3.00 credits
20.0 h
Q1 or Q2
Teacher(s)
Brabant Stéphanie; Dagneaux Estelle; Delghust Jean-Luc; Deneumoustier Aurélie; Desterbecq Fanny; Duelz Marie; Grommersch Claudine; Kefer Adrien (compensates Mulkers Sandrine); Mulkers Sandrine (coordinator); Piwnik Marc (coordinator); Stas Françoise; Toubeau Anne-Julie; Volpe Marine;
Language
English
Prerequisites
A2 upper-level course (Common European Framework of Reference for Languages).
Main themes
The pedagogical method is mainly based on authentic texts and videos (education, family, advertising, media, new technologies, science, environment).
Learning outcomes
At the end of this learning unit, the student is able to : | |
At the end of the course students are expected to have reached a B1 lower level (Common European Framework of Reference for Languages) in the 3 following skills:
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Content
The main aim of this general English course is to develop students' reading skills, grammar and vocabulary required to have access to the BAC 2 course .
At the end of the course (end of BAC1) students are expected to have reached a B1 lower level (Common European Framework of Reference for Languages) in the 3 following skills: reading, listening, speaking.
At the end of the course (end of BAC1) students are expected to have reached a B1 lower level (Common European Framework of Reference for Languages) in the 3 following skills: reading, listening, speaking.
Teaching methods
The pedagogical method is based on authentic documents and videos (reading and listening comprehension) and involves student interaction. Basic vocabulary and structures are practised and consolidated through written and oral exercises.
Evaluation methods
Assessment BAC 1 students are tested in the following way :
- Entry test and Exemption test: All students must take an entry test during the first week of the academic year. On the basis of the results, top-ranked students will be invited to take an exemption test in the second week of the academic year. This exemption test is the same level as the exam. On the basis of the results, students can be exempted from the course and the final exam.
- Midterm oral test: Around midterm, students who were not exempted must take an oral test.
- End term written exam: Students will be tested on (a) the videos, texts and all the grammar material included in the syllabus as well as on (b) the vocabulary book "English Vocabulary in Use" (pre-intermediate to intermediate) by Stuart Redman, Cambridge University Press, Fourth Edition.
- Continuous assessment evaluates daily work of students attending the course as well as class participation. Continuous assessment is no longer taken into account in the third exam session (August/September).
Other information
- Course attendance is compulsory.
- Optional remedial workshop (ENGLISH +) for weaker students is organized throughout the year (1h/week).
- Optional "Aide à la Réussite" remedial sessions on specific aspects of the course are organized in person and/or on TEAMS during each term. (https://moodle.uclouvain.be/course/view.php?id=4581)
- Teacher available at least one hour a week during office hours.
Online resources
MoodleUCLouvain:
- LANGL1330P – English for ESPO11 Students 2023-2024 Q1, https://moodle.uclouvain.be/course/view.php?id=6310
- LANGL1330S – English for ESPO11 Students 2023-2024 Q2, https://moodle.uclouvain.be/course/view.php?id=9204
- LANGL1330P – English for ESPO11 Students 2023-2024 Q1, https://moodle.uclouvain.be/course/view.php?id=6310
- LANGL1330S – English for ESPO11 Students 2023-2024 Q2, https://moodle.uclouvain.be/course/view.php?id=9204
Teaching materials
- Syllabus d'anglais ESPO 11 - LANGL1330 Niveau Moyen – 1° partie
- English Vocabulary in Use (pre-intermediate to intermediate), Stuart Redman, Cambridge University Press, 4th Edition
- English Grammar in Use, Raymond Murphy, Cambridge University Press, 5th Edition
- A partir de MoodleUCLouvain : le cours LANGL1330 English for ESPO 11 students
Faculty or entity
ILV
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Data Science : Statistic
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Bachelor in Economics and Management
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