Using ethnographic research to improve students’ qualitative literacy

October 15, 2018

This post is republished from Into Practicea biweekly communication of Harvard’s Office of the Vice Provost for Advances in Learning

Mario Luis SmallIn distinguishing fact from opinion, quantitative information is often seen as more reliable, but Mario Luis Small, Grafstein Family Professor of Sociology, wants students also to see the value of qualitative data for assessing such claims. In his course Qualitative Network Analysis, he requires students to analyze empirical research (including their own ethnographic cases) with a qualitative lens and thoroughly evaluate “authors who believe they’re making a defensible claim about some aspect of society.”

The benefits: As the emphasis on quantitative data increases, especially within the journalism industry, Small believes challenging students to analyze data through the lens of ethnographic cases improves their qualitative literacy.

The challenges: While students have ample opportunities to analyze quantitative data in their other courses, Small believes they find it more difficult to distinguish an empirically sound qualitative social science piece from one that is merely well-written.


Takeaways and best practices:

  • Emphasize the nature and power of evidence. Small wants his students to see the power of persuasiveness and urges them to distinguish qualitative data in social science from evidence found within literary contexts. Evidence always matters, but to varying degrees. “We may disagree over your reading of Shakespeare, but it’s not as if at the end of the day we’re going to be arguing that your interpretation or opinion is factually incorrect.”
  • Assign projects applying theory to lived experience. To deepen undergraduate students’ understanding of qualitative evidence, Small engages them in ethnographic research by writing short case studies. Students select a theory discussed in the course and identify an aspect of the world to which the theorist speaks, describing the case—for example, from a book, scene, or movie—and to what degree it supports the theory.
  • Challenge preconceptions on quantity and quality. To push students to think more deeply about criteria distinguishing high- and low-quality research, Small often asks, “are two cases better than one?” In response, students typically say “’two, of course,’ but cannot articulate why.” He then challenges them to think about potential constraints researchers face when conducting multiple case studies, and explains that “working professionally in a context with limited resources means half as much research can be done on two cases as on one.” Small makes the same point when discussing case study assignments, helping students “see more clearly that while you can’t do a deep analysis of 30 movies, you can do a thorough analysis of Mean Girls.”

Bottom line: “The field of social network analysis is technical and quantitative, but also based upon a fundamental set of perspectives on the social world that should be understood conceptually. My courses are almost always designed around conceptually understanding this work.”

See also: FASdataliterature-based learning