Designing Systems to Support Learning Science with Understanding
for All: Developing Dialogues among Researchers, Reformers, and Developers
Andy Anderson
January, 2001
Science education at both the K-12 and postsecondary levels is currently being
reshaped by two long-term trends. One of these is the standards movement,
which seeks to build consensus about goals and methods for science teaching
and encourage their large-scale adoption. These standards are instantiated
in authoritative documents such as the National Science Education Standards
(NSES) and Benchmarks for Science Literacy, as well as
other standards at the state and local levels, teacher proficiency standards,
and so forth. The second trend is the development of information technologies
which provide new resources for science teaching and learning and new opportunities
for economies of scale.
It is clear that these trends are affecting teaching and learning in science
classes. Teachers and professors are changing the content of their courses
and their teaching methods in response to standards. They are using information
technologies to organize their courses, to give students access to resources,
and to create new kinds of "virtual" courses that do not require students
and teachers to come together in the same room at the same time.
It is less clear whether these changes will be improvements. Will these developments
promote student understanding, or will they provide new support systems for
uninspired teaching leading to shallow learning? Will they give students who
are currently marginalized new access to the benefits of scientific literacy,
or will they provide new advantages to already privileged students? Will they
make science teaching richer in resources for sense making, or will they promote
"efficient" ways to deliver conventional content to large numbers of students?
I believe that the answers to these questions will depend in part on the degree
to which work in these trends can be informed by dialogue with research
on science teaching and learning. As I discuss below, the record so far
is mixed at best. The development and implementation of the standards has
been accompanied by some sincere attempts to consult and use research, especially
conceptual change research, but much of the process has involved political
consensus-building in which research and researchers were marginalized. Some
development work using information technologies has used and contributed to
research on science teaching and learning, but many projects have relied mostly
on the instincts and experience of their developers, It is not surprising
that dialogue among these three movements-the standards movement, development
of information technologies, and research on science teaching and learning-is
difficult. Researchers, reformers, and developers often come from very different
backgrounds and use different languages to describe and analyze their work.
I want to make a case, though, that the rewards of such a dialogue are worth
the challenges. The purpose of this paper is to outline two broad sets of
issues around which the current dialogue among these three movements might
productively be deepened and enriched, and to suggest contexts in which that
enhanced dialogue might occur. The paper is written primarily from my perspective
as a researcher who has some awareness of and involvement in the other two
movements. My suggestions about the basis for an enhanced dialogue have three
parts:
- Goals: Participants in all three movements share commitment to a common
goal of learning science with understanding for all. Research
in science studies and science education suggests some basic ideas about
science understanding as sense making about patterns in experience. These
ideas could be used to enrich and deepen our dialogue around this common
goal.
- Challenges: Some fundamental challenges are inevitable for person or system
that attempts to help large numbers of students learn science with understanding.
Science education researchers have explored four challenges that "come
with the territory" of teaching science for understanding for all. These
common challenges could provide a basis for dialogue among people taking
different approaches to teaching science for understanding for all.
- Opportunities for dialogue. Participants in the three movements cannot
stop their current work in order to talk to one another. I suggest some
ways in which dialogue around our common goals and challenges could be
built into research and development activities in which we are already
engaged.
Goals: Learning Science with Understanding for All
Almost everyone involved in science education research and development claims
"learning with understanding for all" as our basic goal. However, our apparent
consensus is based in part on the vagueness of that phrase. Because we can
all attach our own implicit meanings to the phrase, we can all agree that
this is what we want. I would like to suggest some ways in which we might
make the meaning of this phrase more precise and connect it to the research
literature in science studies and science learning. In particular, I want
to argue that we could take "understanding" to mean something like sense-making
about patterns in experience. For me, this phrase captures the
essence both of what scientists do and of what science educators want learners
to do. I will use this section to elaborate on this idea.
The task of science
I would like to start my case with a quote that David Hawkins uses from Niels
Bohr:
The task of science is both to extend our experience and reduce it to order,
and this task represents various aspects, inseparably connected with each
other. Only by experience itself do we come to recognize those laws which
grant us a comprehensive view of the diversity of phenomena. As our knowledge
becomes wider we must always be prepared, therefore, to expect alterations
in the points of view best suited for the ordering of our experience.
There are many things I like about this quote, both as a description of "the
task of science" and as a description of the task of science education. Let
me start with one. In this quote Bohr suggests an epistemological position
that is intermediate between modern empiricism and postmodern relativism.
