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515
17
Developing Understanding Through
Model-Based inquiry
James Stewart, Jennifer L. Cartier, and
Cynthia M. Passmore
A classroom of students need only look at each odher to see remarkable
variation in height, hair color and texture, skin tone, and eye color, as well
as in behaviors. Some differences, such as gender, are discrete: students are
male or female. Others, such as hair color or height, vary continuously widhin
a certain range. Some characteristics 10 fingers, 10 toes, and one head do
not vary at all except in The rarest of cases. There are easily observed simi-
lanties between children and Their parents or among siblings, yet There are
many differences as well. How can we understand The patterns we observe?
Students need only look through the classroom window to take These
questions a next step. Birds have feadhers and wings characteristics on
which They vary somewhat from each odher but on which they are com-
pletely distinct from humans L)ogs, cats, and squirrels have four legs. Why
do we have only two? As widh much of science, students can begin The study
of genetics and evolution by questioning The familiar The questions mark a
port of entry into more than a century of fascinating discovery that has
changed our understanding of our similarities, our differences, and our dis-
eases and how to cure Them. That inquiry has never been more vital Than it
is today.
It is likely that people observed and wondered about similarities of
offspring and their parents, and about how species of animals are similar
and distinct, long before The tools to record Those musings were available.
But major progress in understanding These phenomena has come only rela-
tively recently Through scientific inquiry. At The heart of That inquiry is The
careful collection of data, the observation of patterns in The data, and The
generation of causal models to construct and test explanations for those
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516 HOW STUDENTS LEARN: SC ENCE N THE C ASSFOOM
patterns. Our goal in teaching genetics and evolution is to introduce stu-
dents to the conceptual models and the wealth of knowledge that have been
generated by that scientific enterpr se Equally important, however, we want
to build students' understanding of scientific modeling processes more gen-
erally—how scientific knowledge is generated and justified. We want to
foster students' abilities not only to understand, but also to use such under-
standings to engage in inquiry,
For nearly two decades, we have developed science curricula in which
the student learning outcomes comprise both disciplinary knowledge and
knowledge about the nature of science. Such learning outcomes are realized
in classrooms where students learn by "doing science" in ways that are
similar to the work scientists do in their intellectual communities. We have
created classrooms in which students are engaged in discipline-specif~c in-
quiry as they learn and employ the causal models and reasoning patterns of
the discipline. The topics of genetics and evolution illustrate two different
discipline-specific approaches to inquiry. While causal models are central in
both disciplines, different reasoning patterns are involved in the use or con-
struction of such models. The major difference is that the reconstruction of
past events, a pnrnarv activity in the practice of evolutionary biology, is not
common in the practice of genetics. The first section of this chapter focuses
on genetics and the second on evolution. The third describes our approach
to designing classroom environments, with reference to both units.
Our approach to curriculum development emerged as a result of col-
laborative work with high school teachers and their students (our collabora-
tive group is known as MUSE, or Modeling for Understanding in Science
Education).' As part of that collaboration, we have conducted research on
student learning, problem solving, and reasoning. This research has led to
refinements to the instruction, which in turn have led to improved student
understanding,
GENETICS
An important step in course design is to clarify what we want students
to know and be able to do.2 Our goal for the course in genetics is for
students to come away with a meaningful understanding of the concepts
introduced above—that they will become adept at identifying patterns in the
variations and similarities in observable traits (phenotypes) found within
family lines. We expect students will do this using realistic data that they
generate themselves or, in some cases, that is provided. However, while
simply being familiar with data patterns may allow students to predict the
outcomes of future genetic crosses, it provides a very incomplete under-
standing of genetics because it does not have explanatory power Explana-
tory power comes from understanding that there is a physical basis for those
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D EVEEOF NG UNDERSTAND NG THFDUGH MDDEE BASED INDU BY 517
patterns in the transmission of genetic material (i.e., that there are genes,
and those genes are "corned" on chromosomes from mother and father to
offspring as a result of the highly specialized process of cell division known
as meiosis) and as a result of fertilization.
To achieve this understanding, students must learn to explain the pat-
terns they see in their data using several models in a consistent fashion.
Genetics models (or inheritance pattern models) explain how genes interact
to produce variations in traits. These models include Mendel's sample domi-
nance model, codominance, and multiple alleles. But to understand how the
observed pairings of genes (the genotype) came about in the first place,
students must also understand models of chromosome behavior, particularly
the process of segregation and independent assortment during meiosis (the
melotic model).
We have one additional learning outcome for students—that they will
couple their understanding of the transmission of the genetic material and
their rudimentary understanding of how alleles interact to influence pheno-
type with an understanding of the relationship of t)NA to genes and the role
played by t)NA products (proteins) in the formation of an organism's phe-
notype (biomolecular models) L)NA provides the key to understanding why
there are different models of gene interaction and introduces students to the
frontier of genetic inquiry today.
