Difference between revisions of "CS382:Attributes-guidelines"

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(New page: In Silico is designed to meet Earlham's Analytical Reasoning general education requirement, specifically the Quantitative Reasoning component. The full description is here: http://www.ear...)
 
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** Open-ended to a degree  
 
** Open-ended to a degree  
 
** Using science to illustrate the diversity and complexity of the world around us
 
** Using science to illustrate the diversity and complexity of the world around us
 +
 
* Technology
 
* Technology
 
** Sensor nets  
 
** Sensor nets  
Line 22: Line 23:
 
** Agent based modeling  
 
** Agent based modeling  
 
** Building a physical model?
 
** Building a physical model?
 +
 
* Techniques  
 
* Techniques  
 
** Estimation  
 
** Estimation  
 
** Visualization  
 
** Visualization  
 +
 
* Structural
 
* Structural
 
** Metric system  
 
** Metric system  
 
** OSX, Windows, Linux whenever possible (lab sizes and locations)
 
** OSX, Windows, Linux whenever possible (lab sizes and locations)

Revision as of 07:25, 23 January 2009

In Silico is designed to meet Earlham's Analytical Reasoning general education requirement, specifically the Quantitative Reasoning component. The full description is here: http://www.earlham.edu/curriculumguide/academics/analytical.html

There are a number of themes that run through the units:

  • Quantitative reasoning
  • Using models, modifying models, developing models
  • Validation and verification
  • Using tools, broadly defined
  • Data -> information -> knowledge
  • Algorithmic thinking
  • Abstraction
  • Computational thinking

The units should have the following attributes, for the pedagogical ones all units should try to adhere to them, for the others we just need to make sure at least one unit covers them.

  • Pedagogical
    • Inquiry based learning
    • Scaffolded
    • Open-ended to a degree
    • Using science to illustrate the diversity and complexity of the world around us
  • Technology
    • Sensor nets
    • Mashup and Google Earth
    • Agent based modeling
    • Building a physical model?
  • Techniques
    • Estimation
    • Visualization
  • Structural
    • Metric system
    • OSX, Windows, Linux whenever possible (lab sizes and locations)