We had to write a teaching philosophy statement, summarizing our approach/attitude towards teaching math and stats, for our seminar class. I’m going to post mine here. It explains how I like to think about teaching stats and emphasizes what I consider to be the most important things to keep in mind while delivering the subject to students who may be less than enthusiastic about anything number-related.

I have, for the majority of my life, been a student, but only recently have I taken on the role of a teacher. From 2012 to 2014, I worked as a lecturer at the University of Idaho, teaching introductory statistics to undergraduate students. Though I was brand new to teaching and wary about teaching material that had the reputation of being boring, difficult, or both, it took me only my first semester to solidify my teaching philosophy and to develop instructional techniques that have been proven effective in getting students interested in and engaged in learning statistics.

My approach to teaching can be best broken into four key components: empathy for the students, flexibility in the teaching techniques and methods, enthusiasm for the material, and the ability to show real-world application of the material. These four components work together to emphasize my core teaching philosophy and goals: in order to best foster learning, teaching should not only cater to the student but cater to the subject being taught as well, allowing for students to have a learning experience that allows them to see both the technical and the practical side of the material.

Unlike many who end up as lecturers in mathematics or statistics, I come from a background heavy in the humanities and the social sciences. Due to this background, I am able to easily empathize with students who may lack a strong mathematical background and thus may be intimidated or nervous about taking a statistics course. Such students are common in introductory courses similar to the ones I have taught, as these courses are usually used to fulfill a course requirement and are often the only classroom exposure to statistics that many students get.

An empathetic mindset—especially when introducing “basic” concepts and notations that may be brand new to many of the students in the class—is a mindset I try to adopt when teaching. Telling students that it’s okay if this is the first time they’ve seen how to calculate a mean or how to read summation notation, and then to walk them through it slowly but without condescension, can go a long way towards fostering a good relationship with them while also making them feel more comfortable with the material. In my two years of lecturing, I had many students comment that they appreciated the fact that I took the time to teach them the very basic components of statistics before delving into the more complicated material and that this helped them feel more at ease in the class.

Along with empathy for the students, another important component in my approach to teaching is to be flexible with how the material is taught. Most statistical concepts can be explained in several different ways—showing students the equations, explaining a concept using an analogy, creating a visual representation of the concept, among others. I have learned that it is important to try to approach and explain a concept from several different angles to allow as many students to grasp the concept as possible. For example, when students are learning about analysis of variance, I have found that some students understood it by looking at the equation for the F statistic, while others understood it by seeing a visual of the variances that the F statistic is actually comparing. Being able to explain a concept from multiple angles helps to make sure that every student is able to grasp the concept and understand it in a way that’s best for them.

The third component to my teaching approach is one that I feel is especially important but often overlooked in the field of statistics—showing enthusiasm for the material. In my own experience as a student, when an instructor fails to show interest for the topic they are teaching, it becomes difficult to remain engaged in the class and ultimately more difficult to learn. For a subject like statistics, which already seems to have a reputation of being dry and boring for many students, it is important for an instructor to be able to show that the material and concepts that they are teaching are more than just equations on a page.

For me, part of showing my enthusiasm for the subject is to really try to give students an “under the hood” look at statistics. Rather than just show them a formula or tell them a theorem, I’ve found that students remain much more engaged if they are shown why a formula is the way it is or why a theorem is important. For example, when teaching students the general formula used to calculate binomial probability, I choose to “derive” the formula by using some basic probability examples and then work up to the actual formula itself. Giving them this deeper glimpse into why the formula is written the way it is not only gives them a better understanding of the formula itself (they are no longer just “blindly” using it but understand the reasons behind it), but it also engages them in the process of seeing how and why the formula works.

Another way of showing enthusiasm for the subject is to present students with fun and interesting examples of concepts they are being taught. For example, after students learn about visuals like bar charts and histograms, I like to take a few minutes and show them some examples of poorly constructed or exaggerated graphs used by the media or by politicians. Bringing some humorous or interesting examples into the classroom can help keep students engaged and make them more interested in the subject.

Related to the concept of showing enthusiasm for the material, the fourth and final component of my approach to teaching is to make sure to give students some real-world applications of the material they learn in the classroom. This is a component that I think is especially important in teaching an introductory statistics course, as nearly all academic fields employ statistical procedures to some degree, but students from other disciplines often think that they will never use the techniques they learn in class. The main way I employ this component is by using actual data from various different fields in my in-class examples. When teaching regression, I use data from a published psychology study. When teaching analysis of variance, I use data from a plant breeding program or data from a business-related study. I feel that it is important to emphasize to students through examples that the techniques they learn in their statistics courses can and often are applied in their own fields.

My application of these four key components in my teaching has proven effective in providing a good learning experience for students. I consistently received positive teaching reviews during my time at the University of Idaho, with many students commenting that they felt like they truly understood the material and had actually developed some enthusiasm for the field of statistics. I have also recently received a Graduate Teaching Assistant Excellence Award from the University of Calgary for my work as a TA in the fall of 2014. I plan to continue to adapt and modify my teaching strategies and techniques to further my goals as a teacher and to provide a comfortable, thorough, and enjoyable statistics education for students in both introductory courses and more advanced courses.