CS382:Topics Matrix

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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?

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

Total Gen Ed Coverage

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