My teaching philosophy is built on a foundation of uncertainty. Uncertainty is at the heart of science, of course; what we know today may be revised or overturned tomorrow. Hence, when I teach a course on, say, cognitive psychology or linguistics, the tentative nature of scientific knowledge is always present, whether it is lurking in the background or serving as the topic of discussion. I try to build strong intuitions about this in my students by having them design and critique research projects and analyze real data. I want students to learn both the content of a field of inquiry and the nature of how that content has come to be. While reading and attending lectures can provide enormous amounts of valuable information, I believe that actually conducting science – even if it is science of limited scope – is crucial to the integration of that information into a broader knowledge base.
Uncertainty is even more central to my teaching of statistical analysis and research methods. At its core, statistical analysis is the quantification of uncertainty, and research methodology is, at least in part, concerned with the careful consideration and manipulation of sources of uncertainty. In teaching these topics, I strive to provide students with a set of tools that enable a degree of rigor in thought that is difficult, if not impossible, to achieve without these tools. My education in statistical modeling, probability theory, and research methodology is, naturally, the heart of my research, but it also powerfully informs the way I look at the world in general. The importance of thorough training in statistics and research methods is underscored by the abundance of quantitative information – in research and in the world at large – and the ready availability of powerful computational tools.
My teaching is informed by uncertainty in a more pragmatic sense, as well. Although I consider myself a good teacher, I am never absolutely sure that I am taking the best available approach to a given class. Effective pedagogy requires flexibility and awareness of the tenor in a classroom. I am willing to change course midstream if need be, making adjustments to better meet the needs of the students or a particular topic. Over the course of my many years of schooling, I have taken classes from some truly extraordinary teachers. This has enriched both my research and teaching toolsets immeasurably.
I have taught courses on introductory linguistics, phonological analysis, and statistical analysis. I have been the assistant instructor for a graduate course on mathematical psychology, and I have been the grader for courses on Bayesian data analysis and mathematical psychology. I am prepared to teach courses on a wide variety of statistical topics (e.g., linear models, categorical data analysis, Bayesian data analysis, multilevel models), as well as introductory and advanced courses on general linguistics, phonetics, phonology, experimental design, and quantitative methods for linguists, applied linguists, and speech and hearing scientists.