Difference between revisions of "CS382:Attributes-guidelines"
Jump to navigation
Jump to search
(moved content around since I copied it over to the CS382:Topics Matrix) |
|||
Line 17: | Line 17: | ||
** 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 | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
* Structural | * Structural | ||
Line 36: | Line 26: | ||
** Automated assessment tools | ** Automated assessment tools | ||
** Effective use of TAs | ** Effective use of TAs | ||
+ | |||
+ | === Moved Stuff === | ||
+ | The stuff below has been added to the checklist/n-by-n matrix of "necessary stuff": [[CS382:Topics Matrix|Topics Matrix]] | ||
+ | |||
+ | * Technology | ||
+ | ** Sensor nets | ||
+ | ** Mashup and Google Earth | ||
+ | ** Agent based modeling | ||
+ | ** Building a physical model? | ||
+ | |||
+ | * Techniques | ||
+ | ** Estimation | ||
+ | ** Visualization |
Revision as of 12:00, 28 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
- Structural
- Metric system
- OSX, Windows, Linux whenever possible (lab sizes and locations)
Mechanical and structural stuff:
- Scales well, say 20-80 students
- Automated assessment tools
- Effective use of TAs
Moved Stuff
The stuff below has been added to the checklist/n-by-n matrix of "necessary stuff": Topics Matrix
- Technology
- Sensor nets
- Mashup and Google Earth
- Agent based modeling
- Building a physical model?
- Techniques
- Estimation
- Visualization