These three models (genetic, melotic, and biomolecular) and the rela-
tionships among them form the basic conceptual framework for understand-
ing genetics. We have designed our instruction to support students in put-
ting this complex framework in place.
Attending to Students' Existing Knowledge
While knowledge of the discipline of genetics has shaped our instruc-
tional goals, students' knowledge—the preconceptions they bring to the
classroom and the difficulties they encounter in understanding the new
material—have played a major role in our instructional design as well.
The genetics course is centered around a set of scientific models. How-
ever, in our study of student learning we have found, as have others,3 that
students have misunderstandings about the ongin, the function, and the
very nature of causal models (see Box 12-1). They view models in a "naive
realistic" manner rather than as conceptual structures that scientists use to
explain data and ask questions about the natural world 4
Following our study of student thinking about models, we altered the
instruction in the genetics unit to take into consideration students' prior
knowledge about models and particular vocabulary for describing model
attnbutes. Most important, we recognized the powerful prior ideas students
had brought with them about models as representational entities and explic-
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518 HOW STUDENTS LEARN: SC ENCE N THE C ASSFOOM
BOX12-1 Student Conceptions of Models
One early study of student learning in the genetics unit focused on identifying the
criteria students used when assessing their models for inheritance phenomena.5
The study was predicated on a commitment to developing with students early in
the course the idea of consistency as a basis for model assessment. Students read
a mystery scenario involving a car accident and evaluated several explanations of
the cause of the accident. Each explanation was problematic because it was either
(1) inconsistent with some of the information the students had been given, (2)
inconsistent with their prior knowledge about the world, or (3) unable to account
for all of the information mentioned in the original scenario. Students discussed
these explanations and their shortcomings, and the teacher provided the language
for talking about model assessment criteria: she instructed them to seek explana-
tory power, predictive power (which was discussed but not applied to the accident
scenario), internal consistency (among elements within the model), and external
consistency (between a model and one's prior knowledge or other models).
Throughoutthe genetics unit, students were prompted to usethese criteria to
evaluate their own inheritance models. Despite the explicit emphasis on consis-
tency as a criterion for model assessment, however, we found that very few stu-
dents actually judged their models this way. Instead, students valued explanatory
adequacy, visual simplicity, and "understandability" more strongly. A closer look at
the work of students in this study showed that most of them viewed models not
as conceptual structures but as physical replicas, instructional tools, or visual rep-
resentations. In fact, the common use of the term to describe small replicas—as in
model airplanes—sometimes interferes with students' grasp of a causal model as
a representation of a set of relationships. Similarly, when attempting to apply model
assessment criteria to their explanations for data patterns in liquid poured from a
box, several students treated "internal consistency" and "external consistency"
literally: they evaluated the box's proposed internal components and the external
phenomena (observations) separately Th is conf usion stemmed f rom students' prior
understanding of concepts associated with the vocabulary we provided: clearly
"internal" and "external" were already meaningful to the students, and their prior
knowledge took precedence over the new meanings with which we attempted to
imbue these terms. Given this misunderstanding of models, it was not surprising
that our genetics students neither applied nor discussed the criterion of conceptual
consistency within and among models.
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DEVEEOF NG UNDERSTAND NG THFDUGH MDDEE BASED INDU BY 519
itly addressed These ideas at The outset of The unit. In The genetics unit,
teachers employ tasks early on that solicit students' ideas about scientific
models and explicitly define The term "model" as it will be used in The
science unit. Frequendy, teachers present sample models dhat purport to
explain The phenomena at hand and ask students to evaluate These models.
Teachers create models dhat have particular shortcomings in order to prompt
discussion by students. Most commonly, students will describe The need for
a model to explain all The data, predict new experimental outcomes, and be
realistic (dheir term for conceptual consistency). Throughout the course, teach-
ers return to These assessment criteria in each discussion about students'
own inheritance models.
A subsequent study has shown dhat These instructional modifications
(along with other curricular changes in The genetics unit) help students un-
derstand The conceptual nature of scientific models and learn how to evalu-
ate Them for consistency with o her ideas 6 We now provide an example of
an initial instructional activity—The black box—designed to focus students'
attention on scientific modeling,
As Chapter 1 suggests, children begin at a very young age to develop
informal models of how things work in the world around them. Scientific
modeling, however, is more demanding. Students must articulate Their model
as a set of propositions and consider how those propositions can be con-
fimmed or disconf rmed. Because tills more disciplined modeling is different
Tom what students do in their daily lives, we begin The course with an
activity that focuses only on The process of modeling. No new scientific
content is introduced. The complexity of The task itself is controlled to focus
students on the "modeling game" and introduce Them to scientific norms of
argumentation concerning data, explanations, causal models, and Their rela-
tionships. This initial activity prepares students for similar modeling pursuits
in The context of sophisticated disciplinary content.
