Part of my educational duties this past semester was as a teaching assistant for an undergraduate introductory biostatistics course. We went over the usual topics—calculating probabilities from tables, test statistics, hypothesis testing, linear and logistic regression—and I felt that the curriculum made a great effort to contextualize the material by organizing the content into goal-oriented modules. For example, linear regression was introduced as a tool for the specific goal of explaining college students’ GPA based on alcohol consumption-related characteristics. Whether or not the dataset that we gave to the students was the best source of information for investigating this relationship, I felt that there were two pedagogical ideas behind this module that were well implemented. First, the relationship being explored (I would guess) is one that piques the interest of a large percentage of the students. A lot of college students drink and almost everyone knows someone who drinks. It was great that the theme for this module was self-motivating. Second, the structure of the main assignment for the module forced students to write in a substantive way. The students had to come up with their own linear regression models to explore the relationship between GPA and drinking-related characteristics, and they were asked to write a report of their process, findings, and model interpretations—all things that are essential to understand when reading, writing, and discussing research findings.
I want to focus on these two teaching ideas for a bit and give my perspective on what we might need to do to adapt education for the future. Current events have precipitated a lot of intense and particularly emotion-backed discussion about racial injustice and inequality in general. From discussions with people much more knowledgeable and well-spoken than I am, I would have to say that perhaps the most essential asset that a lot of people don’t get from their education is an ability to think critically and argue rationally. These are hard things to do, and I think that school is the place to get people to practice.
As I’ve explained in previous posts, case-based learning is a great way to motivate the concepts being taught in class so that students can see their practical uses and therefore remember the ideas for the long-term. In creating examples and giving context to classroom content, we need to think hard about what those examples will be. Perhaps the best way to really engage students and get them to care about what they’re learning is to use the most current issues possible. For example, I think that someone who decided to create a case-based statistics course for the current generation might have a lot of success using both news and research articles about social inequality. I think the key is to relate what is being presented in the news to what research has actually been performed and get students to closely examine the relationship between these sources of information.
Rational argumentation is another skill that is lacking in our generation. Very often we tend to talk to and become friends with like-minded people, and we are not as easily forced to question our views and see fallacies in the bases for our opinions. Forcing conversation in an educational setting is a great way to break that comfort zone because there is such a diversity of opinion. I love that the statistics course that I taught for emphasized writing because it forced students to at least put some words behind what they were learning. Just having those words is several steps above rote calculation and memorization in terms of really embedding meaning and understanding. But the way to truly make the most of those words is to construct them carefully to tell a story, to make a point. Words as a list of facts do little to reinforce understanding. To this end, I think that educators should elevate the role of writing to the level of speech and debate. I see this having great potential in mathematics and statistics classrooms. Throughout a statistics course we teach students about tools and the assumptions behind them that are used to draw conclusions from data. To truly assess their understanding of statistical concepts and to put these concepts in a meaningful context, perhaps one of the key assignments or activities of the course would be to read scientific papers and have a debate. In this way, we can prepare students for the types of discussions that they’ll have throughout their life by helping them recognize reasoning flaws in the arguments of others as well as their own.