CS382:Total-geneds

General Education Alignment ( in progress)

Helpful Total Geneds Coverage Table, Fig. 18c.

Gened	Foundations	Fire	Static	Visualz	Structural	Equation	Compsoc	Predator/Prey	Chaotic
ARa	Yes	No	Yes		Maybe	No	Yes		Yes
ARb	Yes	maybe?	Yes		Yes	no	Yes		Yes
ARc	Yes		no		no	no	Yes		no
QRa	Yes	Yes	Yes		maybe?	Yes	no	Yes	Yes
QRb	Yes	Yes	Yes?		Yes	Yes	no	Yes	Yes
QRc	Yes	Yes	Yes		Yes	Yes	no	Yes	Yes
QRd	Yes	Yes	maybe?		no	Yes	no?	Yes	no
QRe	Yes	Yes	Yes		Yes	Yes	no	maybe	Yes
QRf	Yes	Yes	Yes		Yes	Yes	maybe	Yes	Yes
QRg	no	Yes	maybe?		Yes	Yes	Yes	Yes	Yes
SIa	foundation	Yes	Yes		Yes	Yes	Yes	Yes	Yes
SIb	Yes	Yes	Yes		Yes	Yes	no	Yes	no
SIc	Yes	Yes	Yes		Yes	Yes	Yes	maybe	no