Turing The first few days of The genetics course, The teacher presents The
students widh a black box—eidher an actual box or a diagram and descnp-
tion of a hypothetical box—and demonstrates or describes the phenomenon
associated with it. For example, one box is a cardboard detergent container
that dispenses a set amount of detergent each time it is tipped, while anodher
is a large wooden box widh a funnel on top and an outlet tube at The bottom
that dispenses water in varying amounts, shown in Figure 12-1. Once The
students have had an opportunity to establish The data pattern associated
widh The particular box in question, The teacher explains dhat The students'
task is to determine what mechanisms might give r se to tills observable
pattern L)unng This activity (which can take anywhere from 3 to 11 class
penods, depending on The black box That is used and The extent to which
students can collect Their own data), the students work in small teams. At the
conclusion of The task, each team creates a poster representing its explana-
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520 HOW STUDENTS LEAFN: SC ENCE N THE C ASSFOOM
1- ~
If and so forth.
Black Box
A typical pattern of data would be:
Water in (ml) Water Out (ml)
400
400 400
400 600
400 400
400 O
400 1000
400 O
400 400
FIGURE 12 1 One block box used in the MUSE science curriculum and ~picol doto
patterns ossocio ad with he box
tion for the box mechanism and presents it to the class. Classmates offer
cnticism and seek clarification during these presentations
As the dialogue below suggests, the exercise begins with students en-
gaged in a central activity of scientists making observations.
Teacher Making observations is important in science. I
want you to observe this carton. Just call out
what you notice and I will write it on the board.
The students respond with a variety of observations:
lan
Delia
Sarah
Owen
The box is white with blue lettering.
The contents slosh around and it looks like
liquid soap when we pou r it.
Hey, it stopped coming out! Try to pour it
again so we can see what happens.
It always pours about the same amount then
stops.
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DEVEEOF NG UNDERSTAND NG THFDUGH MDDEE BASED INDU BY 521
After several minutes of listening to the students, the teacher stops them
and invites them to take a closer look at the carton, prompting them to
identify patterns associated with their observations. Their reflection on these
patterns leads the students to propose manipulations of the container, which
in turn produce more observations. The teacher now inter upts them to
guide their attention, saying:
Teacher Okay, you've made some wonderful observa-
tions, ones that you are going to be using in
just a few minutes. But, there is more to
science than making observations. Scientists
also develop ideas of what is not visible in
orderto explain that which is. These ideas are
called models.
She goes on to challenge them:
Teacher imagine an invisible "world" inside the
container that, if it existed in the way that you
imagine, could be used to explain your
observations. I want you to make drawings of
your imagined world and maybe some groups
will have time to develop a three-dimensional
representation too. And, one last thing, I want
each group to develop at least one test of you r
model. Ask you rself, "If the wo rid inside the
carton is as I imagine it and I do X to the
carton, what result would I expects"
Over the next two class periods, the students work in animated groups
to develop models that can be used to explain their observations. They
describe, draw, and create three-dimensional representations of what they
think is in the carton. They argue. They negotiate. They revise. Then they
share drawings of their models with one another
Sarah
Scott
Delia
Hey Scott, you have a different idea than ours.
How does that flap works
The flap is what stops the detergent from
gushing out all at once when you tip it.
Yeah, I get that, but does you r design allow the
same amount of detergent to come out every
times Because we tried a flap, too, but we
couldn't figure out how to get the amount to
be the same.
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522 HOW STUDENTS LEARN: SC ENCE N THE C ASSFOOM
The students also propose tests of their models:
Sarah
Delia
Well, Scott is saying that the flap is like a
trapdoor and it closes to keep the detergent in.
But I think that if there is a trapdoor-like thing
in there, then we should be able to hear it
close if we listen with a stethoscope, rights
Hey, Mrs. S., can we get a stethoscopes
A visitor to the classroom would notice that Mrs s. listens attentively to
the descriptions that each group gives of its model and the observations the
model is designed to explain. She pays special attention to the group's inter-
actior s with other groups and is skillful in how she converses with the
students during their presentat ons. Through her comments she demonstrates
how to question the models of others and how to present a scientific argu-
ment. To one group she says, "I think I follow your model, but I am not sure
how it explains why you get 90 milliliters of liquid each tme you tip the
box." To another she comments, "You say that you have used something
similar to a toilet bowl valve. But I don't understand how your valve allows
soap to flow in both directions." And to a third group she asks, "t)o you
think that lan's model explains the data? What question would you ask his
group at this points" By the end of the multiday activity, the students are
explicit about how their prior knowledge and experiences influence their
observations and their models. They also ask others to explain how a pro-
posed model is consistent with the data and challenge them when a compo-
nent of a model, designed to explain patterns in observations, does not
appear to work as described.
