Learning in
Interactive Environments: Prior Knowledge and New Experience
Jeremy Roschelle
University of Massachusetts, Dartmouth
This article
summarizes research on the roles of prior knowledge in learning.
Educators often focus on the ideas that they want their audience
to have. But research has shown that a learner's prior knowledge
often confounds an educator's best efforts to deliver ideas
accurately. A large body of findings shows that learning proceeds
primarily from prior knowledge, and only secondarily from the
presented materials. Prior knowledge can be at odds with the
presented material, and consequently, learners will distort
presented material. Neglect of prior knowledge can result in
the audience learning something opposed to the educator's intentions,
no matter how well those intentions are executed in an exhibit,
book, or lecture.
Consider
a hypothetical book on wool production in Australia. Australian
ranchers raise sheep in an extremely hot desert climate. The
sheep are raised to have wool so thick that without yearly
trimmings the sheep would be unable to walk. To many children,
these facts together are absurd. Children think wool is hot;
if you put a thermometer inside a wool sweater, the mercury
would go up (Lewis, 1991). Wouldn't sheep grow more wool in
cold places where they need to stay warm? Is wool hot because
the sheep absorb the desert warmth?
Alternatively,
consider a hypothetical exhibit on fish schooling. Fish follow
each other in close formation that looks highly organized.
But no single fish is the leader, and none of the fish know
how to command the others. Many people assume that any organized
system is the result of a centralized planner who directs the
others. They think "there must be an older fish, who is smarter
than the rest, and who leads the school. If marine biologists
believe otherwise, well I guess its true, but I'll never be
a marine biologist!"
Then again,
consider a hypothetical lecture on jazz. Upon a first listening,
one might hear the music as ugly, chaotic, and meaningless- "its
just a lot of notes." Many years later, same music provides
a rich and rewarding experience, and with more listening, yet
more difficult music becomes accessible. How can you learn
jazz if all you understand is classical music or pop?
To help
people make the most of a new experience, educators need to
understand how prior knowledge affects learning. To the child
who does not yet understand heat and temperature, no quick
explanation can possibly resolve the contradiction between
the hot desert and the warm wool; it takes weeks to years for
this understanding to emerge (Lewis, 1991). The adult who is
unfamiliar with the possibilities of decentralized systems
can't quickly be convinced that schooling fish have no leader
(Resnick, 1992) - and instead they may be alienated from the
setting. There is no way to give the first-time jazz listener
the epiphany available to more practiced ears. Prior knowledge
determines what we learn from experience.
Prior knowledge
also forces a theoretical shift to viewing learning as "conceptual
change." (Strike & Posner, 1985; West & Pines,1985). Previously
learning was considered a process of accumulating information
or experience. Prior knowledge is the bane of transmission-absorption
models of learning. Mere absorption cannot account for the
revolutionary changes in thought that must occur. The child
simply can't absorb knowledge about wool, because prior knowledge
about heat renders incoming ideas nonsensical. One can't assimilate
fish schooling to a centralized mindset; distinct concepts
for understanding decentralized systems must be developed.
Jazz can't be translated into rock; one must cultivate ears
for its unique organization.
On the other
hand, it is impossible to learn without prior knowledge. Eliminating
prior undertanding of heat won't explain why that sweater is
still so nice in the winter, or how thick-coated sheep can
be raised in the desert. The idea of decentralized systems
must be built from some anchor in prior experience. It is easiest
to appreciate unfamiliar music by starting with "crossover" artists
who populate the periphery between jazz and rock or classical
music.
The aspects
of learning, prior knowledge and experience drawn out in these
examples have a solid basis in research on learning. There
is widespread agreement that prior knowledge influences learning,
and that learners construct concepts from prior knowledge (Resnick,
1983; Glaserfeld, 1984). But there is much debate about how
to use this fact to improve learning.
This article
presents a set of research findings, theories, and empirical
methods that can help the designer of interactive experiences
work more effectively with the prior knowledge of their audience.
It focuses on the central tension that dominates the debate
about prior knowledge. This tension is between celebrating
learners' constructive capabilities and bemoaning the inadequacy
of their understanding. On one hand, educators rally to the
slogan of constructivism: "create experiences that engage students
in actively making sense of concepts for themselves." On the
other hand, research tends to characterize prior knowledge
as conflicting with the learning process, and thus tries to
suppress, eradicate, or overcome its influence.
The juxtaposition
of these points of view creates a paradox: how can students
ideas be both "fundamentally flawed" and "a means for constructing
knowledge?" The question cuts to the heart of constructivism:
constructivism depends on continuity, because new knowledge
is constructed from old. But how can students construct knowledge
from their existing concepts if their existing concepts are
flawed? Prior knowledge appears to be simultaneously necessary
and problematic.This version of the learning paradox (Bereiter,
1985) is called the "paradox of continuity" (Roschelle, 1991).
Smith, diSessa, and Roschelle (1993) argue that educational
reforms must include strategies that might avoid, resolve,
or overcome the paradox. Throughout the article, I endeavor
to show how designers can work with prior knowledge despite
its apparent flaws and without succumbing to an irresolvable
contradiction. This requires careful consideration of assumptions
about knowledge, experience, and learning.
The article
is organized in three sections:
In the first
section, I present findings both on how scientists learn, and
on how students learn science. Evidence on scientific conceptual
change leads to a recommendation to view science learning as
refinement of everyday ideas, requiring a long time and in
a rich social context. Consideration of how students learn
science leads to additional recommendations: we should study
successful learning, avoid interpreting prior knowledge in
terms of dichotomies, see prior knowledge as providing flexible
building blocks, and look for long-term transformations in
the structure and coordination of knowledge.
The second
section presents several major theoretical perspectives on
the process of conceptual change. Piaget emphasizes changes
in the structure of prior knowledge. His theory and methods
suggest that designers create tasks that engage learners and
create tension between assimilation and accommodation. Engagement
in physical aspects of a challenging task can lead to reformulation
of intellectual aspects of the task. Dewey emphasizes the conditions
under which inquiry can resolve problematic experience. He
suggests that designers discover that which is problematic
for learners, and establish conditions that support the process
of inquiry: time, talk, and tools. Vygotsky emphasizes the
role of social process in learning, suggesting that new concepts
appear first socially, and only gradually become psychological.
He suggests that designers provide social models of appropriate
activity, enable groups of learners to do more complex activities
than they could handle individually, and use signs to enable
people to negotiate the different meanings they find in social
activity. Perspectives from information processing and situated
learning theories are also briefly discussed in this section.
The third
discussion summarizes some useful empirical methods. Successful
design of interactive learning experiences builds on an understanding
of how learners think. This requires using empirical methods
to uncover prior knowledge. Traditional tests are written from
the experts' perspective, and label learners' differences as "errors." More
modern and sophisticated methods allow educators to discover
and work with the logic of learners' reasoning. These methods
include clinical interviews, think-aloud problem solving, and
video interaction analysis.
