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  • Writer's pictureCharlene Holkenbrink-Monk

On Teaching Stats

“I feel so smart!” one student exclaimed. I looked over as she had her phone out, using the Desmos app as her calculator. Calculating her IQV, or index for qualitative variation, she was excited to see the variability for her nominal variable, race, and situating it within the larger picture. Meanwhile, a group in the far left corner of the room was reviewing their data, connecting pieces, and researching articles that were related to race and income, looking at the sociopolitical and historical conditions that have contributed to the many socioeconomic disparities across social identities.


At one college where I teach, I teach an Introduction to Social Statistics course, where generally speaking, in a class of 40 students I may find between 2-5 sociology majors. Most students who take this course with me public health, kinesiology, communications, or other majors housed in arts and letters. While they may have been introduced to an introductory sociology course, or even these critical perspectives, sociological theory is the last on their list of topics to learn, and yet, students from different backgrounds majors are applying newly discovered, fostered, or developed sociological imaginations.

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In my sociology courses, they do not have midterms or final exams. Let me preface this by saying that I am not against tests; they absolutely have their place. However, due to the nature of my teaching approach, which relies heavily on collaborative and dialogic pedagogy, what I have found best aligns with my philosophy and goals is that of periodic quizzes, case studies, and a final portfolio. Let me explain as they relate to the timing of the course.


The very first assignment my students have is a math journey map and reflection. This ends up going into their portfolio. In this journey, students reflect on their relationships to math, identifying the important moments that have impacted their positive or negative views of taking statistics. And this was absolutely influenced by two things: a very similar assignment I was assigned by a professor in my PhD program, Dr. Felisha Herrera Villarreal, as well as my own experiences. I speak upfront with my students that I struggled in statistics in undergrad, finally having it make sense in its applied form and going on to take several quantitative reasoning courses. I can identify a few key moments that devastated my relationship with math as well as doing damage to my own Korean cultural identity (but something I’ll discuss in more detail another time.) This transparency and honesty often build a strong relationship with students, as many of them are either taking this a second time or have severe math anxiety. After they’ve created visual maps in class, they share them in small groups, up to what they are comfortable with sharing, and then put them into their portfolios with a short written reflection.


Additionally, I have created ten student learning outcomes (SLOs)** I expect my students to meet by the end of the semester. These student learning outcomes are clearly defined in the syllabus, and I revisit them throughout the course. These SLOs are vital as they must share how they have met them in their portfolio. Essentially, throughout the semester they collect various pieces of work that meet each of the student learning outcomes, expected to provide evidence of 2-3 pieces of work. They must be able to articulate and justify how they have met the outcomes; merely cutting and pasting the work is not enough, but they must be able to articulate the concepts present in the materials, have an understanding of the statistical ideas, and be able to highlight how they learned them and what they mean in the context of the social world. Meanwhile, at the end of the portfolio, which can be done either through a website, a set of Google slides, or any other modality so long as they meet the rubric outline, they provide a final reflection. One of the key goals of the course is not to only learn statistics, but to also build confidence. Yes, statistical concepts are necessary and there is no denying it, and a requirement of the course curriculum and materials. However, students will not be able to progress and proceed beyond an introductory social statistics course into higher levels of quantitative reasoning if they do not feel confident in their ability to calculate materials, articulate them, and interpret the data.


While they have quizzes and their final portfolio, they have two other assessments: case studies and creative projects. I’ll explain the case studies first. For the case studies, I give them raw data. In the very first case study, they create surveys. We review articles and surveys and then ask what types of questions they can ask; from there, they separate them into nominal, ordinal, and interval-ratio variables. They administer the surveys only in the class and we discuss sample sizes and representation as well. From there, they begin calculating the data, putting them into percentage distribution tables. (Also, these tables end up being incredibly valuable because they eventually learn how the formulas do not need to be scary, having all of the numbers directly in front of them and being able to plug in the values directly into formulas.) Through this, they also explore visual representation, accessible to introductory levels, such as pie charts and bar graphs, important components of labeling these, and how to interpret the data. Let me note that while these are done collaboratively and in a group, each individual person is graded individually. I have a rubric that outlines what each person should have completed. I choose a collaborative group approach for two reasons: 1) To create smaller classroom communities that can work together, support each other, and help each other learn through their calculations and 2) to be able to learn to work together to identify patterns. So, while they are graded individually, they then collaborate to find details, and patterns, and come to some sort of conclusion while discussing what their limitations are. And yes, this is an introductory stats class still. And yes, using raw data has highlighted the accessibility and applicability of social statistics for many.


We repeat this 4 times throughout the semester, and each group is randomized. By the final case study, they interpreted the data, ran hypothesis tests, and articulated how they would explore bivariate tables as a few examples (and each case study is in alignment with the chapters and concepts we cover; I scaffold the concepts so they are progressive.) They have looked up articles, highlighting statistics and media literacy, and connected those materials to their final data. Then, they take the materials they’ve done and create individual creative projects. I have a rubric that discusses all of the elements that they must incorporate, including how they would run ANOVA tests, Chi-Square tests, and more. They are not expected to calculate new data, but instead, use materials from their case studies to creatively, and accessibly, report on the data while also discussing the social implications and utilizing a sociological imagination to problem-pose. Some examples in the past have included news skits, poems, artistic displays (with a written explanation), or, in one instance, a video of somebody taking data on states and cross-stitching the shapes of the states along with the statistics notations and interpreting them within the social world and explaining various outcomes and proposed solutions. The intention of this is to ensure that social statistics can be articulated and accessible, to understand what they mean rather than merely what the numbers are.


And then lastly, of course, is their finalized portfolio. The portfolio, again, takes work samples and they make a justification for each SLO as to how they met them and the ways that their work exemplifies their understanding. I also provide a rubric so they are fully aware of how they will be graded while allowing them autonomy to be creative with their final project of the semester as well.


Throughout the semester the students are paired up in randomized groups as I noted earlier. One of the coolest things that I have witnessed is not just statistical progression, but students’ exclamations of, “I feel so smart!” Or even the moments where they say, “I was really overthinking this - this is a lot better than I thought it would be.” My goal is never for them to become statisticians by the end of a class, though if they want that, of course, I would support them. I explain to them that I am aware this is the last class many of them want to take, but my job is to make them feel confident, develop an understanding of the materials, and understand how to collaborate and dialogue in a classroom setting, yes, even if it has to do with numbers.


I design my statistics classes in a way that aligns with my teaching philosophy, one that is rooted in collaborative, dialogic, and critical perspectives. It is important for me to recognize my students’ abilities beyond the scope of traditional schooling expectations. I see my role as not just a teacher, but someone who is responsible for fostering a learning environment that builds confidence, centers community, and investigates the social world.

I am a big advocate for collaborative classroom settings and have found that this has been no different in the social statistics classes I have taught. They discuss lived experiences, become friends, support each other, and explore data and realities on things that they had no idea existed, such as healthcare disparities, access to education, and more. This is so vital to me within the scope of social statistics and application. And though I do not typically conduct quantitative research (merely because I am the nature of qualitative research and storytelling,) I do love teaching statistics for the sole reason of seeing my students light up and smile when they realize that they are, in fact, capable.


**If you’d like to see my student learning outcomes, stay tuned and hit subscribe as I’ll share those in another post.

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