https://orcid.org/0000-0003-2186-2163
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ABSTRACT
Whilst the links between learner corpus research (LCR) and Second Language Acquisition (SLA) have long been debated, McEnery et al. (2019. “Corpus Linguistics, Learner Corpora, and SLA: Employing Technology to Analyze Language Use.” Annual Review of Applied Linguistics 39: 74-92. doi:10.1017/S0267190519000096) claim that learner corpus data are not yet sufficiently integrated in SLA research. This article aims to go one way towards bridging the LCR/SLA gap by illustrating the benefits of collecting and analyzing data sets that better document multiliteracy practices. We first contextualize our work within the field of LCR where calls for more multidimensional data sets have been made. We then present a new database called MulTINCo - Multilingual Traditional, Immersion, and Native Corpus - collected in the framework of a project on Content and Language Integrated Learning in French-speaking Belgium. As our data set contains rich metadata and blends corpus data with other data types, we illustrate its potential for SLA research. In Sections 3 and 4, we describe the data collected and the interface. In the last section of the paper, we wrap up with a discussion on the methodological assets of such multidimensional data sets for SLA studies, and present directions for future research.
Acknowledgements
We would like to thank the anonymous reviewers for their most valuable comments on earlier versions of the article.
Our work was supported by a Concerted Research Action grant (ARC 14/19-061) from the Université catholique de Louvain (UCLouvain) and the Université de Namur (UNamur). We would like to warmly thank our ARC colleagues, and all the schools and pupils who took part in the various data collection points of the project.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
2 See section 2.6 for contextual details on CLIL (number of hours, types of content courses taught in the target language, etc.).
3 See for instance the definitions provided in the Dictionary Of Language Teaching And Applied Linguistics (available online at https://archive.org/details/DictionaryOfLanguageTeachingAndAppliedLinguistics).
4 For more details and references on the corpora listed above, their design, the targeted language studied and the data type covered, see Meunier (Citation2015).
5 This index, approved by the Government of the French community, is defined on the basis of an inter-university study which updates the calculation formula every five years. The five types of main variables used are income per capita, level of education, unemployment rate, professional activities and housing comfort.
6 Lime Survey: https://www.limesurvey.org/about-limesurvey/team-contributors.
7 The only difference is that the written data from the English native speakers were collected using the online software Qualtrics – the American ethical commission did not accept Lime Survey.
8 In the demo version, transcriptions of the spoken data are available, but the audio files are not included. Readers interested in accessing the demo version should contact [email protected] to obtain a username and password.
9 This may seem discriminating but the mother’s level of education is very frequently used as a proxy for SES because it has a low rate of missing responses and is highly correlated with father’s education (Entwisle and Astone Citation1994).
Additional information
Funding
Notes on contributors
Fanny Meunier
Fanny Meunier is Professor of English language, linguistics and didactics at the Université catholique de Louvain (Belgium). Her main research interests include the SLA/language pedagogy nexus, the teaching and acquisition of multilingualism and multiliteracies. She has been one of the promotors of the research project "Assessing Content and Language Integrated Learning (CLIL): Linguistic, cognitive and educational perspectives” (2014-2019).
Isa Hendrikx
Isa Hendrikx is an associate researcher at the Université catholique de Louvain on a multidisciplinary research project on Content and Language Integrated Learning (CLIL). She studies the translation and the L2 acquisition of morphological constructions in L2 Dutch and English by French-speaking learners, drawing on the theoretical framework of Construction Grammar.
Amélie Bulon
Amélie Bulon is a researcher at the Université catholique de Louvain. She is involved in several research projects on the acquisition and teaching of multilingualism. Her research focuses more specifically on the acquisition and teaching of multiword units to learners of English.
Kristel Van Goethem
Kristel Van Goethem is Research Associate of the Belgian National Research Fund (F.R.S.-FNRS) at the Université catholique de Louvain. Her research focuses on morphology, contrastive linguistics, second language acquisition, corpus linguistics and Construction Grammar. She has been one of the promotors of the research project "Assessing Content and Language Integrated Learning (CLIL): Linguistic, cognitive and educational perspectives” (2014-2019).
Hubert Naets
Hubert Naets works at the Center for Natural Language Processing (Cental) of the Université catholique de Louvain as a Natural Language Processing scientist. His work and research cover a fairly wide range of fields related to natural language processing, including corpus processing in modern and ancient languages, second language acquisition, semantic information extraction and text mining.