Food Science Class Lab 1: Testing oven temp

The on-line food science class has begun.  Just to clarify: I am taking this class, not teaching it.  Our first lab was to use sugar to test the temperature of our ovens.  Sugar melts at 366F.  So we were instructed to put 1/2 Tbsp of sugar in the oven at 350F, wait 15 minutes to see what happens, and raise the temp by 10 degrees until it melts.  To make things more interesting, I did this experiment in 10 spots (5 spots in the middle of the oven and the same 5 spots in the bottom of the oven).

Here is my sugar at 350F.

Here it is at 325F.

Some of the brown underneath the sugar that didn't melt is leftover sugar from 350F experiment. I tried to scrub it off the foil the best I could, but some of it was stuck and I didn't want to waste a ton more foil. But the bottom left corner is indeed melted even when my knob says 325F.

What was interesting to me was the difference in temperatures from front to back, and middle to bottom of the oven.  Bottom back was the hottest and front middle was the coolest.  My oven is roughly 25-40 degrees off if you average all the spots.  I can't measure it more accurately since my knob only goes in 25 degree increments.  

Since I am a teacher, I couldn't help analyzing the educational value of this exercise.  It does raise awareness about the imprecise nature of most cooking equipment.  It also makes you think out of the box, and helps you realize that a thermometer is not the only way to measure temperature.  But I think the lab fails to demonstrate to students what science is all about.  High school and even most undergraduate science courses taught us that science is mostly made out of formulas.  There are constants, like the melting temperature of sugar and there are variables, like your oven knob.  You plug in the numbers and out comes an answer.  But your ability to plug numbers into formulas is not what makes a good scientist or cook. 

The easiest way to explain a scientific mindset is to show you two types of cooking questions that I get from students.  For privacy purposes, I have changed the names of students and the ingredients in question.

E-mail from John:

My steak is always tough when I grill it.  Can you help me.

E-mail from Jane:

I can't get consistent results with hard boiled eggs.  I start with large eggs out of the fridge.  When I add them to water, I return it to 200F as quickly as possible and then set the timer for 9 minutes (I maintain 200F with a thermometer).  Sometimes, they come out just right -- solid white, solid yolk, no green ring.  Yet, sometimes my yolk is not completely solid.  Can you help me.

I tried to ask John for more information.  What cut of meat did he use?  How thick was the steak?  What was the internal temperature of the steak when it came off the grill?  How long did the steak rest and what was the temperature after resting?  Unfortunately, he couldn't give me any answers and without them, it was hard to pinpoint the problem.

Jane on the other hand gave me a lot of info.  She paid attention to the temperature, the time, the size of the eggs, and the final result.  This made it very easy to help her.  "Large" eggs vary in size tremendously.  There is a minimum size for the egg to be sold as "large," but no maximum size.  I suggested that Jane weigh her eggs to figure out their real size and adjust the timing accordingly.  We added an extra minute of cooking for eggs that were closer to "extra large" size, and the problem was solved.

Jane is thinking like a scientist.  She understands what the variables are and makes careful note of them: time, temperature, egg size.  She is keeping all the variables the same, thus expecting the same result.  Because she observes a different result, she suspects that there is another variable she is not taking into account and is trying to find it.  It turned out it was not another variable, but a wrong assumption.  Jane, of course, knew that the size of the eggs would matter.  But she assumed that all "large" eggs were the same size.  I made that mistake for years.  Being clear about what your assumptions are, what's outside of your control and might result in an error is crucial for good experiment design.  

Drawing good conclusion from data is also important.  After our lab in the food science class where we measured the temperature of our oven, one of the students was so dismayed that he was off by 45 degrees that he thought he needed a new oven.  That's like saying that you need a new carton of "large" eggs because some are larger and some are smaller.  If you know your oven runs hot, it's easy to always set it cooler than the recipe specifies.  What would interest me more is learning the location of the hot spots and cold spots in my oven so that I could use them to my advantage.  It would also be interesting to know if the 45 degree deviation is the same at higher temperatures and lower temperatures.  So, let's not run out to get a new oven just yet, but let's keep asking questions.  

Here is an idea for how this exercise could be changed to help teach science more than formulas.  

Come up with some hypothesis about how your oven works.  Maybe you suspect that the right side is hotter than the left.  Maybe you don't think one on/off cycle is sufficient to preheat it to desired temperature.  Maybe the oven seems to run hot or cold.  Hypothesis is a guess based on preliminary observation.  Set up an experiment to test your hypothesis.  Record your data, assumptions, and possible errors.