Empirical
Findings in Science and Mathematics Learning
Because prior
knowledge is usually specific to a subject matter, it is difficult
to state general facts about prior knowledge across all areas of
human interest. Therefore, this article focuses on one area, science
and mathematics learning, in order to provide a detailed example
of prior knowledge at work.Prior knowledge has been studied more
extensively in science and mathematics than in other areas. While
the specific forms of prior knowledge in art or history may be
different, we can expect that similar issues will arise.
Prior knowledge
can be viewed from two perspectives, that of the accomplished
scientist or, of that of the learner. Let's start with the
scientist.
Science
as Refinement of Prior Knowledge In this section we discuss
the role that prior knowledge plays in thinking of accomplished
scientists. I use the term "scientific knowledge"
broadly here, referring both to "concepts," and also scientists'
modes of perception, focus of attention, procedural skills, modes
of reasoning, discourse practices, and beliefs about knowledge.
It is conventional to think that scientific knowledge is different
from everyday knowledge, and must replace everyday knowledge.
But when we look more closely, it becomes apparent that scientists
reuse metaphors and ideas drawn from prior knowledge. Moreover
we see that this transformation occurs very gradually, and depends
on the social practices of the scientific community. Only over
long periods of time, and through extended conversations with
their colleagues do scientist shape theories that are distinct
from their commonsense roots.
The cartoonist
presents the typical scientist as an Einstein scribbling mathematical
formulae on a blackboard. Study of the scientific process reveals,
however, that science does not always begin with mathematical
abstractions nor empirical findings, but rather with ideas
close to the surface of everyday knowledge. Einstein, for example,
roots his own intellectual development not in mathematics,
but rather in everyday ideas of rigidity, simultaneity, and
measurement (Einstein, 1950; Wertheimer, 1982; Miller, 1986).
Einstein
(1950) said that everyday knowledge provides a huge store of
useful metaphors and ideas. From these, the scientist makes
a free selection of a set of axioms, and thereupon begins constructing
a theory. Einstein thought the origin of his theory might relate
to a childlike exploration of space, and consulted with Piaget
on the possible similarities between his personal intellectual
development and that of children (Miller, 1986). In analyzing
the work of other scientists, philosophers (Black, 1962; Kuhn
1970; Toulmin, 1972) and historians (Miller1 986, Nercessian
1988) emphasize that science is a constructive activity. Its
materials are drawn in part from the familiar images and metaphors
of prior knowledge (Lightman, 1989, Miller, 1986).
If science
draws upon everyday knowledge, why does scientific knowledge
often appear so different from everyday knowledge, both in
its form and content? In traditional accounts, philosophers
searched for a Great Divide that separated scientific from
everyday knowledge, much like the division between sacred and
profane knowledge. If such a divorce could be made, scientific
learning could be cut free of the biases of prior knowledge.
These traditional accounts have not succeeded in establishing
a firm divide between everyday and scientific knowledge.
An alternative
to the Great Divide account comes from the work of sociologists,
historians, and anthropologists who have studied scientific
work (e.g. Latour, 1987; Knorr, 1981). From their inquiries,
we learn that the properties of scientific knowledge arise
from the social practices enacted by specific scientific communities.
Discourse processes transforms prior knowledge into refined
concepts that can be applied consistently by members of the
scientific community. Scientific knowledge is not a type of
knowledge, but rather a refined product, for which prior knowledge
supplied the raw materials and social interaction supplied
the tools.
The preceding
discussion illustrates the contrast between replacement and
re-use. New knowledge does not replace prior knowledge, rather
new knowledge re-uses prior knowledge. Re-use is made possible
by a process in which prior knowledge is refined, and placed
in a more encompassing structure. The more encompassing structure
comes in part from the social discourse norms that prevail
within a community of practice.
The importance
of time and social context become apparent when we consider
how scientists learn. Kuhn (1970) argues that scientific knowledge
does not always progress smoothly, but calls for "paradigm
shifts" that involve large scale conceptual change. To invent
Relativistic physics, Einstein had to depart from the very
foundations of Newtonian science (Einstein, 1961). In paradigm
shifts, the paradox of continuity again arises: how can scientists
formulate a better theory if all they have is a flawed prior
theory?
Analyzing
conceptual change, Toulmin (1972) argues that conceptual change
is not the mere replacement of one theory by another. Conceptual
change occurs slowly, and involves a complex restructuring
of prior knowledge to encompass new ideas, findings, and requirements.
Thus Einstein does not merely replace Newton, he transforms
Newtonian ideas and places them inside a new, encompassing
analysis of space and time. Toulmin emphases that conceptual
change, like normal science, is continual and incremental.
It is mediated by physical tools, and regulated by social discourse.
Only from the distant perspective of history does a paradigm
shift appear as replacement. From a close-up perspective, conceptual
change looks like variation and selection in a interrelated
system of knowledge. Individual scientists vary the meaning
of concepts and the use of methods. Given specific social rules
and a long time over which to operate, selection can result
in large scale changes in concepts.
From this
analysis of the scientific process comes a series of important
lesson for those who study learning: knowledge begins with
the selection of ideas from everyday experience. The construction
of scientific knowledge is a slow, continuous process of transformation
taking place over a long period of time, involving successive
approximation, and only gradually and incompletely becoming "different" from
everyday knowledge.
In general,
learning involves three different scales of changes. Most commonly,
learners assimilate additional experience to their current
theories and practices. Somewhat less frequently, an experience
causes a small cognitive shock that leads the learner to put
ideas together differently. Much more rarely, learners undertake
major transformations of thought that affect everything from
fundamental assumptions to their ways of seeing, conceiving,
and talking about their experience. While rare, this third
kind of change is most profound and highly valued.
These lessons
have three implications for designers of interactive experiences.
First, designers should seek to refine prior knowledge,
and not attempt to replace learners' understanding with their
own. Second, designers must anticipate a long-term learning
process, of which the short-term experience will form an
incremental part. Third, designers must remember that learning
depends on social interaction; conversations shape the
form and content of the concepts that learners construct. Only
part of specialized knowledge can exist explicitly as information;
the rest must come from engagement in the practice of discourse
of the community.
We next
move to the viewpoint of learner. This will stress similar
points, but draw attention to specific difficulties that arise
in trying to interpret learners' prior knowledge. First, we
review data that shows the dominant the paradox of continuity
in science education: science learners need prior knowledge,
but prior knowledge seems to mislead them. Then we present
a guidelines for resolving the paradox by reconsidering assumptions
about learning. These guidelines may help educators interpret
prior knowledge both in science and other areas.
Studies
of Science Learning: Deepening the Paradox Studies of
students' prior knowledge in science and mathematics began
in the 1970s and have since produced a voluminous literature
(see reviews in Confrey, 1990; McDermott, 1984; Eylon & Linn,
1988). Interest in prior knowledge began with the careful
documentation of common errors made by students in solving
physics and mathematics problems. Analysis of interviews
with these students reveals that the errors are not random
slips, but rather derive from underlying concepts.