This act vity creates many opportunit es to introduce and reinforce foun-
dational ideas about the nature of scientific inquiry and how one judges
scientific models and related explanations. As the class shares early ideas,
the teacher leads discussion about the criteria they are using to decide whether
and how to modify these initial explanati ons. Together, the class establishes
that causal models must be able to explain the data at hand, accurately
predict the results of future expenments, and be consistent with prior knowl-
edge (or be "realistic") (see the example in Box 12-2). Through discussion
and a short reading about scientific inquiry and model assessment, the teacher
helps students connect their own work on the black boxes with that of
scientists attempting to understand how the natural world works. This frame-
work for thinking about scientific inquiry and determining the validity of
knowledge claims is revisited repeatedly throughout the genetics unit.
Other modeling problems might serve just as well as the one we intro-
duce here. What is key is for the problem to be complex enough so that
students have experiences that allow them to understand the rigors of scien-
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DEVEEDP NG UNDERSTAND NG THROUGH MDDEE BASED INDU FY 523
BOX12-2 Assessing Knowledge Claims in Genetics
While working to revise Menders simple dominance model to account for an in-
heritance pattern in which there are five variations (rather than two), many stu-
dents propose models in which each individual in the population has three alleles
at the locus in question. However, such a model fails to hold up when evaluated
according to the criteria established during the black box activity because it is in-
consistent with the students' prior knowledge about meiosis and equal segrega-
tion of parental information during gamete formation:
Teacher
David
Michelle
David
Michelle
Chee
David
Chee
I'm confused. I'm just curious. I'm a newcomerto this
research lab and I see you using two alleles in some
areas and three in other areas.
We got rid of the three allele model.
Cross that out. It didn't work.
We didn't know how two parents who each had three
alleles could make kids with three alleles.
When we tried to do the Punnett square and look at
what was happening in meiosis, it didn't make sense.
Right. We thought maybe one parent would give the
kid two alleles and the other parent would just give
one. But we didn't like that.
We had to stick with only two alleles, so we just made
it three different kinds of alleles in the population.
But now every person has only two alleles inside their
cells. Right?
Teacher in otherwords, you didn't like this first, three allele,
model because it is inconsistent with meFosis7
tific modeling. In particular, the activity is designed to give students an op-
portunity to do the following:
· Use prior- knowledge to pose problems and generate data. When sci-
ence teaching emphasizes results rather than the process of scientific in-
quiry, students can easily think about science as truths to be memorized,
rather than as understandings that grow out of a creative process of observ-
ing, imagining, and reasoning by making connections with what one already
knows. This latter view is critical not only because it offers a view of science
that is more engaging and inviting, but also because it allows students to
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524 HOW STUDENTS LEARN: SC ENCE N THE C ASSFOOM
grasp that what we understand today can be changed, sometimes radically,
by tomorrow's new observations, insights, and tools. By carrying out a mod-
eling activity they see as separate from the academic content they are study-
ing in the unit, students are more likely to engage in understanding how
models are generated rather than in learning about a particular model.
· Search for patterns in data Often the point of departure between
science and everyday observation and reasoning is the collection of data
and close attention to its patterns. To appreciate this, students must take part
in a modeling activity that produces data showing an interesting pattern in
need of explanation.
. Develop causal models to act for patterns.7 The data produced
by the activity need to be difficult enough so that the students see the mod-
eling activity as posing a challenge. If an obvious model is apparent, the
desired discourse regarding model testing and consideration of the features
of alternative models will not be realized.
· Use patterns in data and models to make predictions. A model that is
adequate to explain a pattern in data provides relatively little power if it
cannot also be used for predictive purposes. The activity is used to call
students' attention to predictive power as a critical feature of a model.
. Mace ideas public, and revise initial models in light of anomalous
data and in response to critiques of others. Much of the schoolwork in which
students engage ends with a completed assignment that is graded by a teacher
Progress in science is supported by a culture in which even the best work is
scrutinized by others, in which one's observations are complemented by
those of others, and in which one's reasoning is continually antiqued. For
some students, making ideas public and open to critique is highly uncom-
fortable. A low-stakes activity like this introductory modeling exercise can
create a relatively comfortable setting for familiarizing students with the cul-
ture of science and its expectations. A teacher might both acknowledge the
discomfort of public exposure and the benefits of the discussion and the
revised thinking that results in progress in the modeling effort. Students
have ample opportunity to see that scientific ideas, even those that are at the
root of our most profound advances, are initially critiqued harshly and often
rejected for a period before they are embraced.
Learning Genetics Content
Having provided this initial exposure to a modeling exercise, we turn to
instruction focused specifically on genetics. While the core set of causal
models, assumptions, and argument structures generated the content and
learning outcomes for our genetics unit, our study of student understanding
and reasoning influenced both the design and the sequencing of instruc-
tional activities. For example, many high school students do not understand
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DEVEEOF NG UNDERSTAND NG THFDUGH MDDEE BASED INDU BY 525
the interrelationships among genetic, melotic, and biomolecular models, re-
lationships that are key to a deep understanding of inheritance phenom-
ena.9 To deal with this problem, we identified learning outcomes that ad-
dress the conceptual connections among these families of models, and the
models are introduced in a sequence that emphasizes their relatedness. Ini-
tially, for example, we introduced genetic models, beginning with Mendel's
model of simple dominance, first. This is typical of many genetics courses.
