2/23 Steve: teacher assumptions & how they influence teaching

            Harlowe Et Al. study the small chunks of conceptions that pre-service teachers have about teaching and how those conceptions shape the way they might teach using modeling.  The strongest connection for me was that many of the concerns that teachers voiced are questions I have been asking myself as we learn more about model based instruction.  For example, the teachers in the study are unsure about how to balance the “right answer” with the messiness of the modeling method.  How important is it to make sure that kids know the scientific reality compared to the importance of understanding the scientific method?  Can guiding be done successfully with large classes?  These are issues that I wonder about as we learn how to teach with modeling. 

            It would have been very interesting to follow the teachers in the study through their first year of teaching to see how the course actually affected them instead of just seeing how it affected the way they analyze videos.  Because they study does not include real teaching, it generates many more questions than answers for me. 

            The 4^th resource from the article is something that we have discussed often in class.  Children are creative thinkers, and science is actually a creative pursuit.  There are elements of scientific work that are very process oriented and rote, but cutting edge research involves a lot of creative problem solving.  This was an interesting part of the article because the pre-teachers had mixed feelings about the benefits of kids doing creative thinking.  Some of the teachers thought it was dangerous for students to be too creative about science because they might end up believing something totally wrong.  I think that scientific modeling stresses the right combination of creativity and logic.  Students must use creativity to come up with models, but then the teacher helps them check their model against logic and observable facts. 

            Most students enjoy using creativity.  When an activity uses creativity it is automatically better for most students than one that does not.  This is another reason that the 4^th resource should be counted as a benefit of model based learning is that kids will enjoy model based learning more than standard non-creative science because it makes them think creatively which they generally enjoy. 

            The Harlowe article connects to our own NetLogo modeling in that it mentions how teachers are more likely to teach a certain way if they have experienced that type of teaching.  It is hard to teach with a certain technique if you’ve never seen it done.  In the case of this study, the teachers watched videos of model-style teaching.  In our case, we are actually experiencing modeling-based instruction by modeling ourselves. 

            The connection to my future classes is that the article provides an interesting way to think about how our knowledge and ideas about kids impact our teaching decisions.  The undergrads have certain things they think about how teaching and learning happens, and they evaluate potential teaching strategies based on those assumptions.  This is true for me too, yet I hadn’t spent much time thinking about what I actually think about teaching and learning until this Master’s program. 

Questions:

·         For which concepts should the efficiency of just telling kids the answer outweigh the benefits of guiding them to an answer?

·         When we are using the guiding method but on a whole class, how do we make sure that everyone is being guided successfully and not just nodding along?

·         Does creativity practiced in one discipline transfer well to other subjects?

2/23 Joey: Applying Appropriate Pedagogical Principles

The article by Harlow Et Al. gives some great insight into how potential teachers might apply pedagogical resources in appropriate or inappropriate ways to a model-based course.  This article was very relevant to me because I am a prospective teacher and understanding how to navigate the new modeling-based approach to teaching is key to my future success.  The article cites three problems of practice teacher educators must help preservice science teachers understand, “ (1) engaging students in science, (2) organizing instruction, and (3) understanding students’ ideas (p. 678)” (pg. 1100).  The paper makes reference to both diSessa and A Framework for K-12 Science Education.  The article draws on the importance of modeling and how the model-based approach to science education helps unify students’ understanding. Attending to students’ ideas and challenging students’ current understandings of scientific phenomena is key to scientific inquiry and the modeling process.  The research drew on how potential science teachers viewed certain pedagogical resources appropriately or inappropriately.  The goals of the class were, “(1) an appreciation for the role of students’ ideas in the teaching and learning of science and (2) an introduction to how to teach science through modeling” (pg. 1104).  The study looked specifically at four pedagogical resources held by the potential teachers in the course:  The teacher’s role is to provide the right answer, guiding students is less certain than telling them (the right answer), a good model includes scientific terms, and children are creative thinkers.  It was really interesting to see how some students viewed these resources so differently compared to others.  I agree that a good teacher consistently poses, rather than answers, questions (pg. 1116).  Guiding students towards a more accepted scientific model allows them to engage more with the material and get more out of the experience compared to just telling them facts from a textbook.  The article also brought up a great point that it is not necessarily the scientific terms that are most important in a good model, rather it is the testability and alignment with evidence(pg. 1116).  Finally, it is important to understand that creativity is not a hindrance when modeling scientific phenomena, rather it is an essential part of the modeling process.

