The two Wilensky readings are about how embedded
computational modeling can help students learn about complex scientific systems
and concepts. Many of the points made in the Wilensky papers correspond to the
arguments made in the other papers, such as Nersessian, Shwarz and diSessa. One
of them being that science students are owed a chance to learn the same tools
that a scientist would be expected to have. For example, being able to observe,
make theories and revise those theories, instead of simply learning what has
already been learned. Wilensky also says that students who learn what doing
science means, they will be able to appreciate the discipline more, whether or
not they go into the science field as a career.
A major point emphasized in the studies was the idea that
science concepts are usually complex and are inter-dependency and
interconnectivity on other systems, and that these systems can be explored and
learned through computational modeling. One of Wikensky’s studies used the term
‘levels’ to describe the interconnectivity between larger and smaller systems.
Wilensky’s other study focused on inter-dependence between groups and
individuals (wolf, grass and sheep, and fireflies coordinating). Students should have to be able to reason and think about connections between systems, as many concepts they will have to learn will be dependent on other concepts.
The computational modeling helps students see how
individuals, following certain rules, can create group (higher level)
phenomena. In other word, the students can move to understanding the mechanics
behind an event. When I had a chance to play around with a similar Netlogo
wolf-sheep model, I was able to see more clearly what factors could affect how
long the population could survive. I was able to come to the same conclusions
as Talia; the grass, the number of organisms, and other mortal factors lead to
how steady the populations will stay. This is similar to what diSessa was
arguing about for having computational modeling in the classroom. Modeling can
help students see how something works (the kinetics behind the kinetic
formulas, or the cars in a traffic jam), instead of just knowing that it works.
I am curious as to how long the students had to complete
their models and learning on the wolf-sheep and firefly models. In a course, I
will only have so much time to give to a unit. Furthermore, I will still have
to teach my students the material that will be on end of year tests. If the
NGSS, or similar standards, is implemented, I might have more time to give my
students the chance to experience more deep and constructive modeling. However,
if they are not, then how can I cut down the time that such experiences would
take? Would careful, but efficient scaffolding help? Or would I have to decide
which concepts in population dynamics I would want my students to learn?
Furthermore, how much scaffolding would I need for my students to reach the
same reasoning and thinking skills the students in the Wilensky studies were
able to do?
Caitlin, the question about scaffolding is one that I have thought about as well. The best answer I can come up with so far is that it would have to be determined on a case by case basis. I think different students would need different amounts of scaffolding for different topics. As a teacher, I think a big challenge is determining how to accommodate the different levels of need within the same classroom. I think these two issues go hand-in-hand.
ReplyDeleteI forgot to put in some kind of science question for the week. How do the muscular, skeletal (and neural) systems work together to create force? Also, how do lightbulbs that have more than one brightness work?
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