In our early studies (as well as in similar studies on problem solving in
genetics9), students often did not examine their inheritance models to see
whether they were consistent with meiosis. In fact, students proposed mod-
els whereby offspring received unequal amounts of genetic information from
their two parents or had fewer alleles at a particular locus than did their
parents.'° Because of their struggles and the fact that meiosis is central to
any model of inheritance, we placed this model first in the revised curricular
sequence. Students now begin their exploration of Mendelian inheritance
with a firm understanding of a basic melotic model and continue to refer to
this model as they examine increasingly complex inheritance patterns.
A solid integration of the models does not come easily, however in
early versions of the course, it became apparent that students were solving
problems, even sophisticated ones, without adequately drawing on an inte-
grated understanding of melotic and genetic models." In response, we de-
signed a set of data analysis activities and related homework that required
students to integrate across models (cytology, genetics, and molecular biol-
ogy) when conducting their genetic investigations and when presenting
model-based explanations to account for patterns in their data. By providing
tasks that require students to attend to knowledge across domains and by
structuring classrooms so that students must make their thinking about such
integration public, we have seen improvements in their understanding of
genetics.'
We then focus on inheritance models, beginning with Mendel's model
of simple dominance. Mendel, a nineteenth-century monk, grew generation
after generation of pea plants in an attempt to understand how traits were
passed from parent plants to their offspring. As Chapter 9 indicates, Mendel's
work represented a major breakthrough in understanding inheritance,
achieved in large part by selecting a subject for study—peas that had dis-
continuous trait variations. The peas were yellow or green, smooth or
wrinkled Peas can be self-fertilized, allowing Mendel to observe that some
offspring from a single genetic source have the same phenotype as the
parent plants and some have a different phenotype. Mendel's work con-
fimmed that individuals can car y alleles that are recessive—not expressed in
the phenotype. By performing many such crosses, Mendel was able to de-
duce that the distribution of alleles follows the laws of probability when the
pairing of alleles is random. These insights are fundamental to all the work
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556 HOW STUDENTS LEARN: SC ENCE N THE C ASSFOOM
and the extent to which students' knowledge is integrated). We have seen,
time and again, teachers becoming aware of students' common struggles
and beginning to "hear" dheir own students differently. Thus, an important
feature of instructional activities dhat give students opportunities to make
dheir thinking and knowledge public and Therefore visible to teachers is dhat
they make assessment and instruction seamless. This becomes possible when
students articulate The process of arriving at a solution and not simply the
solution itself
Because students struggle widh conceptual problems in The genetics unit,
for example, we incorporate a number of assessments that require them to
describe The relationships between models or ideas that they have learned
(see Box 12-7). Whenever possible, we design formal assessments as well as
written classroom tasks dhat redect The structure of students' work in The
classroom. Our students spend a great deal of dheir class time working in
groups, pouring over data, and talking with one another about dheir ideas.
Thus, assessments also require dhem to look at data, propose explanations,
and describe the thinking that led to particular conclusions.
In The evolution course, students are required during instruction to use
The natural selection model to develop t)arwinian explanations that account
for mich data sets. To Then ask them about data or The components of natural
selection in a multiple-choice format dhat would require them to draw on
only bits and pieces of knowledge for any one question appears incomplete
at best. Instead, we provide dhem with novel data and ask dhem to describe
dheir reasoning about those data using the natural selection model—a task
analogous to what they have been doing in class. An instance of tills type of
assessment on The final exam asks students to write a t)arwinian explanation
for The color of polar bear fur using information about ancestral populations.
In tills way, during assessment we draw on students' ideas and skills as They
were developed in class rather than asking students to simply recall bits of
information in contrived testing situations.
While assessments provide teachers with information about student un-
derstanding, students also benefit from assessments that give them opportu-
nities to see how their understanding has changed duling a unit of study.
One method we have used is to require each student to critique her or his
own early work based on what she or he knows at The conclusion of a
course. Not only does This approach give teachers insights into students'
knowledge, but it also allows students to glimpse how much their knowl-
edge and their ability to critique arguments have changed. Students' consid-
eration of dheir own ideas has been incorporated into The assessment tasks
in bodh units. On several occasions and in different ways, students examine
their own ideas and explicitly discuss how Those ideas have changed. For
example, one of the questions on The final exam in evolution requires stu-
dents to read and critique a t)arwinian explanation they created on The f 1 st
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DEVEEOF NG UNDERSTAND NG THROUGH MDDEE BASED INDU FY 557
BOX12-7 Sample Exam Question: Consistency Between Models
This exam question is one of several tasks designed to produce evidence of stu-
dents' understandings about the need for models to be consistent with one an-
other and with the data they purport to explain.