The importance of revision of models as discussed in multiple papers, can also be seen when modeling with NetLogo.  Re-writing code and making manipulations to add more variables or account for different factors is key.  As far as creativity goes (which is such a key in the modeling process), NetLogo offers almost infinite possibilities for model creation and revision.  I would love to use NetLogo in my future classroom, at least some of the models that exist to let students explore different scientific phenomena.  However, from my own experience struggling with learning what each specific code word means (let alone how to revise and write it) I could see how challenging it could be for students to learn (almost like a new language).  That being said, I like how it is color-coded and tells you problems with your code.  Given enough time (not sure how long) I am sure myself and students could benefit greatly from computational modeling through NetLogo.  

Questions: 

What other pedagogical resources besides the four mentioned could be used appropriately or inappropriately by potential teachers?  I think this could make for a fruitful discussion, as the four mentioned brought up some important ideas.

It seems to me scaffolding and making sure to give just the right amount of guidance would be one of the biggest challenges, how can teachers manage the uncertainty of student models? and how do we know what questions to ask to guide students to a more accepted scientific model?  Assuming it depends on the student and current model, would it almost have to be like a clinical interview?  If so, how could a teacher do this with 30 students and such limited time?

2/16 Jenna - The Mangle

In The Mangle of Practice, Pickering examines scientific practice through his lens of "the mangle," which he defines as the reciprocal interactions between "human and material agencies" in the mutual transformation of each other and scientific culture (23). He derives this concept from his argument for the performative idiom. In contrast to the representative idiom, which believes scientific knowledge needs to identically mirror nature, the performative idiom looks at scientific knowledge as it is produced in specific material, social, and historical contexts.

I found much of Pickering's argument pretty difficult to understand, and based on his description of Chapter 2, I wish I could have read that to get a concrete example of his theory at work. In lieu of that, I thought about his theory as it relates to Wertsch's writings about mediated action in Mind as Action. Wertsch argued that the social world could only be understood through an analysis of an agent acting in the world through their agency (which for him meant their use of cultural and material tools). Wertsch helped me make Pickering's talk about mutual transformation of human and machines more salient, as Wertsch similarly argues that the agent and mediational means are both redefined through the action, and one cannot be defined without its relation to the other. I'd like to hear how others made sense of Pickering's "mutual transformation," and what you understood this to mean.

Another author I thought about while reading Pickering was Gee, who differentiated "big-d Discourse" from "little-d discourse." For Gee, discourse is a social language (with its own vocabulary, syntax, colloquialisms, etc) that is situated within the associated Discourse (the socially accepted ways of communicating, acting, and believing that mark one's membership in a community). I feel like Gee's distinction is analogous to Pickering's of scienctific practice ("Practice" - the "extension and transformation [of scientific culture] in time") and practices ("practice" - the "activities on which scientists rely in their daily work" to produce knowledge). In this respect, I am puzzled by where Pickering is placing modeling. The NGSS seems to place modeling as a practice,while Pickering (despite the fact that he calls it a "process") seems to regard modeling as Practice, essential to the way the imagined future is brought forth in the transformation of the presently-existing culture and scientific goals. What does Pickering understand modeling to be? How does his vision fit into our discussions of computational modeling with NetLogo?

I found a few models that I think would work well in a high school physics classroom. I was browsing the library with the lens of a New York State teacher, where state-wide standards are established for physics students and assessed through a Regents exam (part multiple choice, part short answer). In New York City, these standards are rigorously planned out in a city-wide scope and sequence, which states what each unit consists of and how long each unit is. In the state-wide curriculum, Standard 6.2 is devoted exclusively to modeling - but since Standards 6 and 7 (which deal with STEM themes and problem-solving, respectively) are not mapped onto the state assessment, they are frequently overlooked in the classroom. Teachers instead focus on Standard 4, which defined the physics concepts students will be assessed on. Some models that I thought would work well with these standards in mind were:

• All of the NIELS programs, which are on circuits (ex: NYS Physics 4.1.viii-xiv, HS-PS3.C)
• GasLab Single Collision, which would be useful for momentum and energy conservation (ex: NYS Physics 4.1.v and 4.5.xii,, HS-PS2.A)
• N-bodies, for planetary gravitation (ex: HS-ESS1.B)