For example,
when students are asked to explain a toss of a ball straight
up in the air, they describe the motion in terms of an "initial
upwards force" which slowly "dies out," until it is "balanced" by
gravity at the top of the trajectory. Physicists, in contrast,
explain the ball toss in terms of a single constant force,
gravity, which gradually changes the momentum of the ball:
On its way upwards, the momentum is positive and decreasing;
at the top, it is zero; and going down, the momentum is negative
and increasing.
From analysis
of students' thinking, researchers have determined that this "mistaken" explanation
is not peculiar to this problem. Students commonly give explanations
in terms of "imparting force," "dying out," and "balancing"(diSessa,
1993). From these commonsense ideas, students can generate
endless explanations for different situations. In many cases,
these explanations disagree with conventional Newtonian theory.
The text
below examines the complex findings that have emerged from
investigations of students' concepts. Notice that research
tends to deepen the paradox of continuity: as we learn more
about students' prior knowledge, the construction of scientific
knowledge not only seems slow, but also seems increasingly
improbable.
After they
established the existence of prior concepts, researchers investigated
the consequences of those concepts for subsequent learning.
Most studies have looked at the role of prior knowledge in
a conventional science course. The results depend on the nature
of the task used to probe students' learning. If the task is
procedural calculation, students can often learn to get the
right answer independent of their prior knowledge. However,
if the task requires students to make a prediction, give a
qualitative explanation, or otherwise express their understanding,
studies show that their prior knowledge "interferes. diSessa
(1982), for instance, found students who were receiving an "A" grade
in freshman physics at MIT, but could not explain the simple
ball toss problem correctly. Using their prior knowledge, students
often construct idiosyncratic, nonconforming understandings
of the scientific concepts.
The prevalence
of this effect has been widely documented. Halhoun and Hestenes
(1985a & 1985b) found that 30% to 40% of physics students who
pass freshman physics at various universities misunderstood
the concepts. This also has been found at the elementary and
secondary school levels, across both Western and non-Western
cultures around the world. Indeed, some researchers suggest
that 30% to 40% of physics teachers at the secondary school
level misunderstand physics concepts because of their prior
knowledge.
The processes
by which
"misconceptions" arise from a combination of prior knowledge
and instructed subject matter are not unique to Newtonian mechanics.
Children have concepts that differ from scientists in biology
(Carey, 1985; Keil 1979), heat and temperature (Lewis, 1991;
Wiser & Carey, 1983), electricity (Cohen, Eylon & Ganiel, 1983;
Gentner & Gentner, 1983), mathematics (Resnick & Ford, 1981;
VanLehn, 1989), probability (Shaughnessy, 1985), statistics (Tversky & Kahneman,
1983) and computer programming(Spohrer, Soloway, & Pope, 1989),
and encounter difficulties as they interpret the scientific theories
of these subjects. Furthermore, its not just children who produce
mistaken interpretations by combining prior knowledge with instruction.
Consider Tversky & Kahneman's (1982) findings about simple statistics.
They have identified erroneous prior concepts about statistical
phenomena that are widespread among professional psychologists
- scientists who use statistics regularly. For example, both
students and scientists suffer from "confirmation bias" that
distorts experience to fit prior theory.
Prior knowledge
exists not only at the level of "concepts," but also at the
levels of perception, focus of attention, procedural skills,
modes of reasoning, and beliefs about knowledge. Trowbridge
and McDermott (1980) studied perception of motion. Students
perceive equal speed at the moment when two objects pass, whereas
scientists observe a faster object passing a slower one. Anzai
and Yokohama (1984), Larkin (1983), and Chi, Feltovich, and
Glaser (1990) studied how students perceive physics problems
and found they often notice superficial physical features,
such as the presence of a rope, whereas scientists perceive
theoretically-relevant features, such as the presence of a
pivot point. Larkin, McDermott, Simon and Simon (1980) studied
students' solutions to standard physics problems and found
that students often reason backwards from the goal towards
the known facts, whereas scientists often proceed forward from
the given facts to the desired unknown. Similarly, Kuhn (Kuhn,
Amsel, & O'Loughlin, 1988) studied children's reasoning at
many ages and found that children only slowly develop the capability
to coordinate evidence and theory in the way scientists do.
Finally, Songer (1988) and Hammer (1991) studied students beliefs
about the nature of scientific knowledge. They found that students
sometimes have beliefs that foster attitudes antagonist to
science learning.
In summary,
prior knowledge comes in diverse forms. It affects how students
interpret instruction. While it may not prevent them from carrying
out procedures correctly, it frequently leads to unconventional
and unacceptable explanations. Prior knowledge is active at
levels ranging from perception to conception to beliefs about
learning itself. Moreover, its effects are widespread through
lay and professional population, from young children through
to adults, and from low to high ability students.
Implications
of Prior Knowledge: Learning as Conceptual Change The
overwhelming weight of the evidence has forced informed educators
to fundamentally change the way science is taught. Learners
are more likely to construct an interpretation that agrees
with prior knowledge, and consequently disagrees with the
viewpoint of the teacher. Thus, the effects of prior knowledge
require a change from the view that learning is absorption
of transmitted knowledge, to the view that learning is conceptual
change (Resnick, 1983; Champagne, Gunstone, & Klopfer, 1985).
Over time, learners need to accomplish the rarest form of
change, a paradigm shift in their basic assumptions about
the natural world, and the accompanying ways they see, conceive,
and talk about the world. Conceptual change is a process
of transition from ordinary ways of perceiving, directing
attention, conceptualizing, reasoning, and justifying. Slowly
learners transform prior knowledge to accommodate new scientific
ideas (Posner, Strike, Hewson, & Gertzog, 1982).
Most of
the data on science learning stresses differences between prior
knowledge and scientific knowledge, rather than commonalties
(Smith, et al, 1993). This has had an unfortunate consequence:
rather than making education seem easier, it now appears to
be impossible. Teachers get the impression that students need
prior knowledge to learn new concepts, but prior knowledge
misleads students to unconventional interpretations of concepts.
Moreover, as the perception of a gap has increased, the metaphors
used to describe the learning process have become more adversarial:
prior knowledge must be confronted, challenged, overcome, replaced,
eradicated, or destroyed in order for new knowledge to take
its place. Educators celebrate students' constructive capabilities,
and then roll out the heavy artillery to destroy it. The weight
of the evidence makes paradox of continuity appear as a gaping
void- there seems to be no bridge from prior knowledge to desired
knowledge, with many apparent pitfalls along the way.
Undoing
the Paradox of Continuity in Science Learning Smith et
al. (1993) recently investigated the paradox of continuity
that arises in science education research. They suggest a
interpretative theoretical framework that accepts the flawed
character of some prior knowledge, but still gives it a positive
role. The gist of their argument is that the paradox arises
from implicit biases in theory and method. To undo the paradox,
one must reconsider the implicit assumptions in science learning
research.
