English Linguistics : Corpus Linguistics

lgerm2829  2023-2024  Louvain-la-Neuve

English Linguistics : Corpus Linguistics
5.00 credits
22.5 h
Q1
Teacher(s)
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 hands-on exercises will be organized to familiarize students with text handling software tools.
Evaluation methods
In this course, students are assessed in two ways:
- During the term: one written assignment involving the analysis of corpus data and counting for 30% of the final grade. In case of second exam enrolment, the students who have not obtained at least 10/20 for this assignment will have to do it again. The use of generative artificial intelligence is not allowed for the preparation or writing of this assignment.
- In January and/or in August/September: written exam counting for 70% of the final grade.
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.
Online resources
Moodle
Teaching materials
  • Documents PowerPoint sur Moodle
  • Notes de cours de l'étudiant·e
  • Portefeuille de lectures
Faculty or entity


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [60] in Modern Languages and Literatures : German, Dutch and English

Master [120] in Translation

Master [60] in Modern Languages and Literatures : General

Master [120] in Linguistics

Master [120] in Modern Languages and Literatures : German, Dutch and English

Master [120] in Modern Languages and Literatures : General