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10.00 credits
15.0 h
Q1 and Q2
This biannual learning unit is being organized in 2025-2026
Language
English
> French-friendly
> French-friendly
Prerequisites
- A bachelor's degree in modern or Romance languages, literature and linguistics
- Solid knowledge of academic English, solid introduction to corpus linguistics
Main themes
The focus of this research seminar is on the linguistic and psycho-experimental study of discourse markers.
The “paradox” mentioned in the title of the seminar refers to Discourse Markers as an inescapable linguistic category, occurring with high frequency in any type of human communication, yet escaping consensual linguistic description. descriptive consensus.
An overview of corpus-based and psycho-experimental studies of discourse markers in a variety of languages will be studied throughout the seminar.
The “paradox” mentioned in the title of the seminar refers to Discourse Markers as an inescapable linguistic category, occurring with high frequency in any type of human communication, yet escaping consensual linguistic description. descriptive consensus.
An overview of corpus-based and psycho-experimental studies of discourse markers in a variety of languages will be studied throughout the seminar.
Learning outcomes
At the end of this learning unit, the student is able to : | |
| 1 | Conduct a scientific study in the field of discourse markers, either corpus-based or psycho-experimental |
| 2 | Present the research questions, methods and results of this research project orally |
| 3 | Present the research questions, methods and results of this scientific project in an academic paper |
| This learning unit contributes to the development and command of the following skills and learning outcomes of the ELAL programmes (ELAL learning outcomes): 1.1 ; 1.4 ; 1.6 ; 2.1 ; 2.3 ; 2.4 ; 2.6 ; 3.1 ; 3.2 ; 3.3 ; 3.5 ; 3.6 ; 4.3 ; 4.5 ; 5.1 ; 5.2 ; 5.3 ; 5.6 ; 6.1 ; 6.2 ; 6.3 ; 6.4 ; 6.5 ; 6.6 |
|
Content
Using the linguistic category of discourse markers as a starting point, this class aims to introduce the students to various methods and empirical approaches which can be used separately or in combination. Readings will illustrate a sample of these approaches, focusing on multi-method studies whenever possible. The students will then be invited to design a research plan, focusing on the relationship between a research question and the methods which are relevant to answer it. In doing so, the notions of research question, hypothesis and methodology will be defined and put to practice so that students work out the complete research process from research question and hypotheses to collection and analysis of the data with adequate methods and discussion of the results.
Teaching methods
Research seminar
Students attend classes prepared, i.e. they have read the selected readings (submission of reading notes) and prepared questions to discuss. They present the (preliminary) results of a research project. If possible, a psycho-linguistic experimental design is set up with the whole group. Special attention will go to the students' ability to extract methodological questions from the papers under review.
Students attend classes prepared, i.e. they have read the selected readings (submission of reading notes) and prepared questions to discuss. They present the (preliminary) results of a research project. If possible, a psycho-linguistic experimental design is set up with the whole group. Special attention will go to the students' ability to extract methodological questions from the papers under review.
Evaluation methods
The evaluation is performed through an individual or co-authored written essay (80% of the grade) verifying the student's ability to resolve problems analogous to the ones presented in class. This project may take the form of a replication study. Active participation in class (oral presentation of research project, timely submission of reading notes etc.) is evaluated at 20% of the final grade (it is not possible to repass this part of the evaluation in August).
Generative artificial intelligence (AI) must be used responsibly and in accordance with the practices of academic and scientific integrity. Scientific integrity requires that sources be cited, and the use of AI must always be reported. The use of artificial intelligence for tasks where it is explicitly forbidden will be considered as cheating.
Generative artificial intelligence (AI) must be used responsibly and in accordance with the practices of academic and scientific integrity. Scientific integrity requires that sources be cited, and the use of AI must always be reported. The use of artificial intelligence for tasks where it is explicitly forbidden will be considered as cheating.
Online resources
Course documents and reading portfolio available on the Moodle platform
Bibliography
cf. Moodle
Faculty or entity
