HS Math Instruction: Surprising similarities to digital art

As I continue my quest for student engagement in high school math, my eyes were opened this morning when I read a digital art curriculum.  I am now a convert that STEM should be STEAM.  Had I read the curriculum any other day, it may not have had the same effect as reading it today has had. Until today, I thought of digital art as the way for students without artistic talent to create cool pictures.  I now understand that producing digital art can mirror scientific method and the design process.  That’s something that should be true of my math class.

Today’s insight was influenced by yesterday’s. Yesterday was the day before spring break, which is a great time to experiment with risky pedagogical strategies because my high school students tend to be least likely to focus well.  I decided to try out the 3-act style, open modeling problem I wrote about feral cats awhile back for linear-exponential comparisons.  I haven’t had the nerve to try before because math curriculum is so dense, and students seem to need so much repetition.  But after I experienced their enthusiasm over an open modeling problem last fall about braking distances, I figured it was worth a try.  When I did braking distances, a colleague’s raised eyebrows made me wonder if I had wasted my student’s learning time because my objectives were fuzzy along with the openness.  On one hand, I saw my students‘ delight and awesome insights, on the other hand, they weren’t exactly reinforcing difficult procedural skills spelled out in the curriculum. The activity definitely peaked their interest and understanding of the usefulness of math, but was it worth it?

Yesterday’s 3-act produced similar results, but I also noticed some other things.  My students were beginning to see that it was okay to not be able to solve the problem.  They realized that there was a lot of math involved  in understanding the problem and in considering ways to possibly lessen the problem.  They realized they would need to have stronger math backgrounds to be able to have meaningful insights for solutions.  The math they needed would go beyond executing procedures with rational terms and logarithms; but most importantly, they realized that math used in real jobs, higher math, was within reasonable reach.

To underscore the fact that problem solving is often open in engineering schools, I played two brief videos of Rube Goldbergs:  Coke and Passover.  The students got the connection between thought processes for analyzing my feral cats problem and thought processes for designing a Rube Goldberg.  Following that, one student who regularly sneaks her crocheting into my class, enthusiastically explained her involvement in robotics competition.  The beautiful part was that few would ever associate a love of crocheting with an appreciation for STEM.  The point was clear:  If you want an interesting job in the 21st century, you need to be able to analyze problems.  The analysis process invariably involves math.

This bring me to today when I read about a Digital Art & Design class.  I learned that the projects begin with ideas that are roughed out and tested.  Some of the initial ideas may  seem outrageous at first but, upon refinement, turn out magnificently.  As I compared my student’s approaches to the feral cat problem (example: luring them to a ship and then sinking it?!), they exhibited those same qualities.  Much of what students would learn in a digital art class, they should also be learning in my math class:

  • You don’t have to have it all figured out before you dive in.
  • Revising your ideas doesn’t mean they were dumb.
  • Failing does not mean you are dumb.
  • Sometimes no one succeeds if someone doesn’t try something bold.
  • Persistence usually pays off.
  • The question should not be, “Where do I put the brush?” (in art); nor, “Where should I put that number?” (in math).
  • Maps, diagrams, and pictures may slow down the process of getting a right answer on a worksheet; but those skills are essential for solving serious problems that happen in real life.
  • Journaling procedures, mistakes, and workarounds helps establish a history of growth.
  • Digital art requires analysis of constraints (ie, cost, density, opacity, proportion, functionality of equipment…)  A little more math and physics can take a starving artist to prosperity.
  • Encoding and decoding artistic thought parallels computer coding and mathematical patterns. Take a computer class to see how it all fits together.
  • Think past 2D and learn about 3D.
  • One doesn’t have to have special genes to produce decent art, think through complex layers of problems, and contribute to creative solutions in collaborative teams.
  • STEM is not about building bridges out of toothpicks or limited to robots.
  • STEM rightfully includes the arts.  STEM should be STEAM because the arts are what connects solutions to stakeholders and product designs to potential consumers.


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