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1 Modeling in MS Science. 2 ANNOUNCEMENTS Q3 Assessments, scantrons due back Apr 13 th end of day (drop off at security if needed) Q4 Assessments: May.

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Presentation on theme: "1 Modeling in MS Science. 2 ANNOUNCEMENTS Q3 Assessments, scantrons due back Apr 13 th end of day (drop off at security if needed) Q4 Assessments: May."— Presentation transcript:

1 1 Modeling in MS Science

2 2 ANNOUNCEMENTS Q3 Assessments, scantrons due back Apr 13 th end of day (drop off at security if needed) Q4 Assessments: May be longer (summative) and include questions from Q1-3. Feedback welcome. Continue to check email for announcements on PD, summer sessions. CT Science Center free (not paid) workshop on Science Inquiry, last week of July?, Peabody 8 th grade geology workshop, 5 th grade astronomy, etc

3 3 Q4 pacing: 7 th grade: will get food chemistry kit to KEEP integrate in food safety unit. Finish human body/digestion by Mid May, food safety, science and society discussions. 8 th grade: Make sure to comprehensively cover earth science topics: rock cycle, earth movements, etc then go onto natural disasters, science and society discussion. See last year example of landslide unit? Need help with data for TVAL?

4 4 Next year: no openings likely until June, but possible 3 ms gen science, 1 hs biology, 1 hs chemistry/phy chem.. Talk to me if you have a reason for requesting a transfer. remember, best interests of the school system. MATERIALS/SUPPLIES:Make sure to make a list, use Frey, Fisher, etc and give to admins before the end of the year! SCIENCE FAIR: Registrations DUE APRIL 13 use online @nhsciencefair.org May 10 drop off, May 11 Science Fair 9-12 (I do buses), Awards May 12

5 5 TODAY ’ S DISCUSSION How do students learn from models, diagrams, maps? What are some of the issues that research tells us about science learning and models? What are some of the ways we explicitly teach students modeling and how to learn from models?

6 6 Modeling construction and test of representations that serve as analogues to systems in the real world representations can be of many forms useful in summarizing known features and predicting outcomes

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14 14 Modeling concepts models as representations of causal or explanatory ideas, there can be multiple models of the same thing, models do not need to be exactly like the thing modeled, models can be revised or changed in light of new data

15 15 Modeling Modeling: recognize data patterns create models to account for phenomena identify components of model design experiments to test models assess models for data fit and consistency revise models based on additional data (model extension) / effect to cause reasoning use model to make prediction

16 16 Student Issues with models models are not copies; they are deliberate simplifications Error is a component of all models development of specific representational forms and notations role of geometry and visualization

17 17 Children Model views Level 1: models merely copies of the world Level 2 : models involve both the selection and omission of features, but emphasis remains on the models themselves rather than on the scientists ideas behind the model. Level 3: models were regarded as tools developed for the purpose of testing theories A learning progression for understanding models as generative tools for predicting and explaining

18 18 Data Modeling what professionals do data are constructed to answer questions Data are inherently a form of abstraction data are represented in various ways

19 19 Scale Models, Diagrams, and Maps make it possible for students to visualize objects or processes depends on the complexity of the relationships

20 20 Diagrams comprehensibility of diagrams three reasons why diagrams miscommunicate: some do not include explanatory information (illustrative or not explanatory), lack a causal chain, fail to map the explanation to a familiar context.

21 21 Maps preserve some analog qualities of the space omit or alter features of the landscape easier to represent objects than to represent large-scale space struggle with orientation, perspective

22 22 Designing Models Task: designing a model that works like a human elbow (Penner et al., 1997). three consecutive 1-hour sessions. Discussed different types of models they had previously seen or made. Considered the characteristics of those models, and how models are used for understanding phenomena. Introduced to the task of de-signing a model that functions like their elbow. Discussed how their own elbows work, Worked in pairs or triads to design and build models that illustrated the functional aspects of the human elbow. Generated an initial model, then each group demonstrated and explained their model to the class followed by discussion of the various models. Modified their models or started over. In interviews conducted after the session, students improved in their ability to judge the functional rather than perceptual qualities of models com pared with non-modeling peers. Also demonstrated an understanding of the process of modeling in general that was similar to that of children 3 to 4 years older.

23 23 Teacher’s Role Provides historical examples of very important people changing their views and explanations over time Begins to use students’ external representations of their thinking as a way of evaluating their ideas/ beliefs (in terms of intelligibility, plausibility, and fruitfulness) in order to (a) create, when necessary, dissatisfaction in the minds of the learner to facilitate conceptual exchange or (b) look for ways of promoting conceptual capture in the mind of the learner SOURCE: Smith et al. (2000).

24 24 Students’ Role Begin to consider the implications and limitations of their personal thinking Begin to look for ways of revising their personal thinking Begin to evaluate their own/others’ thinking in terms of intelligibility, plausibility, and fruitfulness of ideas Continue to articulate criteria for acceptance of ideas (i.e., consistency and generalizability) Continue to employ physical representations of their thinking Begin to employ analogies and metaphors, discuss their explicit use, and differentiate physical models from conceptual models Articulate and defend ideas about what learning should be like


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