First, one
must recognize a bias in the data set. Almost all the data
begins from identifying learning failure-examining a situation
in which students make errors, and then identifying the concept
that causes the error. If we start, on the other hand, by identifying
success, and then investigating the concepts that enable success,
we find an equally strong role for prior knowledge. Prior knowledge
is properly understood not as a causes of errors or success,
but rather as the raw material that conditions all learning.
Second,
biases in research methodology tend to produce "attributes" of
prior knowledge which might be better understood as "attributes
of the learning task." For example, prior knowledge is said
to be resistant to change by conventional instruction. Students
might be resisting the learning experience, and not the knowledge.
For example, most conventional science courses focus on manipulating
mathematical expressions that refer to idealized situations,
i.e. a frictionless plane. We should not expect such an abstract
experiences to enable much change in familiar concepts of motion.
When learning experiences are more concrete, related to familiar
situations and interactive, "resistance" often disappears,
and students construct new concepts quickly. Prior knowledge
and conventional instructed knowledge may not be in conflict,
but rather may be ships passing in the night.
Likewise,
research methods that compare expert and novice performance
tend to characterize their findings in dichotomies. For example,
Larkin (1983) suggests that scientific knowledge is abstract,
whereas prior knowledge is concrete. Other popular dichotomies
are general vs. superficial, theoretical vs. familiar, and
structural vs. superficial. A methodology based on dichotomies
is well suited to sorting objects onto a bipolar spectrum,
but is not well suited to analysis of how emergent wholes integrate
pre-existing parts. For example, dichotomy-based methods mistakenly
assert that science is abstract, and cannot identify how scientific
knowledge successfully coordinates both concrete and abstract
elements. A bias to dichotomies obscures the continuing roles
prior knowledge plays in a more encompassing knowledge structures.
Third, one
must be careful about the status that is attributed to prior
knowledge. Researchers have termed prior knowledge "preconceptions." "alternative
conceptions," "naive conceptions"
"misconceptions" as well as "naive theories" and "alternative
theories." Each term is loaded with theoretical connotations,
that may be quite misleading and inaccurate, even if unintentionally
so.
Terms that
ascribe the status of a "theory" to prior knowledge are particularly
misleading. For example, some researchers have drawn analogies
between students ideas and historical theories, such as medieval
impetus theory (McCloskey, 1983). However, children are not "short
scientists" nor are ordinary adults "medieval scientists." All
people, including scientists, build knowledge from a pool of
familiar metaphors like "balancing" and "dying out." This pool
of metaphors is not structured like a theory; it is not necessarily
consistent, complete, or deductively sound. Rather it is a
loose aggregate of useful ideas that can be flexibly applied.
Although children and ordinary adults sometimes produce explanations
that sound like medieval theory, they do necessarily hold their
knowledge in the same regard that a scientist holds a theory.
Terms that
focus on the mistaken or alternative status of prior knowledge
are also misleading. Prior knowledge can produce mistakes,
but it also can produce correct insights. Sometimes the same
element of prior knowledge can provide both an incorrect alternative
to one theory and be a component of a correct theory in another
topic area. For example, consider the common idea of "force
as a mover," which holds that an applied force results in a
proportional velocity (diSessa, 1983). This is often misapplied
to situation in which a constant force acts on a frictionless
object. Conventional electromagnetism texts, however, assert
that "an electron moves with a velocity proportional to the
applied electromotive force." Thus
"force as a mover," can be either a misconception or a sanctioned
modeling concept, depending on the context of use. The consequence
of such observations is that educators should treat prior knowledge
as a store of generative metaphors, not a collection of wrong
theories. Prior knowledge is like a set of building blocks, and
not like an enemy fortress.
Fourth,
one must beware of a reductionist bias in theorizing about
prior knowledge. In general, research has focused on identifying
a very small number of knowledge elements and attributing great
power to each. Studies of science learning, to the contrary,
remind us is that scientific thinking is comprised of many
diverse components. Learning can occur by recontextualizing,
re-prioritizing, or refining the parts. For example, many "misconceptions" are
correct elements of knowledge which have been over generalized.
By specifying a narrower range of situations, the concepts
become "correct." In mathematics, for instance, students often
have the misconception that the x-intercept of a line is equal
to the inverse of the "b" term in equations of the form "y
= mx + b." This concept is correct, but only in the case where
the slope of the line is 1 (Moschkovich, 1992). One step in
refining knowledge is adjusting the context in which the knowledge
is applicable.
Similarly,
as students learn science, knowledge elements change in priority
(diSessa, 1993). For example, we ordinarily think of surfaces
as rigid. To understand the normal force, however, we must
lower the priority of rigidity and raise the priority of springiness.
In analyzing a book on a table, for instance, the scientist
sees a heavy object compressing the surface of the table slightly,
giving rise to a restoring force upwards. Thus the scientist,
while understanding that books and tables are mostly rigid,
gives a higher priority to springiness. Both springiness and
rigidity are commonsense concepts; to accommodate Newtonian
theory, only their relative priority shifts.
Likewise,
Roschelle (1991) investigated how students develop a concept
of vector addition suitable for understanding acceleration.
Relevant prior knowledge for vector addition includes a commonsensical
notion of addition, as well as concepts of pulling, guiding,
and hinging. Through concrete experience over time, students
form a synthetic vector addition concept that draws upon these
initial metaphors, but is considerably more precise and specific.
According to diSessa (1993), science learning involves many
such shifts in generality, priority, and refinement. The net
result is the transformation of a loose aggregate of knowledge
into a crystalline structure of well-established priorities,
tuned to the demands of conventional scientific theory.
In summary,
we see that students quickly acquiring many different kinds
of knowledge, but only slowly acquire the ability to coordinate
and integrate these different sources of understanding. Students
can learn to calculate from mathematical formulas, and can
learn to give qualitative explanations but it takes a long
time to acquire to the ability to coordinate qualitative explanations
with mathematical formulas that represent a theory.
In the previous
section on scientists use of prior knowledge, it was emphasized
that knowledge changes slowly by restructuring, not replacement.
This is equally true for science students. Moreover, to overcome
the paradox of continuity for science learning, we should attend
to several guidelines for interpreting prior knowledge:
Study success,
not just failure, and identify how prior knowledge enables
success.
Use methods that allow observations of students constructing
integrated wholes, not just shifting valences on a bipolar scale.
Be wary of viewing prior knowledge as an enemy fortresses that
is wrong, alternative, or theoretical in character, and instead
see prior knowledge as a disorganized collection of building
blocks.
Expect learning to occur through gradual refinement and restructuring
of small component capabilities in a large, distributed system,
with increasing coordination.
To the list
discussed above, I would add that theories of prior knowledge
tend to have an individualistic and psychological bias. This
bias is partially reflecting in the selection of
"concepts" as a focus of study. On every occasion of concept
use, however, a learner is in a social and physical situation;
these situations powerfully effect the learning that takes place
(Roschelle & Clancey, 1992).
