Assistant Professor in Language Sciences [Maître de conférences], Section 07 (Sciences du langage : linguistique et phonétique générales), Conseil national des universités (CNU), France. LINK
Assistant Professor in Language and Literature [Maître de conférences], Section 15 (Langues et littératures arabes, chinoises, japonaises, hébraïques, d’autres domaines linguistiques), Conseil national des universités (CNU), France. LINK
Academic Teacher Training Course (five full-time work weeks). The content consisted of theoretical perspectives on learning styles and teaching practices, the constructive alignment of teaching/learning, including teaching, norm-critical and inclusive pedagogy, and education for sustainable development. Participants also carry out a teaching assignment of their own that is subjected to discussion with an experienced teacher (teaching mentor) in mentored sessions prior to and following the teaching performance. PDF
Supervising Students for Degree Project (two full-time work weeks). The course included different supervisory styles, psychological and social aspects of supervision, conversation skills in supervision, conflict management, diversity-and-gender awareness, and evaluation of degree projects. PDF
Assessment, Grading and Feedback (one full-time work week). The course analyses different forms of assessment/examination. Summative (end of course) and formative (during the course) methods are discussed along with various forms of formative practices to use generate feedback from the students. PDF
LINGUISTIC CATEGORIES AND LANGUAGE CHANGE ([3h], Spring 2022) LINK
Instructor for two teaching sessions. The participants (students and researchers) learned and discussed how to conduct linguistic analyses on corpus data. These sessions are included in the summer school 'Linguistics, sociolinguistics, and ethnolinguistics' of the Muséum National d'Histoire Naturelle in Paris.
AN INTRODUCTION TO MIXED MODELS ([3h], Autumn 2021) LINK
Instructor for a 3-week introduction to (generalized) linear mixed models. The participants (students and researchers) learned, discussed, and practiced how to conduct and interpret the analysis of mixed models on language acquisition data. The analysis included topics such as interpreting fixed and random effects.
QUANTITATIVE TYPOLOGY OF LINGUISTIC CORPORA (Postgraduate module [3h], Spring/Autumn 2021) LINK
Instructor for a teaching session on the use of corpora in linguistic research.The participants were taught how to build corpora based on raw data (involving recordings and/or transcriptions) and how to conduct basic analyses (involving data visualization and statistical analyses) on these corpora.
A STATISTICAL ANALYSIS OF THE MORPHOLOGY-SYNTAX DISTINCTION ([3h], Spring term 2020) LINK
Instructor for a 3-hour session introduction to generalized linear mixed models and tree-based computational classifiers. The participants (researchers) learned how to conduct automatic labelling of words, clitics, and affixes with machine learning methods such as generalized linear mixed models and decision-tree classifiers.
FIELDWORK SESSIONS WITH NATIVE SPEAKERS (Summer school module [15h], Autumn term 2019) LINK
Instructor in charge of the full course (15h). During a week, students have 2 hours each day to conduct fieldwork with the native speaker of a language they do not speak. The students are given specific tasks for the course (e.g., identify the word order patterns of the language) and have to present their results at the end.
AN INTRODUCTION TO RANDOM FORESTS (Postgraduate module [5h], Spring term 2018) LINK
Instructor for 90-minute sessions introducing the use of the computational classifier of random forests in linguistics. The teaching modules were taught to an audience without previous experience in programming and provided the participants the skills to perform the test of random forests on a provided linguistic dataset.
CURRENT RESEARCH IN LINGUISTICS (Undergraduate course [30h], Spring term 2019) LINK
Instructor in charge of the full course. The students are taught how to 1) write simple computer programmes using the R language to analyse, visualise, and process data 2) use appropriate methods to cluster data, to measure similarity between linguistic variables, and to test causal hypotheses.
COGNITIVE LINGUISTICS (Undergraduate course [30h], Spring term 2019) LINK
Instructor in charge of the full course. This course provides basic theoretical and methodological knowledge in the area of cognitive linguistics. The students are taught how to use and explain basic concepts of cognitive linguistics in their analysis (e.g., semantic frame, prototype, metaphor).
VISUALISATION AND STATISTICS (Postgraduate course [30h], Autumn term 2018) LINK
Instructor for weekly two-hour lab sessions of R programming in data visualisation an statistical analysis. The teaching content involved basic commands in R, data cleaning and reformatting, multidimensional scaling of data and basic statistical analyses.
FRENCH (High school/University level [2500h], 2013 Autumn term - 2015 Spring term) LINK
Instructor for group courses between A1 and C2 at the Chinese Institute of European Languages. The teaching load was 30 hours/week and the content involved conversation, writing, grammar courses, and preparation for the DELF diplomas. Teaching materials included but were not limited to CIEL1-6, Tempo1, Tempo2, Alter Ego3.