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Corpus d'apprentissage Simuligne -- LETEC (Learning and Teaching Corpus) Simuligne
Title:
Corpus d'apprentissage Simuligne -- LETEC (Learning and Teaching Corpus) Simuligne
ID:
mce.simu.all.all
Link to the object:
Online:
Yes
Archive:
Contributor:
ANR-06-CORP-006 echange de corpus d'apprentissage multimodaux (MULCE), Programme "CORPUS ET OUTILS DE LA RECHERCHE EN SCIENCES HUMAINES ET SOCIALES" 2006, Agence Nationale de la Recherche, France (sponsor)
Projet de recherche Icogad, programme Cognitique 2000-2002, Ministre de la Recherche, France. (sponsor)
Chanier, Thierry ; Lamy, Marie-Noelle ; Reffay, Christophe (author)
Date:
2009-04-20
Publisher:
Mulce (MULtimodal Corpus Exchange) ; Universite Blaise Pascal ; Clermont-Ferrand:France ; http://mulce.org
Description:
Corpus d'apprentissage de la formation en ligne Simuligne (2001), dont le scénario est basée sur une simulation globale pour l'apprentissage du français langue trangère (FLE) et inclut également une étape interculturelle "Interculture" inspirée de Cultura. Ce corpus comprend le scénario pédagogique dans plusieurs formats, le protocole de recherche (et ses données recueillies), les interactions en ligne et les productions des apprenants structurées suivant un schéma XML, la liste des participants, les licences d'utilisation.
This is the Learning and Teaching Corpus of the online educational experiment Simuligne (2001). Its scenario is based on a global simulation for the learning of French as a foreign language. It also includes an intercultural activity, "Interculture", based on the Cultura project. The corpus includes the pedagogical scenario, described in several formats, the research protocol, participant's online interactions and productions (structured in XML), list of participants, licences of use.
Analyses done by researchers on this LETEC corpus can be found on Mulce Website (
or Mulce repository (
. They are contained in distinguishable corpora.
This corpus contains a total of 11638 acts, of which, 6790 are chat acts, 2686 forum acts, 2030 email acts and 132 production acts.
Content language:
English
French
Subject language:
French
Language family:
Indo-European
Italic
Romance
Country:
United Kingdom
France
Linguistic type:
Primary text
Linguistic field:
Applied linguistics
Discourse analysis
Text and corpus linguistics
Discourse type:
Dialogue
Narrative
DCMI type:
Dataset
Collection
Format:
text/html
text/xml
text/rtf
application/pdf
application/msword
image/jpeg
image/gif
audio/x-wav
LCSH subject:
Education
Data processing
Computer-assisted instruction
Language and languages
Study and teaching
Temporal coverage:
name=Simuligne course ; start=2001-04-09; end=2001-07-06
Other rights:
http://lrl-diffusion.univ-bpclermont.fr/mulce/metadata/vdex/mce_licence.xml
Rights holders of this corpus are: Thierry Chanier ; Marie-Noelle Lamy ; Christophe Reffay ; Marie-Laure betbeder ; Maud Ciekanski
Creative Common License: http://creativecommons.org/licenses/by-nc-sa/2.0/
open access after registration
Other subject:
Le corpus d'apprentissage Simuligne est un ensemble de données structurées contenant plusieurs composants décrivant respectivement : le scénario pédagogique, le protocole et les questions de recherche, les interactions des acteurs dans les environnements.
The learning and teaching corpus named Simuligne is a set of structured data containing various interconnected components: learning design, research questions and protocol, actors interaction data coming from virtual environments and right informed consents.
Complete OLAC record:
Link for this page:

Find Related Information:

Archive: Multimodal Learning and teaching Corpora Exchange
Online: Yes
Subject language: French
Language family: Indo-European
Language family: Italic
Language family: Romance
Geographic region: Europe
Country: France
Country: United Kingdom
Linguistic type: Primary text
Linguistic field: Applied linguistics
Linguistic field: Discourse analysis
Linguistic field: Text and corpus linguistics
Discourse type: Dialogue
Discourse type: Narrative
DCMI type: Collection
DCMI type: Dataset
Format: application/msword
Format: application/pdf
Format: audio/x-wav
Format: image/gif
Format: image/jpeg
Content language: English
Content language: French
Date: 2000 - 2009
Date: 2000 and later
Contributor: ANR-06-CORP-006 echange de corpus d'apprentissage multimodaux (MULCE), Programme "CORPUS ET OUTILS DE LA RECHERCHE EN SCIENCES HUMAINES ET SOCIALES" 2006, Agence Nationale de la Reche
Contributor: Chanier, Thierry ; Lamy, Marie-Noelle ; Reffay, Christophe
Contributor: Projet de recherche Icogad, programme Cognitique 2000-2002, Ministre de la Recherche, France.
Contributor: Reffay, Christophe ; Chanier, Thierry ; Betbeder, Marie-Laure
Contributor: rche, France
LCSH subject: Computer-assisted instruction
LCSH subject: Data processing
LCSH subject: Education
LCSH subject: Language and languages
LCSH subject: Study and teaching
Publisher: Mulce (MULtimodal Corpus Exchange) ; Universite Blaise Pascal ; Clermont-Ferrand:France ; http://mulce.org
Temporal coverage: name=Simuligne course ; start=2001-04-09; end=2001-07-06
Title: Corpus d'apprentissage Simuligne -- LETEC (Learning and Teaching Corpus) Simuligne
Other rights: Creative Common License: http://creativecommons.org/licenses/by-nc-sa/2.0/
Other rights: Rights holders of this corpus are: Thierry Chanier ; Marie-Noelle Lamy ; Christophe Reffay ; Marie-Laure betbeder ; Maud Ciekanski
Other rights: http://lrl-diffusion.univ-bpclermont.fr/mulce/metadata/vdex/mce_licence.xml
Other rights: open access after registration
Other subject: interactions des acteurs dans les environnements.
Other subject: coming from virtual environments and right informed consents.
Other subject: Le corpus d'apprentissage Simuligne est un ensemble de données structurées contenant plusieurs composants décrivant respectivement : le scénario pédagogique, le protocole et les questions de recherche, les
Other subject: The learning and teaching corpus named Simuligne is a set of structured data containing various interconnected components: learning design, research questions and protocol, actors interaction data