA: MIT
Press.
Spiro, R.J., Feltovich, P.L., Jacobson, M.J., & Coulson,
R.L. (1991). Cognitive flexibility, constructivism and hypertext: Random
access instruction for advanced knowledge acquisition in ill-structured
domains. Educational Technology, 31, (5), 24-33..
Streibel, M.J. (1991). Instructional plans and situated learning: The
challenge of Suchman's theory of situated action for instructional
designers and instructional systems. In G. Anglin (Ed.), Instructional
technology past present and future. Englewood, CO: Libraries
Unlimited.
Suchman, L.A. (1987). Plans and situated actions. Cambridge: Cambridge
University Press.
Sutherland, I. (1965). The ultimate display. In Proceedings of the IFIP
Congress, Vol 2., 506-508.
Tennyson, R.D., & Rasch, M. (1988). Linking cognitive learning theory to
instructional prescriptions. Instructional Science, 17, 369-385.
Tobias, S. (1976). Achievement treatment interactions. Review of
Educational Research, 46, 61-74.
Tobias, S. (1989). Another look at research on the adaptation of
instruction to student characteristics. Educational Psychologist, 24,
213-227.
Varela, F.J., Thompson, E., & Rosch, E. (1991). The embodied
mind. Cambridge, MA: MIT Press.
Vygotsky, L. (1978). Mind in society. Cambridge, MA: Harvard University
Press.
Wenger, (1987). Artificial intelligence and tutoring systems. Los Altos,
CA: Morgan Kaufman.
Winn, W.D. (1990). Some implications of cognitive theory for
instructional design. Instructional Science, 19, 53-69.
Winn, W.D. (1993). A constructivist critique of the assumptions of
instructional design. In T. Duffy, J. Lowyck, & D. Jonassen (Eds.),
Designing environments for constructive learning. New York: Springer.
Winn, W.D., & Bricken, W. (1992). Designing virtual worlds for use in
mathematics education: The example of experiential algebra. Educational
Technology, 32 (12), 12-19.
Winograd, T., & Flores, F. (1986). Understanding computers and
cognition: A new foundation for design. Reading, MA: Addison Wesley.
Zucchermaglia, C. (1993). Toward a cognitive ergonomics of educational
technology. In Duffy, T., Lowyck, J., & Jonassen, D. (Eds.). Designing
environments for constructive learning. New York: Springer. Conceptual
Basis for VR. 14.