On the one hand, Bohr does not suggest that through our experience we can
ever fully understand the world as it is. There will always be parts of the
world that are beyond the range of our experience, differences in our ways
of experiencing the world, and differences in our ways of reducing experience
to order. On the other hand, Bohr suggests a way of judging the quality of
theories or world views that moves beyond relativism. As Bazerman suggests,
theories that encompass a more extensive range of experience or more thorough
and thoughtful attempts to reduce that experience to order deserve special
respect.
Western scientific subcultures have been especially successful in extending
the collective experiences of their members and reducing those experiences
to order. This success has been based in part on a set of epistemological
distinctions that are woven into the practice of Western science. In particular,
the program of Western science involves coordinating knowledge claims of three
different types:
- Experience in the material world (data). We
think of the material world as consisting of systems and phenomena that
are the basis for our experience, but we can know these systems and phenomena
only through our interactions with them--through our experience in the
material world. The success of Western science has been based in part
on a decision not to try to account for all experiences in the material
world, but instead to concentrate on experiences that have been verified,
reproduced, described or measured precisely, recorded, and shared--in
other words, data. Thus data are created from selected and refined
experience. Data are created, not merely collected.
- Patterns in experience. Scientific facts, laws,
and generalizations are statements about patterns that scientists see
in their data. Thus pattern finding is an essential scientific
practice, a key step in "reducing our experience to order." These patterns
in experience are the essential links between data and theories.
- Explanations of patterns in experience. Scientific
models and theories are metaphors, or stories, or symbolic systems that
are designed to explain patterns in experience. Although they
can be used to explain individual phenomena, their power lies in the fact
that they provide parsimonious accounts of broad patterns that encompass
many different systems or phenomena.
In pursuing the task of science--both extending our experience and reducing
it to order--members of scientific communities routinely recognize and use
the epistemological distinctions described above. That is, they share common
meanings for key terms such as data, laws, models, and theories, and they
use those terms to organize their professional practices. Thus these distinctions
have been essential to the success of Western science.
There are many important similarities between this view of science and the
science education consensus views as presented in documents such as Science
for All Americans and the National Science Education Standards.
I think, though, that there are three ways in which this view differs in emphasis
or approach from the consensus view. This view presents data creation as active
selection and refinement of experience; it emphasizes the importance of patterns
in experience; and it presents a unified view of scientific practice and scientific
knowledge.
Data creation as active selection and refinement of experience.
The consensus view emphasizes the importance of data and the complex relationship
between data and theories. It is largely silent, however, on the complex epistemology
and creative practice involved in "data collection." In contrast, the science
studies literature reveals the process of creating data to be a complex enterprise
that is intensely controversial in scientific communities. Three core problems
are especially salient. First, scientific communities must separate data
from noise. That is, they must decide which experiences merit their attention
and which experiences they will dismiss as distortions of the "true nature"
of the material world. Standards such as reproducibility and precision play
an important role in this process, but ultimately decisions about which experiences
count as data are negotiated within scientific communities. The second core
problem concerns techniques for data creation. The most precise and
reproducible data rely on methodologies and instruments that are designed
to provide new experiences that extend our senses and create new phenomena
for observation. A third core problem is data representation. Scientists
must invent ways of representing and communicating about their experiences
that allow others to share in those experiences and make patterns apparent.
This is an active, creative, process, not just an exercise in recording and
displaying measurements.
The importance of patterns in experience. The consensus
view emphasizes the distinction between data and theories-these are different
types of knowledge claims that are created and used differently by scientific
communities. However, the consensus view does not emphasize the importance
of pattern-finding practices and their products (e.g., laws, generalizations,
data displays) as ways of "bridging the gap" between data and theories. I
think that this is a mistake. Pattern finding practices lie at the core of
the scientific enterprise, patterns in data are the essential elements that
create coherence and parsimony in scientific knowledge claims; and the applications
of scientific knowledge rely on our ability to find and use the appropriate
patterns.
A unified view of scientific practice and knowledge.
Although the consensus view sees science content, scientific inquiry, and
the nature of science as intimately related-all part of the same big picture-these
domains of scientific understanding tend to be represented separately. They
draw on different bodies of scholarly literature and use different theoretical
frameworks. The view above suggests a way in which we could talk about these
three domains in a coherent and parsimonious way:
- Scientific inquiry consists of the set of practices by which scientific
communities create shared bodies of experiences with the material world,
patterns in those experiences, and explanations for those patterns. In
this view, the "scientific method" is a formalized form of argument. A
research report that includes questions, hypotheses, methods, results,
and conclusions must combine experiences, patterns, and explanations in
a coherent argument that can be understood and discussed by other members
of the scientific community.
