{"id":1163,"date":"2016-08-19T16:43:24","date_gmt":"2016-08-19T20:43:24","guid":{"rendered":"https:\/\/www.causeweb.org\/sbi\/?p=1163"},"modified":"2016-08-21T15:04:42","modified_gmt":"2016-08-21T19:04:42","slug":"chocolate-tactile-simulations-without-data-collection","status":"publish","type":"post","link":"https:\/\/www.causeweb.org\/sbi\/?p=1163","title":{"rendered":"Chocolate: tactile simulations without data collection"},"content":{"rendered":"

\"jo_headshot8\"<\/a>Jo Hardin – Pomona College, Claremont, CA<\/strong><\/p>\n

Many of us will agree that using tactile demonstrations is super fun and can also be an excellent way to teach a particular concept.\u00a0 Students engage with the material differently when they can touch, smell, or taste the objects as opposed to only seeing or listening to a demonstration.\u00a0 The SBI blog has had many excellent articles describing in-class tactile simulations, see here<\/a> and here<\/a> and here<\/a>.<\/p>\n

However, sometimes the logistical constraints setting up the demonstration take away too much from an already packed 50 minute class session.\u00a0 And those details get even harder with large classes.\u00a0 One of the biggest challenges comes from collecting data or getting results back from the students.\u00a0 Although some classes have sophisticated clickers that make data collection easier, setting up and using clickers is also a logistical challenge (well worth it for using all semester, but not for a one day class demonstration).<\/p>\n

[pullquote]The conversation that ensues about the experimental design is incredibly valuable for understanding paired design (and the motivation for the pairing) or survival analysis (and the need for tools to analyze censored data).\u00a0[\/pullquote]
\nMy view on classroom demonstrations is that doing most of the tactile demonstration can communicate the vast majority of the pedagogical ideas.\u00a0 I will demonstrate what I mean with examples using chocolate chips.\u00a0 I have used chocolate chips in class many times to teach two different concepts: (1) censored data analyzed with survival analysis (example taken from Practicing Statistics<\/em> by Kuiper and Sklar) and (2) paired tests (example taken from Investigating Statistical Concepts, Applications, and Methods<\/em> by Chance and Rossman).<\/p>\n

In both classroom experiences, I provide small Dixie cups with two visibly different types of chocolate chips (typically two of either white chocolate, milk chocolate, semi-sweet chocolate, or peanut-butter chips).<\/p>\n

Then we spend some time as a class talking about the experiment and the goal of the experiment.\u00a0 For both of the statistical methods I cover in class, the goal is to compare the length of time taken to melt the two different types of chips (the length of time is described by: the average if doing t-tests; the distribution if doing signed-rank test; the survival curve if doing survival analysis).\u00a0 \u00a0I will give some details of the class interactions below, but many of these ideas are also discussed in the texts mentioned above and in the references.\u00a0 For simplicity, I will describe using a paired t-test to determine if milk or white chocolate chips melt faster, on average.<\/p>\n

I always start with a basic question: What will we do to determine which chocolate chip melts faster on average?<\/p>\n

Inevitably, I get a basic answer in return: Put chocolate chips in mouth, see how long it takes to melt, record data, decide which one melts faster.<\/p>\n

And then I stop and ask them how in the world they\u2019ll know how to do what they just suggested?\u00a0 There is a tremendous amount of additional information necessary before running a viable experiment.\u00a0 Among the important decisions to be made (by class consensus) are:<\/p>\n