I really enjoyed both the Wilensky and Reisman and the Wilensky and Resnick articles this week as I think they outlined more clearly the ways in which computational modeling can be incorporated into the biology classroom in a way that supports both computational and biological literacy. I definitely see the potential of Netlogo as a strategy that is visual, interdisciplinary, revisable, authentic, and predictive, all with lower prior knowledge requirements. I see a conflict, however in the way the two articles discuss both student perspective and the value of a plurality of model types.
While both articles clearly value the individual-orientation of embodied modeling, it seemed Wilensky and Reisman championed the viewpoint in isolation, like it was an inherently better way for students to visualize population dynamics, where Wilensky and Resnick were more aware that both the global and individual points of view are necessary to comprehension of the complex system. Similarly, in Wilensky and Reisman, embodied modeling is presented as an alternative to classical modeling that is better for certain types of problems, while Wilensky and Resnick I think aim for a more integrated approach, “What is needed is a more pluralistic approach, recognizing that there are many different approaches to modeling.”
I think this difference in approach is critical in the ultimate application of both computational and classical modeling in the classroom. I agree with Wilensky and Resnick, that optimally the methods would be used in concert as each has its own strengths and weaknesses that would, hopefully, balance the students’ experience and create a more complete understanding. For example, in the population dynamics experiments referenced by both articles, both the embodied and classical methods make assumptions that limit their application. The classical method assumes carrying capacity of the environment, making it difficult to repeat in a lab and requiring explanation as the model is presented. The embodied model assumes that individual behaviors are governed by a small set of rules, which is more relatable to students but is not true in the wild. Therefore, population dynamics necessarily requires students to see individual behaviors alongside population behavior, to see that individuals are not driven by the same rules/desires as a population and that the net result of individual action is not always intuitive. I think Wilensky and Resnick said it best, in that “the whole is more (or, at least, different) than the sum of the parts,” so in order to understand a concept you need to understand both the micro and macro mechanisms, and the ways in which they interact.
I’m interested to hear if people had similar reactions, as I am definitely biased by my background in population ecology. Additionally, I’m interested to hear people’s thoughts on the following questions:
- Are population dynamics necessarily abstract, or is it a problem with their traditional presentation, similar to our discussion of algebra last week?
- Is there danger in allowing students to anthropomorphize scientific concepts? Or is the only way we can possibly understand something (i.e. our only frame of reference)?
- Is there danger in an individually-oriented view of a system? I see potential for existential crisis down the road as students grapple with the disconnect between an individual’s course and larger driving forces.
- Two weeks ago we discussed decision process behind choosing rules, how do we help students avoid curve fitting as they choose what rules to apply?
- How do we help students maintain awareness of their assumptions when modeling?
Science question this week:
What nutrients do we necessarily need for survival? What are the possible the effects of eating a minimally diverse diet? (for example, a friend of mine is eating 30 bananas a day for 30 days... ala http://thebananagirl.com/my-trip-to-banana-island.php)
Also- What happens to candle wax when you burn a candle?
The fun part about science is that everything is indeed interconnected. Population dynamics and ecology are well known examples of this, but it is true in all levels and concepts in Science. Parts of the body depend on other parts of the body, DNA is information for all the systems, Newton's laws depend on the size of the objects, etc. Why should this not apply to how people learn about science? Scientific facts can be learned, and computational modeling can definitely help with the understanding of the underlying mechanics, but other methods should also be used as support or even introductions to computational modeling. Anthropomorphize is a good way for students to learn, but can be risky as it is not usually the accepted form when presenting ideas in a scientific community. Students can learn this way, but will need some support on learning the terminology and wording for presentation purposes.
ReplyDeleteI think the use of modeling is already set up as a great way to make students aware of the assumptions they are making. Part of the scientific process is creating a model based on what one supposes would happen with a phenomena and when the results do not end up quite as one assumed, one would need to make adjustments. Hopefully that would make someone (aka a student) realize that he/she is missing levels of complexity and therefore needs to adjust his/her model. Computer programming is turning out to be a great vessel for this process because students can simply change/add/adjust/remove codes.
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