- Scientific content consists of the results of the cumulative practices
of scientific inquiry-a body of experiences, patterns, and explanations
that have been accepted by consensus of scientific communities.
- The nature of science is our label for our attempts to understand the
history, nature, and limitations of the cumulative efforts of scientific
communities. What kinds of experiences have scientific communities paid
attention to and what kinds of experiences have they ignored? What are
the historical origins of our present practices and bodies of knowledge?
How can we compare the experiences, patterns, and explanations of Western
scientific communities with those of other communities?
One final note about the task of science. Though the discussion above portrays
scientific practice and knowledge as complex, the goal of sense making about
patterns of experience with the material world is the unifying core of those
practices. Scientific communities engage in collective sense making by creating
coherent systems of experiences, patterns, and explanations.
The task of science education
We include science in the school curriculum because of the success of the Western
scientific enterprise. Scientific communities have devised ways of accumulating
vast stores of experience with the material world, of selecting and refining
those experiences into precise and reproducible data, and of recording, sharing,
and preserving those data. They have been successful in finding patterns in
those data and in developing theories to explain those patterns. We want our
students both to see and use patterns in their own experiences with the material
world and to benefit from the cultural heritage accumulated by their forebears.
Thus Bohr has described the task of science education as well as the task of
science. Science educators should help learners to extend their own experiences-both
personal and vicarious-and reduce them to order. For students, as for scientists,
learning with understanding requires sense making about patterns in experience.
I would like to suggest two complementary definitions of understanding, one
focusing on interactions with the material world, the other focusing on social
interactions.
Understanding as sense-making in the material world.
If we look at the NSES content standards or the Project 2061 Benchmarks, we
find many statements about scientific laws or theories. What does it mean
to "understand" these statements? One kind of definition would focus on understanding
as a way of interacting with the systems and phenomena of the material world.
We could say that understanding involves an ability to coordinate experiences
in the material world, patterns in those experiences, and explanations of
the patterns.
This definition implies that learners would understand a particular theory,
for example, when (a) they have access to the relevant experiences in the
material world, (b) they can see patterns in those experiences, and (c) they
can use the theory to explain the experiences and patterns. In extending their
experience they need both to interact personally with systems and phenomena-to
create their own data-and to make use of data created by others. Those data
created by others need to be, in Paul Cobb's words, "experientially real"
to the students. Similarly, their ways of reducing experience to order need
to be both personally meaningful to them and consistent with canonical scientific
laws and theories.
Understanding as participation in sense-making communities.
A complementary definition of scientific understanding focuses on learners'
capacity to participate in communities of practice that are engaged in sense
making about the material world. Understanding in this sense has canonical,
participatory, and personal dimensions.
- Canonical understanding involves being able to discuss experiences,
patterns, and theories in terms that members of scientific communities
would recognize and approve.
- Participatory understanding involves being able to play a productive
role in a community of practice that is collectively making sense of experience
in the material world. Some individuals who have serious gaps in their
canonical understanding may participate quite successfully in collective
inquiry. Conversely, some individuals who have excellent canonical understanding
may not be able to communicate with other members of a group or contribute
to its work.
- Personal understanding involves making sense in ways that are
personally meaningful. Some students who can reproduce canonical explanations
may not find them personally satisfying. Conversely, some students may
be quite satisfied with explanations or sense-making styles that are not
recognized by scientific communities. Other communities may recognize
those explanations or sense-making styles as valid.
Understanding for all. For me, a goal of "understanding
for all" entails obligations in each of the senses discussed above. Teaching
for understanding obligates us to extend the depth and breadth of learners'
experiences in the material world and their resources for making sense of
those experiences. Sense making is a collective as well as a personal enterprise,
so we are also obligated to help learners participate in communities of practice
that produce and use data, patterns, and explanations. We can have legitimate
differences of opinion about the relative importance of these different criteria
for understanding, but we must recognize that all of them are important for
our students.