2/16 Joey: Mingling With Mangling

I found the article to be pretty interesting.  Pickering talked a lot about human and material agency and the interconnectivity between the two.  Pickering writes, “Scientists are human agents in a field of material agency which they struggle to capture in machines.  Further, human and material agency are reciprocally and emergently intertwined in this struggle” (pg. 21).  There was also talk about tuning and how ideas and intentions are always changing.  I thought there was an interesting parallel between the modeling aspect of science and the randomness observed.  Just as in the NetLogo models, If you run the wolf-sheep model ten times, every time you will get a different looking graph and outcome based on the randomness involved.  Like Pickering says, “Modelling is and open-ended process with no determinate destination” (pg. 19).  I found the idea of human creating these machines with specific plans and goal in mind reminiscent of the NGSS guidelines and the idea of engineering.  It seemed to make the interaction more social, moving from the science end game being find an explanation to a question, toward the engineering end game of find a solution to this problem (build a machine in this case). 

I would like to really unpack the term mangle and flesh out what exactly Pickering is getting at.  I did like the idea of moving away from a black and white distinction of humanism/anitihumanism towards a posthumanist view, but I wonder where exactly that falls on a sliding scale?  These ideas are interesting and even though Pickering says representations are important, I wonder what all of these ideas would look like in a classroom?

I would be interested in using the NetLogo Model Bug Hunt Camouflage to cover the standard “Environmental factors also affect expression of traits, and hence affect the probability of occurrences of traits in a population. Thus the variation and distribution of traits observed depends on both genetic and environmental factors. (HS-LS3-2),(HS-LS3-3)”  To show how different traits effect gene expression and occurrence in the population.  This could connect to Pickering and how the different environmental or material agency effect humanistic (or in this case bug agency).  This would be interesting to embody a bug and think where would I hide to have the best chance at survival?

2/16 Laura: Interconnectivity and the Mangle

            The first chapter of Pickering’s book, “The Mangle of Practice,” challenges the two conventional views of science as either humanist or anti-humanist and argues instead for a ‘mangled’ view, where human and material agencies are interconnected. While his writing is at times obscure, I think he makes important points suggesting that causation in science is not clearly linear, and instead that contemporary knowledge is driven by both human intention, culture, and the history of material practice.  I think this is an important distinction, as many scientists are wont to believe that knowledge is purely objective, without consideration for the human biases and intentions that drive their questions and interpretation of experiment. 

            I think that Pickering would consider Netlogo, and computational modeling as a whole, to be a material practice of science that is inextricably tied both to modern human culture’s value of technology as well as a broad history of practice and discovery.  Just as the adoption of is Netlogo driven by culture, Netlogo and computational modeling can in turn impact human’s potential for new knowledge and expand the realm of answerable questions by providing power beyond raw human brainpower.      

            In my classroom, I would hope to capitalize on this expanded potential and help students access more complicated topics at a younger age.  The models that I especially enjoyed were Tumor (MS-LS1-3: Use argument supported by evidence for how the body is a system of interacting subsystems composed of groups of cells), Bug Hunt, Peppered Moth (both of which address: MS-LS2-4: Construct an argument supported by empirical evidence that changes to physical or biological components of an ecosystem affect populations,  MS-LS4-4: Construct an explanation based on evidence that describes how genetic variations of traits in a population increase some individuals’ probability of surviving and reproducing in a specific environment, and MS-LS4-6: Use mathematical representations to support explanations of how natural selection may lead to increases and decreases of specific traits in populations over time), and Wolf Sheep Predation (MS-LS2-1: Analyze and interpret data to provide evidence for the effects of resource availability on organisms and populations of organisms in an ecosystem, MS-LS2-2: Construct an explanation that predicts patterns of interactions among organisms across multiple ecosystems.)

Questions:

Where do you place your self on the humanist to anti-humanist scale (with ‘mangled’ being somewhere in the middle)?

How do you think Netlogo will impact human practices and scientific culture in schools?

Modeling question:

What is the best way to model weather prediction?  What information is necessary for prediction?  Do we need more weather balloons?  Or is it possible to create a new (more sustainable) method of gathering the necessary information?  

