1.
Articles
a.
These
articles made me think about how it is so important to consider different
topics within a course like physics as requiring very different instructional
methods. Not all science topics can be
done with modeling, but there are certainly a large number that would be so
much better with this kind of agent based modeling.
b.
Obviously
in a biology class these examples would be very helpful showing the questions
teachers need to ask students as they test their models. Having good
investigative questions for students engaged in modeling seems critical with
these kinds of tasks.
c.
The
articles continue the theme of models that constantly adapt and change with new
information and test results. Another continued focus is the importance of
pushing students to evaluate their models over and over again. Also stressed is how models are more than
just showing other people how something works; they give the model-makers
insight into how the system works as well.
In this case, the model-makers have to put themselves into the shoes of
the wolf/sheep/slime and look at the system from that perspective.
d.
Most
of the authors so far seem mostly in agreement.
DiSessa so far has stressed a more general computational literacy and
showed us some concepts that it would be useful for, while these pieces provide
specific case studies of computational literacy being used to better understand
a concept. Nersessian’s work was similar
to this week’s papers but in a non-educational context. This week’s authors suggest that science is
more like modeling, and Nersessian’s article gives anecdotal evidence of that
claim.
e.
These
pieces on agent based modeling made me very excited to get to model with more than
one turtle. The degree of complexity
that we can see thanks to this kind of modeling while only knowing some very
simple things is amazing. I hope I get
to apply it to some cool realms of science.
Playing with variable such as chance of reproduction seems like it could
be a fun logical exercise as well. I
find computer science modeling like what we do in class to be so helpful for
teaching how to look at things from other perspectives. Even with just one turtle acting, I often catch
myself thinking of turning right or turning left relative to my north rather
than the turtle’s heading.
2.
Questions
a.
How
does assessment play a role in modeling exercises? Is it mostly effort based?
b.
I
would be curious to see what a great entry event into this wolf modeling
activity looks like. I can imagine
showing a video about wolves and elk in Yellowstone. Can anyone think of a good entry event for
the slime modeling?
3.
Possible
questions to model
a.
How
do we get maple syrup?
b.
How
does lightning decide which path to take?
c.
How
does the golden ratio emerge from a spiral sea-shell?
I think you brought up a great question, how does assessment play a role in modeling exercises? My response would be, we have to look at what we are assessing (measuring). Are we more interested in seeing if a student can create a successful model given a specific computer program? Or are we more interested in assessing what a student has gained from their attempt at creating a model and how well they engaged in the eight practices recommended in the NGSS framework? I personally think that in a scenario like the ones described, assessment should be mostly effort based. I think what is most important is that students are engaged, clearly giving effort into what they are doing, and learning something from the experience. Hopefully they will be scaffolded and supported to the point they aren’t “dead in the water” so to speak, but at the end of the day students will get out of the experience the effort they put in. It should be a collaborative community and whose model is best I could care less about. Who gained some insight into a scientific phenomenon and had a genuine experience engaging in true scientific modeling is what I care about. That being said, as an instructor I should make sure that is happening for all of my students, so in theory they should all “get an A”. However, if there is clearly some issue with a student’s work ethic they obviously wouldn’t deserve an A. All of that is just my opinion and just as there is more than one way to skin a cat; I’m sure there are plenty other plausible ways to assess a modeling exercise.
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ReplyDeleteSteve, I agree that all sciences require varying types of models and that certain sciences may stress some more than others. Students may be more interested/engaged in the wolf-sheep model rather than the rate of crystallization model because of the graphics or what you can manipulate. However, for physics, the OneTurtleJar model is great because it allows them to manipulate many factors while at the same time learn about motion. It is interesting to see which models are most useful for certain sciences.
ReplyDeleteFor your questions regarding the best way to model the path of lightning, you should base you presentation and model off of what your students already know/prior knowledge. If there is a Netlogo model for lightning/path of energy that would be awesome. However, since modeling lightning is not easy, I think it would be best to model something that acts/moves like lightning, such as the energy in liquids. Just like there are multiple paths of lightening that fan out to find the least resistive path, a liquid fans out and finds the best/weakest area and flows there. This could be demonstrated by running a liquid through a pipe or another object with a whole in it and showing that the liquid will flow out of the object because it is the least resistive area. Is that even a good example? Any help?