English Linguistics : Corpus Linguistics

Teacher(s)

Gilquin Gaëtanelle;

Language

English

Prerequisites

/

Main themes

The course introduces the main tenets of corpus linguistics and the methods and techniques used to work with large collections of spoken or written electronic data.
It covers the following topics: corpus design:
- data collection, archiving and markup.
- corpus typology: spoken and written corpora; monolingual vs multilingual; native vs learner; diachronic vs synchronic.
- major electronic corpora: British National Corpus, International Corpus of English, International Corpus of Learner English, MICASE, Louvain International Database of Spoken English Interlanguage, etc.
- corpus annotation (POS-tagging, lemmatization, parsing, semantic tagging, prosodic annotation, error tagging).
- automated analysis of lexis, grammar and discourse.
Special attention is paid to the links between corpus linguistics and foreign language learning, contrastive and translation studies and natural language processing.

Learning outcomes

At the end of this learning unit, the student is able to :
1	By the end of the course, students are expected to have a solid theoretical background in corpus linguistics and master the main techniques and tools used to analyse spoken and written computerized data. They will be able to read the scientific literature and conduct their own research in the field.

Content

The course provides a theoretical and practical introduction to corpus linguistics. It presents the main concepts related to corpus linguistics, as well as some of its possible applications in different fields.

Teaching methods

Lectures relying partly on required readings that the students are expected to do before class and that will lead to discussions (in class and/or online) in which the students should be ready to participate fully. Several assignments will be organized to familiarize students with text handling software tools.

Evaluation methods

As we are aiming to train language specialists, particular attention will be paid to language accuracy in the assignments and exams related to the course. For the same reason, the use of generative artificial intelligence is not allowed for any parts of the evaluation. Their use by the student will be considered as cheating.

Online resources

Moodle

Teaching materials

• Documents PowerPoint sur Moodle
• Notes de cours de l'étudiant·e
• Portefeuille de lectures

Faculty or entity

> ELAL