Modelling Textbook English using a Modified Multi-Feature/Dimensional Analysis (MDA) Framework
Creators: name: Le Foll, Elen
Publisher: name: Zenodo
Year: 2025
Subjects: corpus linguistics
English Language Teaching
English as a Foreign Language
English education

description: Abstract

English as it is represented in secondary school English as Foreign Language (EFL) textbooks is often perceived as somehow different from ‘real-life’, ‘authentic’ English. Indeed, previous studies have shown that individual lexico-grammatical features are often misrepresented (see Le Foll 2024 for a synthesis of the literature). This is problematic given that textbooks are an important and highly influential vector of foreign language input in secondary education. It is therefore worth asking: Does Textbook English constitute a special variety of English? And, if so, in what ways does it differ from ‘real-life’, extra-curricular English?

This talk focuses on the modified version of the multi-feature/multi-dimensional analysis (see Biber 1988; Berber Sardinha & Veirano Pinto 2014; 2019: 19) framework used to answer these questions in Le Foll (2024). MDA is used to compare the language of nine series of EFL textbooks used at in lower secondary education in Germany, France and Spain with three target language reference corpora. Inspired by Diwersy et al. (2014) (2014) and Neumann & Evert (2021), this modified MDA framework is based on principal component analysis (PCA) and extensive multi-dimensional visualisations. The framework further incorporates additional steps designed to increase both the reproducibility and replicability of the results.

Following a theoretical introduction to both the research questions at hand and the MDA framework, the open-source tools used to conduct MDAs in this study are presented from a practical point of view. Together, we examine the functionalities of the Multi-Feature Tagger of English (MFTE Le Foll 2021; see also Le Foll & Shakir 2023) and a number of useful R libraries. To this end, we draw on the RMarkdown scripts that are part of the Online Supplements of Le Foll (2024; https://elenlefoll.github.io/TextbookMDA). Finally, we discuss the steps taken to improve the reproducibility and replicability of the results, in line with the principles of Open Science.

References

Berber Sardinha, Tony & Marcia Veirano Pinto (eds.). 2014. Multi-Dimensional Analysis, 25 Years on: A Tribute to Douglas Biber (Studies in Corpus Linguistics 60). Amsterdam: John Benjamins.

Berber Sardinha, Tony, Marcia Veirano Pinto, Cristina Mayer, Maria Carolina Zuppardi & Carlos Henrique Kauffmann. 2019. Adding Registers to a Previous Multi-Dimensional Analysis. In Tony Berber Sardinha & Marcia Veirano Pinto (eds.), Multi-Dimensional Analysis: Research Methods and Current Issues, 165–188. New York, NY: Bloomsbury.

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Diwersy, Sascha, Stephanie Evert & Stella Neumann. 2014. A weakly supervised multivariate approach to the study of language variation. In Benedikt Szmrecsanyi & Bernhard Wälchli (eds.), Aggregating dialectology, typology, and register analysis: Linguistic variation in text and speech, 174–204. Berlin: De Gruyter.

Le Foll, Elen. 2021. Introducing the Multi-Feature Tagger of English (MFTE). Perl. Osnabrück University. https://github.com/elenlefoll/MultiFeatureTaggerEnglish. (5 January, 2022).

Le Foll, Elen. 2024. Textbook English: A Multi-Dimensional Approach (Studies in Corpus Linguistics 116). Amsterdam: John Benjamins.

Le Foll, Elen & Muhammad Shakir. 2023. Introducing a New Open-Source Corpus-Linguistic Tool: The Multi-Feature Tagger of English (MFTE). Presented at the ICAME44, NWU Vanderbijlpark (South Africa).

Neumann, Stella & Stephanie Evert. 2021. A register variation perspective on varieties of English. In Elena Seoane & Douglas Biber (eds.), Corpus-based approaches to register variation (Studies in Corpus Linguistics 103), 144–178. Amsterdam: Benjamins.