CEP 909 Nov 16, 2000 The Big Picture of What We’ve Done so Far What We’re Going to Do The Big Ideas Behind Simulations.

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Presentation transcript:

CEP 909 Nov 16, 2000 The Big Picture of What We’ve Done so Far What We’re Going to Do The Big Ideas Behind Simulations

The Big Picture Exploring Ways in Which New Technology has Potential to Change the Way we Learn or Think –Electronic Portfolios –Writing and Reading on the Web –Linked Representations –Simulations Tried to Address the Scholarship of these Topics Along with some Exemplar Hands-On Activity

Electronic Portfolios Theory and Scholarship –Portfolios as a way to foster reflective learning –Portfolios as a form of assessment –New possibilities offered by electronic portfolios (sharable, modifiable, dynamic, multi-media, etc) Hands on Exemplar –Making your own portfolios for this class

Writing and Reading on the Web Theory and Scholarship –Design of websites –How to structure information in non-linear (or linear) sites –How people navigate (move around) sites Hands on Exemplars –Design of your portfolios –Representing information in two different ways –Tracking and representing how a person moved through the Digital Divide web site

Linked Representations Theory and Scholarship –How the new possibilities of dynamically linked representations might lead to better learning –An argument for how this might “play out” in mathematics education Hands on Exemplar –SimCalc example of learning about the relationship between characters walking, position representations, and velocity representations.

Where We’re Going One More Context where Technology Potentially Affords New Ways of Thinking, Teaching, and Learning (i.e. Simulations) Ways in Which Technology Impacts People (from a Cognitive Stance) –Gender Equity in Technology How gender impacts views about technology, how access to technology might impact these views, and how software design interacts with gender. –Online Communication How conversing online is “different” than talking face to face

Simulations: What’s the big deal? Simulations afford students the opportunity to do otherwise impossible, difficult, or impractical (e.g., launch a rocket) Simulations can focus on the relevant, and ignore the irrelevant (i.e. they can make the “phenomena” more ideal) Simulations can allow students to make manipulations and see their effects

Simulations: What’s the big deal? continued Simulations can make stuff that is hidden in the real world visible in the simulation (e.g. vectors of momentum, a trail of movement, color to represent temperature, etc). In one view of science, theory building (and by extension modeling) is paramount to “doing science”. By simulating, the process of modeling becomes visible, accessible, assessable, and sharable

Simulations: Strengths or Weaknesses Simulations afford students the opportunity to do otherwise impossible, difficult, or impractical (e.g., launch a rocket) –IMPOSSIBLE: Distorts reality (e.g., shooting someone in a video game) –DIFFICULT or IMPRACTICAL: Virtual pendulum, why not a real one?

Simulations: Strengths or Weaknesses Simulations can focus on the relevant, and ignore the irrelevant (i.e. they can make the “phenomena” more ideal) –Who gets to decide? –What if the “irrelevant” is relevant? –Danger of oversimplifying –Confusing the theory with reality –Hiding the process of theory building and modeling

Simulations: Strengths or Weaknesses Simulations can allow students to make manipulations and see their effects –Manipulations might not be possible in the real world. –Cognitive overload: requires reasoning about multiple causations

Simulations: Strengths or Weaknesses Simulations can make stuff that is hidden in the real world visible in the simulation (e.g. vectors of momentum, a trail of movement, color to represent temperature, etc). –Lack of correspondence between reality and the simulation –Obscures the process of deciding what to make visible, and what representations are profitable for that phenomena

Simulations: Strengths or Weaknesses In one view of science, theory building (and by extension modeling) is paramount to “doing science”. By simulating, the process of modeling becomes visible, accessible, assessable, and sharable –Who’s doing the science? –Hides the complexity of science, (e.g. “The Mangle of Practice”)