Dialogue around scientific understanding for all
For me, the import of the discussion above is that "scientific understanding
for all" has a simple core meaning around which many complexities and ambiguities
accumulate. The simple core meaning is this: Scientific understanding is a
product of personal and a social sense making in which we "extend our experience
and reduce it to order." That is we (a) create data out of our experiences
with the material world, (b) find patterns on those data, and (c) explain
those patterns. When we say we want understanding for all, we declare our
intention to allow all students to participate in this personal and social
sense making and to gain access to the body of data, patterns, and explanations
created by scientific communities. The complexities arise when we begin to
study the various ways in which scientific communities (and other communities
of practice) have extended their experience and reduced it to order, as well
as the various ways in which individual students or classroom communities
might themselves make sense of the world. There will always be inescapable
value judgments as we decide which practices count as "real" understanding.
Researchers, reformers, and developers currently use many different frameworks
and vocabularies for discussing scientific understanding. These differences
tend to obscure both the common core meanings and the surrounding complexities.
The lack of a deeper and more precise vocabulary makes it difficult either
to find common ground or to understand our differences. This is my attempt
to suggest some ways of understanding "understanding" that might help us to
achieve a deeper consensus about our areas of agreement and to understand
better how we disagree.
Challenges: Teaching for Understanding in an Information Age
Let's think of the goal of scientific understanding for all as a challenge
to classroom systems or classroom communities. Teachers are the leaders of
these classroom communities. Supported by textbooks, laboratory materials,
and other resources, teachers need to help their students extend their experiences
in the material world and reduce them to order. That is, teachers need to
help their students construct for themselves coherent systems of experiences,
patterns, and explanations.
Research on science teaching and learning has documented many examples of successes
and (mostly) failures of classroom communities as teachers have tried to lead
their students toward understanding for all. In many cases, the failures can
be attributed to lack of appropriate goals or of resources to achieve those
goals. If the teacher doesn't understand a relevant theory and the textbook
doesn't explain it adequately, for example, then students aren't likely to
make sense of the theory. Similarly, if students access to experientially
real data (real or vicarious), then they are unlikely to see the related theories
as tools for sense making-ways of explaining patterns in experience.
New standards and information technologies could help us to address these problems.
Standards could help us agree on goals that are reasonable and appropriate.
Information technologies could be used to make new resources available to
classroom communities. Students could have access to new tools for creating
data and finding patterns in their own experiences. They could gain access
to vicarious experiences in many different forms. They could construct and
compare their own explanations or find explanations appropriate to their own
needs as learners. In theory, at least, information technologies could greatly
reduce the resource limitations of class communities.
So what might we need to DO with these new resources? What enduring challenges
do classroom communities face in helping their members to learn science with
understanding? I read the research on science teaching and learning as suggesting
four fundamental challenges arising from the nature and diversity of science
learners:
- Creating appropriate curricula,
- Developing sufficient learning activities and resources,
- Accommodating different styles of sense-making, and
- Cultivating students' interest and effort.
1. Creating appropriate curricula
What's the right content to teach? Teachers have to select or create goals
and learning experiences that are scientifically important, yet meaningful
to the students in their classes. What are the opportunities for sense making
about patterns in experience that will work best for a particular group of
students? What is the proper balance between personal sense making and mastery
of canonical practices and knowledge claims? Conceptual change and sociocultural
research reveal that there are often serious mismatches between the sense-making
styles and capacities of students in science classes and the content that
is taught in those classes. These mismatches often lead to situations where
students stop trying to make sense of the content that they are being taught.
They resort to procedural display or stop trying entirely.
For example, one very common problem is that theories are taught to students
who have little or no exposure to the experiences and patterns that those
theories explain. Teaching the structure of the atom is one example. Students
commonly are required to memorize quantum numbers and the structure of electron
shells in courses where they will have little or no access to the patterns
that these theories explain, such as the three-dimensional shapes of molecules
or patterns of emission lines in rare gases. Even patterns of valence and
electronegativity in the Periodic Table (which could be explained with less
complex theories) are far removed from any phenomena that are experientially
real to most students.
Even experiences that are accessible to most students are not necessarily ones
that they have refined into data and noticed patterns in. For example, few
students can describe the apparent path of the sun across the sky, or patterns
they have noticed in floating and sinking of liquids in one another, or the
growth of plants and animals in their back yards. Not all students have back
yards, of course. Social and cultural diversity make the task of deciding
what experiences, patterns, and theories are appropriate for a particular
class particularly challenging.
Documents such as the National Science Education Standards and
Benchmarks for Science Literacy contain consensus suggestions
about which experiences and theories are appropriate for students of different
ages. These documents, though, are based mostly on the experiences of their
writers and consultants, with a little bit of help from conceptual change
research. A broader look at the research could lead to deeper discussions
of how we might select and present content for particular groups of students.
