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 The "Acadia Learning" program is
the
outreach program at SERC that
works with teachers across Maine to engage them and their students in
science that is connected to research here at the park and at the
Mitchell Center for
Environmental and Watershed Research, our partner organization at the
University of Maine.
This past weekend we conducted a workshop with teachers from
Scarborough, Old Town, Mt. View, and Nokomis high schools to introduce
some new thinking we have done in the area of helping students work
with
graphs. Graphs are important because they are a way for students
to express their understanding of what is going on in the streams,
forests, and fields that they study. They are also a tool that teachers
can use to see how students use data that they collect to develop that
understanding.
Over the past three years of looking at students' graphs and poster
presentations as part of the Acadia Learning project, we have observed
that many students seem confused about how to express their findings on
a graph. The problems go beyond simple graph mechanics -- titles,
labels, and the like. A lot of graphs just don't seem to make
sense in ways that we would expect. So, over the past year we
developed the first version of a written diagnostic tool to probe
student understanding, and misunderstanding, of how to organize and
present their findings. The workshop this past weekend introduced
teachers to the tool and engaged them in a day-long discussion about
students, graphs, and data. Many kids have real difficulty in making sense out of data.
This
is true even when the data are pretty simple. The difficulty
comes in an interesting place: the kids appear to have trouble
thinking in terms of groups
of things.
For example, on our written test we gave students some data on the
abundance of
dragonfly larvae in two streams. The data consisted of a count of
dragonflies found in each of ten samples, identified as samples "A"
through "J," taken from the streams.
One stream had a rocky bottom; one had a mucky bottom. We asked
the students to "draw one graph showing the data in a way that helps
you figure out if the type of stream bottom has to do with dragonfly
abundance (number of dragonflies)." What we were expecting to see was something that summarizes the results for each stream, comparing them in a graph something like this:
However, what we got back from most students was a graph that looks more like this:
In this graph each bar is the number of dragonflies found in each
sample. What is missing is an answer to the question of how the
streams differ. Most of the students responded in a similar way,
dealing well with the individual data but -- for some reason -- failing
to go beyond the data to create a generalization that answers the
question that we asked.
Each of these students knows how to compute an average and probably
would have done so had we asked for a comparison of the "average number
of dragonflies" in each stream. But we didn't tell them how to answer the question.
We just asked them to figure out the relationship between stream bottom
and dragonfly abundance. Given that question, and a set of data
related to it, most students had difficulty connecting the data and the
question.
We are concerned about this dificulty because science literacy
involves
being able to make useful generalizations on the basis of observed
data. Even more fundamentally, science literacy requires
understanding how science works -- what it is.
Last year we asked several hundred high school students some
questions to get at this central notion: Just what is science?
For the most part, their notion of scientific discovery was much like
the discovery of a new island or of a lost continent. You look
(using something called "The Scientific Method") and, if you keep
looking, you find things. Sort of like finding a lost sock.
The "discovery" was there all the time, waiting to be uncovered.
I suppose this notion might come from common perceptions of things like
discovering a new miracle drug. It was really there. It is
a fact and was always a fact. It just took a scientist to
"discover" it.
What was largely missing from the students' view of science was an
understanding that science is constructed.
The discovery of a new drug builds on generalizations -- theories --
constructed over years by chemists, biologists, pharmacologists, and
others. More simply, the only way that you can begin to say
anything about dragonfly abundance in two streams is to move beyond
observed phenomena. You need to be able to construct an
aggregation of some kind, abstracted from all the individual
observations.
It is not just the idea of using an average in place of all the
individual observations that gives kids difficulty. When we show
them a set of data showing a relationship between two things, they have
difficulty seeing the general relationship if there are couple of data
points that don't quite fit. Or, when comparing groups, they tend
to make decisions on the largest or smallest values, rather than seeing
the data as a group. The tendency to focus on phenomena, rather than on
patterns and on generalizations supported by the data, shows up in many
places.
Here's the problem: we would like to work with students to get
them to understand concepts such as the mercury cycle, food chains, or
ecological balance. And they do learn about these things and can
talk about them, as concepts. But when we send them into the
field to put these concepts to use, collecting data and thinking about
what their data might mean, they get stuck. They have great
difficulty finding meaning in the data, connecting what they observe to
the bigger ideas.
A lot could be written -- and probably should be written -- about
the danger of having powerful ideas that are not rooted in facts, or of
having a lot of facts uninformed by insight. Here I will simply
say that it is at the heart of what science teachers try to help
students learn to do.
The teachers who participated in our workshop this past weekend went
away armed with the first, test version of the diagnostic tool that we
developed and with classroom activities that we hope will help students
make connections between things that they count and measure and the
bigger concepts that we want them to think about and understand.
Over the coming months we will get some first-level evidence about how
well this works and about how we might improve it.
This educational research grows directly out of the work we have
been doing for the past several years, exploring ways to engage
teachers and students in research. That work has uncovered new
problems and challenges, and we have extended our educational research
and developed new professional development and curriculum materials in
response to what we have learned. In many ways, this is just
another step along that path.
But in other ways, this feels like engagement with issues that are
somehow more general and fundamental. The ability to keep a question in
mind as one looks at data, and to then use those data to shed light on
the question, is at the heart of our use of science. This is not
know-how needed only by scientists, but also a capability that citizens
need as they work to understand issues related to resource use and
conservation. We will keep you posted as we continue to work with
teachers across Maine to understand what students are doing and to
assist them in leading students toward new capabilities.
-- Bill Zoellick
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