2/16 Dan - Mangling with Models

1. The main theme that I was able to discern from Pickering’s opening chapter is that science is not the static observations of isolated phenomena. It is a fluid, interactive process that continually involves that action and reactions between human and non-human agents. If we accept this as a fundamental truth, then it follows that science classrooms cannot be approached as a set of facts that need to be learned, but instead needs to reflect this relationship between people and the world around us. I think this relationship is what Pickering meant by the “mangle”, although it this is definitely a topic that I would like to clarify in class. I think that computational modeling is a good way to explore science in this manner because it does not limit science to just a set of facts or equations, but instead lets an individual interact with the environment. It also replicates an important part of the relationship between human and non-human agents that Pickering calls tuning. This is similar to the ideas the Nersessian expressed in her article, as she highlighted the importance of refining the model of the brain to more closely replicate the behavior that the researchers observed in the real samples of synapses.

2. Does modeling only work with organisms that don’t have agency, or at least have “less agency” than humans? Or can we expect human behavior to follow a few simple rules that would essentially ignore the idea of free will?

3. I could use the “Gravitation” model in a Physics class, to help with Newton’s Law of Universal Gravitation (HS-PS2-4). It models how bodies motion are influenced by the inverse-square law. I could also use the “Rope” model that shows how waves travel and how individual points simply oscillate. This would be helpful when studying waves and electromagnetic radiation (HS-PS4-1).

2/16-Elizabeth-(Trying to) Pick apart Pickering

In his novel, The Mangles of Practice, Andrew Pickering discusses the true definition of science and how it should be practiced.  I found his writing to be very dense and hard to understand, as he used many new words or made up his own names for concepts.  One passage that stood out to me was his discussion about material agency verses representational idiom and how these idioms cast science in a different light.  Currently, science is often viewed as representational, where the goal is to recreate/mirror scientific outcomes that are already found in nature.  The problem with this approach is that it limits the questions one can ask, requires little higher level thinking and promotes the view that science is a stagnant body of knowledge.  Pickering makes this statement regarding representational idioms: “people and things tend to appear as shadows of themselves. Scientists figure as disembodied intellects making knowledge in a field of facts and observations” (6).  What does he mean by this statement?  I thought it alluded to the separation between science/its practices and human beings that comes about through representational idioms.

However, with material agency, people become active agents and see science as “a continuation and extension of this business of coping with material agency” which is carried out through “machines” as Pickering terms it (6-7).  With this view of science, you engage both your mind and body, unlike the representational idiom.  Now science seems much closer and relatable to the individual.  I really liked how Pickering used the concept of weather and strong vocabulary words (“force”) to make his point and show the strong and consistent interaction one has with science.     

Many of our previous articles have touched upon this interactive nature of science.  Schwarz et al talked about this dynamic nature within the concept of computational modeling, how students continually change and build upon their own models as they learn new things.  I think Nersessian’s article is also applicable because it shows Pickering’s words in action.  When the researchers could not understand certain concepts, for example bursting, they made computational models.  These models were innovative and necessary in the fact that they were able to show what was going on that their own observations and data collections could not.  I think this applies to Pickering’s quote “Much of everyday life has this character of coping with material agency that comes from outside the human realm and that cannot be reduced to anything within that realm” (6). 

I do think NetLogo applies to the Pickering article.  It allows students to be active and manipulate variables on their own, collect data, and use it not as an end, but as a means to an end.  I could see my students using some of the kinetic computational models within the classroom and maybe as an additional resource/part of a lab.  When doing a lab involving kinetics, or it could even be a different topic, students could use the model to see how certain variables influence the rate of reaction.  However, I am not seeing Netlogo being a huge part of my classroom just because I do not seeing it holding students' interested for an extended period of time.  So what would be a good way to incorporate it into a class?  Should you only use one per class, give students several options...?

Netlogo models I would use:

1.     Simple Kinetics 2 (1 and 3 are also good)-focuses on LeChatelier’s Principle.

This model would be good because students can see the effect certain variable have on a chemical reaction and the concentration of reactants and products.  Students can also note the relationship between reactants and products.  This correlates with NGSS MS-PS1-2.  (My computer is not allowing me to open the NGSS website so I cannot provide any other standards). 

Questions:

1.     How could I make a lab experiment (containing some computational modeling) more interactive and similar to the ideas of material agency expressed by Pickering and not those of representational idiom?      

2.      How could I make computational modeling more prevalent in a chemistry class?  It seems like these models could only be used for a short amount of time.