Below is a concept map that represents the relationships among
specific models, models in general, and data. Use the map to
respond to the tasks below.
a. Remember that a line in a concept map represents a relationship
between two terms (concepts, ideas, etc.) in the map. Write a few
sentences that describe the numbered relationships between the
terms given. Be as specific as you can: use the appropriate vocabu-
lary of genetics to make your point as clearly as possible.
b. Draw a line (not necessarily a straight one) to separate the world
of ideas from that of observations on this map. Please label both
sides. Justify your placement of that line.
-
~ data
( scientdic~~~
~C~\ \2
_ ~ a ~ ~ ( meiosis ~ \
~ atomic ~ 3 I/
\ model j / / .
/ ~ 4 I pedigree
Mendel ``
day of class (see Box 12-8). We have found this to be one of the most
powerful moments for many students, as they recognize how much their
own ideas have changed. Many students are critical of the need-based lan-
guage that was present in their original explanation, or they find that they
described evolutionary change as having happened at the individual rather
than the population level.
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558 HOW STUDENTS LEARN: SC ENCE N THE C ASSFOOM
BOX12-8 Examples of Students' Critiques of Their Own Darwinian
Explanations
On the first day of class, students were asked to explain how the carapace of
Galapagos tortoises may have changed from the dome shape to the saddleback
shape. As part of the f inal exam for the class, students were asked to critique the
explanation they had given on the first day. Below are the original explanation and
critique offered by one student.
Original Answer
The saddleback carapace came into being due to the need of
migrating tortoises to adjust to a new environment. On Albermarle
Island the domed shaped carapaces served wed for shedding rain
and eating ground vegetation. However, when the tortoises began to
migrate to a smaller, drier island with less ground vegetation, they
had to adapt in order to survive. The majority of the food was now
higher up and the domed shell served as a hindrance. Over time, the
saddleback carapace developed to allow the neck to extend further,
thereby allowing the tortoises to reach the fleshy green parts of the
prickly pear cactus. This evolutionary process created a new species
of giant tortoise that could live successfully in a new environment.
Critique on Final Exam
In my original answer, I used an almost exclusive Lamarokian
definition of evolution. In my introductory statement I stated that the
saddleback carapace came into being due to the need of the tortoise
to fit its environment. I needed to acknowledge the existence of
variation within the tortoise population of the shape of the shelf My
original explanation makes the evolutionary process sound like a
physical change taking place during the life of the tortoise and then
being passed on to the of Spring. I now know that variations that are
advantageous give animals a better chance of survival (survival of
the fittest!) and allow them a better chance of passing on their
advantageous trait to their of Spring. In my original explanation I
also touched on ideas of use and disuse to explain how the
saddleback carapace came to be, this is a Lamarkian model of
evolution which is incorrect. I did explain how the saddleback
carapace was an advantage because it allowed the tortoise to eat
higher vegetation. Since I didn't understand evolution through the
generations, I wasn't able to describe how the species changed over
time. Overall, I would say I had a basic but flawed understanding of
evolution but I lacked the tools to explain evolution from a scientific
and Darwinian perspective, until now.
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DEVEEOF NG UNDERSTAND NG THFDUGH MDDEE BASED INDU FY 559
Community-Centered
As Chapter 1 suggests, The knowledge-centered, learner-centered, and
assessment-centered classrooms come together in The context of a class-
room community. The culture of successful scientific communities includes
bodh collaboration and questioning among colleagues. It involves norms for
making and justifying claims. At The source of The productivity of such a
community is an understanding of central causal models, The ability to use
such models to conduct inquiry, and The ability to engage in the assessment
of causal models and related explanations. We have found that These out-
comes can be realized in classrooms where students are full participants in a
scientific community.34 Interestingly, one unexpected outcome of structur-
ing classrooms so that students are expected to participate in The intellectual
work of science has been increased involvement and achievement by stu-
dents not previously identified as successful in science.
In addition to establishing expectations for class participation and a
shared framework for knowledge assessment, MUSE curricula promote
metacognitive redection on The part of students by incorporating tasks that
require discourse (formal and informal) at all stages of student work. While
working in groups and presenting results to the class as a whole, students
are required to share Their ideas even when those ideas may not be fully
formed. Moreover, recall dhat The context for idea sharing is one in which
discipline-specific criteria for assessment of ideas have been established.
Thus, discourse is anchored in norms of argumentation that reflect scientific
practice to The extent possible.
