Difference between revisions of "CS382:Topics Matrix"

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__NOTOC__
 
__NOTOC__
When it's ready to be reviewed update the Status to be "Ready".  This is the only signal that the reviewers will look for.  When it's being reviewed the status will be "In Review" and then "Done".
 
  
 
<center>
 
<center>
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! Who
 
! Who
 
! Discipline(s)
 
! Discipline(s)
! Skill(s)
 
! Tool(s)
 
! Notes
 
! Status
 
 
|-
 
|-
 
| 1
 
| 1
| [[Unit-foundation-templated|What's a Model?]]
+
| [[CS382:Unit-foundation-templated|What's a Model?]]
 
| Foundations
 
| Foundations
 
| Sam, Mikio
 
| Sam, Mikio
 
| Generic
 
| Generic
| TBD
 
| TBD
 
|
 
| Ready
 
 
|-
 
|-
 
| 2
 
| 2
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| Philip, Bryan
 
| Philip, Bryan
 
| Generic
 
| Generic
| Accuracy, precision, estimation
 
| Mashup
 
| Software and physical
 
| Ready
 
 
|-
 
|-
 
| 3
 
| 3
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| Fitz, Vlado
 
| Fitz, Vlado
 
| Forestry
 
| Forestry
| Critical parameter, parameter sweep
 
| Cellular Automata, NetLogo
 
|
 
| Ready
 
 
|-
 
|-
 
| 4
 
| 4
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| Matt, Nate
 
| Matt, Nate
 
| TBD
 
| TBD
| TBD
 
| Mashup
 
| Tufte based approach? 
 
|
 
 
|-
 
|-
 
| 5-6
 
| 5-6
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| Bryan, Dylan
 
| Bryan, Dylan
 
| Bridge Building
 
| Bridge Building
| Physics
 
| Simulation
 
| Computational and physical models
 
| Ready
 
 
|-
 
|-
 
| 7-8
 
| 7-8
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| Vlado, Sam
 
| Vlado, Sam
 
| Math, Physics
 
| Math, Physics
| Math, estimation skills and physics
 
| TBD
 
| Software and physical
 
| Ready
 
 
|-
 
|-
 
| 9  
 
| 9  
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| Nate, Philip
 
| Nate, Philip
 
| Sociology
 
| Sociology
| TBD
 
| Agent modeling, NetLogo
 
|
 
| Ready
 
 
|-
 
|-
 
| 10-11
 
| 10-11
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| Dylan, Matt
 
| Dylan, Matt
 
| Biology
 
| Biology
| TBD
 
| Systems dynamics modeling, NetLogo, and Agent-based
 
|
 
| Ready
 
 
|-
 
|-
 
| 12-13
 
| 12-13
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| Mikio, Fitz
 
| Mikio, Fitz
 
| Lots
 
| Lots
| TBD
 
| TBD
 
|
 
| Ready
 
 
|-
 
|-
 
| 14
 
| 14
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| TBD
 
| TBD
 
| Lots
 
| Lots
| TBD
 
| TBD
 
|
 
|
 
 
|}
 
|}
 
</center>
 
</center>
 +
'''
  
 
= Concepts, Techniques and Tools =  
 
= Concepts, Techniques and Tools =  
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* SecondLife or OpenSim
 
* SecondLife or OpenSim
  
== Overall Context ==  
+
= Overall Context =
 
* Pedagogical  
 
* Pedagogical  
 
** Inquiry based learning  
 
** Inquiry based learning  
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** Classroom response system - questions for each unit, participation/attendance measured by response rate?  
 
** Classroom response system - questions for each unit, participation/attendance measured by response rate?  
  
== Items to be sorted ==  
+
= General Education =
 +
* [[CS382:Total-geneds|Total Geneds]]
 +
* Consider moving the scraped pages here from the main page for gen eds, labs, etc.
 +
 
 +
= Items to be sorted =
 
* Quantitative reasoning
 
* Quantitative reasoning
 
* Using tools, broadly defined
 
* Using tools, broadly defined
  
Mechanical and structural stuff:
+
* Mechanical and structural stuff:
* Scales well, say 20-80 students  
+
** Scales well, say 20-80 students  
** Automated assessment tools
+
*** Automated assessment tools
** Effective use of TAs
+
*** Effective use of TAs
  
 
* What data do I need to collect, how do I collect it accurately, and then how do I build it
 
* What data do I need to collect, how do I collect it accurately, and then how do I build it
 
** Perhaps one unit where they have to go out and collect data to see how hard it really is, how about modeling campus (rectangle and heart)
 
** Perhaps one unit where they have to go out and collect data to see how hard it really is, how about modeling campus (rectangle and heart)
 
* Data collection: sensor nets, lasers
 
* Data collection: sensor nets, lasers
 
= Total Gen Ed Coverage =
 
[[total-geneds|Total Geneds]]
 

Latest revision as of 14:10, 29 April 2009


Topic Matrix
Week Topic Unit(s) Who Discipline(s)
1 What's a Model? Foundations Sam, Mikio Generic
2 Building a Static Model Area Philip, Bryan Generic
3 Using a Dynamic Model Fire Fitz, Vlado Forestry
4 Visualizing Data Mashup Matt, Nate TBD
5-6 Structural Modeling Bridge Bryan, Dylan Bridge Building
7-8 Equation Modeling Rocket Vlado, Sam Math, Physics
9 Agent Based Modeling and Computational Sociology People Nate, Philip Sociology
10-11 Modeling Predator-Prey Interactions Lynx and rabbits Dylan, Matt Biology
12-13 Chaotic Systems Climate Mikio, Fitz Lots
14 End Notes Wrap-up and review TBD Lots

Concepts, Techniques and Tools

There are a number of recurring themes, standard scientific techniques, and tools for doing science both in the real world and with a computing system contained in this course. Many of them are seen at more than one point.

The plan is to introduce all of them at the start of the course, call them out whenever we encounter them during the course, and then review all of them as a group at the end of the course.

Concepts

  • Using models, modifying models, developing models
  • Data -> information -> knowledge
  • Algorithmic thinking
  • Computational thinking
  • Abstraction
  • Accuracy vs precision

Techniques

  • Validation and verification
  • Interpreting a graph
  • Creating a graph
  • Basic statistics
  • Estimation
  • Parameter sweep
  • Data collection

Tools

  • Spreadsheet; {Open, Neo} Office
  • Plotting; Sigma plot, gnuplot (?!), PlotDrop. Why not just use the spreadsheet's tool?
  • Equation-based modeling; spreadsheet?
  • Agent-based modeling; NetLogo or AgentSheets
  • Systems-based modeling; Vensim
  • Visualization/visual modeling
  • Mashups and Google Earth

Potentially:

  • SecondLife or OpenSim

Overall Context

  • 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)
    • Classroom response system - questions for each unit, participation/attendance measured by response rate?

General Education

  • Total Geneds
  • Consider moving the scraped pages here from the main page for gen eds, labs, etc.

Items to be sorted

  • Quantitative reasoning
  • Using tools, broadly defined
  • Mechanical and structural stuff:
    • Scales well, say 20-80 students
      • Automated assessment tools
      • Effective use of TAs
  • What data do I need to collect, how do I collect it accurately, and then how do I build it
    • Perhaps one unit where they have to go out and collect data to see how hard it really is, how about modeling campus (rectangle and heart)
  • Data collection: sensor nets, lasers