Analytical Reasoning Requirement

• 1. Abstract Reasoning - From the [Catalog Description] Courses qualifying for credit in Abstract Reasoning typically share these characteristics:
  • a. They focus substantially on properties of classes of abstract models and operations that apply to them.
    • Foundations: solid support
    • Fire: This unit deals almost entirely will quantitative reasoning, and would be hard to expand into the abstract world.
    • Static: The concepts covered in the static model are intentionally abstract, and rely on the lab activity to ground those abstract concepts in a practical application.
    • Visualizing:
    • Structural: Sort of. This lab is more concrete. This unit will go early in the semester so it will apply some of the more abstract ideas presented earlier.
    • Equation: Does not apply; this unit is purely quantitative.
    • Compsoc: Agents -> abstract models
    • Predator/Prey:
    • Chaos: Yes.
  • b. They provide experience in generalizing from specific instances to appropriate classes of abstract models.
    • Foundations: solid support, we dedicate an entire lecture to this
    • Fire: Parameter sweeping (one of the primary goals of this unit) can be used in almost every instance of computational simulations. In this sense it can be expanded from this specific model to others, yet it is more of a quantitative method of analysis than it is abstract.
    • Static: Yes, because the static model is an abstract framework that we're contextualizing using an activity that grounds the abstraction in something as concrete as 'the heart'.
    • Visualizing:
    • Structural: Yes, because we're showing how structures and bridges, specifically apply to the abstract model parameters described in the What is a static model and what is a dynamic model units.
    • Equation: Again it does not apply/support.
    • Compsoc: discussion of boids, sugarscape and agent based modeling as a whole
    • Predator/Prey:
    • Chaos: Yes.
  • c. They provide experience in solving concrete problems by a process of abstraction and manipulation at the abstract level. Typically this experience is provided by word problems which require students to formalize real-world problems in abstract terms, to solve them with techniques that apply at that abstract level, and to convert the solutions back into concrete results.
    • Foundations: Kinda what the whole unit is about
    • Fire:
    • Static: Eh, again, this unit isn't geared towards this as far as I can see.
    • Visualizing:
    • Structural: Eh, again, this unit isn't geared towards this as far as I can see.
    • Equation: Does not support it; it could but we have different focus.
    • Compsoc: the emergent behavior is a process of abstract manipulation; comparing emergent behavior back against the real world is "converting solutions back into concrete results"
    • Predator/Prey:
    • Chaos: No.
• 2. Quantitative Reasoning - From the [Catalog Description] General Education courses in Quantitative Reasoning foster students' abilities to generate, interpret and evaluate quantitative information. In particular, Quantitative Reasoning courses help students develop abilities in such areas as:
  • a. Using and interpreting formulas, graphs and tables.
    • Foundations: The discussion of vetting materials strongly supports this objective
    • Fire: This unit is intended to teach the student how to gather data using a specific tool and analyze that data to come to some conclusion.
    • Static: The students will work with tabular data to get a feel for the balance between accuracy and precision
    • Visualizing:
    • Structural: not really. or maybe... If we use the pasco solution, the beam strength will be documented, and the students can perform basic calculations to figure out whether beams will break under a certain load.
    • Equation: It does support this it; as I described above- the unit requires and will develop math, and science skills so it will also include certain number of formulas, graphs and certainly tables.
    • Compsoc: Little of this - the point is to avoid formulas (initially), but graphs and tables come up when analyzing model results.
    • Predator/Prey: In this unit we have students create and examine formulas for modeling the relationships between the different parts of the systems. We also have them draw diagrams for representing their model and then use graphs and tables to analyze their results.
    • Chaos: Yes.
  • b. Representing mathematical ideas symbolically, graphically, numerically and verbally.
    • Foundations: Tufte. Strong coverage of this
    • Fire: The student will need to create a lab write-up in which they express why they went about collecting the necessary amount of data. They will also need to include examples of said data and an explanation of what conclusion(s) can be drawn from that data.
    • Static: Yes. Well... maybe not verbally. The groups will be using the abstract notion of a static model to solve a real world problem.
    • Visualizing:
    • Structural: The models provide a framework for visualizing physical (mathematical) constraints.
    • Equation: It does support this it; as I described above- the unit requires and will develop math, and science skills so it will also include certain number of formulas, graphs and tables which will also have their symbolical, graphical and numerical representations.
    • Compsoc: Little of this. We're working with people, not numbers.
    • Predator/Prey: Systems dynamics is at it's core representing systems symbolically and mathematically.
    • Chaos: Yes.
  • c. Using mathematical and statistical ideas to solve problems in a variety of contexts.
    • Foundations: Our discussion of how to use data covers this
    • Fire: While this unit deals almost entirely with a single tool, the idea of parameter sweeping is necessary in every form of simulation and is thus applicable in a wide range of contexts.
    • Static: Yes. described above.
    • Visualizing:
    • Structural: This is one context where we're using mathematical and statistical ideas.
    • Equation: Still not sure how big will variety be but what is sure that math and statistical ideas will be used to solve problems.
    • Compsoc: Nada.
    • Predator/Prey: We are using mathematics to solve problems.
    • Chaos: Yes.
  • d. Using simple models such as linear dependence, exponential growth or decay, or normal distribution.
    • Foundations: Strong support
    • Fire: This wildfire model clearly shows how the number of burned trees is directly dependent on certain features of the forest (density, wetness, etc) and how minor changes in those features can dramatically change the outcome.
    • Static: Maybe...Not too sure about this one.
    • Visualizing:
    • Structural: Not really.
    • Equation: Probably we will meet linear dependence in this unit; following the graphs of the various bottle pressure bottles, etc.
    • Compsoc: This could be worked in, but isn't there now.
    • Predator/Prey: In this unit we look at the concepts of linear and exponential growth and decay, among others.
    • Chaos: No.
  • e. Understanding basic statistical ideas such as averages, variability and probability.
    • Foundations: Strong support
    • Fire: At the end of this unit the student should be able to understand that one cannot make sufficiently accurate conclusions about a model with only a single data set.
    • Static: Yes. To fill in some of the gaps in their data, students will need to be prepared to formulate estimatations.
    • Visualizing:
    • Structural: Yes, because the traversal (where we test the bridge by simulating a car driving over it) is a deterministic process. Maybe we could introduce the difference between probabilistic and deterministic.
    • Equation: It will certainly contain all the above mentioned ideas cause we are talking about predicting events, simulating models and analyzing predicted events.
    • Compsoc: Nope.
    • Predator/Prey: Only so much as these ideas would be helpful in a particular model.
    • Chaos: Yes.
  • f. Making estimates and checking the reasonableness of answers.
    • Foundations: Vetting data covers this
    • Fire: In the beginning of the lab portion of this unit, the student should take a guess at what the result will be when the density of the forest is varied. After running a number of trials, they should be able to easily assess the accuracy of they're answer as well as the reasonableness of their results from the lab.
    • Static: Totally
    • Visualizing:
    • Structural: Yes, because students will try to build different types of bridges and determine the 'reasonableness' of their solutions by the simulated test outcome.
    • Equation: "Yes, estimation and confirmation are important part of the unit.
    • Compsoc: In a more abstract way than most mathiness.
    • Predator/Prey: Experimentation is used when developing models and there is an analysis part of our lab.
    • Chaos: Yes.
  • g. Recognizing the limitations of mathematical and statistical methods.
    • Foundations: Analysis of this unit's support or not for this item.
    • Fire: The student should clearly note that this model of wildfires is far from indicative of how they actually happen. It should be stressed that this model is simply proof of concept for showing the profound effect a single variable can have on the overall results.
    • Static: Oh yeah...
    • Visualizing:
    • Structural: yes, because the physical model will not account for all variables, such as wind.
    • Equation: Even if numbers of paper have power to predict and evaluate something; real life experiment can always show more than numbers.
    • Compsoc: This is fulfilled - the point of ABM is the limitation of mathematical and statistical methods.
    • Predator/Prey: When comparing SD to Agent based we will go into the relative strengths and weaknesses of SD in general and as compared to Agent based modeling.
    • Chaos: Yes.