2. Developing sufficient learning activities and resources
How much teaching about a topic is enough? Developing coherent systems of experiences,
patterns, and explanations is a slow and difficult process for most students.
They may need to extend their experiences (either personally or vicariously)
and create data from those experiences. They may need to learn new ways of
recording or displaying data. They may need to see or be introduced to patterns
in data that they have never noticed before. They may need, as Bohr suggests,
to undergo "alterations in the points of view best suited for the ordering
of [their] experience."
The research literature documents numerous cases in which teachers and textbooks
have made poor choices about "breadth vs. depth" issues, almost always in
the direction of going on to the next topic too soon, before students have
made sense the topic that they are studying. In many cases, this may be partly
a resource limitation: If the textbook is your only resource and you have
reached the end of the chapter, then what is there to do except go on to the
next chapter? The availability of new resources does not, however, modifies
rather than eliminates the problem. Teachers must still decide when a community
has reached the point of diminishing returns on one topic and it is time to
move on.
Even more important is the design challenge of coming up with the right combinations
of learning activities to support students' sense making. What kinds of experiences
and activities are necessary, and in what order? There are numerous attempts
in the literature to formulate generally applicable answers to this question,
such as Posner, Strike, Hewson, and Gerzog's conditions for conceptual change
or various versions of the learning cycle. All of them, however, have heuristic
value at best. They suggest categories of experiences or activities that might
help students' understanding; they do not provide prescriptions that teachers
or designers of classroom support systems can follow. Thus the challenge of
creating systems that are sufficient to support students' sense making is
an enduring one for teachers and curriculum developers. The research literature
can provide important guidance for this empirical process.
3. Accommodating different styles of sense-making
What about student diversity? Current curricula that present science content
as sequences facts and concepts to be learned or problem-solving skills to
be mastered tend to divide students into three broad groups. A small number
of students are able to incorporate the symbol manipulation and facts into
their own sense-making strategies. Because the facts and symbols make sense
to the students, they are able to learn them rapidly and remember them easily.
They can proceed rapidly through the established curriculum. A second group
of mostly middle-class students is not particularly successful in making sense
of the symbols and facts, but they are expected by their parents and peers
to be successful in school, and they have a set of strategies for memorization
and symbol manipulation (especially in arithmetic) that they learned both
at home and in school. Their parents provide or find extra help if they fall
too far behind. These students generally make reasonably good grades through
"procedural display," even without understanding the symbols and facts in
any depth. A third group of students, including many lower-class, ESL, and
special education students, lacks the resources or the incentives to engage
in successful procedural display. These students are likely to show active
or passive resistance and alienation.
Given this skills-based curriculum and this range of student responses, there
seems to be little reason to put these three groups together in the same classroom.
If they are tracked, the students in the first group can proceed much more
rapidly through the curriculum. The students in the second group can learn
procedural display much more effectively if the resistant and alienated students
are removed. For the students in the third group, dealing with their resistance
and alienation becomes a more salient problem than teaching science and math
content. Thus tracking is a sensible response to the problems created by a
curriculum that focuses on symbol manipulation and fact learning.
A view of science as sense making about patterns in experience suggests other
possibilities. The science studies literature suggests that written records
such as scientific journals and textbooks are formalized records of much more
complex and culturally embedded sense-making processes. Scientific communities
use symbols and facts as they search for patterns in the phenomena of the
material world and use them in the service of real-world problem solving.
The reasoning and language involved in these sense-making and problem-solving
processes are often personal, informal, and imaginative.
Researchers differ in their assessment of this different view of the scientific
enterprise for science teaching and learning. Some researchers, such as Yerrick,
Ogbu, and many feminists point to the deep cultural divide and differences
in power between scientific communities and marginalized students. They suggest
that new standards or resources may do little to alter enduring patterns of
resistance and alienation in the absence of larger systemic changes.
Other researchers, such as Warren and Rosebery or Lehrer and Schauble, take
a more optimistic view. They suggest that this view of the curriculum reveals
"generative continuities" between the language and reasoning of children,
including children who are poorly prepared for procedural display, and the
language of reasoning of scientists and mathematicians. Warren points specifically
to "embodied imagining" and informal reasoning as examples of those generative
continuities. These researchers include the school curriculum, including the
curriculum in the standards, as "the neck of the hourglass"-a narrow and restricted
view of science that cuts off the generative continuities between students'
and scientists' reasoning. Thus research could help us to discover generative
continuities between students' and scientists' strategies and help students
to use them in the service of their collective and individual sense-making
efforts.
