Difference between revisions of "CS382:Topics Matrix"
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** 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]] |
Revision as of 10:17, 11 March 2009
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".
Week | Topic | Unit(s) | Who | Discipline(s) | Skill(s) | Tool(s) | Notes | Status |
---|---|---|---|---|---|---|---|---|
1 | What's a Model? | Foundations | Sam, Mikio | Generic | TBD | TBD | Ready | |
2 | Using a Dynamic Model | Fire | Fitz, Vlado | Forestry | Critical parameter, parameter sweep | Cellular Automata, NetLogo | Ready | |
3 | Building a Static Model | Area | Philip, Bryan | Generic | Accuracy, precision, estimation | Mashup | Software and physical | Ready |
4 | Visualizing Data | Mashup | Matt, Nate | TBD | TBD | Mashup | Tufte based approach? | |
5-6 | Structural Modeling | Bridge | Bryan, Dylan | Bridge Building | Physics | Simulation | Computational and physical models | Ready |
7-8 | Equation Modeling | Rocket | Vlado, Sam | Math, Physics | Math, estimation skills and physics | TBD | Software and physical | Ready |
9 | Agent Based Modeling and Computational Sociology | People | Nate, Philip | Sociology | TBD | Agent modeling, NetLogo | Ready | |
10-11 | Modeling Predator-Prey Interactions | Lynx and rabbits | Dylan, Matt | Biology | TBD | Systems dynamics modeling, NetLogo, and Agent-based | Ready | |
12-13 | Chaotic Systems | Climate | Mikio, Fitz | Lots | TBD | TBD | Ready |
Context
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)
- Classroom response system - questions for each unit, participation/attendance measured by response rate?
Mechanical and structural stuff:
- Scales well, say 20-80 students
- Automated assessment tools
- Effective use of TAs
Scientific Tools
- Equation-based modeling
- Agent-based modeling: Netlogo or AgentSheets
- Systems-based modeling: Vensim
- Visualization/visual modeling
- Mashups and Google Earth
Potentially
- SecondLife or OpenSim
Foundation Skills
- Creating a graph
- Interpreting a graph
- Basic statistics
- Estimation
- Parameter sweep
- Data collection
Potentially
- Building a physical model in the real world
Thoughts
Some of these should go somewhere, and some of these should be in every unit.
- 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