Educational
experiments that work with prior knowledge have realized considerable
success in provoking and supporting conceptual change. Clement,
Brown & Zeitsman (1989) have developed a science curriculum
based on "anchoring analogies" - everyday concepts from which
scientific concepts can grow. Similarly, Minstrel (1989) has
developed classroom techniques for gradually restructuring
students conceptions. White (1993) has developed a computer-based
curriculum called "ThinkerTools" which develops a scientific
concept of motion gradually over several months. White's curriculum
include explicit attention to differences between scientific
discourse and ordinary discourse (e.g. the meaning of "law"),
and organizes a social context that more closely resembles
the collegial environment of scientific work than the authoritarian
classroom. Roschelle (1991) studied students' learning from
similar computer software and concluded that students learn
the scientific concept of acceleration through a series of
gradual transformations of their prior knowledge.
In reviewing
teaching methods that work, Scott, Asoko, and Driver (1991)
note two successful strategies, one based on explicitly working
with conflicts, and the other based on building on correct
prior knowledge. In any educational situation, there is likely
to be some conflict, and some extensions to prior knowledge.
Learners can succeed in conceptual change as long as appropriate
care is taken in acknowledging students ideas, embedding them
in an appropriate socially discourse, and providing ample support
for the cognitive struggles that will occur.
In summarizing
the broad sweep of research, perhaps the most important lessons
are these. First, we must give up the notion of transmitting
knowledge to absorbent minds; learning is a process of conceptual
change. Second, conceptual change is a slow, transformative
process. Rather than rejecting prior knowledge and accepting
instructed knowledge, learners must gradually refine and restructure
their prior knowledge. Third, to overcome the paradox of continuity,
we should study success, avoid dichotomy-based empirical methods,
see prior knowledge as providing building blocks, look for
learning as long-term transformation knowledge into larger,
more systematically coordinated wholes.
Prior Knowledge
in Theories of Learning
Research in
science and mathematics learning has not yet produced a successful
theory of learning, nor are theories available in other subjects.
The current state of the art, as described above, merely suggests
a set of framing assumptions that dissolve the paradox of continuity
sufficiently to allow education to proceed.
But how
does knowledge change and grow? To answer this question, we
must turn to more general theories of learning. Philosophically,
the issue of prior knowledge arises in Epistemology, the study
of justified true belief (Edwards, 1967) Kant was concerned
with identifying certain knowledge. He distinguished between "a
prior" and "a posterior" knowledge.
"A prior" schemata consist of basic structures that enable us
to detect regularities in the environment. Space and time were
Kant's primary candidates for "a priori"
status. Most other knowledge comes from synthetic combination
of schemata with experience.
Most theories
of conceptual change stick with this framework of "a priori" structures
combining synthetically with new experience, though they vary
the notions of schemata, experience, and the construction process
in which schemata and experience come together. They also differ
in emphasis: Piaget emphasizes psychological changes to schemata,
Dewey emphasizes the transformative possibilities in experience,
and Vygotsky emphasizes the role of social interaction in reconstructing
the relationship of structures to experience. In the few short
pages available here present a quick tour of how these theories
treat the issue of prior knowledge.
Piaget:
Developmental Growth of Schemata Piaget's theory (Inhelder & Piaget,
1958; Ginsburg &
Opper 1979; Gruber & Voneche, 1979) concerns the development
of schemata in relation to new experience. Children, like adults,
combine prior schemata with experience. However, children's notions
of space and time qualitatively differ from adults' (Piaget,
1970) 1. Piaget provides a theory of conceptual change that focuses
on the development of schemata from childhood to maturity.
Piaget provides
a characterization of children's knowledge at four stages of
maturity, termed sensi-motor, preoperational, concrete operational,
and formal operational (Corsini, 1994). At each successive
stage, more encompassing structures become available to children
to make sense of experience. For example, Piaget demonstrates
that children cannot perform controlled experiments with variables,
or reason with ratios, before the formal operational stage.
Prior knowledge, in the form of structural schemata, thus play
a determining role in how children make sense of interactive
experience.
In Piaget's
account of conceptual change, knowledge grows by reformulation.
Piaget identifies a set of invariant change functions, which
are innate, universal, and age independent. These are assimilation,
accommodation, and equilibration. Assimilation increases knowledge
while preserving of structure, by integrating information into
existing schemata. Accommodation increases knowledge by modifying
structure to account for new experience. For Piaget, the critical
episodes in learning occur when a tension arises between assimilation
and accommodation, and neither mechanism can succeed on its
own. Equilibration coordinates assimilation and accommodation,
allowing the learner to craft a new, more coherent balance
between schemata and sensory evidence. Reformulation does not
replace prior knowledge, but rather differentiates and integrates
prior knowledge into a more coherent whole.
Piaget influences
educators not only by his theory, but also by his method. He
spent long hours coming to know children's modes of thinking
(using the clinical interview, discussed later). After Piaget,
we must assume that children will make sense of experience
using their own schemata. Yet, we also must carefully interview
children, seeking an understanding of their form of coherence.
Most followers of Piaget are constructivists who cultivate
a deep appreciation of children's sense-making, and design
interactive experiences accordingly.
Piaget generated
many innovative task-settings in which children become involved
in active manipulation of physical objects. Trying to achieve
a goal in physical task can promote conflict between assimilation
and accommodation in the accompanying psychological task. Moreover,
alternative physical actions can suggest different conceptual
operations, and thus opportunities that arise in physical activity
can inspire mental restructuring. Using these insights, Kuhn
et al. (1988) shows that children can learn to coordinate theory
and evidence in a period of several weeks if provided with
engaging, playful, thought-provoking tasks. Harel & Papert
(1991) extend this point by suggesting that the best tasks
for constructing ideas are those in which children have to
build something that works. While "construction" and "constructivism"
are not necessarily linked, they go well together. Dewey's theory,
discussed in the next section, also identifies designing, making,
and tinkering real things as critical to conceptual change.
In summary,
Piaget suggests that learners overcome the paradox of continuity
with the help of slow, maturational processes that operate
when doing a task provokes conflict between accommodation and
assimilation, and support for equilibration between these.
He suggests that designers of interactive experiences invest
the empirical effort needed to appreciate learner's perspective.
From an understanding of this perspective, one can design tasks
that are likely both to attract learners, to provoke disequilibration,
and to support the necessary but difficult work of knowledge
reformulation. Tasks should be simple and direct, with individual
concrete operations mapping closely to the conceptual operations
at stake. Experience in which learners construct a working
physical arrangement are often powerful for constructing knowledge;
for example, the best way to progress past your prior understanding
of a painting might be to try to paint one like it.
Dewey:
The Conditions for Reflective Experience Whereas Piaget
develops a theory of the growth of structuring schemata,
Dewey elaborates the experiential side of learning (Dewey,
1938b). Piaget exposes Kant's "a priori" structures as genetic
variants, not fixed truths. Dewey exposes the problematic
nature of experience, which is not "given" to us either,
but rather is created in our transactions with nature and
with each other, and thus is dependent on the prior knowledge
that we bring to it.
