This is the second of a two-part blog post in which Suzanne Z. Gottschang from Smith College outlines the benefits of integrating real-world examples into an introductory cultural anthropology course.
In my last blog post, I described how my introductory cultural anthropology class took on a last-minute opportunity and conducted observations and interviews in collaboration with a consulting firm working on plans for a College library renovation. First- and second-year students defined the parameters of our project, conducted observations of study spaces across the campus, and summarized their findings for the consulting firm. In this post, I describe how we used this research opportunity to learn more about data analysis in anthropology and reflect on how their final ethnographic papers turned out.
Once students submitted their PowerPoint summary slides to the consulting firm, I realized there was an opportunity to help them learn more about the subjective nature of data analysis. We had already learned about the importance of reflexivity and positionality in shaping what research questions are asked and the conclusions that can result. Now, students could compare the data analysis they performed using the consulting firm’s methods with coding and textual analysis used in anthropology and other social sciences. I just had to figure out how to revise the syllabus one more time to weave these tasks into my original plan to introduce the students to a selection of key topics and issues in cultural anthropology.
The co-director of Smith’s Design Thinking Initiative, Zaza Kabayadondo and I came up with a series of short exercises we could introduce over the course of a few weeks to take the students through coding and textual analysis. Dr. Kabayadondo’s background in anthropology and education made it possible for the plan to come together quickly. She volunteered to help facilitate the session where students would begin coding. Arriving with lots of supplies—colorful post-it notes, big sheets of paper, and magic markers, Dr. Kabayadondo immediately had the students’ attention. We decided that instead of working with their field notes, we would have students practice coding with transcripts of interviews from one of my research projects. We thought that it would be easier for the class to try out their ideas on data that was not attached to their fieldwork.
I had circulated selections from the transcripts to the students beforehand and asked them to read through them and make some notes before class. They then joined their fieldwork groups and decided on the key themes they found in the transcripts and wrote these on post-it notes. Representatives from each group brought these up to the front board where they posted them. A second group of students then came to the board to start organizing the notes according to common themes, and a third and fourth round brought refinement, and ultimately, identification of some broad categories that captured most of the themes. As we went through these iterations, we discussed the choices being made. It was a bit chaotic but by the end of the class, students had a sense of how to identify key themes and how to cluster these into broader categories. With some practice under their belts the students then turned to coding and analyzing their own data.
When students had completed their own coding, we spent part of a class session comparing their work with the representation of the data using the consulting firm’s template. It was a powerful moment as I witnessed the class develop a sophisticated understanding of the pros and cons of each technique and the implications for analysis and interpretation of the data. In years past, students in my course chose an activity or area to observe, wrote a brief research proposal, and conducted a few observations to provide data for their ethnographic research papers. This year was no different in that students were expected to write an ethnography based on their observations and interviews. What was different was the quality of these papers. They were extraordinary. Almost every paper contained a nuanced and sophisticated analysis of the data and was well argued and well written. I bored friends and family as I graded these essays—making them listen to particularly cogent and articulate passages.
I know that these papers represented the work of truly engaged students. They had mastered their subject matter, owned their analysis, and as a result wrote clearly and thoughtfully. I am looking for another real project for my class next fall with the hope that I will only need to revise the syllabus once or twice.
Suzanne Z. Gottschang is a medical anthropologist with research interests in women, health technology, and policy in the US and China. She is an Associate Professor at Smith College in Anthropology and East Asian Studies. In addition to her work on motherhood, infant feeding, and health policy in China, she is currently researching the commodification of breastmilk, e-medicine and mobile medicine, and traditional Chinese veterinary medicine in the US and China.