Scientific Inquiry Requirement - From the [Catalog Description] Scientific inquiry:

• a. Develops students' understanding of the natural world.
  • Foundations: We lay the framework for understanding the world through models.
  • Fire: After the completion of this unit, the student should understand the world's dependence on a surprisingly small number of variables even though this model is far from accurate.
  • Static: The students are making static models of the natural world.
  • Visualizing:
  • Structural: Modeling physical structures is important because the natural world is comprised of physical structures.
  • Equation: The students are making a model which is going to resist gravity, but also be affected by natural happenings like air drag, and possible weather features.
  • Compsoc: Yes. Agent based methodology informs a way of thinking about natural processes that differs from more typical techniques - the ideas of emergent behavior are present in every day life.
  • Predator/Prey: They can model natural systems including our example, Predator-Prey models.
  • Chaos: Yes.
• b. Strengthens students' knowledge of the scientific way of knowing — the use of systematic observation and experimentation to develop theories and test hypotheses.
  • Foundations: One of the major take-away points of this unit is how to develop a scientific knowledge of a situation.
    • In order to test hypotheses students need to build models and apply them to the real world
    • Well established in this unit
  • Fire: The entirety of this lab is to change a variable, observe the results, and repeat, eventually leading to having enough data to make reasonable theories on the model.
  • Static: Students will define a new framework for describing their environment in a static model.
  • Visualizing:
  • Structural: The students will determine the most appropriate method to build a simulated bridge through both lecture content and trial and error. They will test their models by building physical models of their virtual structures.
  • Equation: The students will have chance to pre-use computer simulators and software which are going to possibly give them ideas to develop their own ideas about the model and predictions of occurrences throughout the lab.
  • Compsoc: None.
  • Predator/Prey: Experimentation is used when developing models.
  • Chaos: No.
• c. Emphasizes and provides first-hand experience with both theoretical analysis and the collection of empirical data.
  • Foundations: The second major point in the above lecture notes is how do we collect data
    • Collecting data is divided into first-hand experience and using other people's data (theoretical analysis)
    • Well established in this unit.
  • Fire: The lab portion of this unit is exactly this: gathering numerical data in order to provide the basis for some sort of conclusion.
  • Static: Again, the students are collecting data and developing an effective way to represent that data to describe a physical space.
  • Visualizing:
  • Structural: The students collect the empirical data by synthesizing lecture content and trial and error. They (potentially in groups) will each devise different models to solve the same problem.
  • Equation: The lab will be the main medium of experiencing the real model evolving; and cause of that will be collection of data and students analysis of ones.
  • Compsoc: Yes. Models = theoretical. Analyzing one's own social circle, for example, is empirical collection.
  • Predator/Prey: We certainly provide some experience with theoretical analysis but not much empirical data will be collected.
  • Chaos: No.