In Dewey's
account of learning (Dewey, 1916; Dewey, 1938a; McDermott 1981),
problematic experience comes to the fore. For Dewey, primordial
experience occurs in a physical and social situation. Moreover,
learners are not "in" a situation like paint is "in" a bucket;
rather experience is an active transaction that coordinates
doing and undergoing (Dewey, 1938b). Even in watching a painting,
we actively direct our gaze, and undergo a transformation of
our field of vision. Experiential transactions have simple
qualities that we can directly apprehend; e.g., they can be
joyful, frightening, tasty, or harmonious.
In most
of life, we proceed smoothly from one transaction to the next,
using and enjoying the objects of our experience. But sometimes,
experience has the quality of being problematic. By this Dewey
means that we feel confused, uncertain, incoherent, unable
to act. We are unable to coordinate prior knowledge and prior
habit to cope with the exigencies of the moment. In the situation
of problematic experience, we can engage a different mode of
life from use and enjoying, which Dewey calls inquiry.
Inquiry
(Dewey, 1938a).is the reflective transformation of perception,
thought, and action, re-unifies experience into a more satisfactory
whole. The process of inquiry involves reflection on experience;
we apply tools like concepts, drawings, and gestures to point
to features of experience that are troublesome. At the same
time, we apply tools to project possible solutions. Through
experiment and reflection, both schemata and perception are
slowly transformed to bring coherence, coordination, and meaning
to our transactions.
Inquiry
involves psychological, physical, and social interaction. Schûn
(1979) gives a good example. A team of engineers was trying
to design a synthetic paint brush, but the paint would not
go on smoothly. One engineer decided to look very carefully
at how a bristle brush works. As he slowly painted, the others
watched. Slowly they saw that the real brush was not like a
sponge. Metaphors of "pumping" and "channeling"
came into discussion to describe how paint flowed smoothly down
the bristles. Over time, the engineers transformed their notion
of painting from absorbing paint, to pumping and channeling paint.
This enabled them to design a successful synthetic brush.
In this
example, we see how a problematic experience involves prior
knowledge. Prior knowledge was invoked both in creating the
original problematic (seeing a brush as releasing paint) and
the new understanding (metaphors of pumping and channeling).
The process of inquiry involves psychological, social, and
physical interaction that gradually enabled the engineers to
transform their puzzlement into a new understanding.
Dewey is
often viewed as a child-centered educator, who emphasized growth
of the child's interest and capabilities over the mandates
of a curriculum. However, Dewey took pains to oppose any attempt
to place a child's prior knowledge and a curriculum's desired
knowledge in conflict or dichotomy (Dewey, 1938b). We should
neither champion children's native desires over the hard-earned
wisdom of disciplines, nor static views into children's minds.
Dewey urged a view of children's knowledge as fluid, flexible,
generative, and unformed. By designing appropriate experiences,
an educator should be able to move from children's interest
and capabilities towards the more stable, definite, and structured
content of organized subject matters. Thus an educators responsibility
is both to enable the child to engage in inquiry, and to guide
inquiry so it leads towards broader participation in the culture
the child is to enter.
Dewey's
life work was concerned with understanding the conditions that
enable inquiry to proceed, and herein lies the most salient
inspiration for designers of interactive experiences. The key
lesson is this: Attend to that which is problematic in an experiential
transaction, from the point of view of the learner, and allow
time and space for inquiry to occur as an activity in its own
right. A secondary concern is provide tools that enable inquiry
to be effective. Inquiry occurs not in the head, but in direct
engagement with the world and with others. To succeed, learners
need ways to sketch and explore ideas and phenomena, and to
test alternatives experimentally. Moreover, language (which
Dewey calls the "tool of tools") can be an invaluable means
for re-describing, re-orienting, and restructuring experience.
Attempts to coordinate one person's understanding with another
gradually shifts idiosyncratic ideas towards a common ground.
Thus educators interested in working with children's prior
knowledge, should look for situations in which that prior knowledge
becomes problematic, and should create three conditions that
enable inquiry to proceed successful: time, tools, and talk.
Dewey overcomes
the paradox of continuity by focusing on the nature of experience.
Under the right conditions, a learner engaged with a problematic
experience can effect a transformation of prior knowledge.
This transformation restructures thought, perception, and action
elements into a more integrated, coherent whole. Over a long
time, with careful guidance, the net result of many local transformations
can be an overall set of ideas and practices approximates the
central core of an organized subject matter.
Vygotsky:
Social Reconstruction of Prior Knowledge Vygotsky developed
his work partially in response to Piaget's neglect of social
interaction. Whereas Piaget emphasizes the maturation of
schemata within the individual, Vygotsky(1986) argued that
advanced concepts appear first in social interaction, and
only gradually become accessible to an individual. Thus Vygotsky
primarily elaborated the role of social interaction in transformation
of prior knowledge.
In one of
his studies, Vygotsky (1986) specifically examined the role
of prior knowledge is science learning. He argued that children
have spontaneous concepts and scientific concepts, and that
these are not in conflict, but rather are part of a unitary
process. In this process, Vygotsky sees spontaneous concepts
growing upwards in generality, preparing the ground for more
systematic reasoning. Simultaneously scientific concepts, which
are introduced by instruction, grow downwards to organize and
utilize the spontaneous concepts. Upon achieving a through
and systematic intertwining, the learner gains both the power
of the abstract (maximum substitutability) and of the concrete
(maximum applicability).
The restructuring
process that the intertwines spontaneous and specialized concepts
occurs in social interaction, and is mediated by sign systems,
such as language and drawing. Whereas Piaget focuses on disequilibrium
among schemata, and Dewey focuses on problematic experiences,
Vygotsky turns our attention to the "Zone of Promixal Development
(ZPD)" (Wertsch, 1985; Newman, Griffith, & Cole, 1989). The
ZPD is formed by the difference between what a child can do
without help and the capabilities of the child in interaction
with others. In this construction zone, the child can participate
in cultural practices slightly above his or her own individual
capability. Successful participation can lead to internalization.
In Vygotsky's account, the primary resources for restructuring
prior knowledge come from culture. Moreover, the restructuring
process itself occurs externally, in social discourse. Children
share, negotiate and try out meanings in social experience,
and adults can shape those meanings by bringing them into the
framework of cultural practice.
Recent translations
of Vygotsky have inspired designers of interactive experience
in several ways. First, the concept of the ZPD suggests that
designers provide "scaffolding"
to enable learners to participate in a more complex discourse
than they could handle on their own (Brown & Ferrara, 1985).
This scaffolding can be in the form of social processes that
manage some of the complexity of a task for learners, allowing
them to participate while focusing only on one aspect. In addition,
educators can engage in "cognitive modeling" whereby they act
out and verbalize a reasoning process that usually occurs only
in an expert's head (Palinscar
& Brown, 1984). Thus learners can acquire reasoning practices
by imitation and apprenticeship (Collins, Brown, & Newman, 1989;
Rogoff, 1990). Finally, Vygotsky inspires designers to create "mediational
means" that enable learners to negotiate the meaning of a concept
verbally (Hickman, 1985). Meditional means can be a graphic notation
system or a set of linguistic conventions that extend students
ability to talk about and act upon the relation between their
understanding and another person's understanding.
