Pedagogies of Evidence, Accident, and Discovery: Teaching and Learning Ethnographic Methodology, Theory, and Serendipity, Part III

Posted by on Mar 7, 2017 in Teaching Anthropology | Comments Off on Pedagogies of Evidence, Accident, and Discovery: Teaching and Learning Ethnographic Methodology, Theory, and Serendipity, Part III

Stephen Chrisomalis
Wayne State University

March 7, 2017

I teach linguistic anthropology at a large public research university as a program requirement for both undergraduate and graduate students in anthropology and linguistics; for most of them, this is their only exposure to the subfield, its methods, and theories. This presents a challenge – to get students out of their typical ways of thinking about evidence and drawing their attention to the relation between discourse and cognition – but also an opportunity. I have never found it to be particularly challenging to interest anthropology students in formal methods and approaches as a complement to other ethnographic approaches. Archaeology students may already have some background in reading and using quantitative data, and the same is true of sociolinguists. Students interested in applied and practicing careers may be able to see how these approaches would be well-received in institutional settings.   Because they are unfettered by any particular pre-existing models of what constitutes ‘valid’ evidence in linguistic anthropology, this frees me up pedagogically to introduce students to a variety of qualitative and quantitative approaches in sociolinguistics, discourse analysis, cognitive anthropology, ethnosemantics, corpus linguistics, and other subfields.

But a real challenge is getting students to be aware of what sorts of questions they might ask, and how they might go about generating methods that would answer those questions without limiting the possibility of novel insights. Almost any question is answerable, but not all are equally interesting – in other words, not all have equal potential to generate new ideas.   I use in-class exercises to require students to specify their research questions, then use an iterative feedback process using small peer groups and, where necessary, my own insight, to get them to ‘good’ questions. But this is very tricky, because even if the potential (or lack thereof) of a question is obvious to me, it is not always apparent to them. Under what circumstances, if any, is it ethical or pedagogically useful to have a student follow a lead that goes nowhere? Under what circumstances is it reasonable to intervene with the ‘right’ question, even if generated by me rather than the student? The answers here are not self-evident. Socratic strategies in one-on-one meetings with students (e.g., in office hours) help, but of course that requires that a student attend such a meeting.   It’s hard enough when faced with a student who is not motivated; perhaps even worse is the student who is motivated but isn’t quite there yet, and feels frustrated or shut down by my caution.

Even trickier than the problem of question-asking, perhaps, is the challenge of teaching students how to work with data in ways that let them reach good conclusions. Because most results of formal analyses are negative, the peril – particularly for students who are first-generation college students – is that the failure of an approach to “work” is treated as more catastrophic than it need be, or worse, as evidence of personal failure. The risk of falling off an epistemological cliff and concluding that nothing can be known is actually greater than for some ethnographic approaches where, no matter what, data can be collected for interpretation.   You can’t have a serendipitous discovery if you too doggedly stick to ‘what I’m supposed to do’, nor can you recover from the failure of a narrowly hypothesis-driven question to reach a result.   Especially at the graduate level, where many students go on to develop complex research projects, I advocate the method of ‘multiple working hypotheses’, first developed by T.C. Chamberlin in the late 19th century but which honestly is the practice of all serious empirical researchers in field disciplines, including cultural and linguistic anthropology.

Serendipity is important because it works – because it is a source of creative insight and hypotheses, across multiple disciplines and epistemologies.   But for students, serendipity is important because it is joyful – it is a source of extrinsic motivation to carry on with work that is, at times, of course, tedious, frustrating, and always time-consuming. Getting undergraduates – particularly but not limited to first-generation scholars who have not had much previous social support in intellectual activities – to take joy in discovery is, perhaps, one of the most exciting parts of our job.

 

Stephen Chrisomalis (BA, McMaster; PhD, McGill) is an Associate Professor of Anthropology at Wayne State University in Detroit, Michigan. He is a linguistic and cognitive anthropologist whose work focuses on cross-cultural mathematics and numeracy across linguistic, cultural, and archaeological anthropology. His recent publications include ‘What’s so improper about fractions? Prescriptivism and language socialization at the Math Corps’ (Language in Society, 2015) and ‘Umpteen reflections on indefinite hyperbolic numerals’ (American Speech, 2016).