Teaching

As primary instructor:

Semantic universals, co-taught with Wataru Uegaki, EGG Summer School 2021

(I also taught a version of this course, Linguistic universals, during Spring 2022 at the Hebrew University of Jerusalem)

In this course, we discussed recent work on competing explanations of semantic universals: pressures for communicative efficiency, ease of learning, and universal grammar, among others. We focused on the use of experimental and computational tools to test competing hypotheses. In particular, we discussed how artificial neural networks work, and how they can be trained and used to test the ease of learning hypothesis. We also learnt how specific hypotheses about what it means for a language to support efficient communication can be made mathematically precise, and empirically tested using computational simulations and cross-linguistic data.

Materials can be downloaded from here.

Experimental methods in semantics, EGG Summer School 2021

This course was an introduction to experimental design and statistical methods for experimental linguistic research. I introduced common experimental paradigms used in linguistics, descriptive statistics, data plotting, statistical hypothesis testing and linear regression analysis. The course included a practice session where students applied the acquired notions to analyze an example data set from an actual linguistic experiment in R.

Materials: Classes 1 and 2, Class 3, Class 4, Class 5: R script and the data set and solutions

Human Cognition, Part 2: Computational models in cognitive science, Spring 2020, University of Amsterdam

This was an introductory course in cognitive science for cognitive science undergraduate students. The course centered on two major approaches to cognitive information processing, symbolic language-of-thought-based approach and neural network models. We discussed their strengths and challenges, as well as some of the applications of these two approaches in the field of AI. As a bonus topic, we covered Bayesian modelingin cognitive science, and applied it to the problem of word learning.

Computational methods, Spring 2020, University of Amsterdam

This was an introductory course in logic and computation for cognitive science undergraduate students. The course covered an introduction to set theory, propositional and predicate logic, formal languages and grammars, and automata theory.

As teaching assistant:

Introduction to linguistics (Primary instructor: Salvador Mascarenhas), Fall 2018, Ecole Normale Supérieure

This was an introductory course to linguistics for cognitive science graduate students. The course covered a classic, but complete and ambitious introduction to each of the major fields of linguistics (phonology and phonetics, syntax, semantics, pragmatics).  

Advanced semantics (Primary instructor: Benjamin Spector), Spring 2018, Ecole Normale Supérieure

This was an advanced course in formal semantics for linguistics and cognitive science graduate students. The students were expected to have completed an introductory course in formal semantics. The topics that were covered included plurals, indefinites, questions, focus and tense semantics.

Meaning and interpretation (Primary instructors: Benjamin Spector, Philippe Schlenker and Salvador Mascarenhas), Fall 2016, Ecole Normale Supérieure

This was an advanced interdisciplinary course in philosophy of language, formal and experimental pragmatics and psychology of reasoning for cognitive science graduate students. It covered major theories of scalar implicatures and of presuppositions, as well as the contact points of formal pragmatics and psychology of reasoning. It also had a component focusing on the interdisciplinary research on animal linguistics.