Like the
other theorists, Vygotsky overcomes the paradox of continuity
by suggesting that learning coordinates spontaneous and specialized
concepts in a gradual transformative process. Unlike Piaget's
maturational account, Vygotsky sees structure coming from culture
and gradually expanding into individuals psychological repertoire
through social interaction in the ZPD. By scaffolding, modeling,
and negotiating, experienced adults are able to guide learning
so as to bring the learner into a specialized cultural community.
Information
Processing and Situated Learning Piaget, Dewey, and Vygotsky
each developed their theories in the first half of the 20th
century. In the second half of the century, information processing
views have dominated, only recently to be challenged by a
loosely coupled set of ideas called "situated cognition." We
briefly survey the additional resources that these advances
contribute to an understanding of prior knowledge.
Information
processing psychology builds on the metaphor of mind as a computer
of symbolic data (Newell
& Simon, 1972; Posner, 1989). Successful information processing
(IP) models utilize mechanisms similar to those described by
Piaget: accommodation modifies a schema, or assimilation modifies
data to fit an existing schema. However, IP modeling has worked
best in areas where prior knowledge is weakest- in rule-dominated
logic and gaming tasks. Modeling learning in areas were commonsense
is rich has proven to be an immense task. Moreover, the analogy
between minds and computers quickly breaks down where prior knowledge
is concerned: you can reprogram a computer, completely replacing
its existing program with a different one, whereas human minds
must make new knowledge from old. Likewise, computer models have
impoverished capabilities for experience and social interaction.
To those
interested in prior knowledge and learning, the major contribution
of IP is the production of innovative representational systems
and sound scientific methodology for analyzing learning processes.
The relevant methodological contributions of IP are briefly
summarized later in this paper. The representations can help
in two ways. First, they can make it easier to describe prior
knowledge precisely. For example, VanLehn (1989) showed how
the concepts underlying mistakes in addition problems could
be given a precise description. From this specific diagnosis,
a teacher could provide more focused instruction. Second, representations
can be a tool that allows the learner to reflect. For example,
children can use
"semantic networks" to map the associations among ideas before,
during and after learning. Likewise, tree diagrams can help students
understand processes that are hierarchically composed rather
than linearly composed, such as the generation of a geometric
proof (Koedinger & Anderson, 1990). Providing a tool for representing
prior knowledge can enable learners to reflect more systematically
on prior knowledge.
Situated
Learning (Brown, Collins, & Duguid, 1989; Lave, 1988) has emerged
in the last decade as a critique of IP's focus on internal
schemata and neglect of physical and social context. Situated
learning, like Deweyian theory, holds that all learning occurs
within experiential transactions- coordinations between personal
agency and environmental structures. Like Vygotsky, situated
learning also emphasis the social construction of knowledge.
Most striking in relation to the IP accounts, is the overall
conception of learning as enculturation. In place of relations
between schemata and experience, situated accounts focus on
learning in terms of relations between people, physical materials,
and cultural communities (Lave & Wenger, 1989). Knowledge is
developed, shared, and passed on to the next generation by
local communities that maintain a particular discourse or work
practice, such as a craft guild or academic discipline. Growing
ability to participate in a community-based culture has precedence
over the ability to know. In fact, situated learning has relatively
little to say about "prior knowledge" as such, but focuses
instead on how ordinary work and discourse practices can become
specialized, and how identities develop.
In its present
(and quickly evolving) state, situated learning offers a constructive
critique of Kantian-derived conceptions of learning. First,
it reminds us that knowledge and social identity are tightly
intertwined. A person's prior knowledge is part of his or her
personal identity in society. Conceptual change almost always
involves a transformation of identity- the specialization of
concepts about motion not only enables a child to think more
like a scientist, but also allows a child to progress towards
becoming a scientist. Becoming a participant in a community
can be a stronger motivation the gaining knowledge This is
a useful corrective to educators who focus on the "right knowledge" and
forget to ask who a learner is becoming.
Lave and
Wenger (1989) offer the notion of "legitimate peripheral participation" (LPP)
to make this more precise. LPP suggests that "becoming " requires
participation in the activities of a community. However, learners
often cannot participate in the core activities of a specialized
group, e.g. an ordinary person cannot join a scientific laboratory.
Thus learning often occurs on the periphery of the community,
in specialized places that have been legitimized as entry points.
Museums, schools, and clubs (e.g. 4H) can serve this purpose.
LPP guides us to develop interactive experiences that form
part of a legitimate trajectory towards full membership in
a specialized cultural community. Because transformation of
identity and conceptual change both operate gradually over
a long period of time, it is important to specify an overall
trajectory that could enable a learner to move from the periphery
to the core of a community.
At the cutting
edge of current work on prior knowledge, we find researchers
concerned with the mutual interaction of social discourse practices
with constructive, participatory experiences.
How to Investigate
Prior Knowledge
Due to the pervasive
influence of prior knowledge on learning, good designers of interactive
experiences need to cultivate a sensitivity to the different points
of view that learners will bring to an experience. This sensitivity
is best gained by first hand experience with other's points of
view; no description in the literature can fully convey the character
and constitution of a learners' prior knowledge. Fortunately, becoming
sensitive to prior knowledge is not hard to do. One must simply
look and listen closely as learners use your materials. When something
strange and incomprehensible occurs, don't give in to temptation
to brush it aside; take the occurrence as opportunity to learn.
Understanding
prior knowledge is 90% perspiration and 10% method. Standard
tests are useless, because they are almost always written from
the perspective of the expert. Instead, it is crucial to get
learners to talk and then to pay careful attention to what
they say and do. Three specific methods from research community
can be helpful:
Piaget developed
the clinical interview as a method for investigating children's
sense-making. A clinical interview (Posner & Gertzog, 1982;
White, 1985; ) usually involves a task in which the learner
manipulates some physical materials. Good tasks are simple
and focus tightly on the concept at stake. Thus, a strange
set of actions in the task readily indicates a different sensibility.
The interviewer then probes the learner's understanding by
asking questions about things the learner has said or done
and avoiding leading questions. As the interview progresses,
it is often helpful to ask the learner to consider alternatives
to see how stable a particular concept is. A transcript of
the resulting interview provides a great deal of detail about
prior knowledge.
Researchers
in information processing theory have developed the technique
of the think-aloud protocol (Ericsson
& Simon, 1984; Simon & Kaplan, 1989), which collects information
about a learner's problem solving process. The learner is trained
to "think aloud" while they perform on a simple task, like addition.
Thinking aloud means simply verbalizing the stream of consciousness,
and not explaining or justifying actions to the interviewer.