Learning with Understanding
While the four features of classroom environments can be described
individually, in practice They must interact if students are to deeply engage
in learning for understanding. High school students have had more Than 9
years of practice at playing The "game of school." Most have become quite
adept at memorizing and reiterating information, seeking answers to ques-
tions or problems, and moving quickly from one topic to anothe -. Typically
during The game of school, students win when they present The correct
answer The process by which one determines The answer is irrelevant or, at
best, undervalued. The students described here are quite typical in this re-
gard: they enter our genetics and evolution classes anticipating dhat they will
be called upon to provide answers and are prepared to do so. In fact, seek-
ing an end product is so ingrained dhat even when we design tasks Blat
involve multiple iterations of modeling and testing ideas, such as within the
genetics course, students frequendy reduce The work to seeking algorithms
that have predictive power instead of engaging in The much more difficult
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560 HOW STUDENTS LEARN: SC ENCE N THE C ASSFOOM
task of evaluating models on The basis of their conceptual consistency within
a family of related ideas s
After studying how people solved problems in a variety of situations,
Klayman and Ha36 noted The frequent use of what they call a "positive test
strategy." That is, solvers would propose a model (or solution) and test it by
attempting to apply it to the situation most likely to fit The model in The first
place. If the idea had explanatory or predictive power, The solver remained
satisfied widh it; if not, The solver would quickly test another idea. The
positive test strategy was frequendy applied by students in early versions of
our genetics course.37 This medhod of problem solving does not map well
to scientific practice in most cases, however: it is The absence of disproving
evidence, and not the presence of confirming evidence that is more com-
monly persuasive to scientists. Moreover, testing a model in limited situa-
tions in which one expects a data-model match would be considered "con-
f~rmation bias" within scientific communities. Nevertheless, Klayman and
Ha point out that this positive test strategy is often quite useful in real-life
situations.
Given our students' facility with the game of school and the general
tendency to apply less scientific model-testing strategies when problem solv-
ing, we were forced to create tasks That not only afford The opportunity for
rejection, but actually require students to drink more deeply about The ways
in which they have come to understand science concepts, as well as what is
involved in scientific argumentation. We want students to realize that The
models and explanations They propose are likely to be challenged and Slat
The conflicts surrounding such challenges are The lifeblood of science. Thus,
we explicitly discuss with our students The expectations for their participa-
tion in The course. Teachers state that the students' task is not simply to
produce an "answer" (a model in genetics or a t)arwinian explanation in
evolutionary biology), but also to be able to defend and critique ideas ac-
cording to The norms of a particular scientific discipline. In o her words, we
ask The students to abandon The game of school and begin to play The game
of science.
Examination of ideas requires more than simply providing space for
reflection to occur; it also involves working widh students to develop sys-
tematic ways of critiquing their own ideas and those of odhers. This is why
we begin each course with an activity whose focus is The introduction of
discipline-specific ways of generating and critiquing knowledge claims. These
activities do not require That students will come to understand any particular
scientific concepts upon Their completion Rather, they will have learned
about The process of constructing and evaluating arguments in genetics or
evolutionary biology. Specific criteria for weighing scientific explanations
are revisited throughout each course as students engage in extended inquir-
ies within These biological disciplines.
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DEVEEOF NG UNDERSTAND NG THFDUGH MDDEE BASED INDU BY 561
SUMMARY
For students to develop understanding in any scientific discipline, teachers
and curriculum developers must attend to a set of complex and interrelated
components, including the nature of practice in particular scientific disci-
plines, students' prior knowledge, and the establishment of a collaborative
environment that engages students in reflective scientific practice. These
design components allow educators to create curricula and instructional
materials that help students learn about science both as and by inquiry.
The students in the biology classrooms described in this chapter have
developed sophisticated understandings of some of the most central ex-
planatory frameworks in genetics and evolutionary biology. In addition, they
have, unlike many high school students, shown great maturity in their abili-
ties to reason about realistic biological data and phenomena using these
models. Moreover, they have accomplished this in classrooms that are struc-
tured along the lines of scientific communities. This has all been made pos-
sible by a concerted collaboration involving high school teachers and their
students, university science educators, and university biologists. That MUSE
combined this collaboration with a research program on student learning
and reasoning was essential. With the knowledge thus gained, we believe it
is possible to help others realize the expectations for improving science
education that are set forth in reform documents such as the National Sci-
ence Education Standards 39 In particular, there has been a call for curricu-
lar refomms that allow students to be "engaged in inquiry" that involves
"combin[ing] processes and scientific knowledge as they use scientific rea-
soning and critical thinking to develop their understanding of science. 9
Recommendations for improved teaching of science are solidly rooted in a
commitment to teaching both through and about inquiry. Furthermore, the
National Science Education Standards do not simply suggest that science
teachers incorporate inquiry in classrooms; rather, they demand that teach-
ers embrace inquiry in order to:
· Plan an inquiry-based science program for their students.
. Focus and support inquiries while interacting with students.
· Create a setting for student work that is flexible and supportive of
science inquiry.
. Model and emphasize the skills, attitudes, and values of scientific
inquiry.