4. Cultivating students' interest and effort
Why should students bother to do the hard work of learning with understanding?
While it is true that students are naturally curious about the world around
them, many students are not naturally inclined to engage in the kinds of sustained
effort necessary to develop coherent systems of experiences, patterns, and
explanations. Exciting experiences or activities are good for catching students'
attention, but student motivation to engage in the work of sense making must
be cultivated and nurtured.
Research on teaching and learning tells us that the issues discussed above
affect students' motivation and interest. Students generally don't keep trying
to make sense of science if they are being taught content that is inappropriate
for them, or if the learning activities in the classroom are culturally inappropriate
or insufficient to support understanding. Not surprisingly students respond
better when the curricula are developmentally and culturally appropriate and
the learning resources and activities are sufficient to support their sense-making
efforts.
It is also clear that students are flexible in their curiosity and their willingness
to work. They can become interested in seemingly arcane issues or they can
find "motivating" activities dull and boring. They can respond to the enthusiasm
of other members of their learning communities. Their interests in pattern
finding and sense making can be cultivated over time, as can their abilities
to find interesting questions in their experiences with the material world.
Feminist and sociocultural researchers point out that students' interests
and efforts are closely tied to their feelings about identity and empowerment.
They put their efforts into activities that are consistent with the norms
of their cultural groups and their images of themselves.
Dialogue around the challenges of teaching for understanding
I read the current research on science teaching and learning as documenting
the importance of these four design challenges for any teacher or developer.
For better or worse, they will be present whenever we try to help students
learn science with understanding. The research documents a few "existence
proofs" of sophisticated and well-supported teachers who meet all four of
these challenges well. Mostly, though, it documents how difficult these challenges
can be and how rarely our current systems meet them well.
Our current research and development efforts tend to emphasize some of these
challenges at the expense of others. The standards, for example, focus primarily
on the first two challenges while paying much less attention to the third
and fourth. Textbooks and support systems using information technologies tend
to address some of the challenges while leaving others to the craft of the
teacher. The challenges are often addressed in ways that are shown by current
research to be predictably inadequate. At best, though, the research provides
spotty and inadequate support for developers who try to use research to meet
these challenges. There are many opportunities for dialogue around these challenges
to enhance our research and development efforts.
Opportunities for dialogue around goals and challenges
I have suggested two issues around which researchers, reformers, and developers
might be able to develop a deeper and more productive dialogue. The first
of these concerns the nature of scientific understanding. It might be possible
to build a consensus around the idea that we want to engage all students in
sense-making about patterns in experience. This means that, individually and
collectively, students need to develop coordinated systems of experiences
with the material world (data), patterns in those experiences (laws, generalizations,
data displays), and explanations for those patterns (theories, models).
The second issue around which researchers, reformers, and developers might
develop a deeper dialogue concerns the enduring challenges of teaching for
understanding. The current research in science education suggests to me that
all teachers and developers face at least four fundamental challenges. They
must (a) create curricula that are appropriate for their students needs and
interests, (b) develop activities and resources sufficient to support students'
learning with understanding, (c) accommodate different styles of sense-making,
and (d) cultivate students' interests and efforts.
It might be worth bringing researchers, reformers, and developers together
for a separate conference around these shared goals and challenges. Such a
conference would be worthwhile, though, only if it stimulated a dialogue that
continued through the daily work of the people involved. For example, here
are some ways in which discussion around these goals and challenges might
inform the activities of research, reform, and development.
- Analysis of science teaching and learning. These goals and challenges
could provide categories around which lessons or units could be analyzed.
- Evaluation of systems for teaching and learning. Systems that include
teachers, textbooks, laboratories, and information technologies could
be assessed on how they address these goals and challenges.
- Design criteria for course development. These goals and challenges could
be used to suggest design criteria for developing K-12 or postsecondary
courses, including courses that rely on information technologies.
- Revision of science education standards. These goals and challenges, and
the research on which they are based, could be used to inform the revision
of national, state, or local standards.
- Science teacher education. Science teacher education programs could try
to prepare teachers to engage these goals and challenges through their
own knowledge and skills and the appropriate use of supporting resources.
The list above is not complete, or even very thoughtful. I hope that the underlying
idea, though, is clear. Our reform and development efforts will be stronger
in the long run if they are supported by a continuing dialogue with science
education research. We may be able to organize this dialogue around our shared
goal of learning with understanding for all and around the shared challenges
that all reformers and developers must address in order to meet this goal.