Quantitative Reasoning Notes
Paragraph describing the issues the Quantitative Skills group is interested in.
Ripon comments–What can they learn in calculus that they need in physics?
How do you get departments to discuss the needs and the wants and ability of departments to meet the needs and the wants
What are some ways to keep the autonomy while meeting the needs and wants.
Needs and wants–calculus at cornell did this, but now it is back to the autonymous piece, so there needs to be the initial discussion and a maintained discussion–let people know where it is coming from; why it is being done that way.
Also the cry for basic mathematical skills–how are the "tools" used in other classes if the other class "says" they require the content.
Ripon math asked for the laundry list of needs from the mathematics department
What can math do and not do?
Need to have discussions:
1. Where the the terminologies among disciplines differ?
2. What are some "discipline approved" examples that can be used in calculus or stats that is not contrived to the discipline but helps people see how to use the concept?
3. In what ways could "discipline-specific" faculty be included as "guests" in the mathematics courses when the examples are used?
4. How can you transfer the scientific concepts into mathematical language?
5. How to facilitate the discussion to make these happen?–work better to have an all-ACM discussion rather than an all-institutional discussion–less possibilities.
Grinnell comment–Bio 150 been helpful in stats class because students need the stats material to do the bio work–now becomes important. Could take direct assignments from science disciplines and do it again in a mathematics course.
Have to be careful–want to make sure that the course is not JUST service to other departments. Must have an honesty though that the courses are filled with people who see it as a service course.
There are models of this
Focus on helping the students, not helping the client discipline.
Would still have the conversations–but the focus would be to help the students, which could lead to the discussion.
"Do you still use this or teach this in your class?"
"What examples are confusing/no longer relevant to the students?"
"What quantitative reasoning skills do your students need in your discipline? Why?"
"What are some examples of things you do in your classes or you expect students to know where students need skills or concepts learned in mathematics courses? Can we use these examples in our courses if we think it makes sense?"
"What primary journal articles could be read by students who don't have a background in your discipline?
"Where are areas where your students collect and analyze data and in what ways do they have trouble in understanding the analysis?"
PURPOSE: To open the lines of communication among science and other department faculty, where the discipline requires quantitative skills taught by the mathematics departments, and mathematics department faculty with the focus of enhancing student learning in both mathematics and the other departments.
Create discussions about helping students learn by understanding the links between programs that use mathematics as a tool and mathematics faculty
A couple of distinct models to begin the discussion:
1) include all ACM schools to ask questions of where the overlap is?
2) include all ACM schools to distill the information
1) create small pods of schools (2 or 3) who would work both from a distance and in person.
IN either case, the first step is to get the conversation going in a non-threatening, non-promising way.
Next steps–Look at lessons learned
One person at each school.
1. How do you make sure the discussions occur?
2. Might be helpful to create initial examples to allow faculty to respond.
Scratch this model
1) mathematics professors sharing with the science and other mathematics faculty of the types of examples they want to use (population model–good data set?, difference between exponential and quadratic data and how calculus can help; global warmiing;....)
- Step 1 1) Across disciplines across ACM; 2) Across disciplines within an institution
- Step b
- Step other