It is just these opportunities that have been described in this chapter
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562 HOW STUDENTS LEARN: SC ENCE N THE C ASSFOOM
NOTES
1. We encou age readers to visit our website (www.wcerwisc.edu/ncusla/muse/).
The site includes discussions of student knowledge and reasoning, intended
learning outcomes, irst uctional activities, inst uctional notes, assessments,
examples of student work, teachers' ref ections, and connections to the Na-
tSonal Science Education Standards and Benclhmarksfor Science Literacy
2. Wiggirs and McTighe. 1998, Chapter 1.
3. Gross ight et al., 1991.
4. Gross ight et al., 1991; Harrison and T¢agust, 1998.
5. Cartier, 2000a.
6. Cartier, 2000b.
7. We consider a causal model to be an idea or set of ideas that can be used to
explain pa ticular natu al phenomena. Mode s are complex constructions that
consist of conceptual objects (e.g., alleles, populations) and processes (e.g.,
selection, independent assortment) in which the objects participate or interact.
8. Cartier, 2000a; Kindfreld, 1994; Wynne et al., 2001.
9. Kindfreld, 1994.
10. Cartier, 2000a.
11. Cartier, 2000a; Wy me et a ., 2001.
12. Cartier, 2000b.
13. Darden, 1991.
14. Mel osis is the process by which sperm and egg cells are formed. During mefo
sis, ch omosomal replication is followed by two rounds of cell division. Thus,
one cell undergoing meiosis produces four new cel 5, each of which contains
ha f the number of ch omosomes of the onginal parent cell.
15. Kitcher, 1984, 1993.
16. Kitcher, 1984, p. 356.
17. Kitcher, 1984, p. 356.
18. Mendel, 1959.
19. Discontinuous traits are those for which two or more distinct categories of
phenotypes (or vanants) am identified. For example, Mendel studied the trait
of height in pea plants. He noted that the pea plants we¢ either short (18 in.)
or tall (84 in.). In cont ast, height is not a discontinuous t art in humans: hu-
man height is best characterized as continuously vanable, or nondisc¢te, be-
cause humans are not simply either 18 or 84 in. tall. Thus, the phenotype
categones for height in humans are not clear-cut.
20. Galley and Jungck, 2002.
21. Achondroplasia is indented in a codominant fashion. Individuals with two
disease alleles (2,2) am severely dwarfed and seldom survive. Individua s who
am heterozygous (1,2) am achondroplastic dwarfs, having disproportionately
short arm and leg bones relative to their torsos. Thus while these two pheno
types differ from nommal stature, they am distinct from one another
22. In the past, our students have developed the following explanations for pa
tein action m traits inherited m a codominant fashion:
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Representative terms from entire chapter:
expanded expanded expanded
DEVEEOF NG UNDERSTAND NG THFDUGH MDDEE BASED INDU BY 563
· One allele (designated 1) codes for an active protein. The other a ele
codes for an inactive protein. Thus, individuals with genotype (1,1) have the
greatest amount (or dose) of active protein and the associated phenotype at
the organismal level. Individuals who are (2,2) have little or no measurable
protein activity, and this is Of e ted in the phenotype. Hetetozygous individu-
a s (1,2) have an intermediate level of protein activity and a phenotype that is
a so intermediate. For example, in the case of achondroplasia, (1,1) individu-
a s would have two alleles for a g owth receptor and a phenotype of normal
stature; (2,2) individuals would have few or no functional receptors and suffer
from severe growth retardation. and heterozygotes (1,2) would have ha f as
much g owth receptor activity as the (1,1) individua s and consequent y be
short-statured achondroplastic dwarves without the additional health prob
ferns of the (2,2) individua 5. This example of codominance is admitted y sim-
plified, as students do not study the systemic effects of achond oplasia. How-
ever, this model is applied widely in genetics and sometimes referred to as the
"dosage" model.
. Both alleles code for active proteins, giving use to observable pheno
types at the macroscopic level. Hetetozygotes display the phenotypes associ-
ated with both alleles. For example, in human blood types, individua s car y-
ing alleles for protein A and protein B have both of these proteins on their
blood cel 5. The phenotype is not blended or dosage dependent as in the
achondroplasia example above. Instead, both proteins are detected intact in
hetetozygous individuals.
23. Cartier, 2000a, 2000b.
24. White and F¢deriksen, 1998, p. 25.
2S Calnel 2000a' 2000b
26. Mayr, 1982, P. 481.
27. Kitcher, 1993, pp. 20 21.
28 Richards'1992' p 23
29. O'Hana, 1988.
30. Mayr, 1997, p. 64.
31. Bishop and Anderson, 1990; Demastes et al., 1992, 1995, 1996.
32. Bishop and Anderson, 1990.
33. Carder, 2000a, 2000b; Passmo¢ and Stewart, 2002.
34. Carder, 2000b; Passmore and Stewart, 2000.
35. Carder, 2000a.
36. Klayman and Ha, 1987.
37 Carher, 2000a
38 National Research Council, 1996.
39 National Research Council, 1996, p. 105.
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