The interviewer does not ask questions, but merely prompts the
learner to "say what you are thinking" whenever the learner stops
talking. Then the learner is given the target problem-solving
task, and recorded on audio tape. The resulting "protocol" can
then be analyzed for evidence of the prior knowledge and differences
in thinking processes (Robertson, 1990).
The situated
learning community is developing techniques for using video
recordings to study prior knowledge in full social and environmental
context (Roschelle & Goldman, 1991; Suchman
& Trigg, 1991; Jordan, in preparation). Typically, a small group
of learners is recorded on video tape as they work on and discuss
a common task. The camera is set to a constant, wide-angle shot
and left unattended, so as to avoid intrusion. Care is taken
to get good audio. When the video is finished it may be put to
several uses. Learners may review the video with an interviewer,
creating an opportunity to interpret their own behavior. In addition,
it is often helpful to watch the video with a multidisciplinary
panel of colleagues; surprisingly diverse interpretations will
often emerge. Finally, the strongest benefit of video is that
when a problematic event occurs, the investigator can review
it repeatedly. With repeated viewing and conscious cultivation
of multiple perspectives, an investigator will begin to sense
each participant's prior knowledge and dispositions.
Conclusions:
Prior Knowledge and Museum Assessment
Prior knowledge
has diverse and pervasive effects on the learning. Museum experiences
cannot eliminate or disable prior knowledge, but rather must work
with it. Thus museums, like all educational institutions, must
come to grips with the paradox of continuity: prior knowledge is
both necessary and problematic. Conceptual change must somehow
resolve, overcome or avoid this paradox.
Prior knowledge
is implicated in both failure and success; thus knowledge is
best seen as raw material to be refined. Instead of assuming
bipolar dichotomies where desired knowledge replaces prior
knowledge, designers should expect learning to occur through
a transformative, restructuring process that produces integrative
wholes that coordinate pre-existing parts. Refinement and restructuring
occurs incrementally and gradually; conceptual change is hard
work and takes a long time.
Museums
are potentially well-positioned as sites for conceptual change.
Museums provide the visitor with opportunities to experience
authentic objects directly. Cognitive confrontations provoked
by interaction with objects are at the heart of Piaget's theory,
as well as Dewey's. Museums allow visitors to learn socially
in small, voluntary groups. Social discourse is the major means
of conceptual change in Vygotsky's theory, as well as the contemporary
views of situated learning. Museums can provide novel and challenge
settings with opportunities for interaction, contemplation,
and inquiry. Dewey focuses attention on the problematic nature
of learning experiences, and the need for educators to anticipate
the resources that learners will need to resolve the conceptual
struggles that arise. Museums can provide intellectual, physical,
and social resources to aid in the resolution of problematic
experience.
But too
often in my experience, museums do not rise to this challenge;
rather than acknowledging and working from the learner's point
of view, museums present an aggressively professional point
of view. Too often exhibit seem to assume that a good presentation
will make underlying concepts obvious, and therefore provide
little or no resources when I find the exhibit problematic:
alien, awkward, confusing, frustrating, inaccessible, incomprehensible,
mysterious, offensive, opaque, strange, or just too exotic.
Too often museums neglect the social nature of visits, and
I find interaction difficult or uncomfortable.
Success,
however, need not be hard to come by. Success begins with cultivation
of the ability to look, listen, and understand the learner's
viewpoint, and to discover the seeds from which knowledge and
identity can grow. Other institutions, especially schools,
do a downright awful job of support conceptual change, as is
well-documented throughout the literature. People are naturally
active, life-long learners. As Csikszentmihalyi points out,
museums need not do much more than provide a high quality experience
that engages prior knowledge in an achievable intellectual
challenge, and help visitors assemble the physical, intellectual
and social resources they will need to succeed. Unlike schools,
museums don't have to make visitors learn on a particular schedule;
museums can focus on catalyzing a spontaneous reaction involving
prior knowledge, authentic objects, social interaction, and
resources for inquiry.
Assessing
long-term success is a more difficult matter. As became clear
in during the conference, museums have goals beyond subject
matter content: encouraging curiosity, caring and exploration;
providing a positive, memorable experience; supporting constructivist
learning processes; and developing a sense of personal, cultural
and community identity. An excessive focus on knowledge can
work to the detriment of these other goals, and miss the importance
of museum learning entirely. Throughout this chapter, I have
argued that dramatic conceptual change is a slow, unpredictable,
difficult process. It is thus inappropriate to expect deep
conceptual change to predictably occur in a single or short
series of visits. Conversely, when deep conceptual change does
occur, it will almost certainly involve resources beyond the
museums control such as books, videos, science kits, classes,
clubs, etc. Assigning partial credit for long-term learning
accomplishments is a dubious business at best. Finally, narrowing
the museum's focus to changes in conceptual content may harm
other, equally worthy goals. For example, curiosity and exploration
may fall by the wayside in an attempt to focus on subject matter,
and personal and cultural identity may become defined primarily
in relation to the community that owns the subject matter,
rather than opening to diverse modes of participation.
Prior knowledge
nonetheless is implicated in all the museums goals. Curiosity,
caring, and exploration begin with what you know now. A memorable
experience reaches unites prior knowledge, present experience,
and future purposes in a coherent way. Constructivist learning
requires attention to the continuity of knowledge. Knowledge
and identity are bound together- we choose personal futures
based on what we know and understand today. Thus in assessing
museum learning, we can neither overemphasize nor ignore prior
knowledge.
This suggests
that long-term museum assessment should focus on how museums
activate visitor's prior knowledge, opening new and effective
roads for long-term learning. Do museums raise visitors awareness
of alternative perspectives? Do visitors formulate personally
relevant questions? Do visitors realize how they can tap their
current knowledge to enter a new field of inquiry? Do museums
provide models of constructive learning processes with which
visitors can go on learning? Do visitors become aware of books,
videos, and other resources that start from what they know
already? Are museums a place where visitors can use prior knowledge
to help their friends and family learn? Do museums provide
a setting for integrating diverse that make a rich understanding?
The many
powerful and poignant stories related at the conference suggest
that museums do activate prior knowledge in these and other
remarkably powerful ways. While assessment won't prove that
museums cause long-term conceptual change, a variety of methods
could bring to light the diverse ways in which museums can
start with access points close to what a visitor knows already
and can open the gate to those modes of inquiry, participation,
and experience which our society values most highly.
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1 Piaget
thus undercut Kant's position that one couldn't reason without
certain prior concepts of space and time. Children have different
concepts that Kant assumed, but can reason nonetheless. Piaget
showed that very fundamental elements of reasoning develop
as children mature. Einstein similarly showed that fundamental
concepts of space and time also must change for physics to
mature. Piaget and Einstein thus substantially extend the consideration
of what changes in conceptual change; children and scientists
alter the very foundations of what they know. Of course, such
broad changes occur very slowly.
Reproduced
with permission, from Public Institutions for Personal Learning:
Establishing a Research Agenda.
© 1995, the American Association of Museums. All rights reserved.
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