Category Archives: Math

Webtools for math teaching

This semester I’m using Gradescope for homework and exam grading.  It is working relatively well, although not perfectly.  This enables us to reuse feedback, makes it easy for me to review regrade requests, and gives us access to all student work in the course.

For our discussion board, we’re using Piazza, mainly because it’s easy to type in the math via their built in Latex.

Online homework, via Webwork,  forms a portion of each homework assignment.  These are mainly exercise type questions so that students can receive immediate feedback on whether they are applying procedures properly.

I am curious to take a look at iMathAS at some point.  Webwork has a nice bank of questions from the text our course is aligned with, and there is some convenience to that, but it seems worth checking out other options.

Other versions of multivariable

Resources for multivariable calculus:

Vector calculus earlier in the semester?

Flux is a particularly central scientific and mathematically idea that appears in the context of a multivariable calculus course.  Given a velocity vector field and a surface, the flux of the vector field through the surface tells us the rate at which fluid is flowing through the surface.  This leads to important ideas of balance.  If material is flowing out of a closed surface, then either the amount of material in the enclosed region is changing in time, or there is some source of material sitting within the region.

Flux it is often covered towards the end of a multivariable course, in the vector calculus portion.  In the article “Early Vector Calculus: A Path Through Multivariable Calculus” by Robert Robertson, he discusses a path through the course that makes the idea of flux more central.  To work with flux, and the related divergence theorem, students need to have been exposed to partial derivatives, vectors and the vector dot product, solid regions and their bounding surfaces, triple integrals, surface integrals, and vector fields.  For surface integrals, the cross product is useful for constructing area patches on a surface (with corresponding normal vectors) that are taken to an infinitesimal limit to construct a flux integral.

For a solid region sitting in 3-space, the divergence theorem relates the the triple integral of the divergence of a vector field over a region to the flux through the surface.  Making sense of the triple integral, being able to set it up, and being able to compute the integrand, requires familiarity with vector fields, partial derivatives, solid regions, and triple integration.  This could be done in Cartesian coordinates at first.  Making sense of the flux integral over a surface requires the notion of a surface and of an area element with a surface normal vector.  This ties into the idea of tangent planes with their normal vectors.  It also draws on knowledge of double integration.

The divergence theorem is also used over a region in 2-space with a closed curve for a boundary.  Working with it in this context requires familiarity with double integrals, vector fields, partial derivatives, and boundaries.  In addition, working with the flux across a closed curve requires familiarity with parameterizing curves, computing line integrals, and finding tangent and normal vectors to curves.

Topics often taught prior to the divergence theorem that do not obviously have immediate relevance to the theorem include directional derivatives, the chain rule, and optimization.  Further study of line integrals does make good use of background in directional derivatives and the chain rule, however the specific line integral needed for the 2D divergence theorem can perhaps be explicated without these ideas.

I often include a small amount of probability in the integration section of the course in addition to covering optimization.  It is true that these two topic areas sit somewhat to the side of other content in the course and could potentially be taught later in the course.  This is an intriguing suggestion that perhaps deserves further consideration.

 

Robertson, Robert L. “Early Vector Calculus: A Path Through Multivariable Calculus.” PRIMUS 23, no. 2 (2013): 133-140.

Reading “Student learning objectives and mathematics teaching”

I am working to write learning objectives for multivariable calculus this Fall. This article helped distinguish between overarching goals (that students are able to fit the math in the course into a greater understanding of math and of the world) and the learning objectives, of what I hope students will be able to do mathematically after taking the course.

Thinking about goals reminded me that, as in all classes, learning to learn within a disciplinary setting is a goal I think is important. In addition, specifically for multivariable, there is a real potential to start seeing the world through the lens of the course. Thinking about wind as a vector field, about falling leaves via flux, and about everyday shapes via the functions and parameterizations of the course is a possibility. The article also brought up history as a possible goal. I have not actively worked to situate the math we learn within the history of mathematical problem solving, but it is something I would like to learn more about in the longer term.

Reading “Statistics Done Wrong”

While discussing course design for our mathematical modeling course in the Spring, my colleague recommended paging through Statistics Done Wrong.  I find the book’s description of the p-value useful: “A p value is … a measure of how surprised you should be if there is no actual difference between the groups, but you got data suggesting there is. … I can get a tiny p value by either measuring a huge effect – ‘this medicine makes people live four times longer’ – or by measuring a tiny effect with great certainty.”

The author explains statistical power via a coin-flipping example.  Given some number of coin-flips…

 

Random – to look up: hedonic treadmill.